Abstract
Hemodialysis is a therapeutic procedure used to manage and treat acute and chronic kidney failure, which cannot respond to traditional medical therapy. Patients undergoing hemodialysis frequently experience multiple burdensome symptoms that impact their psychological and physical well-being. Understanding how symptom burden influences self-efficacy and quality of life is essential to improve care for this population. This study aimed to evaluate the impact of physical and mental health symptoms on self-efficacy in managing the chronic disease and quality of life among patients undergoing haemodialysis. This was a multicentre cross-sectional study, including two large hemodialysis centers at An-Najah National University Hospital, Nablus, and Al-Hussein Government Hospital in Beit Jala. The symptom clusters experienced by patients undergoing hemodialysis were assessed via the Dialysis Symptom Index. Self-efficacy and quality of life were assessed using the Self-Efficacy for Managing Chronic Disease 6-Item Scale (SEMCD-6) and the EuroQol-5 Dimension (EQ-5D-5L), respectively. Independent-samples t-test and one-way ANOVA assessed group differences in self-efficacy and quality of life, and multivariable linear regression identified independent predictors of these outcomes. This study involved 306 patients undergoing hemodialysis, with a mean age of 58.1 ± 13.3 years. More than half of the participants were female (54.9%), and most lived in cities (51.0%). More than two-thirds of the participants experienced fatigue (84.3%), anxiety (72.5%), and sadness (72.5%). More than half reported stress (68.6%), agitation (64.7%), difficulty sleeping (62.7%), dry mouth (58.8%), dry skin (56.9%), depression (56.9%), cough (54.9%), difficulty concentrating (54.9%), itching (52.9%), and vertigo/dizziness (51.0%). The patients were moderately self-efficient in managing their chronic disease though faced challenges with mobility (56.9%), self-care (37.3%), and performing their usual activities (52.9%). The mean health rating of the participants based on the EQ-5D visual analogue scale (EQ-VAS) was 60.3 ± 18.3. Higher QoL was significantly associated with lower symptom burden, higher self-efficacy, urban residence, and younger age (p < 0.05). Having a healthy weight, living in urban areas, living with family, and having higher education were significantly associated with higher self-efficacy (p < 0.001). Symptom burden was negatively associated with both self-efficacy and quality of life (p < 0.001). This research provides significant insight into the factors affecting self-efficacy and overall quality of life among patients undergoing hemodialysis in Palestine. The findings suggest that self-efficacy and quality of life are negatively affected by greater symptom burden. Interventions targeting symptom burden and enhancing self-efficacy may improve patient outcomes. This underscores the need to integrate the clinical and psychosocial aspects of patient treatment in Palestine to enhance patient self-efficacy and overall health.
Keywords: Hemodialysis, Self‐efficacy, Self‐management, Quality of life, Physical symptoms, Mental health
Subject terms: Health care, Nephrology, Signs and symptoms
Introduction
Hemodialysis is used as a therapy for treating chronic and acute kidney failure when usual treatments fail1. The prevalence of hemodialysis-dependent chronic kidney disease is increasing and strains most healthcare systems worldwide2. Between 2000 and 2019, the number of patients with newly registered end-stage renal disease (ESRD) in the United States increased from 94,466 to 134,862, representing a 42.8% increase3.
According to 2020 statistics, there are 11 dialysis units in the West Bank, Palestine. Ten are operated by the Ministry of Health and have a total of 247 hemodialysis machines. One additional unit at An-Najah National University Hospital in Nablus contains 45 machines4. Moreover, in Gaza, there are 5 units with 124 machines. By the end of 2020, 1557 patients had received hemodialysis at the West Bank.4
Patients with ESRD ultimately experience many pathological changes, such as cardiovascular problems. In addition, they may face disturbances in fluid balance, electrolytes, bone formation, acid base imbalance, and coagulation problems5.
Patients undergoing hemodialysis experience high symptom burden6. Most patients experience a reduced quality of life, which leads to a higher incidence of morbidity and mortality7. The activities of daily living of these patients are also negatively affected by their psychological and physical situations. In patients undergoing maintenance hemodialysis, physical inactivity may negatively impact bone formation, thereby further reducing their physical activity levels8.
