Vincenzo Sgaramella ⁵, Marco Brescia ⁶, Federico Ruta ⁷, Elena Barile ^8,9,*

1. Healthcare Professions Unit, Department of Hospital and Community Healthcare Services, Local Health Authority of Bari, Bari, Italy.
2. Cardiology and Interventional Hemodynamics Unit, “L. Bonomo” Hospital, Local Health Authority of Barletta-Andria-Trani, Andria, Italy.
3. Department of Infectious Diseases, “Vittorio Emanuele II” Hospital, Local Health Authority of Barletta-Andria-Trani, Bisceglie, Italy.
4. Oncology Counseling Center, “R. Dimiccoli” Hospital, Local Health Authority of Barletta-Andria-Trani, Barletta, Italy.
5. Medical Directorate, “L. Bonomo” Hospital, Local Health Authority of Barletta-Andria-Trani, Andria, Italy.
6. Independent Nurse Researcher, Barletta-Andria-Trani, Bisceglie, Italy.
7. General Directorate, Local Health Authority of Barletta-Andria-Trani, Andria, Italy.
8. Hemodialysis Unit, “Don Tonino Bello” Hospital, Local Health Authority of Bari, Molfetta, Italy.
9. Department of Biomedicine and Prevention, University of Rome Tor Vergata, Rome, Italy.

Corresponding author: Elena Barile. Hemodialysis Unit, “Don Tonino Bello” Hospital, Local Health Authority of Bari, Molfetta, Italy, and University of Tor Vergata, Rome, Italy. E-mail: elena.barile@asl.bari.it, ORCID: 0009-0007-1394-6785.

Cite this article

 

ABSTRACT

Background: Health perception is increasingly recognized as a multidimensional concept encompassing physical, psychological, social, and lifestyle-related dimensions. Understanding how citizens conceptualize health is therefore essential for developing tailored public health strategies and community-based interventions. This study aimed to investigate perceptions of health among citizens and to examine associations with selected sociodemographic and clinical characteristics.

Methods: An observational cross-sectional study was conducted in the Italian province of Barletta-Andria-Trani (BAT), Puglia, Italy. A convenience sample of 257 adults (≥18 years) was recruited during public events in five municipalities (Andria, Barletta, Trani, Bisceglie, and Margherita di Savoia). Data were collected using the validated Health Perception Questionnaire (QPS), consisting of 35 Likert-scale items (1–4) addressing lifestyle, psychological, social, and biomedical aspects. Statistical analysis included descriptive analyses, reliability assessment using Cronbach’s alpha, chi-square tests, and Fisher’s exact tests.

Results: The Health Perception Questionnaire showed excellent internal consistency (Cronbach’s α = 0.940). Items related to lifestyle behaviors—physical activity, a balanced diet, and adequate sleep—showed the highest agreement rates (>90%), whereas items reflecting a purely biomedical or disease-absence approach received the lowest agreement, particularly the association of a vegetarian diet with the concept of health (52.1%). Chi-square analysis of item-level agreement frequencies identified 28 statistically significant associations.

Conclusion: Citizens of the BAT Province conceptualize health predominantly in biopsychosocial and broadly holistic terms, rejecting a reductionist biomedical model. This study provides local data supporting community-based health promotion programs and nursing practice.

Keywords: health perception, Health Perception Questionnaire (QPS), cross-sectional study, public health, Southern Italy.

Introduction

Health represents one of the most widely investigated and, at the same time, most debated constructs in the field of public health sciences. The foundational definition of the World Health Organization (WHO)—“a state of complete physical, mental and social well-being and not merely the absence of disease or infirmity” [1]—marked a fundamental shift from a purely biomedical approach to a biopsychosocial one. This conceptual shift was further reinforced by the Ottawa Charter for Health Promotion [2], which framed health as a dynamic process constructed through everyday life habits and requiring individual empowerment and intersectoral action.

In recent decades, self-perceived health (SPH) has been regarded as a predictor of morbidity, mortality, and health service use, even after adjustment for objective clinical indicators [3]. SPH reflects not only biological conditions but also psychological resources, social connections, and lifestyle-related behaviors, thereby serving as a comprehensive indicator of population health status. Despite a substantial body of international literature, evidence at the local community level remains limited, particularly in Southern Italy, where socioeconomic and cultural factors may distinctively shape subjective representations and assessments of health.

The Health Perception Questionnaire (QPS) is a validated Italian-language instrument specifically designed to assess citizens’ multidimensional perceptions of health [4]. Unlike generic quality-of-life instruments, the QPS explores not only physical and psychological dimensions but also relational, spiritual, economic, and lifestyle-related aspects. This makes it particularly useful for investigating how populations perceive health at the community level.

The objective of public health initiatives should be to promote citizens’ empowerment, strengthen their agency with regard to their own health, and establish stable mechanisms for participation in decision-making processes that affect them [5]. This orientation is consistent with recent developments in the United Kingdom National Health Service, which, through community-centred and community-powered approaches, aims to build structural partnerships with communities by involving citizens and local organizations in the design, implementation, and evaluation of services [5].

Healthcare systems and public health institutions should invest in robust social, economic, and professional engagement with community life, in order to develop choices that are as closely aligned as possible with citizens’ lived experience. This means moving from “doing health for citizens” to “doing health with citizens” [5].

In this regard, nurses are ethically committed to transforming health policies and ensuring the systematic involvement of individuals and communities in health-related decisions [6]. Knowledge of health determinants makes it possible to direct professional actions toward modifiable factors, namely those susceptible to correction and transformation: individual lifestyles, social and community networks, living and working environments, and, finally, the political, social, economic, and cultural context [7]. Given the evolving and multidimensional nature of the concept under investigation and the need to intervene on factors influencing the health status of individuals and communities, it is essential to understand what the concept of “health” means for each individual. The international literature reviewed reports instruments for measuring outcomes related to subjective health, including those associated with quality of life [8] and perceived well-being [9]; however, in the specific population of the Province of Barletta-Andria-Trani (BAT), the available literature is currently extremely limited. The QPS is an instrument developed and validated by Bonetti et al. [4] with the aim of investigating the concept of health from the citizen’s perspective; the present study applies it to this specific geographical population in order to understand which individual variables may influence this concept in the Italian population [4].

 

Objective

This study, promoted by the University and Research Committee of the Order of Nursing Professions of BAT Province (OPI-BAT), aims to describe how citizens of the BAT Province conceptualize and perceive health using the Health Perception Questionnaire (QPS), and to explore possible associations between QPS scores and the main sociodemographic and clinical variables.

 

Materials and Methods

Study design

The study used an observational cross-sectional design. Data were collected using a standardized self-administered digital questionnaire delivered via tablet. The questionnaire included the 35-item QPS instrument, organized according to the original validated structure, and an additional section dedicated to participants’ sociodemographic and clinical characteristics.

Specifically, data were collected on age, sex, educational level, and occupational status. Clinical and medical-history information was also collected, including the presence of chronic diseases, any recent hospitalizations, and medication use. No additional psychometric instruments or scales other than the QPS were included.

 

Setting and participants

The study was conducted in five municipalities of the BAT Province in Puglia, Southern Italy, namely Andria, Barletta, Trani, Bisceglie, and Margherita di Savoia. Together, these municipalities account for the majority of the provincial population and provide adequate geographical and sociodemographic heterogeneity. Data were collected during public events, mainly on weekends, in order to maximize access to a heterogeneous adult population. Specifically, recruitment took place during health promotion and health-awareness initiatives organized by the Order of Nursing Professions (OPI-BAT), local health fairs, prevention campaigns, and community meetings open to citizens and organized in collaboration with the Local Health Authority of BAT.

Potential participants were recruited directly by the researchers, who were present at dedicated information stands or data collection points, and were invited to take part in the study through a brief presentation of its aims and participation procedures. Enrollment was voluntary.

Before participation, all subjects were provided with a digital information sheet, available on the tablets supplied to the researchers, containing the study objectives, data collection and processing procedures, guarantees of anonymity and confidentiality, and the possibility of withdrawing at any time without consequences. Informed consent was therefore obtained electronically directly on the device before completion of the questionnaire.

Data collection took place between 1 February 2026 and 31 March 2026. The inclusion criteria were: age ≥18 years, residence or domicile in the BAT Province, voluntary participation, and provision of digital informed consent. The exclusion criteria were: age <18 years, non-residence in the BAT Province, inability to understand Italian, and refusal to provide consent.

 

Sampling strategy

The sampling strategy adopted was non-probabilistic and based on quota convenience sampling, defined to proportionally reflect the age distribution of the adult population of the BAT Province according to ISTAT 2023 data [10]: 18–25 years (9.3%, n = 24), 26–44 years (30.7%, n = 79), 45–64 years (30.7%, n = 79), and ≥65 years (29.3%, n = 75), for a total sample of 257 participants. No formal a priori sample size calculation was performed, as the study was exploratory and descriptive in nature and aimed to provide an initial analysis of the phenomenon under investigation.

 

Data collection instrument

The QPS [4] is a validated 35-item self-report questionnaire that assesses individuals’ perception of health across several dimensions, including lifestyle behaviors, psychological well-being, relational and social aspects, spiritual health, economic factors, and biomedical perspectives.

Each item is rated on a 4-point Likert scale, where 1 indicates strongly disagree and 4 indicates strongly agree. The questionnaire was administered through the Microsoft Forms digital platform and could be accessed via a QR code. To ensure equitable participation among older adults and individuals with limited digital skills, the study authors were available during all data collection sessions to assist with questionnaire completion, including reading questions aloud when necessary.

 

Data analysis

Quantitative data were analyzed using Jamovi software (Version 2.6; [11]). Descriptive statistics, including means, standard deviations, and frequency distributions, were calculated for all QPS items and sociodemographic variables. Cronbach’s alpha was calculated to assess internal consistency in a geographical and cultural context different from that of the original validation study and thus to evaluate psychometric properties in different populations [12]. Following the method adopted by Bonetti et al. [4], responses to each item were dichotomized into two groups. Ratings of 3 (partially agree) and 4 (strongly agree) were considered agreement and coded as 1. Conversely, ratings of 1 (strongly disagree) and 2 (partially disagree) were classified as disagreement and coded as 0. Agreement frequencies for each item were then analyzed across the following subgroups: sex, age group, regular medication use, and presence of chronic disease, the four variables examined in the original study [4]. The chi-square test (χ²) was used for all comparisons, and Fisher’s exact test was applied when expected cell frequencies were below 5 [13]. For contingency tables showing a statistically significant overall association, post-hoc analyses were conducted using adjusted standardized residuals (ASRs) to identify the specific categories contributing to the observed association. Absolute ASR values greater than 1.96 were considered statistically significant, indicating that the observed frequency differed from the expected frequency under the null hypothesis at a two-tailed significance level of α = 0.05 [13]. Positive residuals indicated over-representation, whereas negative residuals indicated under-representation. Statistical significance was set at α = 0.05 (two-tailed).

 

RESULTS

Sample characteristics

A total of 257 participants were included in the analysis. The sociodemographic and clinical characteristics of the sample are shown in Table 1.

 

Variable	N	%
Sex
Female	138	53.7
Male	119	46.3
Age group
18–25 years	24	9.3
26–44 years	79	30.7
45–64 years	79	30.7
≥65 years	75	29.3
Education
Primary school	32	12.5
Lower secondary school	41	16.0
Upper secondary school	124	48.2
Bachelor’s degree	27	10.5
Master’s degree	30	11.6
PhD	3	1.2
Chronic disease
Yes	108	42.0
No	149	58.0
Regular medication use
Yes	124	48.2
No	133	51.8
Hospitalizations in the previous year
Yes	38	14.8
No	219	85.2

Table 1. Sociodemographic and clinical characteristics of the sample (N = 257).

 

The sample included 138 women (53.7%) and 119 men (46.3%). The largest age groups were those aged 26–44 years and 45–64 years, with 79 participants in each group, corresponding to 30.7% of the total. Most participants had completed education up to upper secondary school level, with 124 participants, representing 48.2% of the sample. Chronic disease was reported by 108 participants, corresponding to 42.0% of the group. Of the total sample, 124 individuals, or 48.2%, reported regular medication use. In addition, 38 participants, equal to 14.8%, had been hospitalized in the previous 12 months.

Internal reliability

The QPS showed very strong internal consistency across all 35 items (Cronbach’s alpha = 0.940), supporting its use as a measure of health perception in this sample.

 

Descriptive analysis of QPS items

Response distributions for each item (I1–I35) are reported in Table 2.

 

N	Item	Strongly disagree n (%)	Partially disagree n (%)	Partially agree n (%)	Strongly agree n (%)
1	Health is the desire to live	9 (3.5)	2 (0.8)	103 (40.1)	143 (55.6)
2	A healthy person feels free	8 (3.1)	18 (7.0)	103 (40.1)	128 (49.8)
3	A healthy person is active	8 (3.1)	17 (6.6)	104 (40.5)	128 (49.8)
4	Good sleep promotes health	7 (2.7)	18 (7.0)	79 (30.7)	153 (59.5)
5	A healthy person is able to ask for help	13 (5.1)	21 (8.2)	119 (46.3)	104 (40.5)
6	Physical activity is good for health	6 (2.3)	11 (4.3)	86 (33.5)	154 (59.9)
7	If I need ongoing care, I am ill	9 (3.5)	42 (16.3)	120 (46.7)	86 (33.5)
8	A balanced diet promotes health	6 (2.3)	13 (5.1)	87 (33.9)	151 (58.7)
9	Healthy people are physically fit	12 (4.7)	26 (10.1)	126 (49.0)	93 (36.2)
10	Health is influenced by social relationships	11 (4.3)	30 (11.7)	124 (48.2)	92 (35.8)
11	Healthy people follow a vegetarian diet	60 (23.3)	63 (24.5)	85 (33.1)	49 (19.1)
12	A healthy person is in harmony with themselves and with others	9 (3.5)	20 (7.8)	115 (44.7)	113 (44.0)
13	Taking medication is a sign of illness	28 (10.9)	59 (23.0)	106 (41.2)	64 (24.9)
14	The absence of worries is health	22 (8.6)	45 (17.5)	109 (42.4)	81 (31.5)
15	Family support promotes health	5 (1.9)	25 (9.7)	109 (42.4)	118 (45.9)
16	Having a satisfying sex life is an important component of health	7 (2.7)	26 (10.1)	122 (47.5)	102 (39.7)
17	Relationship difficulties can affect health	8 (3.1)	31 (12.1)	129 (50.2)	89 (34.6)
18	Being healthy means being independent	18 (7.0)	33 (12.8)	99 (38.5)	107 (41.6)
19	Health is influenced by economic well-being	19 (7.4)	27 (10.5)	132 (51.4)	79 (30.7)
20	Spiritual health is important	14 (5.4)	31 (12.1)	110 (42.8)	102 (39.7)
21	Being healthy means being free from worries	26 (10.1)	54 (21.0)	120 (46.7)	57 (22.2)
22	The absence of pain is a sign of good health	31 (12.1)	53 (20.6)	106 (41.2)	67 (26.1)
23	Paying attention to one’s environment promotes health	6 (2.3)	26 (10.1)	130 (50.6)	95 (37.0)
24	Psychological problems are a sign of illness	15 (5.8)	44 (17.1)	123 (47.9)	75 (29.3)
25	If I have no physical signs or symptoms, I am healthy	30 (11.7)	48 (18.7)	120 (46.7)	59 (23.0)
26	A healthy person prevents disease	21 (8.2)	31 (12.1)	117 (45.5)	88 (34.2)
27	A healthy person has an active social life	17 (6.6)	28 (10.9)	123 (47.9)	89 (34.6)
28	Healthy people do not have harmful habits (drug use, alcohol misuse, smoking, or gambling)	34 (13.2)	39 (15.2)	112 (43.6)	72 (28.0)
29	Being healthy means being free from disease	19 (7.4)	42 (16.3)	115 (44.7)	81 (31.5)
30	Having a healthy body weight means being healthy	15 (5.8)	26 (10.1)	119 (46.3)	97 (37.7)
31	A healthy person takes care of themselves	9 (3.5)	18 (7.0)	118 (45.9)	112 (43.6)
32	Having a job influences health	8 (3.1)	25 (9.7)	128 (49.8)	96 (37.4)
33	Sharing with others promotes health	9 (3.5)	18 (7.0)	117 (45.5)	113 (44.0)
34	Being depressed means being ill	20 (7.8)	34 (13.2)	114 (44.4)	89 (34.6)
35	Poor health increases vulnerability	7 (2.7)	20 (7.8)	120 (46.7)	110 (42.8)

Table 2. Distribution of responses to the 35 items of the Health Perception Questionnaire (QPS) (N = 257).

 

The five items with the highest level of agreement, corresponding to ratings of 3–4, were: I6—physical activity promotes health (93.4%), I8—a balanced diet promotes health (92.6%), I1—health is the desire to live (95.7%), I4—good sleep promotes health (90.3%), and I3—a healthy person is active (90.3%). Conversely, the items with the lowest levels of agreement were those reflecting a purely biomedical or reductionist view of health: I21—being healthy means being free from worries (68.9%), I22—absence of pain is a sign of good health (67.3%), I25—absence of physical symptoms means health (69.6%), I13—taking medication is a sign of illness (66.1%), and I11—healthy people follow a vegetarian diet (52.1%).

 

Inferential Analysis

Following the approach of Bonetti et al. [4], agreement frequencies for each QPS item (ratings 3–4) were compared across four sociodemographic and clinical subgroups: sex, age group, regular medication use, and presence of chronic diseases. The chi-square test was applied, while Fisher’s exact test was used when expected cell frequencies were below 5 [13]. Statistically significant results (p < 0.05) are presented in Table 3. Specifically, the table reports only those items showing at least one significant association (p < 0.05) among the items discussed in the text.

 

Item	Variable	Category	Agree n (%)	Disagree n (%)	χ²	df	p	Standardized residue (z)†
I6) Physical activity promotes health	Sex	Female	124 (48.2%)	14 (5.4%)	6.013	1	0.014	-2.45 ↓
		Male	116 (45.1%)	3 (1.2%)				+2.45 ↑
I11) Healthy people follow a vegetarian diet	Age group	18–25 years	6 (2.3%)	18 (7.0%)	19.416	3	< 0.001	-2.80 ↓
		26–44 years	35 (13.6%)	44 (17.1%)				-1.68
		45–64 years	40 (15.6%)	39 (15.2%)				-0.32
		≥65 years	53 (20.6%)	22 (8.6%)				+3.82 ↑
	Chronic disease	Yes	65 (25.3%)	43 (16.7%)	4.832	1	0.028	+2.20 ↑
		No	69 (26.8%)	80 (31.1%)				-2.20 ↓
I13) Taking medications is a sign of illness	Age group	18–25 years	11 (4.3%)	13 (5.1%)	17.259	3	< 0.001	-2.21 ↓
		26–44 years	47 (18.3%)	32 (12.5%)				-1.50
		45–64 years	49 (19.1%)	30 (11.7%)				-0.93
		≥65 years	63 (24.5%)	12 (4.7%)				+3.88 ↑
	Chronic disease	Yes	79 (30.7%)	29 (11.3%)	4.077	1	0.043	+2.02 ↑
		No	91 (35.4%)	58 (22.6%)				-2.02 ↓
I14) Being free from worries means being healthy	Sex	Female	95 (37.0%)	43 (16.7%)	4.005	1	0.045	-2.00 ↓
		Male	95 (37.0%)	24 (9.3%)				+2.00 ↑
	Age group	18–25 years	9 (3.5%)	15 (5.8%)	22.620	3	< 0.001	-4.27 ↓
		26–44 years	55 (21.4%)	24 (9.3%)				-1.05
		45–64 years	63 (24.5%)	16 (6.2%)				+1.42
		≥65 years	63 (24.5%)	12 (4.7%)				+2.36 ↑
	Regular medication use	Yes	99 (38.5%)	25 (9.7%)	4.340	1	0.037	+2.08 ↑
		No	91 (35.4%)	42 (16.3%)				-2.08 ↓
	Chronic disease	Yes	88 (34.2%)	20 (7.8%)	5.512	1	0.019	+2.35 ↑
		No	102 (39.7%)	47 (18.3%)				-2.35 ↓
I18) Being healthy means being independent	Age group	18–25 years	13 (5.1%)	11 (4.3%)	12.422	3	0.006	-3.35 ↓
		26–44 years	65 (25.3%)	14 (5.4%)				+0.57
		45–64 years	63 (24.5%)	16 (6.2%)				-0.11
		≥65 years	65 (25.3%)	10 (3.9%)				+1.68
	Regular medication use	Yes	106 (41.2%)	18 (7.0%)	4.277	1	0.039	+2.07 ↑
		No	100 (38.9%)	33 (12.8%)				-2.07 ↓
I21) Being healthy means being free from worries	Age group	18–25 years	9 (3.5%)	15 (5.8%)	23.072	3	< 0.001	-3.49 ↓
		26–44 years	48 (18.7%)	31 (12.1%)				-1.87
		45–64 years	56 (21.8%)	23 (8.9%)				+0.46
		≥65 years	64 (24.9%)	11 (4.3%)				+3.66 ↑
	Regular medication use	Yes	93 (36.2%)	31 (12.1%)	4.198	1	0.040	+2.05 ↑
		No	84 (32.7%)	49 (19.1%)				-2.05 ↓
	Chronic disease	Yes	86 (33.5%)	22 (8.6%)	10.056	1	0.002	+3.17 ↑
		No	91 (35.4%)	58 (22.6%)				-3.17 ↓
I22) Absence of pain is a sign of good health	Age group	18–25 years	9 (3.5%)	15 (5.8%)	29.001	3	< 0.001	-3.27 ↓
		26–44 years	47 (18.3%)	32 (12.5%)				-1.78
		45–64 years	50 (19.5%)	29 (11.3%)				-0.92
		≥65 years	67 (26.1%)	8 (3.1%)				+4.83 ↑
	Regular medication use	Yes	94 (36.6%)	30 (11.7%)	7.852	1	0.005	+2.80 ↑
		No	79 (30.7%)	54 (21.0%)				-2.80 ↓
	Chronic disease	Yes	82 (31.9%)	26 (10.1%)	6.278	1	0.012	+2.51 ↑
		No	91 (35.4%)	58 (22.6%)				-2.51 ↓
I24) Psychological problems are a sign of illness	Age group	18–25 years	14 (5.4%)	10 (3.9%)	16.751	3	< 0.001	-2.29 ↓
		26–44 years	60 (23.3%)	19 (7.4%)				-0.28
		45–64 years	55 (21.4%)	24 (9.3%)				-1.88
		≥65 years	69 (26.8%)	6 (2.3%)				+3.66 ↑
	Chronic disease	Yes	90 (35.0%)	18 (7.0%)	4.168	1	0.041	+2.04 ↑
		No	108 (42.0%)	41 (16.0%)				-2.04 ↓
I25) If I have no physical signs or symptoms, I am healthy	Age group	18–25 years	8 (3.1%)	16 (6.2%)	24.009	3	< 0.001	-4.06 ↓
		26–44 years	53 (20.6%)	26 (10.1%)				-0.59
		45–64 years	54 (21.0%)	25 (9.7%)				-0.30
		≥65 years	64 (24.9%)	11 (4.3%)				+3.51 ↑
	Regular medication use	Yes	95 (37.0%)	29 (11.3%)	5.496	1	0.019	+2.34 ↑
		No	84 (32.7%)	49 (19.1%)				-2.34 ↓
	Chronic disease	Yes	84 (32.7%)	24 (9.3%)	5.822	1	0.016	+2.41 ↑
		No	95 (37.0%)	54 (21.0%)				-2.41 ↓
I26) A healthy person engages in disease prevention	Sex	Female	103 (40.1%)	35 (13.6%)	4.858	1	0.028	-2.20 ↓
		Male	102 (39.7%)	17 (6.6%)				+2.20 ↑
	Regular medication use	Yes	106 (41.2%)	18 (7.0%)	4.853	1	0.028	+2.20 ↑
		No	99 (38.5%)	34 (13.2%)				-2.20 ↓
	Chronic disease	Yes	93 (36.2%)	15 (5.8%)	4.646	1	0.031	+2.16 ↑
		No	112 (43.6%)	37 (14.4%)				-2.16 ↓
I27) A healthy person has an active social life	Chronic disease	Yes	97 (37.7%)	11 (4.3%)	6.919	1	0.009	+2.63 ↑
		No	115 (44.7%)	34 (13.2%)				-2.63 ↓
I28) Healthy people have no vices (drugs, alcohol, smoking, gambling)	Age group	18–25 years	12 (4.7%)	12 (4.7%)	10.825	3	0.013	-2.46 ↓
		26–44 years	53 (20.6%)	26 (10.1%)				-1.07
		45–64 years	57 (22.2%)	22 (8.6%)				+0.13
		≥65 years	62 (24.1%)	13 (5.1%)				+2.53 ↑
	Regular medication use	Yes	96 (37.4%)	28 (10.9%)	3.996	1	0.046	+2.00 ↑
		No	88 (34.2%)	45 (17.5%)				-2.00 ↓
	Chronic disease	Yes	89 (34.6%)	19 (7.4%)	10.708	1	0.001	+3.27 ↑
		No	95 (37.0%)	54 (21.0%)				-3.27 ↓
I29) Being healthy means the absence of disease	Age group	18–25 years	14 (5.4%)	10 (3.9%)	10.816	3	0.013	-2.17 ↓
		26–44 years	59 (23.0%)	20 (7.8%)				-0.40
		45–64 years	57 (22.2%)	22 (8.6%)				-1.03
		≥65 years	66 (25.7%)	9 (3.5%)				+2.84 ↑
	Regular medication use	Yes	102 (39.7%)	22 (8.6%)	4.755	1	0.029	+2.18 ↑
		No	94 (36.6%)	39 (15.2%)				-2.18 ↓
	Chronic disease	Yes	91 (35.4%)	17 (6.6%)	6.577	1	0.010	+2.56 ↑
		No	105 (40.9%)	44 (17.1%)				-2.56 ↓
I30) Having a healthy weight means being healthy	Chronic disease	Yes	97 (37.7%)	11 (4.3%)	4.622	1	0.032	+2.15 ↑
		No	119 (46.3%)	30 (11.7%)				-2.15 ↓
I34) Being depressed means being ill	Age group	18–25 years	16 (6.2%)	8 (3.1%)	11.511	3	0.009	-1.56
		26–44 years	63 (24.5%)	16 (6.2%)				+0.20
		45–64 years	56 (21.8%)	23 (8.9%)				-2.12 ↓
		≥65 years	68 (26.5%)	7 (2.7%)				+2.95 ↑
	Chronic disease	Yes	94 (36.6%)	14 (5.4%)	7.271	1	0.007	+2.70 ↑
		No	109 (42.4%)	40 (15.6%)				-2.70 ↓

Table 3. Statistically significant associations between QPS items and sample characteristics (N = 257). Chi-square test (or Fisher’s exact test, where appropriate); percentages were calculated on the total sample.

 

In the last column of Table 3, the Adjusted standardized residuals (z) derived from post-hoc residual analysis were reported. Absolute values of |z| > 1.96 indicate categories that were significantly overrepresented (↑) or underrepresented (↓) relative to expected frequencies (α = 0.05, two-tailed test); these values are shown in bold.

Of the 140 combinations tested, comprising 35 items each evaluated across four variables, 28 associations (20.0%) were found to be statistically significant. Age group showed the strongest association, with 11 items displaying significant differences (I11, I13, I14, I18, I21, I22, I24, I25, I28, I29, I34). Items reflecting biomedical or symptom-free conceptions of health exhibited a consistent gradient of increasing agreement across older age groups: I22—absence of pain as an indicator of good health (18–25 years: 37.5% vs. ≥65 years: 89.3%), I21—being healthy means being free from worries, I14—absence of worries is health, and I25—absence of physical symptoms indicates good health (all p < 0.001). Item I11—healthy people follow a vegetarian diet—showed the steepest age-related gradient, with agreement increasing from 25.0% in the 18–25 age group to 70.7% among participants aged ≥65 years (p < 0.001).

The presence of a chronic disease was associated with significantly higher agreement on 11 items (I11, I14, I21, I22, I25, I26, I27, I28, I29, I30, I34). Regular medication use was associated with four significant items (I22, I25, I26, I29). Sex differences were limited to two items: I6—physical activity promotes health (p = 0.028; males: 97.5% vs. females: 89.9%) and I26—a healthy person engages in disease prevention (p = 0.041).

 

DISCUSSION

The findings of this survey provide a clear picture of how health is conceptualized among residents of the BAT Province. Most participants did not conceptualize health as a narrowly biomedical construct. For most participants, being healthy means being active, maintaining social relationships, eating well, sleeping well, and feeling free, rather than simply being free from disease diagnoses. This perspective is consistent with the World Health Organization’s definition of health [1] and with Antonovsky’s salutogenic model [14], which conceptualizes health in terms of the resources individuals draw upon to cope with everyday challenges rather than the mere absence of pathology.

The QPS showed excellent reliability in this sample. A Cronbach’s alpha of 0.940 indicates excellent internal consistency and confirms the value reported in the Italian validation study [4]. This finding is encouraging, as it suggests that the instrument performs well not only in Northern Italy, where it was originally tested, but also in Southern Italian populations. The five items receiving the highest levels of agreement—physical activity, balanced nutrition, adequate sleep, vitality, and active self-care—indicate a conception of health as an active process, something that is cultivated and maintained rather than simply experienced.

These findings are consistent with a growing body of evidence showing that health beliefs among citizens, both in Italy and internationally, are increasingly oriented toward behavioral determinants of health, moving away from passive and exclusively disease-centred models [15,16]. The fact that 95.7% of respondents agreed with the statement “health is the desire to live” (I1) effectively summarizes this perspective: for the participants in this study, health is not merely the absence of disease but, more importantly, an attitude toward life and the way it is lived [17].

The item generating the greatest disagreement, namely “healthy people follow a vegetarian diet” (I11; 47.9% disagreement), warrants brief consideration. Southern Italy, characterized by one of the world’s most deeply rooted Mediterranean dietary traditions, may have led participants to distinguish between healthy eating and adherence to a specific vegetarian dietary pattern. This finding should not necessarily be interpreted as a rejection of healthy nutrition, but rather as a culturally shaped reluctance to equate health with a single dietary model. Results such as these highlight the importance of interpreting health perception instruments within their cultural context. However, the low level of agreement with this item may not be attributable solely to cultural factors. It may also reflect an inherent limitation in the item’s wording, which appears to imply a direct and exclusive association between health and vegetarianism. This ambiguity has already been noted in the literature [4], and its recurrence in the present sample suggests a potential limitation of the instrument that should be considered in future revision and adaptation processes.

Age emerged as the variable most strongly associated with differences in health perceptions. Older adults consistently showed higher levels of agreement with items defining health in terms of the absence of symptoms, pain, medication use, or visible signs of illness. This generational difference likely reflects two complementary factors. On the one hand, many individuals aged 65 years and older were socialized within a more traditional conception of health. On the other hand, they have direct experience of age-related physical decline. As individuals experience increasing age-related physical limitations, the absence of symptoms may indeed come to be perceived as synonymous with good health.

Post-hoc analysis of adjusted standardized residuals (ASRs) [14], conducted for all associations found to be significant in the chi-square analyses, provided insight beyond the overall statistical significance by identifying the specific categories contributing most strongly to each association. An adjusted standardized residual measures, for each cell in a contingency table, the difference between observed and expected frequencies under the assumption of independence, expressed in standard deviation units. Absolute values greater than 1.96 indicate a statistically significant deviation (α = 0.05), with positive values indicating over-representation and negative values indicating under-representation relative to expected frequencies.

In the present sample, for nearly all items reflecting a biomedical conception of health (I11, I14, I21, I22, and I25), individuals aged ≥65 years consistently displayed the highest positive residuals (ASRs ranging from +2.36 to +4.83), whereas participants aged 18–25 years showed the most pronounced negative residuals (ASRs ranging from −2.80 to −4.27). Therefore, it was specifically the oldest age group, rather than a generic age-related trend, that primarily drove the significance of these associations. This level of detail, obtainable only through residual analysis rather than the overall chi-square p-value, strengthens the clinical interpretation that the lived experience of ageing is specifically associated with a symptom-oriented view of health.

Sex differences were limited but interpretable. Men showed higher agreement with items relating to physical activity as a health-promoting behavior (I6) and to the belief that a healthy person actively prevents disease (I26). These patterns are consistent with previous literature reporting sex-specific health behaviors, whereby men tend to associate health more strongly with physical performance and preventive actions [4]. The absence of significant sex differences across most other items suggests that, at least within this sample, men and women share broadly similar conceptions of health.

Participants with chronic diseases showed higher levels of agreement with biomedical-oriented items (I21, I22, I28, and I29) compared with participants without chronic conditions. At first glance, this finding may appear counterintuitive, as individuals living with chronic illness might be expected to develop a more complex understanding of health. However, the result is consistent with the findings reported by Bonetti et al.; the lived experience of disease may reinforce symptom-centred conceptions of health rather than challenge them. Similarly, individuals who reported regular medication use were more likely to agree that health is characterized by the absence of physical symptoms (I25) and pain (I22). This further suggests that the daily experience of managing health conditions influences—and may sometimes narrow—the way health itself is conceptualized.

From a nursing perspective, perhaps the most noteworthy finding is that participants rarely defined health as merely the absence of disease. Several concepts traditionally emphasized in nursing health education—including physical activity (I6), maintaining a healthy weight (I30), avoiding substance misuse (I28), and practicing active self-care (I31)—received widespread support. This provides nurses with a concrete starting point for health promotion interventions. By encouraging healthy behaviors, nurses can build upon individuals’ existing understanding of health rather than attempting to challenge deeply rooted biomedical beliefs. Understanding what health means to each person is not an ancillary aspect of care but a fundamental prerequisite for delivering genuinely person-centred nursing practice.

These findings should also be considered within the broader context of evidence concerning territorial health inequalities in Italy. National studies based on data from the ISTAT Multipurpose Household Survey have consistently shown that self-rated health is less favorable in Southern Italy than in Central and Northern regions, with this disparity becoming more pronounced in recent years and particularly affecting women [19]. Similar geographic gradients are also reflected in ISTAT indicators of healthy life expectancy, which document a structural disadvantage for Southern Italy compared with the North. This national picture is broadly consistent with the present findings. Despite living in a southern Italian context, residents of the BAT Province reported high levels of agreement with items related to active and health-promoting lifestyles. This suggests that subjective conceptions of health do not necessarily align with objective population health indicators but may instead be shaped by local cultural factors, including the Mediterranean dietary tradition and the strong social and community networks typically found in small- and medium-sized Southern Italian settings. However, it should be noted that, to our knowledge, no other Italian studies have applied the QPS instrument in different provinces or regions. Consequently, direct comparison with the original validation study conducted in Northern Italy [4] remains the only instrument-specific benchmark currently available.

Limitations

Several limitations should be considered when interpreting the findings of this study. First, although the quota convenience sampling strategy was designed to reflect the age distribution of the BAT Province according to ISTAT 2023 data, participants were not selected through random sampling. This introduces a potential risk of selection bias and limits the generalizability of the findings to the entire adult population of the province (approximately 300,000 inhabitants).

Second, the cross-sectional design provides a snapshot of participants’ health perceptions at a single point in time and does not allow causal inferences to be drawn regarding the relationships between sociodemographic characteristics and health perceptions.

Third, the dichotomization of Likert-scale responses (1–2 vs. 3–4), although consistent with the methodological approach adopted by Bonetti et al. [4], may have resulted in some loss of information and reduced the discriminative capacity of the analyses.

Additional sources of bias should also be acknowledged. These include social desirability bias, particularly among participants who received assistance from study personnel while completing the questionnaire, potentially leading to unintentional influence on responses; non-response bias, whereby individuals who declined participation may systematically differ from those who took part; and possible incidence–prevalence bias resulting from the over- or under-representation of individuals with chronic diseases or polypharmacy compared with the resident adult population.

Finally, the absence of a formal a priori sample size calculation represents a further limitation. Although this may be justified by the exploratory nature of the study, future research should aim to overcome this limitation through probabilistic sampling strategies and adequately powered study designs.

 

CONCLUSIONS

In conclusion, residents of the BAT Province generally conceptualize health in a holistic manner, considering not only the body but also lifestyle, interpersonal relationships, and mental well-being as essential components of overall health. A purely biomedical perspective, defining health simply as the absence of disease or symptoms, was endorsed by only a minority of participants. Most respondents recognized that an individual may still perceive themselves as healthy while living with a chronic condition or undergoing ongoing treatment.

This finding is particularly relevant, as it has direct implications for how nurses and other healthcare professionals interact with patients and develop care plans [4]. Future research should employ probabilistic sampling methods across different Italian provinces to determine whether these patterns are consistent nationwide and to explore potential regional differences. Longitudinal studies may also help clarify whether individuals’ perceptions of health change over time, for example following significant health-related experiences or as a consequence of ageing. Finally, the QPS appears to be a useful instrument for nursing assessment, as it captures what health means to each individual—precisely the type of information required to support person-centred care [4].

 

Ethical Statements

The study protocol received formal approval from the Ethics Committee of the University Hospital of Foggia (Approval No. 17/CE/2026) on 26 February 2026. The study was conducted in accordance with the principles of the Declaration of Helsinki (2013 revision) [18] and the General Data Protection Regulation (GDPR—EU Regulation 2016/679). Digital informed consent was obtained from all participants prior to data collection. Participation in the study was voluntary and completely anonymous. No personally identifiable data were collected from participating subjects.

 

Conflicts of Interest

The authors declare that they have no conflicts of interest related to this study.

 

Funding

No specific funding was received for this study.

 

Author Contributions

Conceptualization: D.P., Data curation: G.G., E.B., D.P., B.D. Formal analysis: E.B. Supervision: F.R., E.B., D.P. Visualization: M.B., G.P., F.R. Writing – original draft: G.G., E.B., V.S. Writing – review & editing: E.B., D.P., G.G. All authors critically revised the manuscript for important intellectual content and approved the final version for submission. E.B. is the corresponding author.

 

Acknowledgements

The authors would like to thank all individuals who dedicated their time to this project, particularly those who contributed to data collection and all participants who completed the questionnaire.

 

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1. Institute of Nursing Sciences and Research, Malabar Cancer Centre [PGIOSR], Thalassery, Kerala, India.

* Corresponding author: Binuja P., Associate Professor, Institute of Nursing Sciences and Research, Malabar Cancer Centre (PGIOSR), Thalassery, Kerala, India.

E-mail: binu.ombhavan@gmail.com

Cite this article

 

ABSTRACT

Introduction: Nomophobia, the fear or anxiety of being without access to a mobile phone, is an emerging behavioural health issue among young adults. Nursing students frequently use smartphones for academic and social purposes, making awareness of nomophobia essential for promoting healthy technology use.

Objective: To assess the level of knowledge regarding nomophobia among student nurses and to determine its association with selected socio-demographic variables.

Materials and Methods: A descriptive cross-sectional study with an exploratory approach was conducted among 100 B.Sc. Nursing students at a selected college in Thalassery, Kerala. Participants were selected using simple random sampling (lottery method). Data were collected using a structured, self-administered questionnaire consisting of socio-demographic variables and 15 multiple-choice questions assessing knowledge of nomophobia. Each correct response was awarded one mark (total score: 0–15). Content validity was established through expert evaluation (CVI = 0.85), and reliability was confirmed using test–retest and internal consistency methods (Cronbach’s alpha = 0.83). Descriptive and inferential statistics were applied for data analysis.

Results: Among the participants, 52% demonstrated good knowledge, 47% had average knowledge, and 1% had poor knowledge regarding nomophobia. Significant associations were found between knowledge level and age (p = 0.002), academic position (p < 0.001), and years of mobile phone usage (p = 0.003). No significant association was observed between knowledge and gender, type of mobile phone used, participation in public seminars, or primary reason for mobile phone use (p > 0.05).

Conclusion: Although the majority of nursing students had good knowledge regarding nomophobia, a considerable proportion demonstrated only average awareness. Educational interventions and integration of digital well-being concepts into the nursing curriculum are recommended to enhance knowledge and encourage responsible smartphone use.

Keywords: Nomophobia, nursing students, knowledge, smartphone use, digital well-being, cross-sectional study.

 

INTRODUCTION

Mobile phones play such a significant role in today’s lives. It helps to stay connected with others and provide us a sense of security. It aids in work, chat with family and friends, take pictures, buy clothes or books, and even control home appliances. With the increasing affordability and accessibility of smartphones, dependency on these devices has become a growing concern.
Nomophobia, a term coined to denote “no mobile phone phobia,” describes the discomfort or anxiety caused by being out of contact with a mobile device or disconnected from digital communication [1]. The impact of nomophobia on students is multifaceted, influencing their mental well-being, academic performance, social relationships, and overall quality of life. Research on smartphone addiction consistently shows that excessive and compulsive mobile phone use can contribute to numerous health concerns, including increased anxiety, depressive symptoms, and disturbances in sleep patterns. These effects highlight the growing need to understand and address nomophobia as a significant issue among students [2].
In today’s digitally connected world, university and college students—especially those enrolled in healthcare and nursing programs—are increasingly dependent on smartphones for academic activities, communication, clinical learning, and social engagement. Evidence from a recent systematic review and meta-analysis involving 11,219 nursing students demonstrated that 28% experienced mild, 49% moderate, and 15% severe nomophobia, highlighting the widespread nature of this phenomenon. The high prevalence of nomophobia among future healthcare professionals necessitates greater attention to preventive and intervention strategies within nursing education settings to promote healthy technology use and psychological well-being. [3].
Recent study conducted among BSc nursing students in Kollam, Kerala, showed that most students used smartphones for about five hours daily, with 42% checking their phones fewer than ten times a day. The mean age was 21 years. Only 2% of students had severe nomophobia, while 33% had moderate and 54% had mild levels; 11% had no nomophobia [4].
Research indicates that students with mobile phone addiction often exhibit reduced learning ability, poor concentration, and increased distractibility, all of which negatively affect academic performance. This issue is particularly concerning in the field of nursing education, where students are expected to develop strong clinical judgment, attention to detail, and professional responsibility [5].
In health-care settings, the presence of nomophobia among nursing students can have serious implications. Excessive phone use may lead to neglect of essential tasks, forgetting critical patient information, making careless errors, and ultimately compromising the quality of patient care. As future health-care providers, nursing students must be aware of the risks associated with uncontrolled mobile phone use. Therefore, assessing the knowledge regarding nomophobia among nursing students is vital.
This study aims to assess student nurses’ knowledge regarding nomophobia to promote awareness and encourage preventive measures. This concern is crucial, considering that the future workforce of nursing must manage modern digital tools responsibly, maintaining balance between technological benefits and the risks of over dependence.

Research question

1. What is the knowledge level of student nurses regarding nomophobia?
2. What factors are significantly associated with the level of knowledge regarding nomophobia among student nurses?

Objective

1. To assess the knowledge regarding nomophobia among nursing students.
2. To find the association between knowledge regarding nomophobia and selected socio-demographic variables among nursing students.

 

MATERIALS AND METHODS

Research Design and Approach

A descriptive cross-sectional design with an exploratory approach was adopted for the present study, to assess the knowledge level regarding nomophobia among nursing students. The descriptive design was considered appropriate to describe and document the existing level of knowledge and to determine the association between knowledge scores and selected socio-demographic characteristics. The exploratory approach was used to gain insights into the level of awareness and understanding of nomophobia, an emerging behavioural health issue among students.

Study Design and Setting

This study adopted a descriptive cross-sectional design and was conducted in a reputed college of nursing in Thalassery, Kerala, India. The setting was selected based on accessibility, feasibility, and the availability of an adequate number of participants to meet the study objectives.

Study Population

The study population comprised undergraduate student nurses enrolled in the Bachelor of Science in Nursing (B.Sc. Nursing) program. Students from all academic years (first, second, third, and fourth year) were considered eligible. Students who were absent during the data collection period and those unwilling to participate were excluded from the study.

Sample Size and Sampling Method

The sample size consisted of 100 undergraduate nursing students. The size was determined based on feasibility and the availability of eligible participants within the study setting and was considered adequate for a descriptive cross-sectional study aimed at assessing knowledge levels.
A simple random sampling technique was employed using a computer-based lottery method to ensure unbiased selection of participants.

Sampling Details

A comprehensive list of all eligible students across the four academic years was obtained from institutional records, forming the sampling frame. Each student was assigned a unique identification number. These identification numbers were entered into a computer database, and randomization was performed using Microsoft Excel’s random number generator.
The list was then randomized, and the first 100 unique identification numbers generated were selected as study participants. This procedure ensured that each eligible student had an equal and independent probability of selection, thereby minimizing selection bias and enhancing the transparency and replicability of the sampling process.

Recruitment of Students

The selected students were approached and informed about the purpose and nature of the study. Participation was voluntary, and informed consent was obtained prior to data collection. Students who declined participation or were unavailable at the time of data collection were excluded

 

Variables

Socio-demographic variables

Included age, gender, year of study, type of mobile phone used, participation in public seminars, years of mobile phone usage, and most frequent reason for using mobile phones.

 

Research variable
Knowledge regarding nomophobia

 

Tool and Technique

A structured questionnaire developed by the researcher was used as the tool for data collection. The tool was prepared after extensive literature review and expert consultation due to the non-availability of a standardized instrument for measuring knowledge on nomophobia.
The development of the questionnaire was guided by existing conceptual frameworks of nomophobia and related instruments, particularly the Nomophobia Questionnaire (NMP-Q) [6], which identifies key dimensions of mobile phone dependence. Core domains derived from the literature included fear of being unable to communicate, loss of connectedness, inability to access information, and excessive reliance on mobile devices. While the NMP-Q primarily assesses the severity of nomophobia, these domains were adapted to generate knowledge-based items appropriate for nursing students. Furthermore, principles from behavioural addiction and technology dependence were incorporated to ensure a comprehensive conceptual foundation. The questionnaire encompassed items related to the definition, causes, symptoms (early and late), consequences, management and prevention of nomophobia. The tool consisted of two sections:

Section A – contained seven items related to socio-demographic data such as age, gender, academic year, type of mobile phone, participation in public seminars for raising awareness regarding adverse effects of mobile phone, duration of mobile phone use, and main reason for mobile phone usage.

Section B – comprised of 15 multiple-choice questions to assess knowledge related to nomophobia, including its definition, characteristics, signs and symptoms, predisposing factors, health impact, preventive measures, and management. Each correct response was awarded one mark, and incorrect responses received zero marks. The total possible score ranged from 0 to 15 and was graded as follows: scores 11–15 was considered as good knowledge, scores 6–10 as average knowledge, and scores 0–5 as poor knowledge.

 

Validity and Reliability of the tool

The content validity of the instrument was established (CVI -0.85) through evaluation by a panel of experts. Based on their feedback, modifications were made for clarity and relevance. The reliability of the tool was assessed through the test-retest method and internal consistency analysis, which confirmed that the tool was reliable for use with Cronbach Alpha value of 0.83.

 

Pilot study

A pilot study was conducted among 10 nursing students to evaluate the feasibility, clarity, and practicability of the instrument and study procedures. Participant feedback indicated that the items were generally clear; however, minor issues related to wording and item sequence were identified. Based on these observations, slight modifications were made to improve clarity and ensure a logical flow of the questionnaire. The pilot study also provided insights into the time required for completion and the ease of administration of the tool. No significant difficulties were encountered during data collection. Overall, the pilot findings confirmed the feasibility of the study and the suitability of the instrument for the main study.

 

Data collection

Data collection was carried out on a convenient date and time, scheduled in consultation with the course coordinators of each batch. Participants were assembled in a classroom setting, and written informed consent was obtained prior to participation. They were assured of the anonymity and confidentiality of their responses and informed that participation was voluntary, with the right to withdraw at any time without any consequences. Following this, the questionnaire was administered by the researchers. Clear and standardized instructions regarding the purpose of the study, method of responding, and time allocation were provided prior to administration. The questionnaire was self-administered, and participants were given 20 minutes for completion. No personal identifiers were collected to ensure anonymity. The researchers remained in the classroom during data collection to address procedural queries without influencing participants’ responses. All completed questionnaires were collected immediately after the allotted time.

 

Ethical consideration

The study protocol adhered to the ethical principles outlined in the Declaration of Helsinki and was approved by the Institutional Review Board (IRB) and the Institutional Ethics Committee (IEC) of Malabar Cancer Centre (PGIOSR) (No. 161/IEC-ERC/13/MCC/22-8-2023, dated 22 August 2023).

Formal administrative permission to conduct the study was obtained from the study setting.
Informed consent was obtained from all participants. Anonymity and confidentiality of the data were maintained throughout the study.

 

Statistical analysis

Statistical analysis was performed using SPSS Statistics version 25. Both descriptive and inferential statistical methods were employed. Descriptive statistics, including frequency and percentage, were used to summarize the socio-demographic characteristics of the participants and their knowledge levels regarding nomophobia. Inferential statistical analysis was carried out to examine the association between selected socio-demographic variables and knowledge regarding nomophobia. The Pearson Chi-square test was used when the assumptions for Chi-square analysis were satisfied. Fisher’s Exact Test was applied for 2×2 contingency tables with low expected cell frequencies, whereas the Fisher–Freeman–Halton Exact Test was used for larger contingency tables in which more than 20% of the cells had expected frequencies less than 5. As only one participant was categorized under poor knowledge, the poor and average knowledge categories were merged for inferential analysis to ensure the validity of the statistical tests. A p-value of less than 0.05 (p < 0.05) was considered statistically significant. The results were organized and presented in tables and, where appropriate, in figures, following appropriate analysis and interpretation.

 

RESULTS

A total of 100 questionnaires were distributed to the study participants, all of which were completed and returned, resulting in a 100% response rate. The collected data were included in the final analysis, and a summary of the sample’s socio-demographic characteristics is presented in Table 1.

Variable	Frequency (n)	Percentage (%)
Age 18 19 20 21 22 23	06 21 23 22 26 02	06 21 23 22 26 02
Gender Male Female	12 88	12 88
Academic position 1st Year 2nd Year 3rd Year 4th Year	01 47 26 26	01 47 26 26
Type of Mobile phone used Basic Mode Advanced Mode	04 96	04 96
Reason for using Mobile phone Calling Gaming Social networking Texting	12 02 78 08	12 02 78 08
Duration of Mobile phone usage For 2 years 2-3 years More than 3 years	16 23 61	16 23 61
Participation in public seminars/ conferences Yes No	46 54	46 54

Table 1. Frequency and percentage distribution of sample according to socio-demographic variables (N=100).

The majority of the sample (26%, n = 26) were aged 22 years, whereas 6% (n = 6) were 18 years and 2% (n = 2) were 23 years. The sample was predominantly female (88%, n = 88), with males comprising 12% (n = 12).</
In terms of academic position, nearly half of the participants were second-year B.Sc. Nursing students (47%, n = 47), while only 1% (n = 1) were from the first year. A large proportion of participants (96%, n = 96) used advanced mobile phones, compared to 4% (n = 4) using basic models.

Regarding the duration of mobile phone use, 61% (n = 61) reported usage for more than 3 years, 23% (n = 23) for 2–3 years, and 16% (n = 16) for up to 2 years. Social networking was the most common purpose of mobile phone use (78%, n = 78), whereas gaming was reported by only 2% (n = 2) of participants.</
More than half of the participants (54%, n = 54) had not attended any public seminars or conferences related to the adverse effects of mobile phone use, while 46% (n = 46) reported participation in such programs.</

Level of Knowledge	Frequency (f)	Percentage (%)
Poor Average Good	1 47 52	1.0 47.0 52.0

Table 2. Frequency and percentage distribution of sample based on level of knowledge regarding nomophobia (N=100).

Table 2 shows that most of the sample 52 (52%) have good knowledge regarding nomophobia, 47(47%) have average knowledge and 1 (1%) had poor knowledge.

Table 3 depicts the association between socio-demographic factors and knowledge regarding nomophobia. In particular, for the inferential analyses presented in Table 3, the “Poor” and “Average” categories shown in Table 2 were merged into a single category due to the limited number of observations in the “Poor” category.</

Variable	Knowledge regarding Nomophobia		Test Statistic	df	p-value
	Average	Good
Age 18 19 20 21 22 23	03 13 15 13 03 01	03 08 08 09 23 01	Fisher–Freeman–Halton Exact Test	⎯	0.002
Gender Male Female	08 40	04 48	χ² = 1.904	1	0.168
Academic position 1st year 2nd year 3rd year 4th year	0 30 14 04	01 17 12 22	– Fisher–Freeman–Halton Exact Test	⎯	<0.001
Type of mobile phone used Basic mode Advanced mode	03 45	01 51	Fisher’s Exact Test	⎯	0.27
Duration of mobile phone use For 2 years 2 to 3 years More than 3 years	12 15 21	04 08 40	χ² = 11.9	2	0.003
Most frequent reason for using mobile phone Calling Gaming Social networking Texting	06 01 38 03	06 01 40 05	Fisher–Freeman–Halton Exact Test	⎯	0.092
Participation in public seminars Yes No	19 29	27 25	χ² = 1.53	1	0.216

Table 3. Association between knowledge regarding nomophobia and selected socio-demographic variables. Significant tests were reported in bold in the table.

The results indicated that there is a significant association between knowledge regarding nomophobia
and the variables age, academic position, and duration of mobile phone usage at (p < 0.05). No significant association was found between knowledge regarding nomophobia and gender, type of mobile phone used, participation in public seminars, and with the reason for using mobile phones.

 

DISCUSSION

The present study found that more than half of the nursing students (52%) demonstrated good knowledge regarding nomophobia, while 47% had average knowledge and only 1% had poor knowledge. These findings suggest that the majority of participants had satisfactory awareness of nomophobia and its potential consequences.
These findings contrast with those reported by Shalini et al. [7], who found that only 8.3% of nursing students had good knowledge regarding nomophobia, whereas 50% demonstrated poor knowledge. In contrast, a study evaluating a structured teaching programme among nursing students reported a significant improvement in knowledge following the intervention, highlighting the effectiveness of educational strategies in enhancing awareness regarding nomophobia [8]. Similarly, a study among college students in Punjab found that most participants had good knowledge of smartphone use and nomophobia [9]. Collectively, these findings suggest increasing awareness of nomophobia among young adults and support the value of educational interventions in promoting knowledge regarding responsible smartphone use.
The present findings are particularly relevant in light of growing international evidence highlighting the burden of nomophobia among university and nursing students. A systematic review and meta-analysis by Tuco et al. [10] reported high prevalence rates of moderate and severe nomophobia among university students worldwide. Likewise, Guillari et al. [11] identified moderate-to-severe nomophobia among a substantial proportion of nursing students and reported associations with psychological distress, anxiety, depression, sleep disturbances, impaired academic performance, reduced concentration, and potential risks to patient safety during clinical practice. Similarly, Lazo-Caparros et al. [12] demonstrated significant associations between problematic smartphone use and adverse psychological, academic, and clinical outcomes among nursing students. Recent primary studies have further documented a high prevalence of nomophobia among nursing students and its associations with social anxiety, procrastination, smartphone-use behaviours, and academic factors [3,13–16]. Moreover, nomophobia has been shown to be strongly associated with smartphone addiction and distraction, suggesting that excessive smartphone dependence may contribute to broader behavioural and psychological concerns [17]. Collectively, these studies indicate that nomophobia is a prevalent and multifaceted phenomenon among university and nursing students, with important implications for psychological well-being, academic performance, and professional practice. Although the present study assessed knowledge regarding nomophobia rather than its prevalence, the high prevalence reported internationally underscores the importance of ensuring that nursing students possess adequate awareness of the condition and its consequences.
In the present study, age, academic position, and years of mobile phone use were significantly associated with knowledge regarding nomophobia. These findings are consistent with previous studies that identified age- and education-related factors as important determinants of awareness regarding nomophobia [7,18]. The significant association between years of mobile phone use and knowledge may reflect greater exposure to both the benefits and adverse effects of smartphone use over time, thereby increasing awareness of smartphone-related behavioural concerns [19]. In contrast, gender, type of mobile phone, participation in public seminars, and the primary reason for mobile phone use were not significantly associated with knowledge. The absence of a gender difference is consistent with findings reported by Khummukcham and Thomas [20], although studies conducted in other settings have reported higher nomophobia levels among female students, suggesting possible cultural and contextual influences on smartphone-use patterns [21].
While previous research has predominantly focused on the prevalence, predictors, and psychosocial consequences of nomophobia, relatively few studies have examined nursing students’ knowledge regarding the condition. The present study contributes to addressing this gap by demonstrating that a majority of nursing students possess good knowledge regarding nomophobia and by identifying factors associated with knowledge levels. Nevertheless, knowledge alone may not necessarily translate into healthy smartphone-use behaviours. Given the growing evidence linking nomophobia with adverse psychological, academic, and clinical outcomes, integrating educational content on digital health, responsible smartphone use, and digital professionalism into nursing curricula is warranted. Such interventions may enhance awareness, promote healthier technology-use behaviours, strengthen professional conduct, and contribute to safer patient care in clinical settings.

Implications

The findings emphasize the growing awareness of nomophobia among nursing students. However, nearly half of the participants still had only average or poor knowledge, indicating a need for continuous educational interventions, workshops, and curriculum integration focusing on digital dependency and its psychosocial consequences.

Limitations of the study

The study was conducted among 100 nursing students from a single institution, which limits the generalization of the findings to other colleges or universities. As the study used a descriptive cross-sectional design, it captured data at one point in time and could not determine causality or changes in knowledge over time.
The use of a self-administered questionnaire may have introduced self-report bias, as participants’ responses could have been influenced by social desirability and recall bias. Additionally, participants may have tended to complete all items in the knowledge questionnaire, potentially resorting to guessing, which could have introduced bias in the assessment of knowledge levels.

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors.

Conflict of interest

The authors report no conflict of interest.

Authors’ contribution

Dr. Rohini T.: Conception, Design, Supervision, Funding, Materials, Data Collection and Processing, Analysis and Interpretation, Literature Review, Writing and Critical Review

Dr. Binuja P.: Conception, Design, Supervision, Funding, Materials, Data Collection and Processing, AnalysisandInterpretation, LiteratureReview, Writing and Critical Review

Prof. Naveesh P.K.: Literature Review, Writing, Critical Review

Ms. Maneeja S.S.: Literature Review, Writing, Critical Review
Ms. Sreetha P.: Literature Review, Writing, Critical Review
Ms. Linju T.K.: Literature Review, Writing, Critical Review
Ms. Rinjuna K.P.: Literature Review, Writing, Critical Review

Acknowledgements

Dr. Ratheesan K. (Lecturer in Biostatistics),
Ms. Jisha Abraham (Lecturer in Psych oncology)
Ms. Arunima.P.K., Ms. Arya.A.K., Ms. Aswani.C.P., Ms. Aswani. I.T.K.,
Ms. Athira T., Ms. Sonima K.P., Ms. Soorya N., Ms. Stephy Mathew
Ms. Surabhi.U.S., Ms. Surya Govindan (B.Sc. Nursing students).

 

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

1. Department of Nursing, Elizabeth Rani College of Nursing and Allied Health Sciences Mardan, Khyber Pakhtunkhwa, Pakistan.
2. Department of Management Sciences, Abasyn University Peshawar, Khyber Pukhtunkhwa,
3. Institute of Public Mental Health and Behavioral Science, Khyber Medical University, Khyber Pakhtunkhwa, Pakistan.

* Corresponding author: Abdur Rahman, Department of Nursing, Elizabeth Rani College of Nursing and Allied Health Sciences Mardan, Khyber Pakhtunkhwa, Pakistan.

E-mail: abdur.rahman.hea@gmail.com

Cite this article

 

ABSTRACT

Introduction: Diabetes mellitus is a growing worldwide health issue. Nursing students are the future health workforce who should have adequate knowledge and clinical practice skills to manage the disease. In nursing, however, there has been shown to be significant variation in diabetes education programs.

Aim: (1) assess perceived and actual diabetes knowledge among nursing students in Pakistan; (2) quantify the discrepancy between self-assessed and objectively measured competence; and (3) identify demographic and educational predictors of both perceived and actual knowledge.

Methods: A cross-sectional descriptive study was conducted among 423 nursing students from four nursing colleges in Pakistan from September 2024 to January 2025. A validated questionnaire was used to measure the knowledge and skills of nursing students and consisted of three sections: a) demographic information; b) self-reported knowledge (20 items measured using a 4-point Likert scale); and c) actual knowledge (50 multiple-choice questions). Descriptive, independent t-test, ANOVA, Pearson correlation and multiple linear regression were used for statistical analysis.

Results: The mean actual knowledge score was 33.69 ± 7.45 (67.4%). Acute complications and foot care had the highest scores (79.6% and 75.6%, respectively) while the lowest scores were obtained in oral antidiabetic drugs and insulin therapy (53.4% and 62.2%, respectively). The mean self-reported knowledge was 52.34 ± 10.87 (65.4%). They underestimated their knowledge (actual > self by 2.0%, p = 0.01). Actual knowledge predictors were: year of study (internship: β = 5.89, p < 0.001); clinical experience (β = 3.45, p < 0.001); formal training (β = 4.28, p < 0.001); workshop attendance (β = 3.89, p < 0.001); family history of diabetes (β = 1.98, p < 0.001); and self-assessed knowledge (β = 0.21, p < 0.001). The regression model explained 57.2% of the variance (R² = 0.584, adjusted R² = 0.572, p < 0.001).

Conclusions: Students demonstrated moderate diabetes knowledge (67.4% correct) but revealed clinically important discrepancies between perceived and actual competence. While 42.1% accurately self-assessed, 21.0% overestimated and 36.9% underestimated their knowledge. The largest knowledge gaps were in pharmacological management (oral antidiabetics: 53.4% correct) and diabetes technologies (continuous glucose monitoring: 31.7% correct). Nursing practitioners should improve diabetes curricula (especially pharmacology and insulin management) and provide supervised clinical experiences to facilitate the students’ preparedness to care for people with diabetes.

Keywords: Diabetes mellitus; nursing students; clinical competence; health knowledge; nursing education; Pakistan.

 

INTRODUCTION

Worldwide, diabetes mellitus is considered to be one of the major health challenges of the 21st century. The International Diabetes Federation reports that 463 million adults had diabetes in 2019 and it is projected that by 2045, 700 million adults will have diabetes [1]. This chronic metabolic condition is caused by impairment of insulin secretion and/or action, which results in debilitating microvascular and macrovascular complications, including retinopathy, nephropathy, neuropathy, heart disease and stroke [2]. The burden of diabetes is also increasing in Pakistan, with an estimated 33 million adults affected according to the second National Diabetes Survey of Pakistan [20], and many people either undiagnosed or poorly managed; therefore, there is a pressing need for good quality health care providers [3]. Nurses, as the largest group of all health-care providers, serve on the frontlines of diabetes management for the management of diabetes. They play an important role in educating patients, administering medication, monitoring complications and providing ongoing psychosocial support [4,5]. The level of nursing care will affect patient outcomes, such as blood glucose control, self-management behaviors, and quality of life [6]. Nurses are usually the major educators for the patients who will help them to navigate the complex journey of self-management such as insulin administration, self-monitoring blood sugar, lifestyle changes and foot care [7]. Nursing education supports nursing competency. Nursing students are the future workforces and must be ready to manage the growing number of patients with diabetes, with knowledge, skills and attitudes [8]. Unfortunately, literature confirms a disquieting lack of knowledge among nursing students in various countries. In Jordan, Tawalbeh and Gharaibeh [9] highlighted a lack of awareness and significant gaps in knowledge of pathophysiology, management and complications of diabetes. In European settings, Kudlová and Kočvarová [16] found that Czech general practitioner nurses had significant gaps in insulin treatment and nutrition knowledge, while Kobos et al. [12] identified discrepancies between perceived and actual competence among Polish school nurses, particularly in managing acute complications. In Rwanda, lack of knowledge of diet, complications, insulin use and stress was reported [10]. Another study in Iraq also showed lack of knowledge about type 1 diabetes in children and recommended further education in this area [8]. In Pakistan, Ahmed et al. [3] also found inappropriate diabetes knowledge among residents and nurses and as substandard care was found in many aspects of diabetes care. Lack of congruence between perceived and real knowledge is also a recurring theme. Alsolais et al. [1] found Saudi nursing students felt their diabetes knowledge was good, but their actual performance revealed deficiencies in nutrition, blood glucose monitoring, and injecting insulin. Albagawi et al. [11] reported the gap of perceived and actual knowledge was significant in which overconfidence will be a barrier to further learning and may lead to safety issues. Similarly, Kobos et al. [12] found that school nurses perceived their knowledge on type 1 diabetes to be adequate; however, they found gaps in their knowledge, particularly on management of acute complications. Diabetes knowledge of nursing students and nurses had a number of predictors. These include study year, work experience, prior formal education about diabetes, rotations with diabetic patients and organisational factors such as curriculum and teaching and learning strategies [1,13]. To evaluate the influence of years of study, years of practice and attendance at diabetes workshops on self-perceived and actual knowledge of nursing students, Alsolais et al. [1] found that these factors significantly impact the latter. Song et al. [13] identified that experience, previous diabetes education and clinical environment are significant factors for non-endocrinology nurses in a tertiary general hospital. Other factors include individual ones; having a family member with diabetes is a motivator in most cases to study more and be knowledgeable [11]. The lack of diabetes knowledge is a global one and evident in most settings. A scoping review of nurse-led practice in sub-Saharan Africa by Nyalapa and Gombachika [14] showed that nurses are always deficient in knowledge and having gaps in their theoretical knowledge and practical skills. Buxton [15] conducted a study in Ghana and found that professional nurses had insufficient knowledge about type 2 diabetes, particularly in medication management and complications prevention. In the Czech Republic, Kudlová and Kočvarová [16] found that general practitioner nurses had good knowledge but very poor knowledge in insulin treatment and nutrition. Lack of knowledge on diabetes has a significant impact. Inadequate knowledge results in inadequate education of patients, wrong management decisions, delay in diagnosis of complications and poor outcomes [7]. Al-bawi et al. [7] reported knowledge deficit was associated with a delay in the recognition of hypoglycemia and its inadequate management. Alassaf et al. [17] noted that the diagnosis and management of type 1 diabetes in medical graduates in developing countries is not very popular, hence the need for improvement in their knowledge. Lack of knowledge also perpetuates negative attitudes of diabetes care, which then leads to another round of inadequate management and outcomes [4]. Healthcare professional’s knowledge can be improved through education. Celik et al. [5] conducted a study to evaluate diabetes education in Turkey and found that education methods were effective in improving the knowledge of nurses and resulting in better outcomes. Farzaei et al. [6] found that nutrition education improved knowledge, attitude and practice of nurses. However, the quality of education in nursing programs is still relatively low as many do not include enough education about diabetes, leaving graduates ill-prepared to respond to the growing epidemic [1,8]. There are many skills required in diabetes care. Nurses must administer and teach insulin injections, measure blood glucose levels, educate about foot care, develop personalised dietary plans and provide on-call services to manage acute conditions such as hypoglycemia and hyperglycemia [6,7]. These skills are not well understood by nursing students and nurses, although they know plenty of theory [1]. Albagawi et al. [11] found nurses feel confident in their competence, but are not competent based on objective measures. This is concerning as the skills are important for quality patient care. Diabetes is rapidly rising in Pakistan and it is necessary to assess the knowledge of nursing students about diabetes and their skills. These students will become the future workforce of the medical professions [3]. The current study aims to fill this gap by an extensive assessment of the level of knowledge and skills, using a reliable questionnaire, adapted from Alsolais et al. [1]. This study aims to identify some gaps, correlation between perceived and actual competence, and demographic and educational variables that predict success.

 

Objective

This study aimed to: (1) assess perceived and actual diabetes knowledge among nursing students in Pakistan; (2) quantify the gap between self-assessed and objectively measured competence; and (3) identify the demographic and educational predictors of both perceived and actual knowledge.

 

MATERIALS AND METHODS

Study Design and Setting

We used a quantitative, descriptive and cross-sectional study design. This method is suitable to examine the knowledge and skills of a population at a particular point in time and to explore the relationship between competencies and predictor variables.

The research was undertaken from September 2024 to January 2025 in four nursing colleges in Khyber Pakhtunkhwa, Pakistan: Elizabeth Rani College of Nursing and Allied Health Sciences Mardan, Institute of Health Sciences Mardan and two other affiliated colleges.

The study followed the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines for cross-sectional studies.