Understanding how hemodialysis impacts patients’ quality of life is crucial for developing targeted interventions that enhance patient care and well-being. Multiple studies have focused on how hemodialysis affects patients’ quality of life. For example, Bastos, Reis, and Cherchiglia (2021) reported that Brazilian hemodialysis patients frequently experience fatigue, pain, poor sleep quality, and mental health challenges, highlighting the substantial impact of dialysis on patients’ quality of life9. Similarly, research from Turkey highlighted the importance of self-care and efficacy in the management of symptoms and reported a better quality of life in patients with self-efficacy10. In support of these findings, a study from Indonesia reported that self-efficacy and self-care behaviors were significantly associated with health-related quality of life (QoL) among patients undergoing hemodialysis11. Despite these findings, there is a notable gap in research regarding the self-efficacy of hemodialysis patients in the Palestinian context, where differences in healthcare infrastructure and cultural perceptions may influence outcomes.
In patients undergoing hemodialysis, it is crucial to understand how self-efficacy, symptom management, and quality of life interact with each other. Self-efficacy is defined as an individual’s belief in their personal management ability; therefore, it is very important in health behavior and improving patient outcomes. However, the specific symptom clusters and their impact on self-efficacy and QoL remain unexplored in the Palestinian context. This gap may hinder the development of effective patient-centered interventions.
This study aimed to evaluate the quality of life among hemodialysis patients in Palestine and examine the relationship between various physical and mental health symptoms, patients’ self-efficacy, and their overall quality of life. By identifying key variables that influence quality of life, the findings can contribute to improving patient care strategies and informing policy decisions related to dialysis treatment.
Methods
Study design and population
This cross-sectional study was conducted between January 2023 and January 2024 at two major hemodialysis centers in the West Bank, Palestine: An-Najah National University Hospital in Nablus and Al-Hussein Government Hospital in Beit Jala. Patients aged 18 years and older with end-stage renal disease who were on maintenance hemodialysis and willing to participate were included. Patients with cancer, those receiving chemotherapy, or those with mental limitations preventing questionnaire comprehension were excluded.
Sample size and calculation
The sample size was calculated via Raosoft12 and was based on the number of patients who received hemodialysis services in West Bank hospitals, which totaled 1557 patients in Palestine in 20204. With a 95% confidence level, a 5% margin of error and a 50% response distribution were used. Although the calculated sample size was 309, 306 participants were ultimately recruited due to availability during the data collection period. Participants were recruited via a convenience sampling method from three dialysis centers.
Measures and data collection
Data were collected via a questionnaire developed for this study to ensure consistency and completeness, which was based on previous studies1,10,11,13–20. Data collection was conducted through interviewer-administered questionnaires.
The demographic section was developed by the research team based on the literature review, while validated tools were used to assess symptoms (Dialysis Symptom Index)13, self-efficacy (the Self-Efficacy for Managing Chronic Disease 6-Item Scale (SEMCD-6)14, and QoL (5-level EuroQol-5 Dimension (EQ-5D-5L) and the EQ visual analogue scale (EQ-VAS)) among participants20. The tools have been previously validated in Arabic-speaking populations21–23.
The questionnaire included five parts. The first and second variables covered sociodemographic and clinical characteristics, including age, marital status, educational level, smoking status, disease history, comorbidities, time elapsed since receiving hemodialysis, number of hemodialysis sessions per week, and length of hemodialysis session. The third part included the symptoms experienced by the patients undergoing hemodialysis via the Dialysis Symptom Index13. These symptoms included constipation, nausea, vomiting, diarrhea, loss of appetite, muscle cramps, swelling in the legs, shortness of breath, vertigo/dizziness, instability of the legs, cough, dry mouth, bone or joint pain, chest pain, difficulty sleeping, depression, lack of libido and others. Patients rated the severity and frequency of symptoms on a 10-point Likert scale, with higher scores indicating greater discomfort.
The fourth part assessed self-efficacy for managing chronic disease via the Self-Efficacy for Managing Chronic Disease 6-Item Scale14. The scale evaluates patients’ confidence in managing their disease by assessing their ability to manage fatigue, physical discomfort, emotional distress, other symptoms, and activities to reduce their doctor visits. Patients rated their confidence in managing their illness and its impact on daily life via a 10-point Likert scale, where 1 indicated “not confident” and 10 indicated “completely confident”. The scale aims to help patients feel more confident in managing their health condition and reduce the need for medication.