Study Population

The study population was all Bachelor of Science in Nursing (BSN) nursing students of nursing colleges in Northeastern Pakistan. The total target population was 2,500 in the 2nd, 3rd, 4th, and internship years of the Bachelor of Science in Nursing (BSN) program.

Inclusion Criteria

• In the 2nd, 3rd, 4th, or internship year of a Bachelor of Science in Nursing (BSN) program
• In 2nd, 3rd, 4th or internship year
• Able to give consent and participate
• Understands and able to complete the questionnaire in English

 

Exclusion Criteria

• First-year nursing students
• Non-nursing students
• Students on leave during the data collection period
• Students who declined to participate

 

Sampling Technique

A convenience sampling technique was employed. This non-probability sampling technique is often used in nursing education research and allowed the recruitment of all accessible and consenting students at the time of data collection. The limitations of this approach are addressed in the limitations section.

 

Sample Size Calculation

Sample size was calculated for cross-sectional studies with finite population using OpenEpi version 3.0, as suggested for epidemiological and nursing studies.

OpenEpi Formula for finite population:

In Table 1, we report in detail all the parameters used for the sample size calculation.

 

Parameter	Description	Value
DEFF	Design effect (for simple random sampling)	1
N	Target population size	2,500
p	Expected proportion (max variability)	0.5
d	Margin of error (absolute precision)	0.05
Z	Z-score for 95% confidence level	1.96

Table 1. Parameters used for sample size calculation

 

The formula recommended in the OpenEpi program was used to estimate the minimum sample size of 334. Guidelines for multiple regression analysis (10-15 participants per predictor variable) suggest that for the expected number of predictor variables (approximately 10), at least 100-150 participants were required.

The calculated sample size (334) was greater than this. The estimated sample was inflated to allow for possible incomplete surveys (10-15% attrition). The sample size of 423 was higher than the required size calculated using OpenEpi and higher than the minimum recommended sample size for regression analysis.

The sample size 423 was confirmed by using G*Power 3.1.9.7, which showed the sample has adequate power (> 0.99) with a medium effect size (f² = 0.15) at α = 0.05 for multiple regression analysis with 10 predictors.

Instruments

A self-administered questionnaire was used to gather data, which was adapted from Alsolais et al. [1]. The questionnaire was broken down into three sections (see Table 2).

 

Section	Content	Number of Items
A	Demographic and educational characteristics	10 items
B	Self-assessed diabetes knowledge and clinical skills (DSRT)	20 items
C	Actual diabetes knowledge and clinical skills (DBKT)	50 items

Table 1. Sections of the Questionnaire.

 

• Section A: Background and Educational Characteristics – gathered information on the participants’ age, gender, year of study, and whether or not they had completed the Adult Health Nursing course; their clinical experience in the management of diabetes patients; whether they had attended workshops/seminars on diabetes; whether they had received formal training in diabetes care; family history of diabetes; and how they perceived their overall competence in diabetes care.
• Section B: Self-Rated Knowledge and Clinical Skills in Diabetes Care – used the Diabetes Self-Report Tool (DSRT) adapted from Drass et al. [18] and the one used by Alsolais et al. [1] to assess perceived competence and confidence in diabetes care. The tool has 20 items and four subscales:

 

Subscale	Number of Items
Diabetes Fundamentals	5 items
Diabetes Medications	5 items
Clinical Skills	6 items
Diabetes Management	4 items

Table 2. Subscales of the Diabetes Self-Report Tool (DSRT) for Self-Assessed Knowledge 

 

The survey used a 4-point Likert scale (1 = Strongly Disagree to 4 = Strongly Agree). The overall score ranged from 20 to 80 points and a higher score reflected greater perceived knowledge.

 

• Section C: Actual Knowledge and Skills of Diabetes – used the Diabetes Basic Knowledge Tool (DBKT) adapted from Drass et al. [18] and used by Alsolais et al. [1] to assess actual knowledge about diabetes clinical skills. Importantly, this section measures knowledge aboutclinical skills (e.g., knowing the correct insulin injection technique, understanding foot examination procedures) rather than directly observing performance of these skills in clinical or simulated settings:

 

Subscale	Number of Items
Diabetes Fundamentals	14 items
Blood Glucose Monitoring	6 items
Insulin Therapy and Administration	10 items
Oral Antidiabetic Medications	5 items
Nutrition and Lifestyle Management	5 items
Diabetic Foot Care	5 items
Acute Complications and Emergency Management	5 items

Table 3. Subscales of the Diabetes Basic Knowledge Tool (DBKT) for Actual Knowledge

 

The highest score was 50 points, with 1 point awarded for each correct answer. The higher the score, the greater the knowledge and skills. The questionnaire content was reviewed by two senior diabetes nurse educators to ensure alignment with current clinical practice in Pakistan, including the continued use of NPH insulin in public sector hospitals and the gradual introduction of continuous glucose monitoring systems in tertiary care centers.

 

Validity and Reliability

Validity and reliability of the original DSRT and DBKT have been reported. Alsolais et al. [1] have reported a content validity index of 0.98, Cronbach’s alpha of 0.688 for the DSRT and Kuder-Richardson 20 coefficient of 0.887 for the DBKT. In this study, the adapted questionnaire was piloted with 30 nursing students for clarity, comprehensibility and reliability. Reliability coefficients were:

 

Section	Tool	Reliability Coefficient
Section B	DSRT	Cronbach’s α = 0.71
Section C	DBKT	Kuder-Richardson 20 = 0.89

Table 4. Reliability Coefficients of the Adapted Questionnaire (Pilot Study, N = 30)

Data Collection Procedure

The study was approved by the Institutional Review Board of Elizabeth Rani College of Nursing and Allied Health Sciences (Approval No. ERCON/IRB/2024-015). Written permission was obtained from the institutions. Potential participants (nursing students) were invited to participate during class, and the researcher provided them with information about the aim, process, risks and benefits of the study. All participants provided their written consent. The questionnaire was completed in a quiet classroom setting, with no time limit set (up to 60 minutes). No books, notes, electronic devices or discussions were allowed during Section C. The data was collected over 6 weeks from October to November 2024.

Ethical Considerations

This study was approved in accordance with the Declaration of Helsinki. Data were collected after approval by the Ethics Committee. Participants were asked to provide written informed consent and were assured they could withdraw from the study at any time without repercussion. The questionnaire did not gather any identifying data, and all data were securely stored on a password-protected computer accessible only to the researchers. Only aggregate data are reported.

Statistical Analysis

IBM SPSS Statistics 26.0 was used to perform the statistical analyses. Prior to inferential analyses, assumptions for parametric testing were assessed. Normality was evaluated using the Kolmogorov-Smirnov test and visual inspection of Q-Q plots; all continuous variables (self-assessed and actual knowledge scores) were approximately normally distributed (p > 0.05). Homogeneity of variance for ANOVA comparisons was confirmed using Levene’s test (p > 0.05 for all comparisons). For ANOVA with three or more groups, post-hoc comparisons were conducted using Tukey’s Honestly Significant Difference (HSD) test. For multiple linear regression, the “enter” method was used, entering all predictors simultaneously based on theoretical relevance. Multicollinearity was assessed using variance inflation factor (VIF), with all VIF values < 2.5, indicating no significant multicollinearity. Likert-scale data from Section B (20 items, 4-point scale) were treated as continuous variables, a common approach in educational research when summing items to create a total score with approximate normality. All regression results are reported using unstandardized coefficients (B) and standardized coefficients (β), The regression coefficients were presented with 95% confidence intervals. A significance level of α = 0.05 was adopted.

 

Analysis	Statistical Test
Demographic characteristics	Frequencies, percentages, means, standard deviations
Comparison between two groups	Independent t-test
Comparison across three or more groups	One-way ANOVA
Relationship between continuous variables	Pearson’s correlation coefficient
Self-assessed vs. actual knowledge	Paired t-test
Predictors of knowledge	Multiple linear regression

Table 5. Summary of Statistical Analyses Performed

RESULTS

Demographic Characteristics of Participants

There were 423 nursing students in this study. The demographic and educational characteristics are presented in Table 6. The mean age was 22.4 ± 2.1 years. Most were females (63.1%), 4th-year nursing students (30.3%) and those who had taken the Adult Health Nursing course (73.8%). Of the respondents, 70.4% had clinical experience in the management of patients with diabetes while 20.6% attended a diabetes workshop and 15.1% had had diabetes training. Almost half (46.8%) had a family member with diabetes. Self-assessed competence was 44.7% fair and 30.3% good.

 

Variable	Category	Frequency (n)	Percentage (%)
Gender	Male	156	36.9
	Female	267	63.1
Year of study	2nd year	95	22.5
	3rd year	108	25.5
	4th year	128	30.3
	Internship	92	21.7
Completed Adult Health Nursing	Yes	312	73.8
	No	111	26.2
Clinical experience with diabetic patients	Yes	298	70.4
	No	125	29.6
Attended diabetes workshops	Yes	87	20.6
	No	336	79.4
Formal diabetes training	Yes	64	15.1
	No	359	84.9
Family history of diabetes	Yes	198	46.8
	No	225	53.2
Self-rated competence	Poor	106	25
	Fair	189	44.7
	Good	128	30.3

Table 6. Demographic and Educational Background of Participants (N = 423)

Self-Assessed Knowledge and Skills Relating to Diabetes

The mean total self-assessed knowledge score was 52.34 ± 10.87 (65.4% of possible). The highest subscale scores were for Diabetes Fundamentals (68.3%), Clinical Skills (65.3%), Diabetes Management (64.4%) and Diabetes Medications (63.5%). The highest mean individual item scores were for “I am confident in performing blood glucose monitoring” (mean = 2.98) and “I can identify risk factors related to diabetes” (mean = 2.92). The lowest scores were for “I can identify different types of insulin” (mean = 2.28) and “I can manage sick days” (mean = 2.32).

Actual Knowledge of Diabetes and Clinical Skills

The mean score for actual knowledge was 33.69 ± 7.45 (67.4% of maximum possible). The subscale scores are shown in Table 7.

The best performance was in Acute Complications (79.6%), Diabetic Foot Care (75.6%) and Blood Glucose Monitoring (72.7%). The least was in Oral Antidiabetic Medications (53.4%), Insulin Therapy (62.2%) and Nutrition Management (64.6%).

 

Subscale	Mean Score (out of max)	SD	Maximum Possible Score	Percentage (%)
Diabetes Fundamentals (14 items)	9.82	2.34	14	70.1
Blood Glucose Monitoring (6 items)	4.36	1.12	6	72.7
Insulin Therapy and Administration (10 items)	6.22	1.89	10	62.2
Oral Antidiabetic Medications (5 items)	2.67	1.08	5	53.4
Nutrition and Lifestyle Management (5 items)	3.23	0.98	5	64.6
Diabetic Foot Care (5 items)	3.78	0.87	5	75.6
Acute Complications and Emergency Management (5 items)	3.98	0.76	5	79.6
Total (50 items)	33.69	7.45	50	67.4

Table 7. Subscale Scores for Actual Diabetes Knowledge (N = 423).

Analysis of individual items showed that the items with the highest performance (>85% correct) were: main side effect of insulin injection (92.0%), site of capillary blood glucose sampling (92.0%), first action for an unconscious diabetic patient (92.0%), and foods that cause rapid rise in blood glucose (92.0%). The poorest performance (<50% correct) was on: HbA1c goal (46.8%), foot inspection frequency (46.8%), continuous glucose monitoring (31.7%), SGLT2 inhibitors mechanism of action (31.7%) and peak action of NPH insulin (36.9%).

Clinical context note

Although NPH insulin has been largely replaced by long-acting insulin analogs (e.g., glargine, detemir) in many high-income countries, NPH remains widely used in Pakistan due to its lower cost, inclusion in national essential medicines lists, and availability in public sector hospitals. Therefore, knowledge of NPH insulin pharmacology and peak action times remains clinically relevant for Pakistani nursing students.

Knowledge Gap Analysis: Self-Assessed vs Actual

There was a 2.0% difference between actual (67.4%) and self-assessed (65.4%) knowledge scores. This was a statistically significant difference (paired t-test: t = 3.42, p = 0.01). There was a small difference in Diabetes Fundamentals (-0.8%). But large differences were found in Clinical Skills, where students underestimated their skills (actual: 72.7% vs. self-assessed: 65.3% for blood glucose monitoring), and Diabetes Management, where students underestimated their knowledge of acute complications (actual: 79.6% vs. self-assessed: 64.4%). When it came to the accuracy of self-assessment, 42.1% were accurate (within ±10% of actual knowledge score), 21.0% overestimated their knowledge (self > actual knowledge by more than 10%) and 36.9% underestimated their knowledge (actual knowledge > self by more than 10%).

Factors Predicting Self-Assessed and Actual Diabetes Knowledge

Self-Assessed Knowledge: Predictors of self-assessed knowledge were identified through multiple linear regression analysis (see Table 8).

The model explained 39.8% of the variance (R² = 0.412, adjusted R² = 0.398, F = 29.45, p < 0.001). Significant predictors included year of study (internship: β = 3.15, p < 0.001), clinical experience (β = 2.68, p = 0.001), formal training (β = 3.42, p < 0.001), workshop attendance (β = 2.89, p = 0.001), and family history of diabetes (β = 1.45, p = 0.034). Completion of the Adult Health Nursing course, age and gender were not significant predictors.

 

Overall model statistics	R²		Adjusted R²			F			p-value
	0.412		0.398			29.45			< 0.001
Predictor	B	SE		β	t		p-value	95% CI
Year of study (Internship vs. 2nd year)	3.15	0.72		0.24	4.38		<0.001	[1.73, 4.57]
Clinical experience (Yes vs. No)	2.68	0.81		0.18	3.31		0.001	[1.08, 4.28]
Formal training (Yes vs. No)	3.42	0.89		0.21	3.84		<0.001	[1.66, 5.18]
Workshop attendance (Yes vs. No)	2.89	0.91		0.17	3.18		0.001	[1.09, 4.69]
Family history of diabetes (Yes vs. No)	1.45	0.68		0.11	2.13		0.034	[0.11, 2.79]
Age	0.12	0.21		0.03	0.57		0.569	[-0.29, 0.53]
Gender (Female vs. Male)	0.87	0.76		0.05	1.14		0.254	[-0.62, 2.36]

Table 8. Multiple Linear Regression of Self-Rated Diabetes Knowledge (N = 423).

 

Actual Knowledge

The regression model for actual knowledge explained 57.2% of the variance (R² = 0.584, adjusted R² = 0.572, F = 48.67, p < 0.001). In Table 9 we reported the results of the Multiple Linear Regression Analysis of Actual Knowledge of Diabetes.

 

Overall model statistics	R²	Adjusted R²	F	p-value
	0.584	0.572	48.67	< 0.001

Predictor	B	SE	β	t	p-value	95% CI
Year of study (Internship vs. 2nd year)	5.89	0.67	0.38	8.79	<0.001	[4.57, 7.21]
Clinical experience (Yes vs. No)	3.45	0.72	0.22	4.79	<0.001	[2.03, 4.87]
Formal training (Yes vs. No)	4.28	0.78	0.25	5.49	<0.001	[2.74, 5.82]
Workshop attendance (Yes vs. No)	3.89	0.81	0.22	4.8	<0.001	[2.29, 5.49]
Family history of diabetes (Yes vs. No)	1.98	0.59	0.14	3.36	<0.001	[0.82, 3.14]
Self-assessed knowledge score	0.21	0.04	0.23	5.25	<0.001	[0.13, 0.29]
Age	0.09	0.18	0.02	0.5	0.617	[-0.26, 0.44]
Gender (Female vs. Male)	0.65	0.64	0.04	1.02	0.308	[-0.61, 1.91]
Completed Adult Health Nursing course (Yes vs. No)	0.98	0.71	0.06	1.38	0.168	[-0.42, 2.38]

Table 9. Multiple Linear Regression Analysis of Actual Knowledge of Diabetes (N = 423).

 

Significant predictors of actual diabetes knowledge were year of study (internship: β = 5.89, p < 0.001), clinical experience (β = 3.45, p < 0.001), formal training (β = 4.28, p < 0.001), workshop attendance (β = 3.89, p < 0.001), family history of diabetes (β = 1.98, p < 0.001), and self-assessed knowledge (β = 0.21, p < 0.001), whereas sex, age, and completion of the Adult Health Nursing course were not significant predictors.

 

Correlation Between Self-Assessed and Actual Knowledge

There was a positive, significant correlation between self-assessed and actual knowledge (Pearson’s r = 0.521, p < 0.01), meaning that the higher the self-assessed knowledge scores, the higher the actual knowledge scores.

 

DISCUSSION

This research assessed diabetes knowledge and clinical skills of nursing students in Pakistan and its predictors. The findings revealed average knowledge (67.4%), good knowledge in acute complications and foot care, but very poor knowledge in the areas of oral antidiabetic drugs, insulin therapy and dietary management. The mean actual knowledge (67.4%) is in line with studies in Saudi Arabia [1] and Ghana [15] but does not meet the standards for safe practice. The poor knowledge in oral antidiabetic drugs (53.4%) and insulin therapy (62.2%) is of particular concern as these are cornerstones of diabetes care. The low percentage of students who knew the mechanism of action of SGLT2 inhibitors (31.7%) and the peak action of NPH insulin (36.9%) are concerning and show a need to improve pharmacotherapy knowledge. This is consistent with Kudlová and Kočvarová [16], who found severe gaps in the knowledge of insulin therapy in Czech nurses. The low percentage (46.8%) of respondents who knew the target HbA1c result is in line with previous studies [11], and reflects the need to improve education and awareness around monitoring of glycemic control in diabetes.

Comparison with European findings

Our results align with studies from other European countries. In the Czech Republic, Kudlová and Kočvarová [16] reported that general practitioner nurses scored poorly on insulin therapy knowledge, similar to our findings (62.2% correct). In Poland, Kobos et al. [12] found that school nurses overestimated their competence in managing acute complications, while we found that Pakistani students underestimated their competence in this area (actual 79.6% vs. self-assessed 64.4%). This cross-national difference may reflect variations in curriculum emphasis, clinical exposure, or cultural factors influencing self-perception. Unlike European studies where CGM knowledge is more commonly integrated into nursing curricula, our finding that only 31.7% of students understood CGM function reflects a technology gap specific to low- and middle-income country settings. As CGM systems, insulin pumps, and digital health tools become increasingly integrated into diabetes care globally—and are gradually being introduced in tertiary care centers in Pakistan—nursing curricula must place greater emphasis on technology-assisted diabetes management. Without this knowledge, newly graduated nurses will be ill-prepared to interpret CGM data, troubleshoot sensor issues, or educate patients on device use. In terms of self-perception of knowledge, 21.0% overestimated their knowledge. This is concerning because it may result in complacency about seeking further education, and a risk to patient safety [11]. However, 36.9% grossly underestimated their knowledge, which could lead to low confidence in clinical practice. Nursing educators need to educate students on how to accurately perceive their own knowledge through feedback and reflective practice as suggested by Kobos et al. [12]. In line with prior research [1,13], academic year was the strongest predictor of actual knowledge, with a difference of almost 6 points between internship and second-year students. This reflects the importance of education and experience. Years of clinical experience, education and attendance of a workshop were also predictors, confirming the importance of hands-on learning and educational workshops [5,6]. The significant positive relationship between family history of diabetes and knowledge score indicates personal experience with the disease may enhance learning motivation [11]. This insight could be applied in teaching methods, such as employing students with family history as peer educators. The high variability at the individual level, and moderate association (r = 0.521) between self-perception and competence, suggests nursing students have some understanding of their competence, but more objective measures are needed. Objective knowledge tests should be included in nursing education in addition to self-assessment, to allow students to compare their assessments to more objective measures [1,12].

 

Implications for Nursing Education and Practice

This study has several implications for nursing education and practice.

First, nursing curricula should provide enhanced education on pharmacological management, specifically oral antidiabetic medications (currently 53.4% correct) and insulin therapy (62.2% correct), as well as nutrition management (64.6% correct).

Second, supervised clinical exposure to patients with diabetes should be mandatory, as clinical experience was a strong predictor of competence (β = 3.45, p < 0.001).

Third, nursing programs should incorporate evidence-based educational strategies including: (a) simulation-based learning with standardized patients for insulin administration and hypoglycemia management; (b) Objective Structured Clinical Examinations (OSCEs) assessing both technical skills and clinical decision-making; (c) supervised diabetes-focused clinical rotations of at least 40 hours; (d) case-based learning using real patient scenarios from local clinical settings; and (e) digital education modules on emerging technologies (continuous glucose monitors, insulin pumps).

Fourth, educators must teach students accurate self-evaluation skills to prevent overconfidence (observed in 21.0% of students) and its associated patient safety risks.

Finally, curricula need to be updated to include emerging diabetes technologies, given the poor performance on continuous glucose monitoring items (31.7% correct) [7,17].

 

Limitations

This study has several limitations. First, the convenience sample of four nursing colleges from one province (Khyber Pakhtunkhwa) in Pakistan may not be representative of all nursing students in Pakistan. Nursing students in other provinces (e.g., Punjab, Sindh, Balochistan) or in private versus public institutions may have different educational experiences, curriculum structures, and access to clinical resources. This limits the generalizability of our findings. Second, the cross-sectional design measures knowledge at a single time point and does not allow for causal inference or assessment of temporal changes in knowledge. Third, the self-reported knowledge items (Section B) may be subject to social desirability bias, potentially leading to overestimation of perceived competence. Additionally, testing conditions (e.g., fatigue, time of day) may have affected performance on the knowledge test. Fourth, this study assessed knowledge about clinical skills rather than directly observing performance of those skills through Objective Structured Clinical Examinations (OSCEs) or real-time clinical assessment. Future studies should include direct observation of clinical skills, evaluate knowledge at multiple time points to assess learning gains, and include multiple sites across different provinces to enhance generalizability.

 

CONCLUSION

This study identified significant discrepancies between perceived and actual diabetes knowledge among nursing students in Pakistan, with 21.0% overestimating and 36.9% underestimating their competence. These findings have important implications for nursing education, self-assessment accuracy, and patient safety. Students demonstrated moderate actual knowledge (67.4%) but had critical gaps in oral antidiabetic medications (53.4%), insulin therapy (62.2%), and diabetes technologies (31.7% for CGM). Knowledge was significantly influenced by clinical practice, education and participation in workshops, highlighting the value of practical experience and educational programs. Over 20% of students had inflated knowledge, which could pose a risk for patients. Nursing educators need to promote diabetes education programs, offer supervised clinical training, and support students to be more accurate in their self-assessment. This will help prepare the next generation of nurses to tackle the increasing diabetes burden in Pakistan.

 

Local Ethics Committee Approval

Institutional Review Board of Elizabeth Rani College of Nursing and Allied Health Sciences, Mardan, Pakistan, approved this study. IRB Approval Number: ERCON/IRB/2024-015. Date of Approval: August 15, 2024. The research was done in compliance with the Declaration of Helsinki.

 

Funding Statement

This study was not funded by any specific agency in the public, commercial or not-for-profit sectors.

Conflict of Interest

Authors report no conflict of interest.

Authors’ Contribution

Conceptualization: Muhammed Awais, Abdur Rahman; methodology: Mahnoor Ali; data collection: Muhammed Awais, Abdur Rahman; formal analysis: Muhammed Awais, Mahnoor Ali; manuscript drafting: Abdur Rahman; critical revision: all authors.

All authors have approved the final version of the manuscript

 

Availability of Data Statement

Data from this study can be made available from the authors upon request using appropriate institutional ethical channels and deidentified data.

 

Acknowledgements

The authors would like to thank all the nursing students for their cooperation and college administration for their assistance in data collection.

 

Application of Artificial Intelligence Tools

No artificial intelligence software other than grammar and spell check was used.

 

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Rita Romano ⁴, Aniello Lanzuise ⁵, Michele Virgolesi ¹, Assunta Guillari ⁶

1. Department of Public Health, University of Naples Federico II, Naples (Italy).
2. Department of Oncology, Hematology and Cell Therapies, Santobono-Pausilipon Pediatric Hospital, Naples (Italy).
3. Freelance Registered Nurse, Naples (Italy).
4. Department of Cardiology, Local Health Authority Naples 2, Frattamaggiore (Naples, Italy).
5. Corporate Health Directorate, A.O.R.N. Ospedale dei Colli, Naples (Italy).
6. Department of Translational Medical Sciences, University of Naples Federico II, Naples (Italy).

* Corresponding author: Chiara Palazzo, Department of Oncology, Hematology and Cellular Therapies, Santobono Pausilipon Hospital, Naples (Italy). E-mail: palazzochiara98@gmail.com

Cite this article

 

ABSTRACT

Introduction: Dance Movement Therapy (DMT), distinct from broader recreational or structured dance activities, has increasingly been proposed as a person-centred, movement-based intervention to address the psychosocial and relational needs of people living with dementia, which are often insufficiently addressed by pharmacological treatments alone. However, the available evidence is characterised by conceptual and methodological heterogeneity, with different dance-based approaches frequently grouped under the same label. A narrative review design was therefore adopted to provide an interpretative and clinically oriented synthesis of how DMT has been conceptualised, implemented, and evaluated across care contexts.

Aim: This narrative review aims to critically synthesize how DMT has been described and applied in the literature for people living with dementia and which psychosocial, physical, and cognitive dimensions have been explored.

Materials and Methods: A narrative review was conducted using searches in PubMed, CINAHL, APA PsycInfo, and PsycArticles between July 2025 and March 2026, and findings were synthesised with attention to clinical relevance.

Results: A total of 11 primary studies were included. DMT for people living with dementia encompasses heterogeneous approaches, ranging from clinical DMT to structured and recreational dance activities, which differ in therapeutic intent and should not be considered equivalent. Overall, the evidence suggests potential multidimensional benefits, particularly in psychological and behavioural domains, including improvements in mood, emotional well-being, and social interaction. Some studies also report gains in mobility, balance, and selected cognitive functions, although findings are inconsistent and often context dependent. Most interventions were conducted in institutional settings, where feasibility was influenced by organisational and logistical factors. The heterogeneity of interventions, study designs, and outcome measures, together with methodological limitations, limits comparability and requires cautious interpretation of the findings.

Conclusion: DMT may represent a promising person-centred and relational approach that can enrich dementia care, particularly in institutional settings. However, current evidence remains limited, heterogeneous, and exploratory. Future research should adopt more rigorous designs, clearly distinguish DMT from other dance-based interventions, and include longer follow-up periods.

 

Keywords: dementia; Dance Movement Therapy (DMT); quality of life; well-being; cognitive function; narrative review

 

INTRODUCTION

Dementia is a progressive neurodegenerative condition characterised by a deterioration of cognitive functions, affecting memory, language, orientation, and decision-making abilities. It is estimated that the number of individuals living with dementia will increase dramatically by 2050, exceeding 139 million cases worldwide [1]. Available pharmacological treatments, although capable of alleviating certain symptoms, present significant long-term limitations and are associated with adverse effects, including an increased risk of mortality among patients treated with antipsychotic medications [1,2]. In response to these limitations, there has been growing interest in non-pharmacological interventions, which offer a safer and more holistic approach to the management of dementia-related symptoms. Among these, Dance Movement Therapy (DMT) has been increasingly explored as a person-centred psychotherapeutic intervention based on movement and embodied relational processes within dementia care [3]. Unlike recreational dance activities or broader dance-based interventions. DMT is grounded in psychotherapeutic principles and focuses on the integration of emotional, relational, and bodily dimensions through the therapeutic use of movement.

It has been hypothesised that rhythmic and repetitive movement may engage neural networks involved in memory and spatial orientation, although these mechanisms are still under investigation [4]. Furthermore, DMT has been described as providing a safe environment in which patients can express emotions that may be difficult to verbalise, thereby potentially supporting overall psychological well-being and modulating neuropsychiatric symptoms such as anxiety, apathy, and agitation [5]. One of the major challenges in dementia care is the management of behavioural and psychological symptoms of dementia (BPSD), which include agitation, depression, and aggression. Within this context, DMT has been described as a relational and experiential intervention that may facilitate emotional regulation, participation, and social interaction [3].

Although an increasing number of primary studies have investigated the use of DMT and dance-based interventions in people living with dementia, the available evidence is characterised by considerable heterogeneity in terms of intervention models, outcome measures, clinical settings, and methodological quality. Moreover, these interventions are often grouped under the broad category of dance-based interventions, making it difficult to identify DMT’s specific contribution as a psychotherapeutic intervention.

To date, no narrative synthesis has critically examined how DMT has been conceptualised, implemented, and evaluated across different care contexts for people living with dementia.

A narrative review design was therefore considered appropriate for the present work, as it allows for the integration of heterogeneous forms of evidence, including qualitative and quantitative studies, while also supporting a broader interpretative exploration of clinical applications, conceptualisations, and contextual aspects of DMT and broader dance-based interventions that may not be adequately captured through effectiveness-focused review methodologies.

Within this framework, the present review aims to provide a critical, thematically oriented synthesis of the literature on DMT in dementia care, focusing on its multidimensional applications, contextual conditions for implementation, and areas requiring further investigation.

 

Objective

This narrative review aims to critically synthesise how DMT and broader dance-based interventions have been described and applied in the literature for people living with dementia and which psychosocial, physical, and cognitive dimensions have been explored.

MATERIALS AND METHODS

Study design and research strategy

A narrative literature search was conducted in PubMed, CINAHL, APA PsycInfo and PsycArticles consulted between July 2025 and March 2026. Keywords such as “dementia”, “dance therapy”, “dance movement therapy”, “well-being” and “social interaction” were used to identify relevant contributions, combined with Boolean operators (“AND” and “OR”) to narrow down the results. The search box is shown in the following Table 1.

 

Database	Search box
PubMed	(dementia OR cognitive impairment) AND (dance therapy OR dance movement therapy) AND (psychological effects OR social effects OR outcomes OR well-being OR cognitive function OR emotional well-being OR social interaction)
Cinahl	(dementia OR cognitive impairment) AND (dance therapy OR dance movement therapy OR movement-based therapy) AND (psychological effects OR social effects OR outcomes OR well-being OR cognitive function OR emotional well-being OR social interaction)
APA Psycarticles e APA Psyclinfo	(dementia OR cognitive impairment) AND (dance therapy OR dance movement therapy OR movement-based therapy) AND (psychological effects OR social effects OR outcomes OR well-being OR cognitive function OR emotional well-being OR social interaction)

Table 1. Search strings used for each database.

 

Inclusion and exclusion criteria

Consistent with the narrative and interpretative nature of this review, the literature search and selection process were guided by relevance to the topic rather than by rigid procedural criteria.

Studies focusing on the effects of DMT and related dance-based interventions in individuals diagnosed with dementia were considered, including both quantitative and qualitative primary research. Given the variability in terminology across the literature, studies describing broader dance-based interventions were also considered when relevant to the aims of the review; however, particular attention was paid to distinguishing DMT as a structured psychotherapeutic intervention from other movement- or dance-based activities during data interpretation. Particular attention was given to studies exploring outcomes related to cognitive functions, emotional well-being, physical or motor abilities, social interaction, and quality of life. Preference was given to studies involving participants with a clinical diagnosis of dementia and published in English or Italian.

Studies were excluded if they did not involve participants with a diagnosis of dementia, focused on interventions other than DMT or broader dance-based interventions, or did not provide sufficiently detailed information on their specific effects. Studies conducted in non-dementia populations were not included in the review sample; however, they were considered, where relevant, to provide theoretical or interpretative context for the discussion of findings. Titles, abstracts, and, where appropriate, full texts were explored to identify contributions considered conceptually and clinically relevant to the objectives of the review. The literature was examined collaboratively by the authors to support a balanced and reflective interpretation of the available evidence, consistent with the exploratory nature of narrative reviews. When the same study was retrieved through different search strategies, it was considered only once to avoid redundancy. Although the search strategy was informed by predefined keywords, it remained exploration and flexible. Different combinations of terms, including synonyms and controlled vocabulary where available, were used across databases. In addition, the reference lists of the included studies were manually screened to identify further relevant contributions.

In accordance with the narrative design, no formal risk-of-bias assessment tool was applied. Instead, a qualitative appraisal of the studies was conducted, considering aspects such as sample characteristics, study design, intervention features, and follow-up duration. This process supported the identification of key methodological limitations and informed the critical interpretation of the findings.

This review adopted a narrative, interpretative, and thematic approach aimed at providing a clinically oriented synthesis of the literature rather than a systematically reproducible assessment of evidence [6,7]. The conduct and reporting of this review were guided by the SANRA (Scale for the Assessment of Narrative Review Articles) recommendations to enhance transparency and methodological coherence [8].

 

RESULTS

The search yielded a total of 378 articles (218 from PubMed, 60 from CINAHL, and 100 from APA PsycArticles and APA PsycInfo). Articles retrieved from the databases were subjected to a screening phase. Ultimately, 11 studies met the established inclusion criteria and were selected for the review.

Across the eleven included studies, substantial heterogeneity emerged in relation to study design, intervention characteristics, settings, and outcome measures.

 

Dance Movement Therapy

Studies specifically describing DMT as a structured psychotherapeutic intervention mainly reported outcomes related to emotional expression, psychosocial well-being, communicative engagement, and relational dimensions [3,4,11]. Reductions in depressive symptoms, loneliness, and selected neuropsychiatric manifestations were described primarily in individuals with mild to moderate dementia, although findings remain preliminary due to methodological limitations and variability across studies. Qualitative investigations additionally highlighted the role of non-verbal communication, affective engagement, and interpersonal attunement within therapeutic movement settings [3,10,12]. Some studies also explored cognitive and functional dimensions, reporting improvements in selected cognitive domains and daily functioning [4,11], although evidence remains limited and not systematically replicated.

 

Broader dance-based interventions

Broader dance-based interventions, including tango, ballroom dance, circle dance, and recreational group movement activities, more frequently focused on physical, functional, and social outcomes [1,2,9,5]. Several studies described improvements in balance, gait, mobility, functional autonomy, and perceived quality of life, although findings were not consistent across intervention types or participant populations. Social participation and relational engagement also emerged as recurring themes, particularly in residential care contexts where group movement activities appeared to facilitate interaction and emotional connection [9,12]. Additionally, some studies [9,14] reported perceived benefits involving caregivers and shared relational experiences, although these findings were mainly derived from qualitative or small-scale investigations. The heterogeneity of intervention formats, intensity, and therapeutic aims, however, limits direct comparison across studies.

Although these findings are sometimes interpreted through mechanisms such as rhythmic cueing, procedural memory activation, and embodied engagement, the current evidence does not allow firm conclusions about underlying neurocognitive processes.

Complementary findings from non-dementia populations are reported here for contextual and theoretical support only. These studies were not included in the review sample but are used to support the plausibility of motor–cognitive integration mechanisms, whose applicability to people living with dementia remains uncertain [13,14].

Most interventions were conducted in residential or semi-residential care settings, with fewer studies addressing community-dwelling individuals [1,10,13,14], and feasibility was frequently influenced by organisational and contextual constraints such as space, staffing, participant comorbidities, and logistical barriers [9,12]. Adherence and continuity over time also emerged as relevant challenges, potentially contributing to variability in outcomes [4,11].

Overall, the reviewed literature descriptively reports potential multidimensional benefits associated with DMT and broader dance-based interventions; however, the marked heterogeneity of approaches, together with methodological limitations and exploratory study designs, requires cautious and context-dependent interpretation.

A synoptic overview of the main characteristics and findings of the included studies is provided in Table 2 to facilitate comparison across interventions and outcome domains.

Author (year of publication)	Study design	Setting & population	Intervention type	Outcome domains	Key findings
Hamill et al. (2011)	Pilot study	UK – People living with dementia (PwD) and caregivers (n=10), nursing home/community	Dance-based intervention (circle dance)	Psychological; social	Improved quality of life and mood in PwD; limited effects on caregivers
Ho et al. (2020)	Randomized controlled trial (RCT)	Hong Kong – Community-dwelling older adults with mild dementia (n=204)	Dance Movement Therapy (DMT)	Psychological; cognitive; functional	Reduced depression and loneliness; improved daily functioning and delayed recall
Gomaa et al. (2019)	Qualitative study	Australia – Therapists working with frail older adults (including PwD) (n=7)	Dance-based intervention (therapeutic dance)	Physical; social	Improved motor coordination and social participation
Borges et al. (2018)	RCT	Brazil – Institutionalised older adults with cognitive impairment (n=60)	Dance-based intervention (ballroom dance)	Physical; cognitive	Improved functional autonomy, balance, and cognitive performance
Bracco et al. (2023a)	RCT	France – People living with dementia in sheltered units (n=31)	Dance-based intervention (adapted tango)	Physical	Increased gait speed compared to control group
Bracco et al. (2023b)	Pre–post study	France – Nursing home residents with dementia (n=54)	Dance-based intervention (adapted tango)	Psychological; physical	Improved quality of life; no significant changes in physical performance
Ho et al. (2015)	RCT	Hong Kong – Community-dwelling older adults with early dementia (n=201)	Dance Movement Therapy (DMT)	Psychological; cognitive; social	Improved neuropsychiatric, cognitive, and psychosocial outcomes
Hokkanen et al. (2003)	Pilot study	Finland – Nursing home residents with dementia (n=4)	Dance Movement Therapy (DMT)	Cognitive; social	Improved narrative language; stable cognitive performance
Hameed et al. (2018)	Pilot study	Singapore – People living with dementia and caregivers (n=10)	Dance-based intervention (“Everyday Waltzes”)	Psychological; social	Improved overall quality of life
Palo-Bengtsson & Ekman (2002)	Qualitative study	Sweden – Nursing home/day-care people living with dementia (n=6)	Dance-based intervention (social dance)	Psychological; social	Increased emotional engagement and non-verbal communication
Zhang et al. (2026)	RCT	China – Community-dwelling older adults (n=50)	Dance-based intervention (adapted tango)	Cognitive; physical	Improved executive and global cognitive function compared to control

Note: PwD = people with dementia; MD = mild dementia; CD = community-dwelling; NH = nursing home; DMT = dance movement therapy; QoL = quality of life; IADL = instrumental activities of daily living; RCT = randomized controlled trial.

Table 2. Synoptic map

 

DISCUSSION

This narrative review aims to critically synthesise how DMT and broader dance-based interventions have been described and applied in the literature for people living with dementia (PLWD), and which psychosocial, physical, and cognitive dimensions have been explored.

Within this framework, the available evidence does not allow definitive conclusions regarding effectiveness but instead highlights recurring descriptive and interpretative patterns that may help clarify the potential role and scope of these interventions.

A key issue emerging from this synthesis concerns the conceptual distinction between DMT as a clinically grounded psychotherapeutic intervention and broader dance-based or recreational activities. While these approaches are often grouped, they differ substantially in terms of therapeutic intent, structure, and required professional competencies. This lack of distinction contributes to the heterogeneity of findings and complicates the interpretation of outcomes, particularly when emotional, relational, and functional dimensions are considered together [12].

From an interpretative perspective, the potential value of DMT appears to lie in its embodied and relational nature.

The integration of rhythm, repetition, and structured movement has been hypothesised to support engagement even in the presence of cognitive decline, possibly through relatively preserved forms of non-declarative functioning. In this sense, the patterns described across the included studies in mood, communicative engagement, and affective expression [3,4,9,10,11] may be interpreted as reflecting the interaction between bodily activation, relational attunement, and environmental context, rather than from isolated cognitive changes. The group dimension further reinforces this process by promoting interpersonal synchrony and shared experiences, contributing to reduced loneliness and improved relational climate within care settings [9,12].

At the same time, interpretations related to neurobiological mechanisms should be considered with caution. Although previous studies (mainly conducted in non-dementia populations) suggest that motor–cognitive integration and the learning of movement sequences may be associated with neural activation and adaptive processes [15,16], the studies included in this review were not designed to directly investigate such mechanisms. Therefore, any reference to neuroplasticity or specific neural pathways remains indirect and should be regarded as hypothetical rather than conclusive. In parallel, qualitative evidence suggests that psychological factors, such as enhanced self-esteem, self-efficacy, and sense of belonging, may play a significant role in mediating improvements in well-being [9,17].

Recent systematic reviews further support a cautious but consistent pattern of multidimensional benefits. For example, Mabire et al. highlights that dance interventions can be implemented with either therapeutic (DMT) or recreational intent and may positively influence physical, cognitive, psychological, and social domains, while also emphasising the lack of standardisation and the need for clearer practice recommendations and methodological rigour [18,19]. Similarly, more recent reviews indicate that dance-based interventions may reduce behavioural and psychological symptoms such as agitation and improve emotional expression and relationships, although conclusions remain limited by the small number and heterogeneity of studies [20]. Additional evidence suggests potential benefits on cognitive functions, including memory and attention, supporting the role of dance as a multidimensional non-pharmacological intervention, while consistently calling for larger and better-designed trials [21]. Overall, these reviews reinforce the view that dance interventions may have broad therapeutic potential but remain constrained by methodological limitations and variability in intervention models.

Beyond individual outcomes, the findings highlight the importance of contextual and organisational factors. DMT appears to have been explored primarily within institutional and semi-institutional settings where opportunities for meaningful interaction are often limited. However, its impact seems closely linked to implementation conditions, including frequency, intensity, staff involvement, and environmental constraints [2,5,21,22]. This suggests that observed benefits are not solely attributable to the intervention itself but also to the context in which it is delivered.

From a broader perspective, DMT may be more appropriately understood not as an intervention intended to modify disease progression, but as a person-centred approach that can support emotional expression, relational engagement, and meaningful participation in care contexts [16,21,22].

Although the literature search was extended through early 2026, few additional primary studies specifically investigating DMT in dementia care were identified. Recent publications were more frequently represented by reviews, conceptual reflections, and methodological discussions rather than by new large-scale empirical investigations. This may reflect the continuing developmental nature of the field and the practical and methodological challenges associated with conducting controlled studies in dementia care settings.

 

Limitations and strengths

Several limitations related to the included studies should be considered when interpreting the findings. The evidence base is characterised by marked heterogeneity of interventions, ranging from DMT in the strict clinical sense to ballroom dance, adapted tango, and broader movement-based programmes, which limit comparability and makes it difficult to isolate the specific contribution of DMT. In addition, many studies are based on small samples, lack control groups, or adopt qualitative or pilot designs, thereby reducing the robustness and generalisability of the findings. In some cases, the inclusion of participants without a clearly defined diagnosis of dementia further complicates interpretation. Overall, these aspects suggest that the current evidence remains exploratory and hypothesis-generating rather than definitive. Some limitations are inherent to the design of this narrative review. The interpretative and non-systematic nature of the methodology, while appropriate for exploring a heterogeneous field, may introduce a degree of subjectivity in study selection and synthesis. Furthermore, no formal risk-of-bias assessment was conducted, and the search strategy, although broad and flexible, may not have captured all relevant studies. The absence of studies conducted in Italy may also limit the contextual transferability of the findings.
Despite these limitations, this review has several strengths. It provides a comprehensive and clinically oriented overview of the use of DMT across different settings and populations, allowing a broader understanding of its potential applications. In addition, the multidimensional perspective adopted, encompassing psychological, emotional, social, and physical domains, contributes to a more integrated interpretation of the potential impact of these interventions. Overall, the findings should be interpreted with caution. Further research based on larger samples, more rigorous designs, standardised outcome measures, and longer follow-up periods is needed to strengthen the evidence base and support future clinical applications.

 

Implications for clinical practice

This narrative synthesis suggests that DMT and other dance-based activities may represent potentially meaningful person-centred approaches within some dementia care contexts, particularly in relation to emotional expression, social interaction, and perceived well-being. However, given the methodological limitations of the available studies and the interpretative nature of this review, these findings should be considered exploratory. It is also important to distinguish between DMT, typically delivered by trained therapists within a therapeutic framework, and more general dance activities, which may differ in aims and structure.

In some residential and day-care settings, group movement interventions have been described as offering opportunities for interaction and engagement, although the extent and consistency of these effects remain uncertain. Existing studies do not allow clear conclusions regarding optimal frequency, duration, or intensity of interventions.

Their implementation appears closely influenced by contextual factors, including organisational support, staff availability, environmental characteristics, and access to appropriately trained professionals. Within this framework, healthcare professionals, including nursing staff, may potentially contribute to facilitating participation and observing behavioural or emotional responses, although these roles are likely to vary considerably across care settings.

Overall, DMT may be viewed as a complementary and context-dependent approach rather than a standardised intervention. It may also be useful to better define intervention frameworks, clearly distinguish DMT from other dance-based approaches, and identify optimal parameters in terms of frequency, duration, and intensity, alongside the development of more methodologically consistent studies, longer follow-up periods, and greater coherence in outcome measures to support more robust interpretative conclusions and potentially inform future clinical applications.

CONCLUSION

This narrative review offers an interpretative overview of DMT and dance-based interventions for people living with dementia. The available evidence suggests potential benefits in emotional expression, social participation, and perceived quality of life, while cognitive and functional outcomes remain heterogeneous. However, these findings are limited by methodological variability, small samples, and short follow-up periods, and should be considered exploratory. A key limitation of both the literature and this review is the lack of a clear distinction between DMT, as a structured psychotherapeutic intervention, and more general dance-based activities, which differ in aims and implementation. Within these limits, DMT may represent a person-centred approach that could support dementia care. Future research should prioritise clearer conceptual distinctions and more consistent, longitudinal designs.

 

Funding statement

This research did not receive any specific funding from public, commercial, or non-profit agencies.

 

Conflict of interest

The authors declare that they have no conflicts of interest.

 

Author contributions

All authors have made substantial contributions to the conception, design, acquisition of data, analysis, and interpretation of the data. The specific contributions of each author are as follows: Study design: TR,VG, CP, AL, AG Data collection: VG, ADA, MG, RR Data analysis: VG, ADA, MG, RR Data interpretation: TR, VG, CP, MV, AG  Manuscript drafting: TR, VG, CP, AG  Manuscript revision: TR, VG, CP, AL, MV, AG  All authors have approved the final manuscript and agree to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

 

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

1. Professional Nursing Program, Faculty of Health Sciences, Institut Teknologi Sains dan Kesehatan Insan Cendekia Medika, Jombang, Indonesia.
2. Bachelor Nursing Program, Faculty of Health Sciences, Institut Teknologi Sains dan Kesehatan Insan Cendekia Medika, Jombang, Indonesia.

* Corresponding author: Dessy Ekawati., Professional Nursing Program, Faculty of Health Sciences, Institut Teknologi Sains dan Kesehatan Insan Cendekia Medika, Jombang, Indonesia. 

E-mail: dessyekawati.s1201@gmail.com

Cite this article

 

ABSTRACT

Introduction: Non-Suicidal Self-Injury (NSSI) has become an increasing mental health concern among adolescents and is strongly associated with negative cognitive–emotional states, particularly hopelessness. Adolescents experiencing hopelessness are more vulnerable to engaging in maladaptive coping behaviors, including self-injury. 

Objective: This study aimed to examine the relationship between hopelessness and NSSI and to determine the role of hopelessness as a predictor of self-injurious behavior among adolescents.

Materials and Methods: This study employed a quantitative cross-sectional design involving 138 senior high school students aged 15–19 years selected using stratified random sampling. Hopelessness was measured using the Beck Hopelessness Scale (BHS), while  Non-Suicidal Self-Injury (NSSI) was assessed using the Inventory of Statements About Self-Injury (ISAS). Data were analyzed using Spearman’s rank correlation test to determine the relationship between variables.

Results: The findings revealed that most respondents experienced moderate levels of hopelessness (40.6%) and mild levels of NSSI (59.4%). Statistical analysis showed a significant very strong positive correlation between hopelessness and NSSI (r = 0.876; p-value < 0.001), indicating that higher levels of hopelessness were associated with increased frequency and severity of self-injurious behavior.

Conclusion: The results indicate that hopelessness plays a significant role in the development of NSSI among adolescents. Adolescents with higher levels of hopelessness tend to have poorer emotional regulation and are more likely to engage in self-injury as a coping mechanism. These findings highlight the importance of early identification of hopelessness in adolescents and the need for targeted mental health nursing interventions to reduce the risk of Non-Suicidal Self-Injury (NSSI).

 

Keywords: Adolescents; Hopelessness; NSSI; Mental health; Self-injury

INTRODUCTION

Non-Suicidal Self-Injury (NSSI) has emerged as one of the most concerning mental health problems among adolescents. This behavior is no longer viewed as a transient or incidental phenomenon, but rather as a significant psychological response to prolonged emotional distress and internal conflict [1]. Adolescence is a developmental period characterized by identity formation, emotional instability, and interpersonal challenges, which increases vulnerability to maladaptive coping strategies such as self-injury. Non-Suicidal Self-Injury (NSSI) is often used as a means to regulate overwhelming emotions, reduce psychological pain, or cope with feelings of emptiness and helplessness. Clinically, NSSI manifests through intentional tissue damage such as cutting, burning, or scratching without suicidal intent. This characteristic distinguishes it from suicidal self-injury where the primary goal is to end one’s life. Unlike suicidal behavior, NSSI often serves as a maladaptive affect regulation strategy to relieve intense psychological tension. If left unaddressed, this behavior may persist and increase the risk of more severe mental health problems, including suicidal behavior [2].

Globally, the prevalence of Non-Suicidal Self-Injury (NSSI) among adolescents ranges from 10% to 35%, with higher rates reported in individuals aged 15–19 years. Studies conducted in Europe and North America indicate that approximately 17–24% of adolescents have engaged in at least one form of self-injurious behavior, while in several Asian countries the prevalence exceeds 30% [3]. In Indonesia, national data indicate that emotional and mental health problems among adolescents aged 15–24 years have increased significantly, reaching more than 20%, accompanied by a growing trend of self-harm behavior and suicidal ideation [4]. These findings highlight the urgency of addressing Non-Suicidal Self-Injury (NSSI) as a major public health concern.

Various psychological factors have been associated with Non-Suicidal Self-Injury (NSSI), including depression, anxiety, emotional dysregulation, trauma, and cognitive distortions. Among these, hopelessness is considered a central cognitive–affective factor [5]. Hopelessness reflects negative expectations about the future, a loss of meaning in life, and the belief that current difficulties will not improve. In adolescents, this condition may arise from academic stress, family conflict, bullying, and social rejection [6]. Previous studies have shown that hopelessness is strongly associated with depressive symptoms, increased risk of self-injury, and progression toward suicidal ideation. It also contributes to impaired social functioning, decreased academic performance, and withdrawal from social interactions [7].

From a nursing perspective, hopelessness represents a critical psychosocial problem that affects an individual’s motivation, coping ability, and overall well-being. Nurses play a pivotal role in early detection, yet many professionals, particularly in school settings, report challenges in distinguishing subtle signs of NSSI and hopelessness due to a lack of specialized psychiatric training. In the Indonesian context, the presence of dedicated school nurses to assess and manage student mental health is still limited, with responsibilities often falling to general health teachers or school counselors. Nursing interventions that focus on enhancing hope, restructuring negative cognitions, and strengthening adaptive coping strategies are essential in preventing Non-Suicidal Self-Injury (NSSI). However, effective intervention strategies require strong empirical evidence regarding the role of hopelessness and its association with self-injurious behavior among adolescents [8].

 

Objective 

This study aims to examine the relationship between hopelessness and Non-Suicidal Self-Injury (NSSI) among adolescents and to analyze the strength and direction of the association between these two variables using a cross-sectional approach.

  

MATERIALS AND METHODS

Study Population

This research employed a cross-sectional study design to investigate the relationship between hopelessness and Non-Suicidal Self-Injury (NSSI) behavior. The study was conducted across three selected Senior High Schools in Jombang Regency, East Java, Indonesia, during the period of February to March 2026. A total of 138 adolescents were recruited as participants through a stratified random sampling technique, with strata defined by grade levels (Grades X, XI, and XII) across the selected schools. The sample size was determined using the G*Power 3.1.9.7 software for a correlation bivariate model with an effect size of 0.3 which represents a medium effect, an alpha level of 0.05, and a power of 0.95. These parameters yielded a minimum required sample of 134 participants, therefore the 138 participants included in this study provided sufficient statistical power. The research protocol was strictly guided by the ethical principles of the Declaration of Helsinki and received formal approval from the Health Research Ethics Committee of the Faculty of Health, Institut Teknologi Sains dan Kesehatan (ITSKes) Insan Cendekia Medika Jombang on January 12, 2026, with the issuance of protocol number KEPK/ICME/031/I/2026. 

 

Inclusion criteria 

The participants eligible for this study were limited to adolescents aged 15–19 years who were actively enrolled as students in the participating schools at the time of data collection. Inclusion also required a demonstrated willingness to participate in the research, which was confirmed by the submission of signed informed consent forms. Furthermore, participants were required to be capable of understanding and completing the research questionnaires independently without external assistance. For participants under 18 years old, additional written consent was obtained from their parents or legal guardians.

 

Exclusion criteria

The study excluded adolescents who had a documented medical history of severe psychiatric disorders, such as schizophrenia or bipolar disorder, as well as those currently undergoing intensive psychological or psychiatric therapy. To ascertain these exclusion criteria, the research team conducted a two-step verification process. This involved reviewing students’ confidential health records in collaboration with school counselors and performing brief clinical screening interviews prior to enrollment to identify any overt signs of psychotic symptoms or cognitive impairment. Additionally, students who withdrew their participation at any point during the data collection process or those who provided incomplete responses to the instruments were also excluded from the final analysis.

 

Data Collection Procedure

Data collection was carried out in a designated quiet room within each school to ensure participant privacy and confidentiality. The researchers first explained the study purpose and the voluntary nature of participation. Once consent was secured, participants completed a sociodemographic questionnaire followed by the BHS and ISAS scales. The sociodemographic questionnaire included items regarding age, gender, grade level, living arrangements, and a specific self-report question asking whether they had ever experienced significant emotional problems in the past. The entire process took approximately 20-30 minutes per student. To ensure language comprehension, a researcher was present throughout the session to clarify any confusing terminology even though the instruments had already been pilot-tested for clarity.

 

Instruments

Data were collected using two primary instruments that underwent a rigorous forward-back translation process into the Indonesian language to maintain linguistic and cultural equivalence. The instruments used in this study are widely recognized in the public domain for academic and research purposes. Hopelessness was measured using the Beck Hopelessness Scale (BHS) developed by Beck et al. (1974) consisting of 20 true or false items that evaluate negative expectations about the future. In this study, the Indonesian version of the BHS demonstrated high internal consistency with a Cronbach’s alpha of 0.88. Non-Suicidal Self-Injury (NSSI) was assessed using the Inventory of Statements about Self-Injury (ISAS) adapted from Nock et al. (2010) which measures the frequency and psychological functions of self-injurious behaviors. The Indonesian adaptation of the ISAS was specifically validated for this study and yielded a Cronbach’s alpha of 0.84. Prior to the main data collection, a pilot study was conducted with 30 adolescents in a similar demographic area to ensure the terminology was easily understood by the target population. This section also included the collection of sociodemographic variables such as age, gender, and family structure which are subsequently reported in the results.

 

Statistical analysis

The collected data were processed and analyzed using IBM SPSS Statistics version 26.0. Descriptive statistics were utilized to summarize the demographic characteristics and profiles of the participants. To determine the strength and direction of the association between hopelessness and Non-Suicidal Self-Injury (NSSI), the Spearman rho rank correlation test was performed utilizing a two-tailed test. This choice was justified considering that the data were not normally distributed, as confirmed by the Kolmogorov-Smirnov normality test, and the variables were ordinal in nature. For all statistical tests in this study, a p-value < 0.05 was considered statistically significant.

 

RESULTS

Sample Characteristics

Based on Table 1, the characteristics of the respondents show that out of 138 students, the largest age group was 16 years old with 42 students (30.4%), followed by those aged 17 years with 39 students (28.3%), 15 years with 28 students (20.3%), 18 years with 21 students (15.2%), and 19 years with 8 students (5.8%). The mean age of the respondents was 16.7 years with a standard deviation of 1.02. In terms of gender, female students predominated, accounting for 77 respondents (55.8%), while male students numbered 61 (44.2%). 

Regarding grade level, most participants were in Grade XI with 49 students (35.5%), followed by Grade X with 46 students (33.3%) and Grade XII with 43 students (31.2%). 

Concerning living status, the majority of respondents lived with their parents (102 students; 73.9%), whereas 21 students (15.2%) lived with relatives and 15 students (10.9%) resided in a boarding school or dormitory. 

With respect to the history of emotional problems, 80 respondents (58.0%) reported having experienced emotional problems, while 58 respondents (42.0%) reported none.

 

Characteristics	N	%	Mean	SD
Age (years)
15 years	28	20.3	16.7	1.02
16 years	42	30.4
17 years	39	28.3
18 years	21	15.2
19 years	8	5.8
Gender
Male	61	44.2
Female	77	55.8
Grade
Grade X	46	33.3
Grade XI	49	35.5
Grade XII	43	31.2
Living Status
With parents	102	73.9
With relatives	21	15.2
Boarding school/dormitory	15	10.9
History of Emotional Problems
Yes	80	58.0
No	58	42.0

Table 1. Sociodemographic Characteristics of Respondents (N = 138).

 

Descriptive Analysis of Hopelessness and Non-Suicidal Self-Injury (NSSI)

The distribution of hopelessness levels shows that the majority of respondents fell into the moderate category (N = 68; 49.3%), followed by mild and high levels (N = 24 for each; 17.4%), while the remaining students reported low levels (N = 22; 15.9%). 

Regarding Non-Suicidal Self-Injury (NSSI), nearly half of the participants were categorized as having a moderate frequency (N = 66; 47.8%), followed by low frequency (N = 41; 29.7%), no Non-Suicidal Self-Injury (NSSI) (N = 18; 13.0%), and high frequency (N = 13; 9.4%).

 

Characteristics	N	%	Mean	SD
Hopelessness Level
Low	22	15.9	2.68	0.944
Mild	24	17.4
Moderate	68	49.3
High	24	17.4
Non-Suicidal Self-Injury (NSSI) Category
No NSSI	18	13.0	2.54	0.838
Low frequency	41	29.7
Moderate frequency	66	47.8
High frequency	13	9.4

Table 2. Distribution of Hopelessness Levels and NSSI Categories (N = 138).

 

Correlation Between Hopelessness and Non-Suicidal Self-Injury Among Adolescents

To determine the relationship between hopelessness and Non-Suicidal Self-Injury (NSSI), a Spearman rank correlation test was performed. As shown in Table 3, the results indicate a positive and statistically significant relationship between the two variables, with a correlation coefficient of r = 0.876 and a p-value < 0.001. This very strong correlation suggests that as the level of hopelessness increases, the frequency of Non-Suicidal Self-Injury (NSSI) behaviors among adolescents also significantly increases.

 

Variable	M (SD)	Median (IQR)	Sig. (2-tailed) Spearman Correlation
Hopelessness	10.27 (5.05)	11 [6.00, 14.00]	Correlation coefficient r = 0.876, p < 0.001*
NSSI	10.24 (7.64)	11 [3.75, 15.00]

Note: *=significant test, SD = standard deviation, IQR = interquartile range [Q1, Q3].

Table 3. Spearman Correlation Analysis of Hopelessness and NSSI (N = 138)

 

Figure 1 presents a scatter plot illustrating the correlation between hopelessness scores and Non-Suicidal Self-Injury (NSSI) frequency among adolescents. The visual distribution of data points reveals a consistent upward linear pattern, where an increase in hopelessness scores is accompanied by a rise in Non-Suicidal Self-Injury (NSSI) scores. The analysis confirms a very strong positive correlation between these two variables (r = 0.876, p-value < 0.001), indicating that higher levels of hopelessness are significantly associated with higher levels of Non-Suicidal Self-Injury (NSSI) behavior. This strong linear relationship underscores the critical role of hopelessness as a psychological factor in self-injurious actions.

 

Figure 1. Scatter plot showing the correlation between hopelessness and NSSI.

 

The crosstabulation analysis further illustrates the distribution of respondents based on hopelessness levels and Non-Suicidal Self-Injury (NSSI) categories. Among respondents with moderate levels of hopelessness, the majority were categorized as having moderate frequency Non-Suicidal Self-Injury (NSSI) (55 students), while 13 students were in the low frequency category, totaling 68 individuals. In contrast, respondents with severe hopelessness were mostly distributed in the moderate frequency (11 students) and high frequency Non-Suicidal Self-Injury (NSSI) categories (13 students), totaling 24 individuals. 

For those with mild hopelessness, all respondents were categorized in the low frequency Non-Suicidal Self-Injury (NSSI) group (24 students). Meanwhile, among respondents with low hopelessness, most reported no NSSI behavior (18 students), while a smaller proportion fell into the low frequency category (4 students), totaling 22 individuals (Table 4).

 

Hopelessness	Non-Suicidal Self-Injury (NSSI)				Total
	No	Low frequency	Moderate frequency	High frequency
Low	18	4	0	0	22
Mild	0	24	0	0	24
Moderate	0	13	55	0	68
High	0	0	11	13	24
Total	18	41	66	13	138

Table 4. Crosstabulation of Hopelessness and Non-Suicidal Self-Injury.

 

DISCUSSION

Based on the respondents’ characteristics, the largest age group was 16 years old (42 students; 30.4%), with a mean age of 16.7 ± 1.02 years, representing the middle-adolescent developmental stage. According to Erikson’s psychosocial theory, this stage corresponds to the phase of identity versus role confusion, in which adolescents are highly sensitive to academic pressure, peer relationships, and identity exploration, making them more vulnerable to emotional distress and feelings of hopelessness [9]. 

The predominance of female students (77 students; 55.8%) is consistent with previous findings indicating that adolescent girls are more likely to experience internalizing problems, including hopelessness and self-injurious behavior, than boys [1,2]. Most respondents were in Grade XI (49 students; 35.5%), a period characterized by increasing academic demands and future-related concerns, which, according to developmental stress theory, may intensify psychological strain. 

The majority of participants lived with their parents (102 students; 73.9%), suggesting that hopelessness and self-injury can occur not only among adolescents separated from their families but also within intact family settings, depending on the quality of emotional support. Furthermore, more than half of the respondents reported a history of emotional problems (80 students; 58.0%), supporting the diathesis–stress model, which posits that pre-existing psychological vulnerability increases the risk of maladaptive emotional responses under stress [5].

The distribution of hopelessness levels showed that the moderate category was the most prevalent (68 students; 49.3%), with a mean score of 10.27 ± 5.05. This finding indicates that a substantial proportion of adolescents experienced pessimistic expectations about the future and a reduced sense of control over life outcomes. According to Beck’s cognitive theory, hopelessness arises from negative cognitive schemas and distorted beliefs about the self, the world, and the future, which are particularly salient during adolescence when individuals face academic, interpersonal, and identity-related challenges [10,11]. Similar patterns have been reported, showing that moderate levels of hopelessness are common in adolescents and constitute an important risk factor for emotional and behavioral problems, including self-injury [12,13]. From a psychiatric nursing perspective, these moderate levels of hopelessness necessitate early identification and cognitive interventions to prevent the development of more severe psychological crises. 

Regarding Non-Suicidal Self-Injury (NSSI), the largest proportion of respondents fell into the moderate frequency category (66 students; 47.8%), followed by low frequency (41 students; 29.7%). A smaller proportion reported no NSSI behavior (18 students; 13.0%), while only 13 students (9.4%) were categorized as having high frequency NSSI. The mean NSSI score was 10.24 ± 7.64. This finding suggests that many adolescents engage in self-injurious behavior at a moderate level, which may reflect repeated use of Non-Suicidal Self-Injury (NSSI) as a coping mechanism rather than isolated incidents. In line with Nock’s (2010) functional model of Non-Suicidal Self-Injury (NSSI), such behaviors primarily serve an affect-regulation function, helping individuals manage intense negative emotions such as sadness, anger, emptiness, or psychological tension [14]. This result is also consistent with previous studies indicating that Non-Suicidal Self-Injury (NSSI) behaviors in adolescents often begin at lower or moderate frequencies and may escalate if underlying emotional distress is not adequately addressed [15]. 

The correlation analysis revealed a statistically significant and very strong positive relationship between hopelessness and NSSI (r = 0.876; p-value < 0.001), with median scores and Interquartile Ranges (IQR) of 11 (8) and 11 (11) respectively. This result supports the hopelessness theory, which emphasizes that negative expectations about the future and a sense of futility can lead individuals to adopt maladaptive coping behaviors, including self-injury [13]. The present findings are also in accordance with previous studies, which identified hopelessness as a significant predictor of Non-Suicidal Self-Injury (NSSI) among adolescents [8,16]. Clinically, this very strong correlation indicates that higher levels of hopelessness are closely associated with greater tendencies and severity of self-injurious behavior, highlighting the importance of assessing hopelessness as a key risk indicator in adolescent mental health and psychiatric nursing practice. Consequently, it is imperative for nursing professionals to integrate hopelessness screening into routine adolescent health assessments, focusing on fostering hope and resilience to mitigate the risk of self-injurious behaviors.

 

CONCLUSION

This study shows a significant and very strong positive relationship between hopelessness and Non-Suicidal Self-Injury (NSSI) among adolescents. Adolescents with higher levels of hopelessness tend to exhibit higher frequency and severity of self-injurious behavior. These findings indicate that negative expectations about the future and feelings of helplessness play a crucial role in the development of maladaptive coping strategies, particularly  Non-Suicidal Self-Injury (NSSI).

The predominance of moderate levels of hopelessness and moderate frequency of Non-Suicidal Self-Injury (NSSI) suggests that emotional distress and self-injurious behavior are already present at a considerable level among adolescents. This highlights the importance of early identification and intervention within school settings. 

Assessing hopelessness as a key psychological risk factor is essential in mental health screening and psychiatric nursing practice. Interventions focusing on enhancing hope, strengthening positive future orientation, and promoting adaptive coping strategies are necessary to prevent the escalation of self-injurious behavior and to improve adolescents’ psychological well-being.

 

Limitations

This study has several limitations. First, the use of a cross-sectional design does not allow for causal conclusions between hopelessness and Non-Suicidal Self-Injury (NSSI). Second, the data were collected using self-report questionnaires, which may be subject to response bias and social desirability, especially given the sensitive nature of self-injurious behavior. Third, although this study involved three different schools, the findings may still have limited generalizability to adolescents in diverse geographical or cultural contexts beyond the study area. Fourth, this study did not control for potential confounding variables, such as symptoms of depression or anxiety, which are known to be significantly associated with both hopelessness and NSSI behavior.  

Despite these limitations, this study has notable strengths, including the use of instruments (BHS and ISAS) that have been culturally adapted and validated for the Indonesian adolescent population. Furthermore, the sample size (N = 138) is robust and highly adequate for correlational analysis, providing strong statistical power for the identified relationships. The focus on clinically relevant psychological variables contributes to a deeper understanding of adolescent mental health and provides a solid basis for future research and intervention development.

 

Funding statement 

This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors.

 

Local Ethics Committee approval

This research was approved by the Health Research Ethics Committee of the Faculty of Health, Institut Teknologi Sains dan Kesehatan (ITSKes) Insan Cendekia Medika Jombang on January 12, 2026, with the issuance of protocol number KEPK/ICME/031/I/2026. 

 

Conflict of interest   

The authors report no conflict of interest.

 

Authors’ contribution

Dessy Ekawati (DE) contributed to the conception and design of the study, data collection, data analysis, interpretation of the results, and manuscript drafting. 

Agustina Maunaturrohmah (AM) contributed to data collection, data analysis, and critical revision of the manuscript. 

Anin Wijayanti (AW) contributed to the study design, supervision, and review of the manuscript. 

Ifa Nofalia (IF) contributed to data interpretation and manuscript revision. 

All authors read and approved the final version of the manuscript.

 

Acknowledgements

The author would like to express sincere gratitude to all respondents who participated in this study, as well as to the school authorities for their support and cooperation during the data collection process. Appreciation is also extended to colleagues and mentors who provided valuable input and guidance throughout the research process.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Triglia ⁶, Antonino Calabrò ⁷, Luana Conte ^8,9‡, Elsa Vitale ¹⁰‡

1. Department of Medical and Surgical Sciences, School of Nursing, University of Bologna, 40126 Bologna, Italy.
2. Department of Surgery, ‘San Giuseppe da Copertino’ Hospital, Local Health Authority (ASL) of Lecce, 73100 Lecce, Italy.
3. RSA “Oasi – Centro per la Terza Età”, Residential Socio‑Healthcare Facility, Via della Resistenza 105, 70013 Castellana Grotte, Bari, Italy.
4. Città di Lecce Hospital, GVM Care & Research, 73100 Lecce, Italy.
5. Hematology Unit, IRCCS Reggio Emilia Local Health Authority (Azienda USL), 42122 Reggio Emilia, Italy.
6. Rizzoli Orthopedic Institute, Hospital of Argenta, Ferrara Local Health Authority, 44100 Ferrara, Italy.
7. Department of Mental Health, Community Mental Health Center (CSM) of Biella, ASL BI, 13900 Biella, Italy.
8. Laboratory of Advanced Data Analysis for Medicine (ADAM) at DReAM, University of Salento and Local Health Authority, “V. Fazzi” Hospital, 73100 Lecce, Italy.
9. Department of Physics and Chemistry, University of Palermo, 90128 Palermo, Italy.
10. Directorate of Health and Nursing Professions, Local Health Authority of Bari, 70100 Bari, Italy.