The fifth part assessed quality of life with the 5-level EuroQol-5 Dimension (EQ-5D-5L) and the EQ visual analogue scale (EQ-VAS)20. The EQ-VAS measures a patient’s health status in five dimensions: mobility, self-care, usual activities, pain, and depression. Patients rate each dimension on a scale from 1 to 5, and their self-rated health is recorded on a 20 cm vertical visual analogue scale. The scale indicates the patient’s current health status by marking an X on it and writing the number in a box. Since specific validation studies in the Palestinian population were not found, we conducted a pilot test among 20 hemodialysis patients to assess clarity and contextual relevance24. Additionally, the internal consistency of the Dialysis Symptom Index, SEMCD, and EQ-5D-5L was assessed via Cronbach’s alphas, which were 0.86, 0.82, and 0.91, respectively.
All participants provided informed consent before data collection. Informed consent was obtained after providing an information sheet and verbal explanation. The participants were given adequate time to ask questions and could withdraw at any time. Data collection was carried out during dialysis sessions without interrupting patient treatments and care.
Data and statistical analysis
The data were entered and analysed via the Statistical Package for Social Sciences program (IBM SPSS) version 21. Data are expressed as the means ± standard deviations (SDs) for continuous variables and as frequencies (n) and percentages (%) for categorical variables. Variables were tested for normality via the Kolmogorov‒Smirnov test, skewness, and kurtosis. Between-group differences in continuous variables were assessed using independent-samples t tests or one-way ANOVA, as appropriate. The significance level was set at a p value < 0.05. Although SEM offers more advanced modelling, it was not used because of sample size constraints and the exploratory nature of this study. Multiple linear regression was deemed appropriate for our objectives. Multiple linear regression was used to identify predictors of self-efficacy and QoL. Independent categorical variables were dummy coded. The assumptions of normality, linearity, and homoscedasticity were checked. Variables were selected on the basis of their theoretical relevance and correlation analysis.
Ethical considerations
The study protocol received approval from the Institutional Review Board (IRB) of An-Najah National University [IRB Reference #: Mas. Oct. 2021/37], and necessary permissions were obtained from the hospitals. The research followed the ethical principles outlined in the Declaration of Helsinki25. Written informed consent was obtained from all participants prior to their inclusion in the study. The consent process included providing both written and verbal explanations of the study objectives, procedures, and potential implications. Participants were assured that their information would be kept strictly confidential and used only for scientific purposes. They were informed of their full right to refuse participation or to withdraw from the study at any stage without providing reasons and without any harm or consequences. Participants were also given the opportunity to ask questions before agreeing to participate, ensuring that their decision was fully voluntary and based on adequate understanding. Confidentiality and privacy were strictly upheld throughout the study, with access to participant data limited to the research team. Data collection took place in private settings to prioritize participant comfort and confidentiality. All the data were anonymized and stored securely in password-protected files accessible only to the research team and used solely for the purposes of this study.
Results
Demographic and clinical variables of patients undergoing hemodialysis
A total of 306 patients undergoing hemodialysis were included. The mean age of the patients was 58.1 ± 13.3 years. Among the patients, 168 (54.9%) were female, 156 (51%) lived in cities, 252 (82.4%) lived with families, 216 (70.6%) were married, 210 (68.6%) were unemployed, 198 (64.7%) had low incomes, and 198 (64.7%) were overweight or obese. The demographic and disease characteristics of the patients who underwent hemodialysis are described in Table 1.
Table 1.
Demographic and disease characteristics of patients undergoing hemodialysis (n = 306).