* Corresponding author: Federico Cucci, Città di Lecce Hospital, GVM Care & Research, 73100 Lecce, Italy. E-mail: fcucci@gvmnet.it

† These authors contributed equally to this work as first author.

‡ These authors contributed equally to this work as last author.

Cite this article

 

ABSTRACT

Background: Patients undergoing dialysis often experience reduced health-related quality of life, poor sleep quality, and increased perceived stress. These dimensions are closely interconnected and represent key aspects of holistic patient care. From a nursing perspective, their assessment is essential to support patient-centered interventions and improve clinical outcomes.

Aim: To evaluate health-related quality of life, sleep quality, and perceived stress in patients undergoing dialysis, and to explore differences across sociodemographic and clinical subgroups.

Methods: A cross-sectional study was conducted among adult patients aged 18 years or older undergoing dialysis. Data were collected using validated instruments, including the Short Form-36 Health Survey developed within the International Quality of Life Assessment Project, the Pittsburgh Sleep Quality Index, and the Perceived Stress Scale 10-item version. Descriptive statistics were computed, and inferential statistical analyses were performed to explore differences between groups and associations between variables. Comparisons between categorical variables were conducted using chi-square tests, while differences in continuous variables between groups were assessed using independent samples t-tests and analysis of variance. Correlations between variables were evaluated using Pearson correlation coefficients.

Results: A total of 148 patients were included. Overall, participants reported reduced quality of life, poor sleep quality, and moderate to high levels of perceived stress. Significant differences emerged across sociodemographic and clinical subgroups, particularly in relation to geographical area and selected clinical characteristics. Significant associations were also observed between quality-of-life domains, sleep quality, and perceived stress.

Conclusions: Patients undergoing dialysis experience multiple interrelated challenges affecting their well-being. From a nursing perspective, the systematic assessment of quality of life, sleep quality, and perceived stress represents a key component of comprehensive care. These findings support the role of nurses in identifying patient needs, guiding personalized care planning, and implementing targeted interventions aimed at improving overall patient outcomes.

Keywords: chronic kidney disease, dialysis, health-related quality of life, sleep quality, perceived stress, nursing.

INTRODUCTION

Chronic kidney disease (CKD) is defined by a persistent reduction in renal function, typically identified by a glomerular filtration rate below 60 mL/min/1.73 m² [1]. Affecting approximately 10% of the global population [2], CKD represents a major public health concern. The progressive increase in patients requiring renal replacement therapies, including dialysis, reflects an epidemiological context characterized by population aging and a high prevalence of cardiovascular and metabolic comorbidities [3]. Beyond its clinical burden, CKD profoundly influences daily functioning, psychosocial well-being, and healthcare organization.

Dialysis, although life-sustaining, imposes a complex and enduring impact on patients’ lives. Frequent treatment sessions, dietary and fluid restrictions, physical symptoms, and technological dependence significantly reshape daily routines and limit participation in work, social, and family roles. Health-related quality of life (QoL) in this context emerges as a multidimensional construct resulting from the interaction between physical health (Physical Component Summary, PCS), psychological-emotional status (Mental Component Summary, MCS), degree of autonomy, social relationships, and treatment-related constraints.

Psychological distress is increasingly recognized in individuals undergoing dialysis. Anxiety, depressive symptoms, and perceived stress are common and often underdiagnosed, despite their association with poorer treatment adherence, reduced quality of life, and adverse clinical outcomes [4]. Similarly, sleep disturbances—including insomnia, sleep apnea, restless legs syndrome, and excessive daytime sleepiness—are highly prevalent and have been linked to increased mortality risk, impaired daily functioning, and diminished well-being [5–8]. These dimensions frequently coexist and may interact, amplifying the subjective burden of chronic kidney failure. Within the Italian healthcare system, which is predominantly public and regionally organized, dialysis services are delivered across heterogeneous clinical contexts, including hospital-based units and home-based programs. Variability in service organization, availability of psychosocial support, and access to home dialysis modalities may influence patients lived experiences. While previous Italian studies have explored specific aspects such as depressive symptoms, stress, or the impact of educational interventions [9–13], recent nationwide data simultaneously examining health-related quality of life, sleep quality, and perceived stress in a heterogeneous dialysis population remain limited. Addressing these dimensions together may provide a more comprehensive understanding of the psychosocial burden associated with dialysis treatment and support the development of multidisciplinary care strategies tailored to the Italian context.

From a nursing perspective, the assessment of health-related quality of life, sleep quality, and perceived stress represents a fundamental component of holistic care in patients undergoing dialysis. Nurses play a central role in the continuous monitoring of these dimensions, as they are directly involved in patient education, symptom management, and the identification of psychosocial needs [14]. A comprehensive understanding of these aspects is essential to support individualized care planning and to improve patient outcomes in this population.

Primary objective

The primary objective of this study was to evaluate health-related quality of life, sleep quality, and perceived stress in patients undergoing dialysis.

Secondary objectives

The secondary objectives were to explore differences in these outcomes across sociodemographic and clinical subgroups and to examine the associations between quality of life, sleep quality, and perceived stress.

MATERIALS AND METHODS

Study design

This was a descriptive cross-sectional study with exploratory analytical components, conducted between January and October 2025 using an anonymous electronic questionnaire.

Questionnaire tools

Data were collected using a structured, self-administered questionnaire consisting of five sections.

 

1. Sociodemographic variables

The first section included direct sociodemographic variables: sex, age (recorded in years and categorized into predefined age groups), marital status, educational level (highest qualification attained), and employment status.

Clinical characteristics included the presence of comorbidities and dialysis-related variables, such as the duration of dialysis treatment. Additional clinical information relevant to patients’ health status, including conditions associated with chronic kidney disease and treatment-related aspects, was also considered. Where available, information related to symptoms commonly reported by patients undergoing dialysis and potential behavioral adaptations to chronic illness was considered.

These variables were collected to characterize the sample and to allow subsequent stratified analyses (Table 1).

 

2. Clinical characteristics, risk factors and lifestyle

The second section comprised structured items addressing:

• main known medical condition before dialysis initiation (single-response item);
• prior awareness of dialysis (defined as patients’ prior awareness or familiarity with dialysis treatment before its initiation, derived from information received through healthcare professionals, previous clinical experiences, or informal sources);
• symptoms and signs before diagnosis (multiple-response item);
• pre-diagnosis lifestyle habits (smoking, alcohol use, illicit drug use, salt intake, weight loss);
• behavioral changes and symptoms during or after dialysis initiation (multiple-response items).

 

For symptom-related questions, multiple answers were allowed; therefore, percentages may exceed 100% (Tables 2 and 3).

Pre-existing medical conditions were recorded as the main perceived disease rather than as a full multimorbidity profile.

 

3. Health-related quality of life (SF-36)

Health-related quality of life was assessed using the official Italian version of the Short Form-36 Health Survey (SF-36) (IQOLA project)[15].

The instrument consists of 36 items grouped into eight domains:

• Physical Functioning (PF) – 10 items
• Role Limitations due to Physical Health (Role Physical, RP) – 4 items
• Role Limitations due to Emotional Problems (Role Emotional, RE) – 3 items
• Vitality (VT) – 4 items
• Mental Health (MH) – 5 items
• Social Functioning (SF) – 2 items
• Bodily Pain (BP) – 2 items
• General Health (GH) – 5 items

Scores are transformed to a 0–100 scale, with higher scores indicating better perceived health status. Physical and Mental Component Summary measures (PCS and MCS) were also derived[16].

 

4. Sleep quality (PSQI)

Sleep quality was assessed using the Pittsburgh Sleep Quality Index (PSQI), developed by Buysse et al. The PSQI is a validated multidimensional instrument composed of 19 self-rated items generating seven components: subjective sleep quality, sleep latency, sleep duration, habitual sleep efficiency, sleep disturbances, use of sleeping medication, and daytime dysfunction.

The global score ranges from 0 to 21, with higher scores indicating poorer sleep quality. For analytical purposes, scores were categorized into three classes: good sleep quality (0–5), moderate impairment (6–10), and severe impairment (>10) [17].

 

5. Perceived stress (PSS-10)

Perceived stress was measured using the 10-item version of the Perceived Stress Scale (PSS-10), developed by Cohen et al. This instrument evaluates the degree to which individuals perceive their life situations as stressful.

Items are rated on a five-point Likert scale (0 = never to 4 = very often), with four positively worded items reverse scored. Total scores range from 0 to 40, with higher scores indicating greater perceived stress. Scores were categorized as low (0–13), moderate (14–26), and high (27–40)[18].

 

Setting

Data were collected through an anonymous electronic questionnaire (Microsoft Forms) administered exclusively online between January and October 2025. The survey link was disseminated via major social networks (Facebook®, Instagram®, Reddit®) and through Italian provincial dialysis associations and patient support groups, allowing nationwide dissemination across Northern, Central, and Southern Italy and the Islands.

Participants completed the questionnaire independently using personal devices (smartphones, tablets, or computers), ensuring anonymity and voluntary participation.

Although data collection occurred in a virtual environment, respondents were individuals receiving dialysis treatment within established clinical settings in Italy, including hospital-based dialysis units, nephrology departments within the Italian National Health System, accredited private dialysis centers, and structured home-based dialysis programs (peritoneal dialysis and home hemodialysis). Therefore, the research setting was digital, whereas the clinical context of reference consisted of organized dialysis services within the Italian healthcare system.

The associations involved in disseminating the survey included regional branches of ANED and other Italian dialysis and transplant patient networks.

 

Participants

A non-probability convenience sampling strategy was adopted. Participants were recruited on a voluntary basis through online dissemination of the survey link via social networks (Facebook®, Instagram®, Reddit®) and provincial dialysis associations and patient support groups.

No formal a priori sample size calculation was performed. Given the exploratory and cross-sectional nature of the study, the aim was to obtain a nationwide snapshot of adults undergoing dialysis treatment in Italy rather than to test predefined hypotheses or estimate population parameters with predetermined statistical power. Eligible participants were adults aged 18 years or older, undergoing dialysis treatment and residing in Italy. Inclusion criteria were current dialysis treatment, residence in Italy, ability to understand the study information, and provision of electronic informed consent. Exclusion criteria were age below 18 years, failure to provide informed consent, and incomplete questionnaire completion. Participation was voluntary and unpaid. Participant recruitment, eligibility assessment, and inclusion in the final sample are summarized in a flow diagram (Figure 1).

Figure 1. Flow diagram of participant recruitment and inclusion.

 

Due to the open-access nature of the online survey and the anonymous recruitment process, it was not possible to determine the exact number of individuals who accessed the questionnaire or were excluded prior to completion.

The figure illustrates the online dissemination of the questionnaire, the eligibility assessment based on predefined inclusion criteria, and the final sample included in the analysis.

 

Statistical analysis

The dataset was created using Microsoft Excel (Microsoft Office®) and subsequently imported into Jamovi software (version 2.3.18) for statistical analysis. Descriptive statistics were performed. Continuous variables were expressed as mean ± standard deviation (SD), whereas categorical variables were reported as absolute frequencies and percentages. The internal consistency of the psychometric instruments (SF-36, PSQI, and PSS-10) was assessed using Cronbach’s alpha coefficient to evaluate their reliability within the study sample. The normality of continuous variables was assessed using the Shapiro–Wilk test and by visual inspection of histograms and Q–Q plots. Based on these assessments, parametric tests (independent samples t-test, one-way ANOVA, and Pearson’s correlation) were applied when normality assumptions were considered acceptable. Independent samples t-tests were used to compare mean SF-36 domain scores between two groups (e.g., sex, geographical area North/Central vs South/Islands, dialysis modality, number of weekly sessions). One-way analysis of variance (ANOVA) was applied to compare mean SF-36 domain scores across variables with more than two categories, specifically age groups and symptom categories reported during or after dialysis treatment. Chi-square (χ²) tests were used to examine associations between categorical variables, including PSQI and PSS-10 categories across sociodemographic and clinical groups. Correlations between continuous variables (PSQI total score, PSS-10 total score, and SF-36 domain scores) were analyzed using Pearson’s correlation coefficient (r). For analytical purposes, the geographical variable was dichotomized into two macro-areas (North/Central vs South/Islands). This grouping was adopted to ensure adequate sample size within each category and to improve the statistical stability of comparisons, given the relatively small sample size and the uneven distribution of participants across regions. All tests were two-tailed, and statistical significance was set at p-value < 0.05.

 

RISULTS

Sample characteristics

Although some deviations from normality were observed, parametric tests were considered appropriate given the sample size and the robustness of these methods.

Sociodemographic and clinical characteristics of our sample were reported in Table 1.

 

 

Socio-demographic characteristics	n (%)
Geographical area North Central South and Islands	51(34.5) 17(11.5) 80(54.1)
Gender Female Male	75(50.7) 73(49.3)
Age 21-30 years 31-40 years 41-50 years 51-60 years 61-70 years Over 71 years	11(7.4) 21(14.2) 36(24.3) 45(30.4) 23(15.5) 12(8.1)
Civil status Married Unmarried Divorced/Separated	84(56.8) 41(27.7) 23(15.5)
Educational level No qualifications Middle school diploma High school diploma Bachelor’s degree Postgraduate education	4(2.7) 33(22.3) 64(43.2) 36(24.3) 11(7.4)
Work employment Housewife/househusband Public employee Freelancer Factory worker Retired Student Other occupation	16(10.8) 17(11.5) 16(10.8) 20(13.5) 41(27.7) 6(4.1) 32(21.6)
How old were you when you started dialysis?	43.9±14.7
Actually you: await a kidney transplant already undergo a kidney transplant undergo Automated Peritoneal Dialysis (APD) undergo Continuous Ambulatory Peritoneal Dialysis (CAPD) undergo home hemodialysis undergo assisted home hemodialysis undergo in-center hemodialysis	5(3.4) 6(4.0) 18(12.1) 10(6.8) 5(3.4) 4(2.7) 100(67.6)
Presence of symptoms/signs during or after dialysis Yes No	81(54.7) 67(45.3)
How often do you undergo dialysis treatment? Every day 5 times/week 4 times/week 3 times/week 2 times/week 1 time/week	22(14.9) 4(2.7) 11(7.4) 92(62.2) 11(7.4) 8(5.4)

Table 1. Sociodemographic and clinical characteristics of the sample (n = 148)

 

A total of 148 participants were included in the analysis; of these, 50.7% were female (n=75). The most represented age group was 51–60 years, accounting for 30.4% of the sample and 45 participants, followed by 41–50 years with 24.3% and 36 participants, and 61–70 years with 15.5% and 23 participants. Most respondents were married, representing 56.8% and 84 individuals, whereas 27.7%, corresponding to 41 participants, were unmarried and 15.5%, corresponding to 23 participants, were divorced or separated.

Regarding educational level, the largest proportion of participants completed lower secondary school, accounting for 43.2% and 64 individuals, followed by upper secondary school with 24.3% and 36 individuals. A minority held a postgraduate degree, representing 7.4% and 11 participants. Retirement was the most common occupational status, accounting for 27.7% and 41 individuals, followed by factory work with 13.5% and 20 individuals, other occupations with 21.6% and 32 individuals, public employment with 11.5% and 17 individuals, and self-employment with 10.8% and 16 individuals. Only 4.1% of the sample, corresponding to 6 participants, were students.

The mean age at dialysis initiation was 43.9 years with a standard deviation of 14.7 years. At the time of survey completion, 67.6% of participants, corresponding to 100 individuals, were receiving in-centre hemodialysis.

The remaining participants were distributed across automated peritoneal dialysis, accounting for 12.1% and 18 individuals; continuous ambulatory peritoneal dialysis, 6.8% and 10 individuals; home hemodialysis, 3.4% and 5 individuals; and assisted home hemodialysis, 2.7% and 4 individuals. A small proportion reported being on the transplant waiting list, representing 3.4% and 5 individuals, while 4.0% and 6 individuals had already undergone kidney transplantation.

Most patients reported three dialysis sessions per week, accounting for 62.2% and 92 individuals. Smaller proportions underwent four sessions per week, representing 7.4% and 11 individuals; five sessions per week, 2.7% and 4 individuals; daily dialysis, 14.9% and 22 individuals; or lower frequencies of one to two sessions per week, representing 12.8% and 19 individuals.

Overall, 54.7% of the sample, corresponding to 81 participants, reported at least one symptom or sign during or after the dialysis session.

 

Medical history and lifestyle before dialysis initiation

More than half of the sample, representing 54.0% and corresponding to 80 participants, reported a known diagnosis of kidney failure before starting dialysis (Table 2). Hypertension was indicated as the main pre-existing medical condition by 18.9% of participants, corresponding to 28 individuals. Smaller proportions reported diabetes mellitus, accounting for 6.8% and 10 individuals, or no other medical condition, representing 11.5% and 17 individuals, indicating the absence of comorbidities beyond chronic kidney disease. Most participants, corresponding to 68.2% and 101 individuals, stated that they had heard about dialysis before initiating treatment, suggesting a certain degree of prior awareness of the therapeutic pathway. The most frequently reported symptoms before diagnosis were marked fatigue, accounting for 23.6% and 35 individuals, and swelling of the feet and ankles, reported by 22.9% and 34 individuals. Other symptoms, including nausea, vomiting, reduced urine output, itching, diffuse cramp-like pain, insomnia, or psychological complaints, were reported less frequently. A non-negligible proportion of participants reported no specific symptoms or only vague complaints.

Regarding lifestyle behaviors, 37.8% of participants, corresponding to 56 individuals, had smoked before diagnosis; 28.4%, corresponding to 42 individuals, reported alcohol consumption; and 12.2%, corresponding to 18 individuals, reported illicit drug use. Most participants did not experience marked weight loss prior to dialysis, accounting for 72.3% and 107 individuals, and 70.3%, corresponding to 104 individuals, did not habitually consume high-salt foods. Nevertheless, 85.1% of the sample, corresponding to 126 participants, stated that they had never received structured dietary counselling after diagnosis.

 

 

	n (%)
Main known medical condition before starting dialysis: Diabetes mellitus Kidney failure High blood pressure No other medical condition Other medical conditions	10(6.8) 80(54.0) 28(18.9) 17(11.5) 13(8.8)
Before dialysis, had you ever heard of dialysis? Yes No	101(68.2) 47(31.8)
What were symptoms and signs before the diagnosis? FatigueSwelling in feet and anklesAnxietyHeart palpitationsRenal colicMental confusionInvoluntary muscle contractions Routine checkups because my father had polycystic kidney disease Depression Diarrhea Diffuse cramp-like pain Postpartum hemorrhage I was young when I found out. I suffered from urinary tract infections Urinalysis Bladder inflammation Pregnancy Insomnia Red spots on lower limbs Congenital disease Loss of appetite Nausea and vomiting No symptoms None Vision problems Heart problems Protein in urine Itching Reduced urine output Cyst rupture and severe bleeding, causing skyrocketing values I have been suffering from CRF for a year, I already knew Missing	35(23.6) 34(22.9) 1(0.7) 1(0.7) 1(0.7) 1(0.7) 4(2.7) 1(0.7) 1(0.7) 1(0.7) 3(2.0) 1(0.7) 1(0.7) 1(0.7) 1(0.7) 1(0.7) 5(3.4) 1(0.7) 1(0.7) 5(3.4) 19(12.8) 2(1.4) 3(2.0) 1(0.7) 1(0.7) 1(0.7) 1(0.7) 13(8.8) 1(0.7) 3(2.0) 3(2.0)
Had you ever smoked before your diagnosis? Yes No	56(37.8) 92(62.2)
Had you ever consumed alcohol prior to your diagnosis? Yes No	42(28.4) 106(71.6)
Had you used drugs before your diagnosis? Yes No	18(12.2) 130(87.8)
Had you lost weight before undergoing dialysis? Yes No	41(27.7) 107(72.3)
Did you consume foods high in salt before the onset of the disease? Yes No	44(29.7) 104(70.3)
After your diagnosis, did you ever receive any dietary advice for your health problem? They told me to eat less salt, no bouillon cubes, canned Foods, or cured meats Nephrologist, and then I went to a nutritionist No Yes	1(0.7) 1(0.7) 7(4.7) 13(8.8) 126(85.1)

Table 2. Medical history and lifestyle before dialysis initiation.

 

Note to Table 2

Participants could report more than one symptom/sign; therefore, the total number of responses exceeds the sample size and percentages do not sum to 100%. Participants were asked to report the main known medical condition before the onset of chronic kidney disease (single-response item); therefore, these data do not capture the full burden of multimorbidity. The modality: “No other medical condition” indicates the absence of comorbidities other than chronic kidney disease.

 

Lifestyle, symptoms, and perceived health after dialysis initiation

Following diagnosis and dialysis initiation, clear changes in health-risk behaviors were observed (Table 3). A total of 81.8% of participants, corresponding to 121 individuals, reported no longer smoking; 87.8%, corresponding to 130 individuals, no longer consumed alcohol; and 90.5%, corresponding to 134 individuals, no longer used illicit drugs, suggesting a shift towards healthier lifestyles. With respect to body weight, 59.5% of the sample, corresponding to 88 participants, reported weight loss since starting dialysis, in many cases exceeding 6 kilograms and, for a relevant minority, more than 20 kilograms. Most participants, representing 83.8% and 124 individuals, stated that they no longer consumed high-salt foods, in line with nutritional recommendations for chronic kidney disease. During or after dialysis sessions, 54.7% of participants, corresponding to 81 individuals, experienced at least one treatment-related symptom. The most frequently reported complaints were swelling of the feet and ankles, accounting for 12.8% and 19 individuals; hypotension or blood pressure drop, 7.4% and 11 individuals; reduced urine output, 6.0% and 9 individuals; and headache, 6.8% and 10 individuals.

	n (%)
Did you continue smoking after your diagnosis? Yes No	27(18.2) 121(81.8)
Did you continue to drink alcohol after your diagnosis? Yes No	18(12.2) 130(87.8)
Did you continue to take drugs after your diagnosis? Yes No	14(9.5) 134(90.5)
Indicate weight loss since diagnosis (for those who answered NO to the previous question, select the answer NONE) None 0-5 kg 6-10 kg 11-20 kg Over 21 kg	60(40.5) 18(12.2) 48(32.4) 8(5.4) 14(9.5)
Have you lost weight since starting dialysis? Yes No	88(59.5) 60(40.5)
After your diagnosis, did you continue to eat foods high in salt? Yes No	24(16.2) 124(83.8)
What symptoms and signs did you experience during or after dialysis treatment? Swelling in feet and ankles Anxiety Asthenia Drop in blood pressure Mental confusion Involuntary muscle contractions Diffuse cramp-like pain Insomnia Hypotension Hypotension, fatigue Low back pain But in the head Loss of appetite Nausea and vomiting None Low blood pressure Reduced urine output Restless legs syndrome Constipation Fatigue and weakness No symptoms	19(12.8) 1(0.7) 1(0.7) 5(3.4) 3(2.0) 2(1.4) 2(1.4) 1(0.7) 1(0.7) 1(0.7) 1(0.7) 10(6.8) 7(4.7) 1(0.7) 2(1.4) 11(7.4) 9(6.0) 1(0.7) 2(1.4) 1(0.7) 67(45.2)
Perceived health status Very good Good Bad Very bad	17(11.5) 71(47.9) 50(33.8) 10(6.8)

Table 3. Lifestyle, symptoms, and perceived health status after dialysis initiation.

 

Other symptoms, including asthenia, diffuse cramps, gastrointestinal disturbances, restless legs syndrome, sleep problems, or psychological symptoms, were reported less frequently. Despite this symptom burden, 58.9% of participants, corresponding to 86 individuals, rated their health status as very good or good, whereas 41.0%, corresponding to 60 individuals, perceived their health as bad or very bad.

 

Psychometric properties of the instruments and score distribution

Table 4 summarizes the internal consistency of the study instruments in the present sample and the distribution of their scores, reported to document measurement reliability and to describe the clinical profile of the study population.

 

Scale	n	%	Cronbach’s alpha (a)
PSQI (Pittsburgh Sleep Quality Index)			0.724
Good sleep quality	—	—
Moderately impaired sleep quality	76	51.4
Severely impaired sleep quality	72	48.6
PSS-10 (10-item Perceived Stress Scale)			0.728
Low	15	10.1
Moderate	106	71.6
High	27	18.2
SF-36 (Short Form-36 Health Survey)	M	SD	Cronbach’s alpha (a)
Physical Functioning (PF)	48.8	29.0	0.911
Role limitations due to physical health, (RP)	30.6	38.0	0.845
Role limitations due to emotional problems (RE)	36.5	41.4	0.822
Vitality (VT)	42.3	20.5	0.684
Mental Health (MH)	49.8	22.0	0.766
Social Functioning (SF)	52.4	23.0	0.716
Bodily Pain (BP)	62.1	25.2	0.878
General Health (GH)	33.5	20.5	0.648
Total	44.1	19.5	0.932

Table 4. Psychometric properties and score distribution of the instruments (PSQI, PSS-10, SF-36).

 

The Pittsburgh Sleep Quality Index demonstrated good internal consistency, with Cronbach’s alpha coefficient of 0.724. According to the predefined cut-offs, none of the participants fell within the good sleep quality category. Moderate sleep impairment was observed in 51.4% of the sample, corresponding to 76 individuals, while 48.6%, corresponding to 72 individuals, presented severe impairment. These findings indicate that clinically relevant sleep disturbances were highly prevalent within the sample.

The Perceived Stress Scale 10-item version showed satisfactory internal consistency, with a Cronbach’s alpha of 0.728. Low stress levels were reported by 10.1% of participants, corresponding to 15 individuals. The majority of the sample presented moderate stress, accounting for 71.6% and 106 individuals, whereas 18.2%, corresponding to 27 individuals, reported high perceived stress.

Regarding the SF-36, internal consistency coefficients across domains ranged from 0.648 for General Health to 0.911 for Physical Functioning, indicating overall acceptable to excellent reliability. The total SF-36 score showed excellent internal consistency, with a Cronbach’s alpha of 0.932.

The mean overall SF-36 score was 44.1 with a standard deviation of 19.5, suggesting a moderate level of health-related quality of life. Domain-level analysis revealed the lowest scores in Role Physical, with a mean of 30.6 and a standard deviation of 38.0, Role Emotional, with a mean of 36.5 and a standard deviation of 41.4, and General Health, with a mean of 33.5 and a standard deviation of 20.5. These findings indicate substantial limitations in both physical and emotional role functioning and in overall health perception. Conversely, Bodily Pain showed relatively higher scores, with a mean of 62.1 and a standard deviation of 25.2, and Social Functioning a mean of 52.4 with a standard deviation of 23.0, suggesting comparatively better preservation of these domains. Vitality and Mental Health displayed intermediate values, with means of 42.3 and 49.8, respectively, indicating moderate impairment in energy levels andmental health.

 

Health-related quality of life, sleep quality, and perceived stress across sociodemographic and clinical subgroups

Differences in SF-36 domain scores across sociodemographic and clinical variables are presented in Table 5.

	SF – 36 (Mean±SD)
	PF	RP	RE	VT	MH	SF	BP	GH
Geographic area
North and Central	54.4±31.3	39.0±40.4	44.6±41.0	42.6±21.4	50.8±24.0	54.6±23.4	63.5±24.5	36.2±20.8
South and Islands	44.1±26.2	23.4±34.5	29.6±40.7	42.1±19.9	48.9±20.3	50.6±22.8	61.0±25.9	31.3±20.2
p-value	t = 2.19;     p = <0.03*	t = 2.52; p = 0.01*	t = 2.23;   p = 0.02*	t = 0.13;     p = 0.89	t = 0.51;   p = 0.61	t = 1.04;   p = 0.29	t = 0.60;   p = 0.54	t = 1.44;   p = 0.15
Age group
21-30	35.0±31.7	22.7±32.5	18.2±31.1	42.7±24.4	38.9±27.0	36.4±23.4	59.5±33.1	34.1±22.1
31-40	62.1±30.2	45.2±41.5	57.1±38.2	48.3±16.1	57.5±17.0	57.7±20.3	69.3±22.3	39.1±15.6
41-50	51.4±29.6	25.0±29.9	35.2±39.0	36.7±22.5	45.7±24.1	51.0±22.6	60.3±24.3	31.9±19.7
51-60	47.9±24.9	26.7±38.2	36.3±44.3	43.4±19.7	49.0±19.8	51.1±24.4	55.3±25.6	29.7±21.0
61-70	43.7±30.1	35.0±43.4	31.4±42.0	43.0±20.2	53.7±22.4	57.5±21.5	69.3±23.1	37.0±22.5
p-value	F = 2.15;    p = 0.07	F = 1.34; p = 0.25	F = 2.04;   p = 0.09	F = 1.19;     p = 0.32	F = 1.98; p = 0.10	F = 2.18; p = 0.07	F = 2.08; p = 0.08	F = 1.26;   p = 0.29
Gender
Female	55.5±28.3	30.3±36.8	35.1±39.9	41.3±21.7	49.3±23.1	51.3±23.5	60.7±24.7	31.7±20.4
Male	42.0±28.3	30.8±39.4	37.9±43.1	43.4±19.2	50.2±21.1	53.6±22.7	63.6±25.9	35.5±20.7
p-value	t = 2.89;     p = <0.01**	t = -0.07; p = 0.93	t = -0.40; p = 0.68	t = -0.60; p = 0.52	t = -0.23; p = 0.81	t = -0.59; p = 0.55	t = -0.68; p = 0.49	t = -1.13; p = 0.26
Dialysis modality (‡)
Peritoneal Dialysis	57.3±30.2	34.8±38.7	38.1±37.1	45.2±17.3	55.6±19.8	50.4±23.4	64.1±23.9	35.4±17.9
Hemodialysis	45.0±27.9	28.4±36.9	33.6±41.7	40.2±21.0	47.3±22.7	51.4±22.8	60.8±25.1	32.3±21.3
p-value	t = 2.04;     p = <0.04*	t = 0.80;   p = 0.42	t = 0.51;   p = 0.60	t = 1.14;      p = 0.25	t = 1.76;   p = 0.08	t = -0.19; p = 0.84	t = 0.62;   p = 0.53	t = 0.69;   p = 0.48
Dialysis sessions per week
≤3 sessions – week	47.6±28.4	31.1±38.3	37.5±43.4	41.5±21.0	48.1±22.6	53.7±22.3	63.4±23.9	34.3±21.0
3 sessions-week	52.6±30.8	29.1±37.5	33.3±35.1	44.9±19.1	54.6±19.6	48.6±25.1	58.4±29.0	31.4±19.3
p-value	t = -0.90; p = 0.36	t = 0.28;   p = 0.78	t = 0.53; p = 0.59	t = -0.86; p = 0.38	t = -1.54; p = 0.12	t = 1.16;   p = 0.24	t = 1.04;   p = 0.29	t = 0.75;   p = 0.45
Symptoms
None	48.8±28.4	37.5±47.9	41.7±50.0	57.5±28.4	74.0±16.5	65.6±23.7	83.1±33.8	20.0±17.8
Gastrointestinal symptoms	46.8±29.3	33.8±37.4	40.0±39.9	51.8±16.7	50.2±20.3	55.6±23.1	62.1±27.9	42.8±19.8
Hypotension-hemodynamic instability	49.5±37.8	40.9±39.2	54.5±47.8	48.2±18.2	57.1±22.3	59.1±33.1	63.0±29.9	32.7±21.5
Musculoskeletal pain	52.5±37.2	28.1±41.1	37.5±45.2	54.4±17.4	58.5±18.0	56.3±25.0	59.4±20.0	35.0±21.9
Fatigue and weakness	47.4±26.8	23.4±34.7	29.4±40.0	35.5±20.5	44.1±22.0	48.5±21.2	58.6±23.5	28.8±19.7
Psychological	46.1±30.4	39.5±40.2	36.8±38.3	42.6±17.8	52.0±19.4	46.7±18.6	64.6±26.9	40.0±19.9
Other	65.0±28.7	50.0±48.6	60.0±43.9	52.5±17.4	63.2±22.1	71.3±21.3	77.3±21.1	44.0±19.3
p-value	F = 0.60; p = 0.72	F = 1.26;   p = 0.27	F = 1.31;   p = 0.25	F = 3.89; p <0.01**	F = 2.93;   p = 0.01*	F = 2.55;   p = 0.04*	F = 1.37;   p = 0.22	F = 2.53;   p = 0.02*

Table 5. Differences in SF-36 domain scores across sociodemographic and clinical subgroups.

Note to Table 5

SF-36 = Short Form-36 Health Survey; PF = Physical functioning; RP = Role limitations due to physical health; BP = Bodily pain; GH = General health; VT = Vitality; SF = Social functioning; RE = Role limitations due to emotional problems; MH = Mental health;

 

Independent samples t-tests were used for dichotomous variables, whereas one-way ANOVA was applied to variables with more than two categories, namely age groups and symptom categories.

 

• Geographical area. Patients living in Northern and Central Italy displayed significantly higher mean scores than those from Southern Italy and the Islands for physical functioning, with a mean of 54.4 and a standard deviation of 31.3 compared with a mean of 44.1 and a standard deviation of 26.2, with a p-value lower than 0.03. Significant differences were also observed for role limitations due to physical health, with mean values of 39.0 and 23.4 and standard deviations of 40.4 and 34.5 respectively, with a p-value of 0.01, and for role limitations due to emotional problems, with mean values of 44.6 and 29.6 and standard deviations of 41.0 and 40.7 respectively, with a p-value of 0.02.

Sleep quality also differed significantly across geographical areas. Participants from Northern and Central regions more frequently showed moderate impairment and less frequently severe impairment compared with those from Southern and Island regions, with a p-value of 0.04, suggesting poorer sleep quality in the latter group. No statistically significant differences emerged for perceived stress levels.

• Age classes. No statistically significant differences in SF-36 domains, PSQI categories, or PSS-10 levels were observed across age groups, as all p-values were greater than 0.05. Nevertheless, some variation in mean scores was observed at a descriptive level.
• Women reported significantly better physical functioning than men, with a mean of 55.5 and a standard deviation of 28.3 compared with a mean of 42.0 and a standard deviation of 28.3, with a p-value lower than 0.01. No significant differences were observed for the remaining SF-36 domains. Sleep quality, however, was significantly worse among women, as the prevalence of severe sleep impairment was higher in females than in males, with a p-value lower than 0.01. Perceived stress levels did not differ significantly by gender.
• Dialysis modality. Patients undergoing peritoneal dialysis showed significantly higher physical functioning scores than those undergoing hemodialysis, with mean values of 57.3 and 45.0 and standard deviations of 30.2 and 27.9 respectively, with a p-value lower than 0.04. No statistically significant differences were observed for the other SF-36 domains, PSQI categories, or PSS-10 levels.
• Number of sessions per week. No significant differences were found in health-related quality of life, sleep quality, or perceived stress between patients undergoing three or fewer sessions per week and those undergoing more than three sessions per week, as all p-values were greater than 0.05.
• Presence and type of symptoms. The presence and type of symptoms during or after dialysis were significantly associated with several SF-36 domains. Significant associations were observed for vitality, with a p-value lower than 0.01; emotional well-being, with a p-value of 0.01; social functioning, with a p-value of 0.04; and general health, with a p-value of 0.02. Patients reporting fatigue and weakness, psychological symptoms, or more complex symptom clusters tended to show lower scores in these domains compared with asymptomatic patients or those reporting predominantly gastrointestinal symptoms.

 

The distribution of sleep quality (PSQI categories) and perceived stress (PSS-10 levels) across the same subgroups is reported in Table 6. Table 6 shows that sleep quality differed significantly according to geographical area, gender, and symptom burden. Participants living in Southern Italy and the Islands, women, and patients reporting fatigue, weakness, or psychological symptoms were more likely to experience severe sleep impairment. By contrast, perceived stress levels did not differ significantly across most sociodemographic and clinical subgroups, although patients with greater symptom burden tended to report higher stress levels. In particular, fatigue and weakness were more frequently associated with high perceived stress.

 

	PSQI (Sleep quality)		PSS-10 (Stress level)
	Moderately	Severely	Low	Moderate	High
	n (%)		n (%)
Geographical area
North and Central Italy	41(53.9)	27(37.5)	11(73.3)	44(41.5)	13(48.1)
South and Islands	35(46.1)	45(62.5)	4(26.7)	62(58.5)	14(51.9)
	c² = 4.03; p-value = 0.04*		c² = 5.42; p-value = 0.66
Age group
21-30	3(3.9)	8(11.1)	1(6.7)	7(6.6)	3(11.1)
31-40	12(15.8)	9(12.5)	4(26.7)	12(11.3)	5(18.8)
41-50	21(27.6)	15(20.8)	3(20.0)	26(24.5)	7(25.9)
51-60	25(32.9)	20(27.8)	2(13.3)	34(32.1)	9(33.3)
61-70	15(19.7)	20(27.8)	5(33.3)	27(25.5)	3(11.1)
	c² = 4.87; p-value = 0.31		c² = 7.51; p-value = 0.48
Gender
Female	28(36.8)	47(65.3)	8(53.3)	51(48.1)	16(59.3)
Male	48(63.2)	25(34.7)	7(46.7)	55(51.9)	11(40.7)
	c² = 12.0; p-value = <0.01**		c² = 1.12; p-value = 0.57
Dialysis modality (‡)
Peritoneal Dialysis	14(19.7)	14(21.2)	5(35.7)	19(19.4)	4(16.0)
Hemodialysis	57(80.3)	52(78.8)	9(64.3)	79(80.6)	21(84.0)
	c² = 0.04; p-value = 0.82		c² = 2.38; p-value = 0.30
Dialysis sessions per week
≤ 3 sessions – week	56(73.7)	55(76.4)	8(53.3)	83(78.3)	20(74.1)
3 sessions – week	20(26.3)	17(23.6)	7(46.7)	23(21.7)	7(25.9)
	c² = 0.14; p-value = 0.70		c² = 4.38; p-value = 0.11
Symptoms
None	4(5.3)	—	2(13.3)	1(0.9)	1(3.7)
Gastrointestinal symptoms	12(15.8)	8(11.1)	2(13.3)	15(14.2)	3(11.1)
Hypotension – hemodynamicinstability	8(10.5)	3(4.2)	2(13.3)	8(7.5)	1(3.7)
Musculoskeletalpain	1(1.3)	7(9.7)	—	8(7.5)	—
Fatigue and weakness	37(48.7)	39(54.2)	7(46.7)	50(47.2)	19(70.4)
Psychological	7(9.2)	12(16.7)	—	16(15.1)	3(11.1)
Other	7(9.2)	3(4.2)	2(13.3)	8(7.5)	—
	c² = 14.4; p-value = 0.02*		c² = 19.7; p-value = 0.07

Table 6. Distribution of sleep quality (PSQI) and perceived stress (PSS-10) across sociodemographic and clinical subgroups.

 

PSQI categories also differed significantly across symptom groups, with a p-value of 0.02, indicating that more symptomatic patients were more likely to experience severe sleep impairment.

The distribution of PSS-10 levels showed a near-significant trend, with a p-value of 0.07, suggesting a possible association between symptom burden and perceived stress.

 

Correlations between sleep quality, perceived stress, and quality of life

Table 7 presents the correlations between sleep quality measured through the Pittsburgh Sleep Quality Index, perceived stress assessed by the Perceived Stress Scale 10-item version, and selected SF-36 domains. A positive correlation emerged between PSQI and PSS-10 scores, with r equal to 0.199 and a p-value lower than 0.05. This finding indicates that poorer sleep quality, reflected by higher PSQI scores, was associated with higher levels of perceived stress. PSQI scores showed significant negative correlations with several SF-36 domains. A negative association was observed with vitality, with r equal to −0.178 and a p-value lower than 0.05, with social functioning, with r equal to −0.273 and a p-value lower than 0.05, and with bodily pain, with r equal to −0.256 and a p-value lower than 0.05. Overall, worse sleep quality was associated with lower energy levels, reduced social functioning, and a greater impact of pain. Similarly, PSS-10 scores were negatively correlated with several domains of health-related quality of life. Significant associations were found with physical functioning, with r equal to −0.376 and a p-value lower than 0.01, with role limitations due to physical health, with r equal to −0.294 and a p-value lower than 0.01, with role limitations due to emotional problems, with r equal to −0.433 and a p-value lower than 0.01, and with emotional well-being, where one of the strongest correlations was detected, with r equal to −0.676 and a p-value lower than 0.01. Additional negative correlations were found with vitality, with r equal to −0.673 and a p-value lower than 0.01, with social functioning, with r equal to −0.480 and a p-value lower than 0.01, with bodily pain, with r equal to −0.377 and a p-value lower than 0.01, and with general health, with r equal to −0.545 and a p-value lower than 0.01. These findings indicate that higher perceived stress was associated with poorer overall health perception, greater pain-related interference, reduced social participation, and broader impairments across both physical and psychological domains. Taken together, these results highlight a strong interplay between sleep quality, perceived stress, and health-related quality of life.

 

	PSQI		PSS-10
	r	p-value	r	p-value
PSQI	—	—	0.199*	< 0.05
SF-36 = Short Form-36 Health Survey,
SF-36 Physical Functioning (PF)	-0.030	0.71	-0.376*	< 0.01
SF-36 Role limitations due to physical health (RP)	-0.090	0.27	-0.294*	< 0.01
SF-36 Role limitations due to emotional problems (RE)	-0.151	0.06	-0.433*	< 0.01
SF-36 Vitality (VT)	-0.178*	< 0.05	-0.673*	< 0.01
SF-36 Mental health (MH)	-0.100	0.22	-0.676*	< 0.01
SF-36 Social functioning (SF)	-0.273*	< 0.05	-0.480*	< 0.01
SF-36 Bodily Pain (BP)	-0.256*	< 0.05	-0.377*	< 0.01
SF-36 General Health (GH)	-0.061	0.46	-0.545*	< 0.01
* = significant test, r = Pearson correlation coefficient

Table 7. Pearson correlation analysis between sleep quality (PSQI), perceived stress (PSS-10), and SF-36 domains.

 

DISCUSSION

Dialysis is a life-sustaining therapy, but it entails a substantial and long-lasting burden on the everyday lives of people with chronic kidney disease. The findings of this study confirm that the dialysis experience simultaneously involves physical, psychological and social dimensions, and that the clinical management of end-stage renal disease cannot be reduced to the control of laboratory parameters alone [9,19,20].

This multidimensional burden has been widely documented in previous studies, which describe dialysis as a condition affecting physical, psychological, and social domains simultaneously, with significant implications for patients’ daily functioning and well-being [21,22].

The absence of data on dialysis vintage and caregiving support may have limited the interpretation of some findings, as these factors are known to influence patients’ adaptation to treatment and perceived burden.

Given the cross-sectional design of the study, the findings should be interpreted as associations observed at a single time point rather than causal relationships.

In our sample, SF-36 scores depict an overall moderate level of health-related quality of life, with marked impairment of role limitations due to physical and emotional problems and of general health perception. This pattern is consistent with previous studies in dialysis populations, which have shown that difficulties concern not only somatic symptom burden, but also the ability to maintain work, family and social roles that are coherent with one’s pre-morbid identity [10–13]. From this perspective, health-related quality of life emerges as the dynamic outcome of a continuous renegotiation between disease, treatment and life projects.

These findings are consistent with previous research showing that patients undergoing dialysis report significantly lower SF-36 scores compared to the general population, particularly in domains related to physical and emotional roles [23,24].

One of the most critical findings of this study is the virtual absence of “good sleepers” according to PSQI criteria and the very high prevalence of moderate or severe sleep disturbance. This observation aligns with a robust body of literature showing that sleep problems are highly prevalent among hemodialysis patients and are associated with substantially poorer quality of life across multiple domains [21,25,26].

Indeed, sleep disturbances have been reported in up to 50–80% of patients undergoing hemodialysis and are consistently associated with poorer quality of life and increased symptom burden [25,27,28].

In our sample, higher PSQI scores (worse sleep) were associated with lower scores in selected SF-36 domains, particularly vitality, social functioning and bodily pain. The association with vitality is particularly relevant, as it suggests that poor sleep may be closely linked to reduced energy levels and fatigue, which can substantially affect daily functioning and coping capacity [28].

This pattern echoes previous studies reporting significantly worse SF-36 profiles in “poor sleepers” than in “good sleepers”, and a negative correlation between global PSQI scores and overall health-related quality of life [21,25].

Clinically, sleep should therefore not be considered a secondary epiphenomenon of chronic kidney disease, but rather a relevant modulator of the dialysis experience: non-restorative sleep may reduce the cognitive and emotional resources required to cope with treatment demands, amplify fatigue, increase pain interference, and compromise the patient’s ability to sustain social participation [27,28].

This interpretation is supported by previous studies suggesting that poor sleep quality is an independent predictor of reduced quality of life and adverse clinical outcomes in dialysis populations [27]. Perceived stress, as measured by the PSS-10, showed significant associations with multiple domains of the SF-36, including physical functioning, role limitations due to physical and emotional problems, vitality, mental health, social functioning, bodily pain and general health. This is consistent with studies in hemodialysis populations reporting that higher stress levels are related to poorer quality of life and, in some cases, reduced resilience [29].

Previous evidence indicates that chronic stress in dialysis patients is associated with treatment burden, uncertainty, and reduced coping capacity, contributing to poorer psychosocial outcomes [30].

In our sample, this pattern suggests that stress may affect not only emotional adjustment but also the patient’s ability to maintain physical roles and daily functioning [29].

The most salient aspect, however, is the positive correlation between PSS-10 and PSQI scores, suggesting a bidirectional relationship between stress and sleep quality.

This bidirectional association has been previously described in the literature, where sleep disturbances and psychological distress mutually reinforce each other, creating a cycle that negatively affects both mental health and daily functioning [31]. On the one hand, chronic stress impairs the initiation and maintenance of sleep and reduces sleep depth; on the other, fragmented and non-restorative sleep weakens coping capacity, makes symptom management more difficult, and ultimately increases perceived stress. The concurrent associations observed between disturbed sleep, elevated stress and lower SF-36 scores—particularly in domains related to vitality, social functioning, pain and role functioning—suggest a potentially interrelated pattern among these dimensions, particularly involving energy levels, social participation, pain perception and role functioning within this cross-sectional sample. This model is in line with work showing that, among dialysis patients, symptom burden, poor sleep and impaired quality of life tend to co-occur and to mutually amplify one another [28]. Subgroup analyses revealed significant differences across macro-geographical areas, with poorer quality of life and worse sleep in some regions of the country. However, the interpretation of these findings should consider that geographical areas were grouped into two macro-categories for analytical purposes, which may have reduced the granularity of regional differences. These geographical differences may reflect regional variability in healthcare organization, access to home dialysis modalities, socioeconomic disparities, and availability of psychosocial support services within the Italian National Health System. However, as contextual variables were not directly measured, these interpretations remain speculative and should be explored in future analytical studies specifically designed to assess organizational and structural determinants. Although the cross-sectional design does not allow causal inferences and organizational variables were not directly measured, the observed geographical differences may reflect contextual variations that warrant further investigation in future analytical studies. This is a relatively unexplored area in Italian research and warrants further investigation from a health-equity perspective.

Differences by dialysis modality represent another clinically relevant aspect. These differences should be interpreted cautiously, as the non-probability sampling design does not allow adjustment for potential confounding variables. In our sample, patients on peritoneal dialysis reported better physical functioning than those on hemodialysis. This is coherent with studies showing more favorable quality-of-life profiles in peritoneal dialysis patients in some settings, possibly related to greater autonomy in treatment management and a stronger sense of control over daily routines [32].Symptom burden further reinforces this systemic view. Patients reporting fatigue, weakness, psychological symptoms or intradialytic/post-dialytic discomfort had markedly lower scores in vitality, mental healthand social functioning. This is consistent with the correlational findings, in which vitality emerged as a shared domain associated with both poorer sleep quality and higher perceived stress [28,29]. These findings, in line with previous work documenting the strong association between symptom distress, sleep disturbance and quality of life, support the view that symptom management is not only a biomedical objective but also a key psychosocial leverage point [28]. Taken together, our findings suggest that quality of life in dialysis patients should be conceptualised as the outcome of a dynamic system in which physical symptoms, sleep disturbance, perceived stress and contextual factors interact with each other. Within the limits of a cross-sectional design, these findings support the potential value of multidisciplinary approaches aimed at addressing sleep, stress, and symptom burden in dialysis populations. These findings are particularly relevant for nursing practice because nurses are ideally positioned to detect early changes in symptom burden, sleep quality, perceived stress, and quality of life during routine dialysis care. This perspective reinforces the role of nursing assessment as a key step in identifying unmet needs and tailoring supportive interventions. For nursing practice, at least three priority areas emerge:

 

• Routine screening:

1.1) systematic assessment of sleep quality (PSQI), perceived stress (PSS-10) and health-related quality of life (SF-36) as part of regular follow-up;

1.2) early identification of high-risk profiles combining poor sleep, high stress and markedly impaired quality of life.

2)  Targeted interventions on sleep and stress:

2.1) tailored sleep-hygiene education that explicitly considers dialysis-related constraints (session schedules, intradialytic symptoms, daytime napping);

2.2) structured psychological and stress-management interventions (nurse-led counselling, peer groups, mindfulness-based programmes), which have shown promising effects on stress, sleep and quality of life in this population [3,33].

3)  Personalisation of care pathways:

3.1) considering geographic area, dialysis modality and symptom profile when stratifying risk and designing educational and supportive pathways;

3.2) when clinically appropriate, promoting treatment options that enhance autonomy and perceived control.

 

In summary, the interplay between sleep, stress and quality of life observed in this study invites us to move beyond a fragmented view of care. Relatively focused interventions on sleep and coping may generate cascading benefits across the psycho-physical equilibrium of dialysis patients, potentially improving not only patient-reported outcomes but also long-term adherence and clinical trajectories.

From a nursing perspective, these findings are coherent with the rationale outlined in the Introduction, where health-related quality of life, sleep quality, and perceived stress were identified as key dimensions of holistic care in patients undergoing dialysis. The strong interrelationship observed among these variables highlights the importance of systematic assessment in routine nursing practice. Nurses play a central role in identifying sleep disturbances and psychological distress, providing patient education, and implementing supportive interventions aimed at improving coping strategies and overall well-being [14,34].

 

Study limitations

The decision to conduct a cross-sectional study prevents analysis and evaluation of the course of the previously listed disorders. A further limitation relates to the sample size, which is not representative of the entire Italian population undergoing dialysis treatment. Moreover, pre-existing medical conditions were assessed through a single self-reported item asking participants to indicate their main known disease before the onset of chronic kidney disease. As a result, our data do not allow a detailed quantification of multimorbidity, which is known to be highly prevalent in dialysis populations, and comorbid burden may therefore be underestimated in this sample. Furthermore, the use of convenience sampling and online recruitment may have introduced selection bias, potentially favoring individuals with greater digital literacy or engagement in patient associations. In addition, given the exploratory nature of the study and the absence of a priori hypotheses, inferential analyses were performed without adjustment for multiple comparisons. Therefore, subgroup differences and associations should be interpreted with caution and considered hypothesis-generating rather than confirmatory. Another limitation of this study is the lack of information on dialysis vintage, defined as the time elapsed since the initiation of dialysis treatment, which may significantly influence patients’ physical, psychological, and adaptive responses to therapy. In addition, variables related to the availability of informal or formal caregiving support, as well as work-related aspects such as absenteeism or presenteeism, were not assessed. These factors may play an important role in shaping patients perceived burden, quality of life, and stress levels. Future studies should incorporate these variables to provide a more comprehensive understanding of the multidimensional impact of dialysis on patients’ daily lives.

 

CONCLUSIONS

To our knowledge, this cross-sectional observational study represents one of the first Italian nationwide attempts to jointly assess health-related quality of life, sleep quality, and perceived stress in a heterogeneous adult dialysis population. Findings indicate a moderate overall level of health-related quality of life, with marked impairment in role limitations due to physical and emotional problems and in general health perception. Nearly all participants reported clinically relevant sleep disturbance, and more than two thirds experienced at least moderate levels of perceived stress. Significant associations between poorer sleep quality, higher perceived stress, and lower SF-36 domain scores suggest an interrelated pattern in which biological, psychological, and contextual dimensions converge to shape the lived experience of dialysis, influencing both functional capacity and psychosocial well-being. Within this framework, quality of life appears as the emergent outcome of a dynamic and multidimensional system rather than a purely physical construct. Observed differences across geographical areas and dialysis modalities, although not allowing causal inference, highlight potential contextual and organizational influences within the Italian healthcare setting and warrant further investigation.Overall, these findings support the systematic integration of sleep and stress assessment into nephrology care pathways and reinforce the value of multidisciplinary models addressing symptom burden, psychosocial distress, and patient-reported outcomes. Future longitudinal studies with larger samples are needed to clarify directional relationships and to evaluate the effectiveness of targeted interventions on patient-centered outcomes and long-term care trajectories. From a nursing perspective, the systematic assessment of quality of life, sleep quality, and perceived stress should be considered an integral part of routine dialysis care. These dimensions provide essential information to guide personalized nursing interventions, strengthen patient-centered care, and support improved clinical outcomes.

 

List of abbreviations

CKD – Chronic Kidney Disease;

QoL – Quality of Life

SF-36 – Short Form-36 Health Survey

IQOLA – International Quality of Life Assessment Project

PSQI – Pittsburgh Sleep Quality Index

PSS-10 – Perceived Stress Scale – 10-item version

PF – Physical Functioning

RP – Role Physical

RE – Role Emotional

VT – Vitality

MH – Mental Health

SF – Social Functioning

BP – Bodily Pain

GH – General Health

PCS – Physical Component Summary

MCS – Mental Component Summary

SD – Standard Deviation

ANOVA – Analysis of Variance

χ² – Chi-square test

r – Pearson correlation coefficient

 

Funding

The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

 

Competing Interests

The authors have no relevant financial or non-financial interests to disclose.

 

Ethics Approval

This study was conducted in accordance with the principles of the Declaration of Helsinki. Ethical approval was obtained from the Ethics Committee of IRCCS Istituto Oncologico “Gabriella Serio”, Bari, Italy (Protocol No. 568, data approval: July 30, 2024).

 

Consent to participate

Informed consent was obtained from all individual participants included in the study.

 

Data Availability

The datasets generated during and analyzed during the current study are available from the corresponding author on reasonable request.

 

Author Contributions

Ivan Rubbi and Roberto Lupo contributed to the study conceptualization and methodology, data collection, analysis and interpretation of results, and drafting of the first version of the manuscript. Luana Conte and Elsa Vitale made substantial contributions to conceptualization, methodology, scientific supervision, and critical revision of the manuscript. Ritiana Marinelli, Stefano Botti, Carmela Triglia, and Antonino Calabrò contributed to data collection and manuscript revision. Federico Cucci contributed to manuscript review and editing. All authors read and approved the final version of the manuscript. Ivan Rubbi and Roberto Lupo contributed equally as first authors. Luana Conte and Elsa Vitale contributed equally as senior authors.

 

 

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Hamza Khan ², Muhammad Shayan ², Zohaib Hussain ³, Mah Noor Mumtaz ⁴,

Wajid Hussain ⁴, Abdur Rahman ²*, Mahnoor Ali ⁵

1. Medical B Ward, Bacha Khan Medical College / MTI Mardan Medical Complex, Mardan, Peshawar, Pakistan.
2. Department of Nursing, Elizabeth Rani College of Nursing Mardan, Peshawar, Pakistan.
3. Department of Nursing, Institute of Health Sciences, Mardan, Peshawar, Pakistan.
4. Department of Biochemistry, Abdul Wali Khan University, Mardan, Peshawar, Pakistan.
5. Department IPMH & BS, Khyber Medical University, Khyber Pakhtunkhwa, Pakistan.

* Corresponding author: Abdur Rahman, Department of Nursing, Elizabeth Rani College of Nursing Mardan, Peshawar, Pakistan. E-mail: abdurrahman888889998@gmail.com

Cite this article

 

ABSTRACT

Introduction: Acid-base balance is one of the most essential physiological terms, which play a crucial role in the examination of the patient and clinical observation. To control the patients well and detect changes when they start to deteriorate, nurses should have a good grasp of acid-base physiology.

Objective: The paper examined the impact of the level of knowledge of acid-base balance on clinical surveillance practices of nurses in Northeastern Pakistan.

Material & Methods: A cross-sectional, correlational, descriptive study was conducted on 403 registered nurses in different clinical settings in Northeastern Pakistan. The questionnaire was structured and validated, and it was completed by over four weeks by five sections: demographics; acid-base knowledge (10 items); clinical monitoring skills (12 items); knowledge to practice application (5 items); and barriers to effective monitoring. The statistical tests included descriptive statistics, Pearson correlation, independent t tests, one way ANOVA and linear regression.

Results: Nurses had high scores on acid-base knowledge (mean of 9.78/10, SD of 0.58) and clinical monitoring skills (mean of 53.8/60, SD of 6.2). There was a great deal of correlation between knowledge and skills (r = 0.82, p = 0.001). Greater qualification, experience, and formal training in ABG was an indicator of superior skills. Heavy workload was the most prevalent (54.1%) and lack of time (36.0%). Knowledge explained 52% of the variance in monitoring skills (R² = 0.52).

Conclusion: The clear understanding of acid-base balance is a key to the formation of clinical monitoring skills of nurses. The enhancement of patient monitoring practices will be achieved by the strengthening of acid-base education and barriers of workload.

Keywords: Clinical monitoring skills, acid -base balance, nurses, Pakistan, nursing education.

INTRODUCTION

One of the fundamental physiologic principles required during the evaluation and observation of patients is acid-base balance. As the first-line caregivers, nurses are very important in the early detection of acid-base disorders. One of their direct impacts on patient outcomes is their ability to detect subtle differences in respiratory patterns, state of consciousness, and vital signs [1]. Systematic observation, assessment, and interpretation of patient data is called clinical monitoring and is one of the core competences that distinguish expert nurses and novices and ensure patient safety [2,3]. Although the nursing curricula addresses the physiology of acid-base, there is most of the time a gap that exists between theory and practice. This gap between theory and practice is an important topic in nursing education with the potential threat to patient safety [4-6]. It has been reported that nursing students performed poorly on written exams, but they failed to apply their learning in the bedside [4,5]. Acid-base disturbances are common in the critically ill patients and are associated with a high mortality. Deviations in the parameters of arterial blood gases are also the foretellers of bad results among patients who are under intensive care [7], low blood pH is also a strong indicator of adverse final results [8]. Septic patients in Pakistan would have metabolic acidosis, and it was associated with fatal outcomes [9]. Physical examination (respiratory rate, depth, pattern, level of consciousness, vital signs) and analysis of diagnostic data, especially arterial blood gas (ABG) are part of clinical monitoring regarding acid-base balance [2,3,10]. The proper understanding of ABG requires a good theoretical foundation [10-12]. Nurses who understand the pathophysiology of acid-base have a greater advantage to diagnose the beginning of deterioration, care formulation, effective communication with the healthcare team, and predict complications [1,2,4,7-9,10-14]. There are a number of factors that determine the capability of nurses to use acid-base knowledge in clinical practice. Increased level of education, deep clinical experience, and formal training in ABG have been associated with better monitoring skills [1,3]. On the other hand, workload, time, lack of confidence, and inadequate continuing education are the obstacles [3,9,15]. Nursing education in Pakistan has evolved in the last thirty years. Pakistan Nursing Council regulates nursing education and licensure and the Generic Bachelor of Science in Nursing program includes pathophysiology and clinical rotations [3,9]. However, the evidence on the association between theoretical knowledge of acid-base and clinical monitoring skills in the Pakistani context among nurses is lacking [3,9]. Therefore, this study was aimed at exploring the role that the classification of acid-base can play in the building of clinical monitoring proficiency in nurses in Northeastern Pakistan.

Aim

This research will focus on the importance of acid-base knowledge in developing clinical monitoring competencies in nurses in Northeastern Pakistan.

Objective: The research questions of this research are as follows:

1. To determine the degree of acid-base knowledge in nurses in Northeastern Pakistan.
2. To determine the self-reported degree of clinical monitoring skills in nurses working in Northeastern Pakistan.
3. To establish the relationship between the knowledge of acid-base and clinical monitoring skills of the nurses.
4. To compare clinical monitoring skills among various demographic and professional groups such as gender, qualification, years of experience and the trainee status of ABG training.
5. To determine the obstacles that do not allow the nurses to monitor patients effectively to detect acid-base imbalances.
6. To produce evidence to guide nursing education and practice on the management of acid-base balances.

MATERIALS AND METHODS

Study Design and Setting 

The study was a descriptive, cross-sectional, correlational study, which was carried out across four weeks among the Registered Nurses (RNs) in various clinical environments in Northeastern Pakistan. The purpose was to test the effect of the knowledge of acid-base concepts on the clinical monitoring ability of nurses.

 

Sampling and Eligibility 

Study Period 

The research was conducted for four weeks, between 1 December 2025 and 29 December 2025.

 

Type of Study 

The relationship between acid-base knowledge and clinical monitoring competence in nurses was examined in a descriptive cross-sectional correlational design.

 

Study Population 

The sample included RNs who were employed in a tertiary hospital, district hospital, private clinic, and community health center in Northeastern Pakistan. The student nurses, post RN nurses and diploma-nurse graduates were not included to give similar clinical experience and training.

 

Inclusion Criteria 

• Registered Nurse and valid license.
• In use in a clinical environment.
• Willing to participate
• Capable of comprehending and filling the questionnaire.

Exclusion Criteria 

• Unregistered (yet) student nurses.
• Nurses out on long leave or out during data collection.
• Informed consent was not given by nurses.

 

Sample Size Calculation 

The OpenEpi v3.0 was used to calculate the sample size based on Cochran formula:

 

 

Where: Z = 1.96 (95% confidence level). p = 0.50 (proportion expected; this maximizes the sample size since there was no previous research in this population) and d = 0.05 (margin of error).

Since we did not know the RN total population, we did not make any correction in terms of a finite population. In this way, the minimum number of nurses was 385. All available and qualifying RNs were invited to minimize the non-response bias. There was adequate statistical power and 403 nurses were responding.

 

Sampling Technique 

Non-probability convenience sampling technique was selected due to the practicality: access to the participants, time and the research exploratory nature. There was no possibility to use random or probability-based sampling since a full sampling frame of all registered nurses in all clinical settings in Northeastern Pakistan was not available. Moreover, the nurses were not always available on their units since they were on shifts, leaves, and caring of patients, which made the use of probability-based sampling impossible. We recognize that convenience sampling can be a source of selection bias because nurses who were available and willing to take part might differ with those who were not. This restricts the generalization of the findings.

 

Participants were recruited through personal contacts 

Several clinical sites that were chosen offered administrative assistance to the nurses. Recruitment was done using nursing supervisors, head nurses and clinical coordinators who used the official communication channels to pass the information about the study.

 

Context of Participation 

The paper questionnaires were issued within the clinical setting. They could be done by nurses during breaks or after shifts. The study details were provided in a concise manner and nurses were not pressured to join in the study.

 

Voluntary Participation 

The participation was on a voluntary basis. Nurses were given a clear information regarding the objectives of the study, procedures and possible benefits and their informed consent form was signed. They were also promised that their participation would not have any impact on their jobs or professional status.

 

Bias Mitigation 

Although convenience sampling may introduce self-selection bias, several measures were implemented to minimize this risk. All qualified nurses were invited irrespective of previous interest and knowledge. There were several reminders which increased representativeness. The fact that the study was represented by various clinical settings in the Northeastern part of Pakistan also minimized bias.

Ethical Considerations 

The research received the consent of the Institutional Review Board (IRB) of Abdul Wali Khan University, Mardan.

• IRB Title: the institutional review board, Abdul Wali Khan University Mardan.
• IRB Number: IRB/2025/Acid-Base/Biochem/Nursing/0011
• Approval Date: 21-Nov-2025

 

The subjects were assured confidentiality, anonymity and the freedom to withdraw whenever they wished without consequences. No personal identifiable data was gathered, all the data were coded by number and safely kept by the research team.

 

Informed Consent 

All the participants signed written consent before data collection. The consent form described the purpose of the study, which was voluntary, the right to leave, and to confidentiality.

 

Incentives 

No economic or non-economic rewards were provided to take part.

Instruments 

Data Collection Tool 

Data were collected using an organized and tested questionnaire that was based on previous and confirmed research about the knowledge of acids and bases and clinical monitoring proficiencies. The questionnaire was created based on regular nursing teaching material and subject-matter experts revised the content of the questionnaires to ensure the content validity. 

The questionnaire has been categorized into five parts as reported in Table 1. 

Section	Content	Number of Items
A	Demographic Characteristics	6 items
B	Acid-Base Understanding (Knowledge Test)	10 items
C	Clinical Monitoring Skills (Self-Assessed Competency)	12 items
D	Knowledge-to-Practice Application	5 items
E	Barriers to Effective Monitoring	1 item (multiple response)

Table 1. Section Number of Items Content.

Section A

Demographic Characteristics such as age, gender, qualification, years of experience, work area and ABG training status were included. 

Section B

Acid-Base Understanding – involved ten multiple-choice question-based tests that evaluate pH, PaCO 2, -HCO 3, nature of disorders, compensatory responses, and typical clinical situations. One point was given a correct answer, making the possible score between 0 and 10. 

Section C

Clinical Monitoring Skills- included twelve questions assessing self-reported abilities in respiratory assessment, ABG and risk identification, prioritisation and communication. The scale was based on a 5-point Likert scale:

• 1 Never/Not Confident,
• 2 Rarely/Slightly Confident,
• 3 Sometimes/Moderately Confident,
• 4 Often/Very Confident,
• 5 Always/Extremely Confident.

Total scores ranged from 12 to 60. 

Section D

Knowledge-to-Practice Application – consisted of five questions which tested how knowledge is implemented in clinical practice. 

Section E

Barriers to Effective Monitoring – had one item which provided the respondent with multi-choice possibility of selecting more than one perceived barrier. 

Validity and Reliability 

Two experts a nursing educator and a clinical instructor validated content validity. Face validity was developed through pilot testing ten registered nurses. Cronbach alpha (0.85) was used to measure Section C internal consistency, which was good. 

Content validity was established by two experts (a nursing educator and a clinical instructor). Pilot testing was carried out to develop face validity using ten registered nurses.

The alpha of Cronbach was determined to determine the internal consistency of every section of the questionnaire:

• Section B (10 items): α = 0.81.
• Section C (12 items): α = 0.85.
• Section D (5 items): α = 0.79.

The values are all above the acceptable level of 0.70, which means good internal consistency.

Data Collection Procedure 

The questionnaire was written and sent out to the clinical situations of participants. The researcher visited the selected health-care facilities at convenient times, approached the potential participants, informed them about the study, and invited them to participate in the study. Informed consent was received by means of written informed consent. The questionnaires were given out and collected on the same day to optimise the response rates. The collection of data went on till the required sample size was achieved. 

Statistical Analysis 

The data were read with the help of SPSS version 26. All the variables were computed using descriptive statistics. Means, standard deviations (SD), median, interquartile range (IQR), minimum, and maximum were presented as the variables were continuous (age, knowledge scores, skills scores, and so on). Categorical variables (gender, qualification, years of experience, work area, ABG training status) were described in the form of frequencies and percentages.

Shapiro-Wilk test was used to test the normality of knowledge and skills scores; p-values were found to be greater than 0.05, which proves that knowledge and skills scores were distributed normally and, accordingly, matches the use of parametric tests. 

Pearson correlation coefficients were used to test a correlation between skills scores and total knowledge scores, and the assumption of linearity and normality was checked and fulfilled. 

Independent-samples t-tests were applied to test the difference in mean scores of knowledge and skills between male and female nurses. 

ANOVA was used to determine the difference between the mean scores of knowledges and skills by comparing groups of years of experience, the level of qualification and the area of work. The reason why the test was selected was that the independent variables had more than two levels. Premeditative homogeneity of variance and normality were investigated: the Shapiro–Wilk test demonstrated non-significant p-values (p > 0.05) in all groups, and Levene test showed that variance was equal (p > 0.05). Type I error was controlled when ANOVA showed significant differences by Tukey, Honestly Significant Difference (HSD) post-hoc tests. 

The skills scores were predicted using knowledge score as the only predictor through simple linear regression. Multiple linear regression was used to determine the independent predictors of the skills scores, such as knowledge score, years of experience, qualification, and status of ABG training. All predictors were included using the enter method. Linearity, independence of residuals, homoscedasticity, and normality of residual assumptions were met. The 95% confidence interval for correlation and regression coefficients was reported to show precision.

Regression assumptions verification: The individual predictive effect of academic knowledge score of acid–base balance on clinical monitoring skills was assessed using simple linear regression. Multiple linear regression was used to determine the independent predictors of clinical monitoring skills after controlling for possible confounders, including qualification, years of experience, and ABG training status.

The linear regression assumptions were checked before analysis. Linearity was assessed by visual inspection of scatterplots of residuals against predicted values, which did not reveal any discernible pattern. Normal distribution of residuals was verified using the Shapiro–Wilk test (p > 0.05) and Q–Q plots. Homoscedasticity was assessed using the Breusch–Pagan test (p > 0.05), confirming constant variance of residuals. Multicollinearity, where multiple regression was used, was evaluated using variance inflation factor (VIF) values, which ranged from 1.12 to 1.89, indicating no significant multicollinearity. Independence of residuals was tested using the Durbin–Watson test (value = 1.98), indicating no autocorrelation.

The statistical significance level was established at p<0.05 and all the tests were two-tailed.

RESULTS

Demographic characteristics

There were 403 registered nurses who took part in the study. The average age of the sample was 34.8 (SD 7.2) and was between 22 and 52 years. The demographic characteristics are provided in Table 1, and the rest of the relevant findings are shown in Figures 1,2,3,4.

 

Variable	Category	Frequency (n)	Percentage (%)
Gender	Male	207	51.4
	Female	196	48.6
Qualification	Diploma	253	62.8
	BSN	117	29
	MSN	33	8.2
Experience	< 1 year	33	8.2
	1-5 years	132	32.8
	6-10 years	123	30.5
	> 10 years	115	28.5
ABG Training	Yes	310	76.9
	No	93	23.1
Training Recency	< 6 months	48	15.5
	6-12 months	54	17.4
	> 1 year	208	67.1

Table 1. Demographic Traits of Participants

 

Figure 1 indicates the gender distribution of the 403 registered nurses. The percentage distribution of males and females is 51.4 (207 nurses) and 48.6 (196 nurses), respectively, which is rather equal.

Figure 1. Gender of Participants.

Figure 2 shows the level of education of the nurses. The majority of them had a Diploma in Nursing (62.8% of 253 nurses), then a Bachelor of Science in Nursing (BSN) with 29.0% (117 nurses), and finally a Master of Science in Nursing (MSN) with 8.2% (33 nurses).

Figure 2. Qualification of the participants

 

Figure 3 provides the clinical experience of the nurses. The highest number was 1-5 years experience (32.8, 132 nurses), then 6-10 years (30.5, 123 nurses), over 10 years (28.5, 115 nurses) and less than one year (8.2, 33 nurses). The majority of nurses (76.9%, n=310) had received formal training in ABG, while 23.1% (n=93) had not.

Figure 4 shows the latest date in which the 310 trained nurses received the ABG training.

The majority (67.1%, 208 nurses) of them were trained more than one year ago, 17.4 percent (54 nurses) trained 6-12 months ago, and 15.5 percent (48 nurses) had been trained within the past six months.

Figure 3. Experience of the participants

Figure 4. Training Recency of the participants

To Test the Acid-Base Knowledge Level of Nurses

Section 10 items assessed the knowledge that nurses had on the acid-base balance. Descriptive Statistics of Knowledge and Skills Scores were shown in Table 2.

 

Variable	Mean	SD	Median	Min	Max
Knowledge Score (out of 10)	9.78	0.58	10	8	10
Skills Score (out of 60)	53.8	6.2	56	38	60
Knowledge Score Distribution (Score)	Frequency (n)	Percentage (%)
8	16	4
9	26	6.5
10	361	89.5
Skills Score Distribution (Score Range)	Frequency (n)	Percentage (%)
35–40	12	3
41–45	42	10.4
46–50	84	20.8
51–55	70	17.4

Table 2. Descriptive Statistics and Distribution of Knowledge and Skills Scores (N=403).

The mean score was 9.78 of 10 (SD=0.58), which means that there is high knowledge.

Very high percentage (89.5%) (n=361) scored 10, which depicts a very good understanding of acid-base concepts.

 

To Evaluate Self-Reported Clinical Monitoring Skills with the Nurses

Clinical monitoring skills were measured using section C (12 items) on a 5-point Likert scale. The average was 53.8 of 60 (SD = 6.2), which was high self-report competence. The highest range (56-60) had almost half (48.4) of the total scores, which reflects good monitoring skills.

To Establish the Relationship between the Acid-Base Knowledge and Clinical Monitoring Skills 

Pearson’s correlation analysis was conducted to examine the relationship between knowledge scores (Section B) and skills scores (Section C). As shown in Table 2, a statistically significant, positive, and strong correlation was observed. Nurses with higher knowledge scores also demonstrated higher clinical monitoring skills scores.

 

Variable Pair	Correlation Coefficient (r)	95% CI	p-value
Knowledge Score & Skills Score	0.82	[0.78, 0.86]	< 0.001
Note: Pearson correlation assumptions were checked before analysis. The Shapiro-Wilk test was used to test normality (p > 0.05). Scatterplots were used to determine the linearity and the relationship was linear. No extreme outliers were observed (no values more than ±3 standard deviations of the mean)

Table 3. Pearson coefficient of Knowledge and Skills Scores.

 

To Compare Clinical Monitoring Skills in the various demographic and professional groups 

Comparison by Gender 

The difference between the scores of the skills of male and female nurses did not show significant differences (p=0.156).

Comparison of Qualification

Higher level qualifications related with better clinical monitoring skills.

Comparison by Experience

As one becomes more skilled the skills increase. The distance between all the experience groups is significant (p < 0.01).

Comparison of ABG Training status

Table 3 summarizes differences in clinical monitoring skills scores according to demographic and professional variables, as assessed through t‑tests and one‑way ANOVA.

ABG trained nurses scored significantly higher (p < 0.001). Central Finding: The greater the level of qualifying is, the greater the monitoring skills. Post-hoc tests indicate that the MSN nurses had scores that were high as compared to the diploma nurses (p = 0.006).

 

Variable	Categories	N	Mean Skills Score	SD	Statistic	p-value
Gender	Male	207	54.2	6	t = 1.42	0.156
	Female	196	53.4	6.4
Qualification	Diploma	253	53.2	6.4	F = 4.89	0.008
	BSN	117	54.6	5.8
	MSN	33	56.1	5.2
Experience	< 1 year	33	44.8	4.2	F = 48.2	< 0.001
	1-5 years	132	51.2	5.1
	6-10 years	123	55.4	5.3
	> 10 years	115	57.8	4.6
ABG Training	Yes	310	55.9	5.1	t = 12.4	< 0.001
	No	93	46.8	5.5

Table.4 Comparison of Clinical Monitoring Skills by Demographic and Professional Groups

Knowledge-to-Practice Application

To assess the application of knowledge into clinical practice, Section D comprised five statements rated on a 5‑point Likert scale. Table 5 summarizes nurses’ responses in terms of mean scores and standard deviations.

 

Statement	Mean	SD
D1: Theoretical knowledge helps recognize problems earlier	4.65	0.48
D2: Consciously apply acid-base concepts when assessing patients	4.42	0.69
D3: There is a gap between class learning and clinical practice	2.82	0.87
D4: Confident connecting lab results to physical assessment	4.38	0.71
D5: Continuing education would improve monitoring skills	4.92	0.27

Table 5. Knowledge-to-Practice Application Statements.

 

Key Findings: 

• 8 percent said they agreed or strongly agreed that theoretical knowledge helps in early problem recognition.
• 1% said that they are aware of using acid-base concepts.
• Perceived gap between learning and practice in classrooms was seen in only 18.6% of the people.
• 5 percent strongly agreed that the continuation of the education would advance monitoring skills.

 

To Determine Bars to Counterproductive Nursing Care in the Surveillance of Acid-Base Imbalances in the Patient

Participants were asked to identify perceived barriers to effective acid–base monitoring. Table 6 summarizes the frequency and percentage distribution of the reported barriers, with heavy workload identified as the most common impediment.

 

Barrier	Frequency (n)	Percentage (%)
Heavy workload / too many patients	218	54.1
Lack of time	145	36
Lack of confidence in interpreting results	32	7.9
Insufficient training	28	6.9
Limited access to ABG results	12	3
Lack of experienced staff to consult	8	2
None	18	4.5

Table 6. Hurdles to Successful Surveillance.

 

The most frequently reported barriers to effective acid–base monitoring were heavy workload and lack of time.

 

Regression Analysis

Simple Linear Regression 

Simple linear regression was used to determine the prediction of clinical monitoring skills using acid-base knowledge scores.

Clinical monitoring skills were explained by knowledge score 0.52. The skills score increased by 8.82 points with each one-point increment in the knowledge score.

 

Model summary	R2	F-statistic	df numerator	df denominator	p-value
0.52	441.0	1	401	<0.001
Predictor	Β	SE	t-statistic	p-value	95% CI
Knowledge Score	8.82	0.42	21	< 0.001	[7.99, 9.65]

Table 7. Simple Linear Regression Analysis.

 

Multiple Linear Regression 

To identify clinical monitoring skills as related to the knowledge score, qualification, experience, and status of the ABG training, the multiple linear regression was performed.

Model summary	R2	F-statistic	df numerator	df denominator	p-value
	0.81	425.6	4	398	<0.001
Predictor	β	SE	t-statistic	p-value	95% CI
Knowledge Score	7.45	0.38	19.6	< 0.001	[6.70, 8.20]
Qualification	1.12	0.28	4	< 0.001	[0.57, 1.67]
Experience	1.89	0.22	8.6	< 0.001	[1.46, 2.32]
ABG Training (Yes)	4.32	0.48	9	< 0.001	[3.38, 5.26]

Table 8. Multiple Linear Regression Analysis.

 

The entire model explained 81 percent of the variance in clinical monitoring skills. Knowledge score was the most significant one with experience coming in next, followed by ABG training status and qualification.

 

Critical Discussion of the Results 

The researchers concluded that the majority of the nurses had a high level of knowledge and a good clinical monitoring ability associated with acid-base balance. However, on closer examination of the individual survey questions and subgroup analyses, there is a more detailed image. The nurses were not equally effective in exhibiting flawless competency in all the clinical monitoring activities. The level of knowledge was very high and K=89.5 and 10 is the highest possible mark, which means that the theoretical basis is strong. Contrastingly, the variation in terms of skills scores was less: 48.4 percent were in the upper tack (56-60), 20.8 percent were in the mid-range (46-50). This implies that academic knowledge may not necessarily become an ideal clinical practice. Self-reported skills differed even in the case of nurses who scored perfectly in terms of knowledge, which suggests that other variables have an impact on performance. Demographic analysis of skills scores was important in identifying some trends. Nurses who are less than one year experienced the lowest average skills score (44.8/60), and those who are over ten years experienced the highest (57.8/60). The gradual change highlights the importance of experiential learning but also brings up the issue of the willingness of novice nurses to be able to monitor the patients in isolation. The significant difference in means of 13 between novice and experienced nurses indicates that the development of skills with the help of structured mentorship might be faster. Formal ABG training was associated with much higher scores in skills (55.9 vs. 46.8, p 0.001). Nevertheless, 23.1 percent of nurses were not sufficiently trained on the use of ABG, which stands as a serious gap in the workforce susceptibility. On the Knowledge-to-Practice Application section, 95.8 percent of the nurses concurred that theoretical knowledge aids in diagnosing the problems at an earlier stage, but only 90.1 percent agreed to be conscious in applying the concepts of acid-base when evaluating patients. The 5.7 percent disparity is the indication of a small yet significant gap between the recognition and the regular use. Moreover, 18.6 per cent of nurses indicated that they felt disconnected between their classroom and clinical practice indicating that theory-practice gap was still present in some. The barriers analysis indicated that the most frequent barriers are heavy work load (54.1) and time (36.0). Such systemic conditions can hamper the implementation of competencies despite nurses being informed. The quality of monitoring is also a problem due to the high incidence of heavy workload which was the main area of concern regarding patient to nurse ratio. The regression models (R² = 0.52; 0.81) and the correlation analysis (r = 0.82) indicate that there is a medium-high correlation between knowledge and skills. But the complete model predicts 81 per cent of the variance leaving 19 per cent unaccounted. The remaining variance can be due to factors that cannot be measured including personal motivation, cognitive burden, work culture, or access to mentors. When most nurses were found not lacking in confidence in their skills, quite a significant number showed concerns. Obstacles connected to the absence of confidence (7.9%), as well as the lack of training (6.9%), indicate that the knowledge does not necessarily ensure the lack of confidence or the positive attitude. These results highlight the importance of developing confidence-building techniques and workload management of nursing education and practice. In general, the findings suggest that even though the nurses are well-equipped in terms of acid-base knowledge, the usage of that knowledge in clinical monitoring is experience-dependent, training-dependent, as well as systemic. The educational interventions must be oriented not just on acquiring the knowledge, but also confidence development, exposure to practical experience in simulation and training exercises, and institutional concerns (workload, time limitations) to facilitate bedside implementation.

 

DISCUSSION

This paper discussed the relationship between acid-base knowledge and clinical monitoring competencies among nurses in Northeastern Pakistan. The results showed that the level of acid-base knowledge (mean = 9.78/10, SD = 0.58) and self-reported clinical monitoring skills (mean = 53.8/60, SD = 6.2) was high and there was a positive correlation between the two variables (r = 0.82, p < 0.001). Such results imply that an excellent theoretical basis in acid-base physiology is inextricably linked with improved clinical monitoring among nurses. The level of knowledge in this study (89.5% stating 10/10) is in line with Dakic et al. [1] in which interactions teaching method enhanced the students’ knowledge of acid-base physiology. On the same note, Brown et al. [2] observed that nursing students excel on written exams, but it is difficult to exercise the knowledge in clinical practice, and this correlates with the current research in which some respondents show a theory-practice gap. The correlation between knowledge and skills (r = 0.82) is strong, which is similar to those of international studies. In their study, Nassar and Schmidt [15] and Prasad et al. [18] noted that proper interpretation of ABG needs a sound theoretical foundation, which explains why we have found that knowledgeable nurses report higher monitoring skills. Moreover, Endacott et al. [5] discovered that successful monitoring involves the combination of technical skills and clinical reasoning, which is also consistent with the high level of skills given by our participants.

No differences in clinical monitoring skills were significant between the genders (p = 0.156), which concurs with Zhang et al. [10], who had no gender differences in metabolic abnormalities in nurses. But, higher qualified nurses showed much better monitoring skills (F = 4.89, p = 0.008), with the MSN-prepared nurses scoring higher than the diploma nurses (p = 0.006). This correlates with the study of Baiee and Ali [19] who observed that increased education is related to enhanced knowledge and skills. Clinical monitoring skills had a strong association with experience (F = 48.2, p < 0.001), which is consistent with Endacott et al. [5], who have found that advanced nursing competencies are acquired with time through clinical exposure. In the same vein, formal ABG training was also connected with much higher skills scores (t = 12.4, p < 0.001), which confirms the results of Fujimoto et al. [16], Zeserson et al. [17], and Prasad et al. [18] about the importance of structured training. Most of the nurses (95.8% said that theoretical knowledge would help them identify problems early and 96.5% said strongly that further education would enhance their monitoring abilities. These results indicate that continuous professional growth is necessary, as it is also stressed by Baiee and Ali [19]. The most common obstacles to effective monitoring were heavy workload (54.1) and lack of time (36.0). These findings are in line with those of Zhang et al. [10] who found that workload and shift-related stress are significant determinants of nurse behavior. These obstacles are especially applicable to the Pakistani environment, where the nurse-to-patient ratios are difficult [20]. The regression analysis showed that the knowledge score alone was sufficient to explain 52 percent of the variance in clinical monitoring skills (R² = 0.52), whereas the complete model that contains knowledge, qualification, experience, and ABG training was sufficient to explain 81 percent (R² = 0.81). Knowledge score was the strongest predictor (β = 7.45, p < 0.001), followed by experience (β = 1.89, p < 0.001), ABG training (β = 4.32, p < 0.001), and qualification (β = 1.12, p < 0.001).

 

CONCLUSION

This paper has shown that there is a close relationship between acid-base education and clinical monitoring competency among nurses in Northeastern Pakistan. These findings revealed that nurses had good acid-base knowledge (mean = 9.78/10) and clinical monitoring skills (mean = 53.8/60), and the two variables had a strong positive correlation (r = 0.82, p < 0.001). Increased qualification, experience, and formal training on ABG were linked to better monitoring skills. The barriers to effective monitoring were most often reported, 54.1%, and lack of time (36.0%).

Regression analysis found the best predictor of clinical monitoring skills is the acid-base knowledge, which explains 52% of variance. The entire model comprising experience, qualification, and training in ABG explained 81 percent of the variance. These results suggest that theoretical understanding of acid-base balance is one of the factors correlated with clinical monitoring competency in nurses.

 

Recommendation

For Nursing Education 

The teaching of acid-base contents should be supported by interactive and case-based methods through nursing education programs to increase knowledge and memory [1,2]. The use of simulation-based training in the curricula is necessary to provide the students with a hands-on experience of ABG interpretation and clinical monitoring practice [5,7].

 

For Clinical Practice 

A formal training process of practicing nurses should be developed by healthcare institutions since formal training was significantly associated with a higher level of monitoring skills [15,17,18]. Continuous education programs must be carried out on a regular basis to sustain and improve clinical competencies, particularly in acid -base management [19].

 

In the case of Healthcare Institutions 

Workload and time issues should be handled with institutional leadership by maximizing the number of nurses per patient, since the issue of workload per patient is the most prevalent one that is reported as an obstacle to effective monitoring [10,20]. ABG results should be made available in a timely manner to assist in clinical decision-making and to enable some timely interventions [12,16].

For Future Research 

Objective data in clinical monitoring skills including direct observation or simulation-based measures should be used in future studies to improve self-reported data [7]. Multi-centered research in the various areas of Pakistan is required to enhance the overall external validity of the results [20].

Limitations

This study has several limitations. To begin with, convenience sampling will restrict the generalizability of the findings to the whole population of nurses in Pakistan. Second, the skills reported by the self might not be the ones that are objective in clinical performance, because perceptions are not necessarily associated with competency. Third, the study design is cross-sectional and therefore no causal inferences can be made; despite a strong association, it is not possible to imply causality. Fourth, the research was only done in a single region (Northeastern Pakistan) and this could not be generalized to other geographical regions. Fifth, causal relationships cannot be drawn because of the cross-sectional design. The interrelationships mentioned in this research are not causal but correlational. These limitations could be overcome by future studies based on probability sampling, objective competency tests, and multi-center studies.

 

Funding statement

This research did not receive any specific grant from funding agencies in the public, commercial, or not for profit sectors.

Local ethics Committee Approval

The study was conducted in accordance with international ethical guidelines of conducting research with human participants. This was done to safeguard the rights, safety and well-being of participants by ensuring we had ethical approval prior to data collection. The study plan was discussed and reviewed by the Institutional Review Board (IRB) of Abdul Wali Khan University, Mardan.

• IRB Title: The Institutional Review Board, Abdul Wali Khan University Mardan
• IRB Number: IRB/2025/Acid-Base/Biochem/Nursing/0011.
• Date of Approval: November 21, 2025

 

The involvement was completely voluntary. The purpose, methodology, possible benefits and the right of the registered nurses to discontinue the study were explained to them without any penalty to their job or personal status. All the participants signed consent papers prior to data collection.

No personal identifiers were obtained, which guaranteed confidentiality and anonymity. Questionnaires were coded in numbers, and all the data were stored safely, in a place where only the research team can access. The data was only utilized in terms of academic and research purposes. The research did not produce any physical, mental, or professional damage. It was not a sensitive topic, and the participants were not required to answer any question that would not be comfortable to them, which was connected to the topic (acid-base understanding and clinical monitoring skills).

Conflict of interest  

The authors do not claim any conflicts of interest.

 

Authors’ contribution

The conceptualization was done by Abdur Rahman and Jihad Hussain and the study design. The methodology and the instruments were developed by Shams Ul Haq, Zohaib Hussain, and Muhammad Shayan. Shams Ul Haq, Mah Noor Mumtaz and Wajid Hussain organized data collection and fieldwork. Zohaib Hussain, Mahnoor Ali and Abdur Rahman took part in the data analysis and interpretation. Muhammad Sohrab Khan, Muhammad Ishaq and Hamza Khan helped in the literature review, drafting of the manuscript and initial validation of data. Muhammad Shayan helped in logistics of the fieldwork and data entry. Abdur Rahman led the research, optimized the methodology, and supervised the writing, revision, and final approval of the manuscript.

The final version of the manuscript was approved by all the authors.

Additional Author Information

The email addresses and ORCID identifiers of the authors are reported below.

Muhammad Sohrab Khan: email: sohrab_dr2002@hotmail.com; ORCID: Not available

Jihad Hussain: email: legendenterprise094@gmail.com; ORCID: 0009-0009-4914-9045

Muhammad Ishaq: email: mishaqlkr0349@gmail.com; ORCID: 0009-0006-5906-1854

Shams Ul Haq: email: qaris729@gmail.com; ORCID: 0009-0004-6055-466X

Hamza Khan: email: khankhan983933@gmail.com; ORCID: 0009-0003-7618-7967

Muhammad Shayan: email: shayanmuhammad847@gmail.com; ORCID: 0009-0007-3498-828X

Zohaib Hussain: email: zk4542471@gmail.com; ORCID: Not available

Mah Noor Mumtaz: email: mahnoor@awkum.edu.pk; ORCID: 0009-0004-3699-7559

Wajid Hussain: email: wajid.awkum@gmail.com; ORCID: 0009-0007-4307-4287

Abdur Rahman: email: abdurrahman888889998@gmail.com; ORCID: 0009-0008-2170-146X

Mahnoor Ali: email: mahnorralimdcat2022@gmail.com; ORCID: 0009-0003-6475-2607

Acknowledgements

The authors are grateful to all registered nurses who took part in this study and also recognize the assistance of nursing supervisors, head nurses, and clinical coordinators that were used during recruitment.

 

Application of Artificial Intelligence Tools

No artificial intelligence software was applied other than a regular grammar and spell.

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Soviaturohmah Nur Rizky ⁴, Resti Febrianti ⁴, Santy Sanusi ¹

1. Department of Nursing, Faculty of Health Sciences, Universitas Aisyiyah, Bandung, West Java, Indonesia.
2. Department of Nursing, Faculty of Health Sciences, Universitas Muhammadiyah, Tangerang, West Java, Indonesia.
3. Centre for Nursing Studies, Faculty of Health Sciences, UiTM Selangor, Puncak Alam, Selangor, Malaysia.
4. Nursing Department, Faculty of Health Sciences, Universitas Aisyiyah, Bandung, West Java, Indonesia.

* Corresponding author: Inggriane Puspita Dewi, Department of Nursing, Universitas Aisyiyah, Bandung, West Java, Indonesia. E-mail: inggriane.puspita@unisa-bandung.ac.id

Cite this article

 

ABSTRACT

Introduction: Spiritual care is essential in holistic nursing; however, nursing students often feel less confident and reflective in providing it. Innovative teaching methods combining active learning and reflection are needed to fill this gap.

Objective: This study evaluated the impact of reflective, flipped-classroom spiritual care training on students’ self-efficacy and reflective thinking.

Methods: A quasi-experimental pretest–posttest design with a control group was conducted among 82 undergraduate nursing students from two universities in Indonesia. Participants were allocated to an intervention group (n = 41) or a control group (n = 41) based on existing class enrollment. The intervention consisted of a 16-week reflective flipped classroom supported by an interactive e-module, while the control group received conventional lecture-based instruction. Self-efficacy and reflective thinking were measured at baseline and post-intervention. Data normality was assessed using the Shapiro–Wilk test. Within-group differences were analyzed using the Wilcoxon signed-rank test or paired sample t-test as appropriate, and between-group differences were examined using the Mann–Whitney U test.

Results: Within-group analyses showed statistically significant improvements in self-efficacy and reflective thinking in the intervention group (p < 0.001). In the control group, changes in reflective thinking were not statistically significant (p = 0.062). Between-group post-test comparisons demonstrated significantly higher self-efficacy and reflective thinking scores in the intervention group than in the control group (p < 0.001), with a large effect (r = 0.67 for self-efficacy and r = 0.61 for reflective thinking).

Conclusion: The findings indicate that a reflective flipped classroom approach is associated with higher self-efficacy and reflective thinking among nursing students in spiritual care education. While causal conclusions cannot be drawn, the results support the educational value of reflective and interactive learning strategies in undergraduate nursing curricula.

Keywords: spiritual care, flipped classroom, reflective learning, self-efficacy, nursing education.

 

INTRODUCTION

Spirituality is increasingly recognized as a core component of holistic nursing, encompassing individuals’ search for meaning, purpose, connection, and transcendence amid health, illness, and suffering [1,2]. In clinical practice, spiritual care plays a crucial role in supporting patients’ emotional well-being, coping processes, and psychological adjustment, particularly among individuals facing chronic illness, serious health conditions, and end-of-life situations [3,4].

A growing body of empirical evidence indicates that spiritual care interventions are associated with positive patient outcomes across diverse healthcare settings. Previous studies have reported that spiritual care may contribute to reducing anxiety, enhancing emotional regulation, improving coping strategies, and a greater sense of meaning and connectedness among patients experiencing vulnerability or existential distress [5,6]. These findings underscore nurses’ professional responsibility to competently assess and address patients’ spiritual needs as an integral part of person-centered care. Despite its recognized importance, spiritual care remains one of the areas in which nurses and nursing students report the lowest levels of confidence. Numerous studies have shown that nurses often feel uncertain, uncomfortable, or inadequately prepared to engage in spiritual care, even when they acknowledge its relevance to quality nursing practice [2,7,8]. This discrepancy suggests a persistent gap between professional expectations and cultural clinical practice. One contributing factor to this gap lies in undergraduate nursing education. Although spirituality is frequently included in nursing curricula, it is often addressed at a conceptual or theoretical level, with limited opportunities for experiential learning, structured reflection, and skill-based application [9,10]. As a result, nursing students may develop theoretical awareness of spiritual care without sufficient confidence or readiness to engage in spiritual conversations and interventions during clinical encounters [11,12]. Research focusing on nursing students highlights particular challenges related to self-efficacy and reflective capacity in spiritual care. Self-efficacy, defined as an individual’s belief in their ability to perform specific tasks [9,10], plays a key role in translating knowledge into action. Students with low self-efficacy may avoid initiating spiritual care interactions, even when they possess adequate theoretical understanding [13,14]. In parallel, reflective thinking is essential for effective spiritual care, as it enables nurses to critically examine their personal values, emotional responses, and professional responsibilities when addressing patients’ existential concerns [15,16]. However, reflective practice is not consistently embedded in nursing education. Previous studies have reported that nursing curricula often lack structured reflective activities, standardized guidance, and intentional pedagogical planning to support the development of reflective thinking alongside clinical competence [17,18]. This limitation may hinder students’ ability to integrate spiritual care knowledge with self-awareness and ethical sensitivity. To address these educational challenges, active and student-centered learning strategies that intentionally integrate reflection are increasingly recommended. The flipped classroom model, which shifts content delivery to pre-class learning and utilizes in-class time for higher-order cognitive activities, has gained recognition as an effective pedagogical approach in nursing education [19,20]. Additionally, flipped classrooms support self-regulated learning and increase student confidence, which are linked to the development of self-efficacy [21,22]. However, the use of flipped classroom strategies in spiritual care education remains limited, particularly when reflective learning is not intentionally integrated into the teaching approach. Within a flipped classroom framework, interactive learning modules can function as structured pre-class resources that integrate content, reflection, and formative feedback. In this study, an interactive module is conceptualized as a structured instructional unit that combines case-based scenarios, guided reflective questions, and multimedia content to support self-directed and meaningful learning [4,19,23]. In a flipped classroom, it serves as a pre-class tool that prepares students for higher-order activities during in-class sessions, which focus on discussion, reflection, and the application of spiritual care concepts in simulated or case-based contexts [24].

The interactive and reflective nature of the module aligns with key outcomes in spiritual care education. Active engagement with realistic scenarios and reflection helps develop self-efficacy and reflective thinking, especially in emotional sensitivity and existential care [16,25]. Despite existing spiritual care competency frameworks, guidance on pedagogical methods that foster reflective thinking and self-efficacy through innovative, student-centered learning is limited.

A significant gap remains in nursing education regarding the effective implementation of spiritual care competencies through integrated, reflective, and interactive flipped classroom approaches.

 

Objective

This study investigates the impact of a reflective flipped classroom, supplemented by an interactive module, on the self-efficacy and reflective thinking of undergraduate nursing students in spiritual care. It is expected that students engaging with this innovative learning model will show notably greater self-efficacy and reflective thinking than those taught through traditional methods approaches.

 

MATERIALS AND METHODS

Design

A quasi-experimental pre-post-test design with a control group was used to examine differences in self-efficacy and reflective thinking between students who participated in a reflective flipped classroom intervention and those who received traditional instruction.

 

strong>Participants and Setting

The study population comprised undergraduate nursing students in Indonesia. The sample size calculation was performed using G*Power version 3.1, based on the Wilcoxon–Mann–Whitney test for two independent groups, with a significance level of 0.05 and a statistical power of 80% [26,27]. This choice was made because the outcome variables were expected to be analyzed using a nonparametric approach if the assumption of normality was violated. A moderate effect size (d = 0.60) was selected based on previous meta-analyses of flipped classroom interventions in nursing education, which report medium to large effects on educational outcomes [26,27]. This conservative estimate was chosen to avoid overestimating intervention effects in applied educational settings.

Based on this calculation, a minimum of 37 participants per group was required. To account for potential participant attrition, an additional 10% was added to the total sample size, resulting in a final sample of 82 participants (41 per group).

A purposive sampling technique was employed. The inclusion criteria were undergraduate nursing students in their third year of academic study who were actively enrolled and willing to participate in the study. The exclusion criteria included undergraduate nursing students who were on academic leave during the data collection period.

The study was conducted at two universities in West Java that had supportive curricula, classrooms, and labs for learning activities and data collection processes.

Group Allocation and Baseline Comparability

Participants were allocated to either the intervention or control group based on their existing class assignments at each institution to minimize contamination between groups. Random assignment was not feasible due to academic scheduling constraints.

To reduce selection bias, both groups were drawn from the same academic year and comparable institutional settings. Baseline comparability was assessed using demographic characteristics (age, gender, and religion), which showed similar distributions between groups (Table 1), supporting demographic equivalence at study entry. However, no baseline psychometric measurements were collected for the outcome variables.

Assessments and Measures

Post-intervention data on self-efficacy and reflective thinking were collected from the intervention group after the instructional intervention concluded. Control group data were collected simultaneously at the corresponding time point in separate classrooms to ensure temporal equivalence and minimize cross-group contamination. The estimated time to complete the questionnaires was 25-30 minutes.

The self-efficacy instrument was adapted from Bandura’s (1997) [25] General Self-Efficacy, and reflective thinking was measured using the Level of Reflective Thinking Questionnaire developed by Kember et al. (2000) [28]. Prior to the main study, the translated instruments were tested for validity with a pilot sample of 30 undergraduate nursing students. The instruments were translated into Indonesian using a forward–back translation procedure, followed by expert review to ensure semantic and conceptual equivalence. A pilot test was conducted with 30 undergraduate nursing students to assess clarity and cultural appropriateness.

Reliability testing demonstrated high internal consistency, with Cronbach’s alpha coefficients of 0.882 for self-efficacy and 0.984 for reflective thinking. While these values indicate strong reliability, the very high alpha for reflective thinking may also suggest potential item redundancy, which should be considered when interpreting results.

Each questionnaire consisted of 20 items, both the reflective thinking and self-efficacy instruments used the same scoring classification, categorizing scores as very (1) very poor [0,20[, (2) poor [20,40[, (3) average [40,60[, (4) good [60,80[, and (5) excellent (≥80).

 

Intervention Procedures

The intervention was developed using a constructive alignment framework to ensure coherence among course learning outcomes (CLOs), learning activities, and assessment strategies. It was grounded in the principles of flipped classroom pedagogy and reflective learning. The total workload was equivalent to 2 academic credit units (approximately 58 hours), delivered over 16 weeks with an average of 4 hours of learning activities per week [9]. The full set of intervention procedures is outlined in Table 1.

 

Phase	Timing	Learning Activities	Learning Materials / Tools	Purpose
Preparation Phase	Before semester	1.    Development of an interactive e-module 2.    Alignment of course learning outcomes, activities, and assessment 3.    Facilitator briefing (lecturers, chaplain, palliative nurses) 4.    Learning management system (LMS) setup	1.   Interactive e-module 2.   Semester learning plan 3.   Google Classroom	Ensure instructional consistency and constructive alignment
Baseline Assessment (Pre-Test)	Week 0 (before intervention)	1.    Orientation session and informed consent 2.    Administration of baseline questionnaires to both groups	1.   Self-efficacy (pre-test) 2.   Reflective thinking (pre-test)	Assess baseline equivalence between intervention and control groups
Pre-Class Learning (Flipped Component)	Weekly (≈ 2 hours/week)	1.    Independent study using an interactive module 2.    Viewing instructional videos 3.    Analysis of case-based spiritual care scenarios 4.    Completion of guided reflective questions 5.    Formative quizzes	1.   Interactive e-module 2.   Instructional videos 3.   Case scenarios 4.   Online quizzes	Build foundational knowledge and support self-directed learning
In-Class Learning (Reflective & Active Learning)	Weekly (face-to-face / synchronous sessions)	1.    Facilitated case-based group discussions 2.    Guided reflective dialogue 3.    Role play and communication skills practice 4.    Spiritual assessment exercises 5.    Practice of religion-based spiritual care (Islamic context)	1.   Case discussion guides 2.   Reflection prompts 3.   Skills demonstration tools	Apply theoretical knowledge, enhance reflective thinking, and strengthen self-efficacy
Reflection and Feedback	Throughout semester	1.    Submission of structured reflective journals 2.    Facilitator feedback on reflection and participation 3.    Ongoing formative assessment	1.   Reflective journal templates 2.   LMS feedback features	Deepen self-awareness and reinforce reflective learning
Post-Intervention Assessment	End of semester	1.    Completion of the self-efficacy questionnaire 2.    Completion of the reflective thinking questionnaire	1.   Self-efficacy scale 2.   Reflective thinking questionnaire	Evaluate post-intervention outcomes and compare groups
Control Group (Comparison)	Throughout semester	1.    Traditional lecture-based instruction 2.    Classroom discussion without structured reflection or flipped classroom elements	1.   Lecture materials 2.   Standard classroom resources	Provide a comparison condition without reflective flipped learning

Table 1. Intervention Procedures.

Data Collection and Statistical Analysis

Descriptive statistics, including means, standard deviations, frequencies, and percentages, were used to summarize participants’ demographic characteristics and study variables. Instrument reliability was assessed using Cronbach’s alpha coefficients.

The Shapiro–Wilk test was used to assess the normality of the distributions of self-efficacy and reflective thinking scores in both the intervention and control groups. In particular, a p-value greater than 0.05 indicates that the null hypothesis of normality cannot be rejected.

To examine within-group differences between pre-test and post-test scores in both the intervention and control groups, paired-sample t-tests were used to assess differences between means. When data were not normally distributed, the non-parametric Wilcoxon signed-rank test was applied as an alternative. To compare between-group differences in outcome scores, independent-sample t-tests were used. In cases of non-normal distribution, the Mann–Whitney U test was employed as a non-parametric alternative.

Effect sizes for the Mann–Whitney U test were calculated using the rank-biserial correlation (r) derived from the standardized Z value to estimate the magnitude of group differences and were interpreted according to established criteria. A two-tailed p-value < 0.05 was considered statistically significant.

All statistical analyses were performed using SPSS software (version 27).

RESULTS

Participants Characteristic

In Table 2 we have reported the main characteristics of our sample of undergraduate nursing students. Participants in both groups were predominantly in early adulthood. The intervention group had a mean age of 21.51 years (median = 21; range, 19–28), while the control group had a mean age of 20.54 years (median = 20; range, 19–26). In the intervention group, the highest proportion of participants was aged 21 years (29%), whereas in the control group, the majority of participants were aged 20 years (51%). Female participants constituted the majority in both groups. In the intervention group, 71% of participants were female, and 29% were male. Similarly, the control group consisted of 85% female and 15% male participants. All participants in the Islamic religion.

Comparable age and gender characteristics across groups indicate baseline demographic homogeneity, thereby supporting the internal validity of the quasi-experimental design.

 

Characteristics	Intervention Group		Control Group
	f	%	f	%
Age (years)
19	4	10	5	12
20	7	17	21	51
21	12	29	10	24
22	9	22	2	5
23	5	12	1	2
24	2	5	1	2
25	1	2	0	0
26	0	0	1	2
28	1	2	0	0
Gender
Male	12	29	6	15
Female	29	71	35	85
Religion
Islam	41	100	41	100
Christianity	0	0	0	0
Buddhist	0	0	0	0
Hinduism	0	0	0	0

Table 2. Participants Characteristics

In the intervention group, the Shapiro–Wilk test showed that both pre-test and post-test scores for self-efficacy (p < 0.0001) and reflective thinking (pre-test p = 0.001; post-test p < 0.0001) were not normally distributed. Therefore, non-parametric statistical tests were considered appropriate for within-group analyses in the intervention group.  In contrast, in the control group, the Shapiro–Wilk test indicated that pre-test and post-test scores for self-efficacy (pre-test p = 0.214; post-test p = 0.149) and reflective thinking (pre-test p = 0.123; post-test p = 0.057) were normally distributed (p > 0.05). Accordingly, parametric tests were applied for within-group analyses in the control group (Table 3).

 

Intervention Group                        Control point		n	p-value
Self-Efficacy	Pre-test	41	< 0.001
	Post-test	41	< 0.001
Reflective Thinking	Pre-test	41	0.001
	Post-test	41	< 0.001
Control Group                                Control point		n	p-value
Self-Efficacy	Pre-test	41	0.214
	Post-test	41	0.149
Reflective Thinking	Pre-test	41	0.123
	Post-test	41	0.057

Table 3. The Shapiro–Wilk Normality Test

 

Table 4 presents within-group comparisons of pre- and post-test scores for self-efficacy and reflective thinking in the intervention and control groups.

 

Variables	Group	Pre-Test (Mean ± SD)	Post-Test (Mean ± SD)	p-value
Self-Efficacy	Intervention	82.10 ± 9.11	90.32 ± 9.59	< 0.001 a
	Control	73.49 ± 8.73	80.15 ± 11.66	< 0.001 b
Reflective Thinking	Intervention	80.54 ± 9.19	87.10 ± 9.97	< 0.001 a
	Control	73.05 ± 8.19	77.49 ± 12.00	0.062 b

Note: a = (Wilcoxon Signed-rank); b = (Paired Sample T-Test)

Table 4. Pre-Test and Post-Test Comparison within Intervention and Control Groups

In the intervention group, statistically significant differences were observed between pre- and post-test scores for both self-efficacy and reflective thinking (p < 0.001), indicating higher post-test scores than at baseline. In contrast, within the control group, no statistically significant differences were found between pre- and post-test scores for self-efficacy or reflective thinking (p = 0.062). These findings suggest different patterns of change over time between the intervention and control groups.

Table 5 further supports these findings through inferential analysis. Nursing students who participated in the reflective flipped classroom showed notably higher self-efficacy scores (mean = 90.32 ± 9.59) than those in the control group (mean = 80.15 ± 11.66), with a difference of 10.17 points (p < 0.001). Similarly, reflective thinking scores were substantially higher in the intervention group (87.10 ± 9.97) than in the control group (77.49 ± 12.00), with a difference of 9.61 points (p < 0.001). These significant and statistically strong differences suggest a meaningful educational impact rather than a minor effect improvement.

 

variables	n	mean±SD	mean difference (IC 95%)	p-value	Z	Effect size
Self-efficacy (intervention group)	41	90.32±9.59	10.17	<0.001	6.10	r = 0.67 large effect
Self-efficacy (control group)	41	80.15±11.66
Reflective thinking (intervention group)	41	87.10±9.97	9.61	<0.001	5.65	r = 0.61 large effect
Reflective thinking (control group)	41	77.49±12.00

Table 5. Comparison of Post-Test Self-Efficacy and Critical Reflection Scores Between Intervention and Control Groups (Mann–Whitney U Test).

 

Comparison of Post-Test Self-Efficacy and Critical Reflection Scores Between Intervention and Control Groups (Mann–Whitney U Test)

The analysis of effect sizes showed a significant educational benefit from the reflective flipped classroom approach to spiritual care education. The effect sizes were large for both self-efficacy (r = 0.67) and reflective thinking (r = 0.61), indicating substantial differences between the intervention and control groups. These results demonstrate that the improvements are both statistically significant and educationally important, indicating a strong enhancement of effective and cognitive skills among nursing students. Reporting effect sizes along with p-values is recommended to provide information on the practical significance of the findings and to help compare results across studies [29].

 

DISCUSSION

This study examined changes in self-efficacy and reflective thinking among nursing students participating in an interactive, module–based reflective flipped classroom compared with those receiving traditional instruction. By incorporating both within-group and between-group analyses, the findings provide a more nuanced understanding of how students’ learning outcomes evolved over the intervention period.

Within-group analyses showed that students in the intervention group experienced statistically significant improvements in both self-efficacy and reflective thinking from pre-test to post-test. These findings suggest that participation in a structured learning environment combining flipped classroom strategies and guided reflection was associated with higher post-intervention scores. Such outcomes align with theoretical perspectives that emphasize the role of active engagement and reflective processes in strengthening learners’ confidence and cognitive development [25], [28]. Reflective learning activities, such as guided journals and case-based discussions, may help students make sense of complex learning experiences and integrate theoretical knowledge with professional values [15,16]. In contrast, in the control group, only self-efficacy showed a statistically significant pre–post change, while reflective thinking did not. This pattern suggests that conventional lecture-based instruction may support certain aspects of learning, such as perceived confidence, but may be less effective in fostering deeper reflective capacities without explicit reflective structures. Previous studies have similarly reported that the absence of intentional reflective pedagogies can limit students’ development of reflective thinking skills, particularly in professional nursing education contexts [29,30].

Between-group comparisons at post-test further indicated that students in the intervention group reported higher levels of self-efficacy and reflective thinking than those in the control group, with statistically significant differences for both outcomes. These findings align with existing evidence demonstrating that flipped classroom approaches in nursing education are associated with improved learning-related outcomes, including self-efficacy, engagement, and reflective abilities [19,26]. Technology-enhanced flipped learning environments may allow learners to engage with content at their own pace while reserving classroom time for higher-order cognitive activities, which may contribute to these observed differences [24,31,32]. The relevance of these findings is particularly pronounced in the context of spiritual care education. Previous research has identified persistent gaps in nursing students’ preparedness, confidence, and competence in delivering spiritual care, often attributed to limited curricular integration and insufficient experiential learning opportunities [3,9]. The reflective flipped classroom approach implemented in this study may offer a pedagogical structure that supports students in engaging with spiritual care content in a more meaningful and culturally grounded manner, particularly within Islamic nursing education contexts [33,34].

Overall, this study contributes to the growing literature on reflective and flipped learning strategies in nursing education by demonstrating differential patterns of change in self-efficacy and reflective thinking across instructional approaches. Future research employing randomized controlled designs, longitudinal follow-up, and qualitative inquiry may further elucidate the mechanisms through which reflective flipped classroom models support the development of nursing students’ professional confidence and reflective capacity.

 

CONCLUSION

This study examined changes in self-efficacy and reflective thinking among nursing students participating in an interactive, module–based reflective flipped classroom, compared with those receiving traditional instruction. The findings showed statistically significant within-group improvements in both outcomes among students in the intervention group, along with higher post-test scores than in the control group. In contrast, changes in the control group were more limited and inconsistent across outcomes.

Together, these results suggest that integrating reflective learning activities and flipped classroom strategies is associated with more favorable learning outcomes in spiritual care education. Although causal conclusions cannot be drawn from the quasi-experimental design, the findings provide empirical support for the educational value of reflective, interactive pedagogical approaches in undergraduate nursing education.

Implications for nursing education and future research

This study advocates integrating reflective flipped classrooms into undergraduate nursing education, particularly for complex topics such as spiritual care. Activities that involve reflective exercises, interactive modules, and active participation can enhance students’ confidence and depth of reflection. Educators could blend these approaches with traditional teaching methods to promote student-centered learning. Utilizing culturally relevant materials, such as Islamic perspectives on spiritual care, can further enhance engagement in contexts where religion plays a significant role. Future research should focus on randomized controlled trials, longitudinal studies, and qualitative methods to investigate the long-term effects and underlying mechanisms of these strategies. Expanding research across diverse settings will provide a more comprehensive assessment of their generalizability and effectiveness in nursing education.

 

Limitations

This study employed a quasi-experimental design without randomization, limiting causal inference. The sample was drawn from two institutions within a specific cultural and religious context, potentially limiting generalizability. Outcomes were measured using self-reported instruments, which may be subject to response bias. Additionally, the use of different statistical tests due to variations in data distribution and the absence of long-term follow-up should be considered when interpreting the findings.

 

Ethical Approval

Ethical approval for this study was obtained from the Ethics Committee of Universitas Aisyiyah Bandung (date approval May 15, 2025; no. 1270/KEP.01/UNISA-BANDUNG/V/20). The study was conducted in accordance with the principles outlined in the Declaration of Helsinki. All participants were informed about the study objectives, procedures, and their right to withdraw at any time, and written informed consent was obtained prior to data collection.

 

Funding statement

This research was funded by the Majelis Pendidikan Tinggi, Pimpinan Pusat’ Aisyiyah, under contract number 036A/PPA/I/IX/2025 and was facilitated by the Institute for Research and Community Service (Lembaga Penelitian dan Pengabdian kepada Masyarakat) at Universitas’ Aisyiyah Bandung.

 

Conflict of interest

The authors declare that they have no competing interests.

 

Authors’ contribution

Inggriane Puspita Dewi: Conceptualization, study design, development of the interactive module, and drafting of the original manuscript.

Popy Irawati: Contribution to spiritual care content expertise, educational evaluation, and critical manuscript revision.

Sharifah Shafinaz Sh Abdullah: Methodology development, data analysis, and critical revision of the manuscript

Soviaturohmah Nur Rizky: Data collection, participant coordination, and data organization

Resti Febrianti: Assistance in data collection, preliminary data processing, and support in manuscript preparation.

Santy Sanusi: Supervision of the flipped classroom implementation, validation of instruments, and manuscript review.

 

Acknowledgements

The authors appreciate all nursing students who volunteered for this study. They also extend their gratitude to the faculty members and academic staff for their support during the reflective flipped classroom activities.

 

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

1. Department of Nursing, Hamad Medical Corporation (HMC), Doha, Qatar.
2. Institut Universitaire de Formation des Cadres (INUFOCAD), Port-au-Prince, Haiti.
3. Higher Institute of Nursing Sciences of Tunis, Tunis, Tunisia.
4. Private College of Nursing, Arar, Saudi Arabia.
5. Higher Institute of Sport and Physical Education of Sfax, University of Sfax , Sfax, Tunisia.
6. Research Laboratory Education, Motricity, Sport Health EM2S, LR19JS01, High Institute of Sport and Physical Education of Sfax, University of Sfax, Sfax, Tunisia.

* Corresponding author: Abdelbasset Ghalgaoui, Graduate Registered Nurse, Department of Nursing, Hamad Medical Corporation (HMC), Doha, Qatar. PhD Student in Education and Governance, Institut Universitaire de Formation des Cadres (INUFOCAD), Port-au-Prince, Haiti. Email: ghalgaouiabdelbasset@gmail.com

Cite this article

 

ABSTRACT

Introduction: Clinical simulation has become an essential strategy in nursing education, particularly for developing cognitive skills such as situational awareness (SA), which is critical for patient safety and effective clinical decision-making. However, evidence on the impact of simulation on SA among nursing students in Tunisia remains limited.

Objective: To evaluate the effect of clinical simulation on the situational awareness of final-year nursing students at the Higher Institute of Nursing Sciences of Tunis.

Methods: A quantitative, quasi-experimental, longitudinal study was conducted with 133 final-year nursing students during the academic year 2024–2025. Situational awareness was assessed using an adapted Situation Awareness Global Assessment Technique (SAGAT), measuring perception, comprehension, and projection. Assessments were performed before simulation training and three months after the intervention. Data were analyzed using descriptive statistics and Wilcoxon signed-rank tests.

Results: Significant improvements were observed across all dimensions of situational awareness. Mean perception scores increased from 3.75 (SD = 1.25) to 3.98 (SD = 1.19), comprehension from 0.96 (SD = 0.67) to 1.17 (SD = 0.62), and projection from 0.64 (SD = 0.86) to 1.17 (SD = 0.80). The total situational awareness score increased from 5.35 (SD = 1.95) to 6.32 (SD = 1.76). All differences were statistically significant (p < 0.001).

Conclusion: Clinical simulation significantly enhances nursing students’ situational awareness, with sustained effects observed three months post-intervention. These findings support the integration of structured simulation-based training into nursing curricula to strengthen cognitive competencies and improve patient safety.

 

Keywords: Clinical competence; Nursing education; Simulation; Situation awareness; Students

 

INTRODUCTION

Nursing education has increasingly embraced simulation as a key component of training, aiming to enhance various aspects of clinical competence among students. Clinical simulation has become a cornerstone of modern nursing education, offering a safe and controlled environment for students to practice and refine clinical skills, integrate theoretical knowledge, and develop complex cognitive competencies before exposure to real patients[1–3]. Simulation offers a controlled environment where nursing students can practice and refine their skills without risking patient safety. It provides an opportunity to engage in realistic scenarios that mimic real-life situations, allowing students to develop critical thinking and decision-making skills crucial for effective patient care. It is essential for cultivating nursing students’ knowledge, skills, collaboration, and confidence[4–7].

The role of nurses in the healthcare system is critically important. Multiple scoping review and systematic reviews studies show that clinical expertise, situational awareness, interprofessional coordination, and specialized training across different hospital departments are essential for significantly improving patient safety, care quality, and clinical outcomes[8–12]. Given the crucial role of nurses in patient care, simulation‑based training is essential for enhancing the situational awareness of future nurses.

Situation awareness, the ability to perceive, comprehend, and predict information about the environment and ongoing situations[13].It is fundamental for nurses to provide safe and effective care. Effective situation awareness allows nurses to anticipate potential issues, make informed decisions quickly, and respond to changing conditions in a timely manner. However, despite  its importance, research specifically examining the impact of simulation on SA in nursing students remains limited. A recent scoping review suggests that SBE may be effective in cultivating SA skills, yet highlights a paucity of experimental studies and standardized assessment methods[14–17].

Furthermore, there is limited research focusing on the specific impact of simulation-based training on situation awareness among nursing students in Tunisia.

In Tunisia’s context, where nursing education is evolving rapidly to meet international standards. Robust learner support and multimodal engagement are the key drivers of nursing students’  satisfaction and self‑confidence in simulation‑based education[18]. while adding a structured, hands‑on simulation session to traditional lectures markedly boosts nursing students’ BLS‑CPR knowledge and psychomotor skills[19]. Although, some studies focus on affective reaction, cognitive learning, and procedural learning, there is no research examining real‑time cognition by assessing students’ situational awareness. Understanding how simulation affects situation awareness can provide valuable insights. The Higher Institute of Nursing Sciences of Tunis plays a pivotal role in shaping future nurses in the country. Assessing the impact of simulation on students’ situation awareness at this institution could offer important implications for educational strategies and curriculum development.

This research seeks to fill a gap in the current literature by exploring how simulation influences the situation awareness of nursing students at the Higher Institute of Nursing Sciences of Tunis. By investigating this relationship, the study aims to contribute to the improvement of nursing education practices and enhance the overall quality of healthcare training in Tunisia.

Situation awareness, the ability to perceive, comprehend, and predict information about the environment and ongoing situations, is fundamental for nurses to provide safe and effective care. Effective situation awareness allows nurses to anticipate potential issues, make informed decisions quickly, and respond to changing conditions in a timely manner. Despite its importance, there is limited research focusing on the specific impact of simulation-based training on situation awareness among nursing students in Tunisia.

MATERIALS AND METHODS

Study Design

A single-group pre- and post-test quantitative, quasi-experimental, longitudinal design to evaluate the impact of simulation-based training on the situational awareness (SA) of final-year nursing students at the Higher Institute of Nursing Sciences of Tunis. The study was conducted in a controlled environment using simulation scenarios that mirror real-life clinical situations.

Assessments of situational awareness were conducted both before and three months after the simulation training to evaluate both immediate and retained effects.

 

Study period

2024–2025 academic year.

 

Participants

All final-year students enrolled in the Bachelor of Science in Nursing program at the Higher Institute of Nursing Sciences of Tunis were invited to participate. The anticipated sample size is N=133 students.

 

Inclusion criteria

• Completion of relevant coursework in clinical nursing.
• Provision of informed consent to participate.

 

Exclusion criteria

• Inability to attend all required sessions or follow-up assessments due to scheduling conflicts or personal circumstances.

 

Instruments

The primary tool for assessing situational awareness will be an adapted version of the Situation Awareness Global Assessment Technique (SAGAT). SAGAT is a validated method for measuring SA across three hierarchical levels: Perception, Comprehension, and Projection (based on Endsley’s model).

Situational awareness was assessed using a questionnaire derived from the Situation Awareness Global Assessment Technique (SAGAT), originally developed by Mica R. Endsley[20]. The instrument was adapted from the Team Situation Awareness Global Assessment Technique (TSAGAT)[21]. The questionnaire included nine items corresponding to the three levels of situational awareness described in Endsley’s model: perception (5 items), comprehension (2 items), and projection (2 items).

The original TSAGAT questions were modified to reflect the simulated patient deterioration scenario used in this study and to ensure relevance to the Tunisian nursing education context. Minor linguistic and contextual adjustments were made while preserving the conceptual structure of the SAGAT framework. The adapted items were reviewed by nursing educators and clinical experts to ensure clarity, relevance, and alignment with local clinical practice.

Each item was scored dichotomously (1 = correct answer; 0 = incorrect), resulting in a total possible score ranging from 0 to 9, with higher scores indicating greater situational awareness. The internal consistency of the adapted instrument was assessed using Cronbach’s alpha based on baseline responses from 133 nursing students, yielding α = 0.633 (standardized α = 0.649). Corrected item–total correlations ranged from 0.106 to 0.431, indicating moderate internal consistency for this multidimensional construct.

 

Adapted SAGAT Questionnaire

The adapted questionnaire included 9 items, distributed across the three levels of situational awareness:

1. Level 1 – Perception (5 items)
   • Check the patient’s oxygen saturation
   • Check the patient’s blood pressure
   • Check the patient’s pulse
   • What is on the wall next to the patient?
   • What is on the patient’s chest?
2. Level 2 – Comprehension (2 items)
   • Is the patient well oxygenated?
   • What is the problem with this patient?
3. Level 3 – Projection (2 items)
   • If you do not intervene properly, what will happen to the pulse?
   • If you do not intervene properly, what will happen to the blood pressure?

 

The SAGAT questionnaire was administered twice: once before the simulation training (baseline) and again three months after the training (follow-up).

Each correct response was assigned a score of one point, while incorrect responses were scored as zero. Scores were calculated for each situational awareness level (perception, comprehension, and projection), as well as a total situational awareness score.

 

Simulation Training

Scenario Development

Simulation scenarios were developed to reflect critical clinical situations (e.g., patient deterioration, emergency response). The simulation scenario involved the management of a critically ill patient presenting signs of clinical deterioration requiring rapid assessment of vital signs and appropriate clinical decision-making. The simulation was conducted using a moderate-fidelity mannequin to reproduce realistic clinical conditions while allowing students to practice patient assessment and intervention in a controlled educational environment. These scenarios were designed to test and develop situational awareness through realistic, immersive experiences.

 

Simulation Sessions

• Each simulation session will last approximately 2–3 hours, including pre-briefing, active simulation, and debriefing.
• All participants will engage in the simulation training during a designated session period.
• The simulation sessions were supervised by instructors who were faculty members at the Higher Institute of Nursing Sciences of Tunis with prior experience in simulation-based education and clinical training.

 

Data Collection

Data will be collected in two phases:

1. Pre-Simulation Assessment (Baseline):

Participants will complete the adapted SAGAT questionnaire before undergoing any simulation training to assess their baseline situational awareness.

2. Simulation Training:
   • Participants will take part in a simulation session, designed to challenge and enhance SA in real-time.
3. Post-Simulation Assessment (Follow-Up after 3 Months):
   • After three months, participants will again complete the same SAGAT questionnaire to evaluate the retention and long-term impact of the simulation training on their situational awareness.

Data Analysis

Data from the pre- and post-simulation SAGAT assessments will be analyzed using SPSS-26. The following statistical techniques were applied:

• Descriptive statistics to summarize demographic data and SA scores.
• The normality of continuous variables was evaluated using the Shapiro–Wilk test, which revealed a non-normal distribution (p < 0.05). Consequently, Wilcoxon signed-rank tests were performed to compare SA scores at baseline and after 3 months.
• A significance level of p-value (p) < 0.05 was used to determine statistical significance.

 

Ethical Considerations

Ethical approval was sought from the Institutional Review Board (IRB) of the Higher Institute of Nursing Sciences of Tunis (Approval No.: 01-07-10/2024; Date: 07/10/2024). Informed consent was obtained from all participants prior to their involvement in the study. Participants were assured of confidentiality and the right to withdraw from the study at any time without penalty.

 

RESULTS

Sociodemographic Characteristics of Participants

The sample consisted of 133 participants, with 52.63% identifying as female (n = 70) and 47.37% as male (n = 63). This represents a sex ratio of approximately 90 males for every 100 females, indicating a slight predominance of females in the study population.

The participants’ ages ranged from 21 to 23 years, with a mean age of 22.01±0.38 years, indicating a very homogeneous age group. The median age was 22, matching the mean, which suggests a symmetrical distribution. In terms of frequency, the vast majority of participants were 22 years old (85.71%), while smaller proportions were 21 years old (6.77%) and 23 years old (7.52%) (Figure 1).

Figure 1. Distribution of participants by age

 

Descriptive Statistics of Pre- and Post-Training Scores

The data show an increase in mean (M) scores from pre-training to post-training across all measured variables (Table 1).

 

Statistical indexes	Pre-training
	Perception	Comprehension	Projection	Total Score
Min	0	0	0	0
Max	5	2	2	9
Median	4	1	0	5
Interqurtile Range (IQR)	[3, 5]	[1, 1]	[0, 1.5]	[4, 7]
Mean	3.75	0.96	0.64	5.35
Standard Deviation (SD)	1.25	0.67	0.86	1.95
	Post-training
	Perception	Comprehension	Projection	Total Score
Min	0	0	0	1
Max	5	2	2	9
Median	4	1	1	6
Interqurtile Range (IQR)	[4, 5]	[1, 2]	[0.5, 2]	[5, 8]
Mean	3.98	1.17	1.17	6.32
Standard Deviation (SD)	1.19	0.62	0.80	1.76

Table1. Descriptive Statistics of Pre- and Post-Training Scores

 

Perception scores increased from M = 3.75, SD = 1.25 to M = 3.98, SD = 1.19. Comprehension scores increased from M = 0.96, SD = 0.67 to M = 1.17, SD = 0.62. Projection scores increased from M = 0.64, SD = 0.86 to M = 1.17, SD = 0.80. The total score increased from M = 5.35, SD = 1.95 to M = 6.32, SD = 1.76.

 

3. Pre- and Post-Training comparison

The Wilcoxon signed-rank tests were conducted to compare pre-training and post-training scores on Perception, Comprehension, Projection, and Total Score variables. Results indicated statistically significant increases across all measures following the training intervention. Specifically, the Perception scores showed a significant increase, Z = 4.71, p < 0.001, indicating a difference in median perception scores after training. Similarly, Comprehension scores increased significantly, Z = 5.01, p < 0.001, suggesting improved understanding post-training. Projection scores showed a larger effect, with Z = 6.44, p < 0.001, reflecting enhanced ability to apply or extend knowledge after training. The Total Score also increased significantly, Z = 7.70, p < 0.001, highlighting an overall improvement in combined performance measures (Table 2).

 

Variable	Test Statistic		Standardized Z-Statistic)	p-value
Perception (pre vs post)	325.0		4.71	< 0.001
Comprehension (pre vs post)	351.0		5.01	< 0.001
Projection (pre vs post)	1326.0		6.44	< 0.001
Total Score (pre vs post)	2850.0		7.70	< 0.001

Table 2. Pre- and Post-Training comparison

 

Multivariate Linear Regression Analysis of Factors Associated with Improvement in Total Score

A multivariate linear regression analysis was conducted to examine whether demographic variables were associated with improvement in total score after the training intervention. The overall regression model was statistically significant (F = 12.90, p < 0.001) and explained 16.6% of the variance in score improvement (R² = 0.166, Adjusted R² = 0.153).

Sex was significantly associated with improvement in total score (B = −0.932, β = −0.407, p < 0.001), indicating that male participants showed greater improvement than female participants. In contrast, age was not significantly associated with changes in total score (B = 0.025, β = 0.008, p = 0.919), suggesting that the observed improvements were not influenced by participants’ age.

These findings indicate that the improvement in total score following the training intervention was primarily influenced by sex, while age did not play a significant role (see Table 3).

 

Variable	B	Standard Error (SE)	Standardized β	p-value	95% Confidence Interval
Sex	-0.932	0.183	-0.407	<0.001	-1.295 to -0.569
Age	0.025	0.242	0.008	0.919	-0.455 to 0.504
Constant	1.846	5.339		0.730	-8.716 to 12.408

Table 3. Multivariate Linear Regression Analysis of Factors Associated with Improvement in Total Score.

 

DISCUSSION

The present study examined the effect of simulation-based training on the situational awareness (SA) of final-year nursing students at the Higher Institute of Nursing Sciences of Tunis. Findings demonstrated significant improvements across all three dimensions of situational awareness perception, comprehension, and projection as well as in the overall SA score following simulation training. These results confirm the efficacy of simulation as a pedagogical strategy for strengthening cognitive and decision-making capacities that are critical for safe clinical practice.

Our findings are consistent with earlier work emphasizing the positive impact of simulation on nursing students’ knowledge acquisition, confidence, and decision-making abilities [4,6]. In particular, the observed improvement in projection scores aligns with [13] theoretical model of SA, in which the ability to anticipate future states represents the most advanced and clinically decisive dimension of situational awareness. Such gains suggest that immersive, scenario-based learning environments foster higher-order cognitive processing that extends beyond simple recognition or comprehension of patient data.

Moreover, this study contributes novel evidence in the Tunisian context, where research on simulation-based learning remains limited despite growing curricular reforms in nursing education [18,19]. Our results reinforce the idea that integrating simulation into undergraduate nursing curricula does not merely enhance psychomotor skills but also supports real-time cognitive processes essential for clinical safety and patient-centered care. This is particularly relevant given the documented importance of situational awareness in preventing adverse events and improving interprofessional team performance [9,10,12].

The current study found that demographic variables had a limited influence on improvement in total score following the training intervention. The multivariate regression model explained a modest proportion of variance (16.6%), suggesting that while sex significantly predicted improvement, the majority of performance gains were likely influenced by other factors such as baseline knowledge, prior experience, or engagement during training. Specifically, male participants demonstrated significantly greater improvement than female participants, whereas age was not associated with score changes. This finding aligns partially with prior simulation-based education research, which indicates that performance gains may be influenced by individual differences, although many studies report comparable improvements across sex and age groups [1,6,7]. The observed sex difference may reflect variations in confidence, prior exposure, or learning preferences within the study sample, rather than inherent ability, and should be interpreted cautiously. Overall, these results suggest that the training intervention effectively improved performance across participants, with sex-related differences accounting for a small but significant portion of the variance. Future research should explore additional factors, such as baseline competency and engagement levels, to better understand the predictors of skill acquisition in simulation-based training.

Another contribution of this study is the longitudinal assessment of SA. By conducting follow-up measurements three months after training, the results indicate that knowledge retention and cognitive benefits persist beyond the immediate post-simulation phase. This durability underscores the value of simulation as a sustainable educational strategy rather than a short-term intervention.

Despite these promising findings, several limitations should be acknowledged. First, the study relied on the adapted Situation Awareness Global Assessment Technique (SAGAT), which, although validated, may not fully capture the complexity of situational awareness in dynamic clinical environments. Second, this study employed a quasi-experimental single-group pre–post design without a control group, limiting causal inference. While significant improvements in situational awareness were observed, the absence of a control group prevents ruling out alternative explanations for the observed changes, such as concurrent learning experiences or natural maturation effects. The quasi-experimental design does not allow for causal inference with the same rigor as randomized controlled trials. Third, the study was confined to a single institution, potentially limiting the generalizability of results to other nursing programs with differing curricula, resources, or student populations. Fourth although the adapted SAGAT questionnaire was reviewed by nursing educators and clinical experts, a full psychometric validation was not conducted. Cronbach’s alpha (α = 0.633) indicated moderate internal consistency, and a few items had lower item–total correlations, which may affect the precision of situational awareness measurement.

 Addressing these limitations in future research would strengthen the evidence base and allow for more nuanced insights into contextual factors that influence simulation effectiveness.

Future research should explore the integration of interprofessional simulation scenarios to evaluate how situational awareness develops in team-based contexts, which more closely mirror real-world healthcare environments [5]. Additionally, examining the role of structured debriefing in consolidating situational awareness would provide valuable pedagogical insights. Finally, comparative studies across diverse institutional and cultural settings would further validate the broader applicability of these findings.

 

CONCLUSION

This study provides empirical evidence that simulation significantly enhances nursing students’ situational awareness at all levels: perception, comprehension, and projection. The improvements observed both immediately and three months after training underscore the effectiveness of simulation not only as an instructional tool but also as a long-term capacity-building strategy in nursing education. By fostering the ability to detect, interpret, and anticipate clinical cues, simulation prepares students to act decisively in rapidly evolving healthcare contexts—an essential competency for ensuring patient safety and improving care outcomes. In the Tunisian context, where nursing education continues to align with international standards, these findings have important implications for curriculum design. Greater incorporation of simulation-based education may bridge the gap between theoretical knowledge and clinical competence, equipping future nurses with the cognitive agility and confidence necessary for professional practice.

Ultimately, embedding structured, simulation into nursing programs is not merely an educational innovation but a pedagogical imperative. As healthcare systems face increasing complexity, preparing nurses with advanced situational awareness through simulation represents a crucial step toward improving both individual clinical performance and overall quality of patient care.

 

Local Ethics Committee approval

The study was approved by the Institutional Review Board (IRB) of the Higher Institute of Nursing Sciences of Tunis (Approval No.: 01-07-10/2024; Date: 07/10/2024).. All procedures were conducted in accordance with the principles of the Declaration of Helsinki and relevant ethical guidelines for research involving human participants. Participant anonymity and data confidentiality were strictly maintained throughout all stages of the study. This study was conducted in accordance with ethical standards. All participants provided informed consent prior to participation.

 

Conflicts of interest

The authors declare no conflict of interest.

 

Sources of funding

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

 

Author contributions

Conception and design: Abdelbasset Ghalgaoui
Data collection: Rihab Salhi, Sawsen Rahmani
Data analysis and interpretation: Abdelbasset Ghalgaoui
Drafting of the manuscript: All authors
Critical revision of the manuscript: All authors
Final approval of the manuscript: All authors.

 

Acknowledgements

The authors would like to thank the administration, faculty members, and students of the Higher Institute of Nursing Sciences of Tunis for their cooperation and support during the conduct of this study.

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