| Variable | n (%) or Mean (SD) |
|---|---|
| Age (year), mean (SD) | 58.1 (13.3) |
| Sex | |
| Male, n (%) | 138 (45.1) |
| Female, n (%) | 168 (54.9) |
| Place of residence | |
| Refugee camp, n (%) | 48 (15.7) |
| Village, n (%) | 102 (33.3) |
| City, n (%) | 156 (51.0) |
| Living conditions | |
| I live alone, n (%) | 54 (17.6) |
| I live with my family, n (%) | 252 (82.4) |
| Educational level | |
| Uneducated, n (%) | 42 (13.7) |
| School, n (%) | 180 (58.8) |
| University, n (%) | 84 (27.5) |
| Marital status | |
| Currently unmarried, n (%) | 90 (29.4) |
| Currently married, n (%) | 216 (70.6) |
| Employment status | |
| Unemployed, n (%) | 210 (68.6) |
| Employed, n (%) | 96 (31.4) |
| Income level | |
| < 2000, n (%) | 198 (64.7) |
| ≥ 2000, n (%) | 108 (35.3) |
| Smoking status | |
| Yes, n (%) | 96 (31.4) |
| No, n (%) | 210 (68.6) |
| Packs/year, mean (SD) | 45.5 (26.9) |
| Time elapsed since receiving hemodialysis (years), mean (SD) | 5.6 (4.5) |
| Number of hemodialysis sessions per week, mean (SD) | 1.9 (0.2) |
| Length of hemodialysis session (hours), mean (SD) | 3.7 (0.4) |
| Height (m), mean (SD) | 1.7 (0.1) |
| Weight (kg), mean (SD) | 76.3 (14.4) |
| BMI (kg/m2), mean (SD) | 27.4 (5.2) |
| BMI categories | |
| Healthy weight, n (%) | 108 (35.3) |
| Unhealthy weight (overweight/obese), n (%) | 198 (64.7) |
| Comorbidities | |
| Received a kidney transplantation, n (%) | 24 (7.8) |
| Diabetes mellitus, n (%) | 174 (56.9) |
| Hypertension, n (%) | 222 (72.5) |
| Arthritis, n (%) | 42 (13.7) |
| Systemic lupus erythematous, n (%) | 6 (2.0) |
| Angina, n (%) | 42 (13.7) |
| Stroke, n (%) | 30 (9.8) |
| Heart failure, n (%) | 84 (27.5) |
| Chronic lung disease, n (%) | 6 (2.0) |
| Other diseases, n (%) | 24 (7.8) |
| Medications | |
| Taking chronic medications, n (%) | 306 (100.0) |
| Do you take medications by yourself, n (%) | 246 (80.4) |
BMI, body mass index; n: number; SD, standard deviation.
Symptoms experienced by patients undergoing hemodialysis
This study revealed that patients undergoing hemodialysis experienced various health symptoms, including gastrointestinal, musculoskeletal, neurological, mental, physical, and sexual issues. The most prevalent symptoms were fatigue (84.3%), dry skin (56.9%), and itching (52.9%). The symptoms rated highest in severity included instability of the legs (mean = 8.0 ± 2.2), difficulty sleeping (7.0 ± 1.8), and bone or joint pain (7.1 ± 1.9). The most bothersome symptoms on the basis of bother mean scores were instability of the legs (8.4 ± 2.0), bone or joint pain (7.1 ± 2.1), and muscle soreness (6.9 ± 2.2). Although fatigue was the most frequently reported symptom, other symptoms, such as difficulty concentrating (54.9%) and itching of the skin (52.9%), were also commonly cited as highly bothersome, highlighting the complexity of symptom experience. These symptoms were reported with variable bother, severity, and frequency, as shown in Table 2.
Table 2.
Symptoms experienced by patients undergoing hemodialysis (n = 306).
| # | Symptoms | n (%) | Bother | Severity | Frequency |
|---|---|---|---|---|---|
| Mean (SD) | Mean (SD) | Mean (SD) | |||
| 1 | Constipation | 120 (39.2) | 5.3 (2.2) | 5.4 (2.2) | 5.4 (2.1) |
| 2 | Nausea | 84 (27.5) | 5.4 (2.2) | 5.1 (1.8) | 4.7 (2.3) |
| 3 | Vomiting | 36 (11.8) | 5.7 (2.2) | 5.0 (1.9) | 3.8 (1.9) |
| 4 | Diarrhea | 102 (33.3) | 5.1 (2.0) | 4.9 (2.2) | 5.0 (2.4) |
| 5 | Loss of appetite | 192 (62.7) | 5.0 (1.7) | 4.9 (1.7) | 4.8 (1.8) |
| 6 | Muscle cramp | 108 (35.3) | 6.7 (1.9) | 6.3 (2.4) | 5.7 (2.6) |
| 7 | Swelling in the legs | 90 (29.4) | 5.5 (2.5) | 5.3 (2.3) | 5.1 (2.7) |
| 8 | Shortness of breath | 102 (33.3) | 5.6 (2.3) | 5.8 (2.2) | 5.6 (2.6) |
| 9 | Vertigo/dizziness | 156 (51.0) | 4.1 (2.6) | 3.4 (2.0) | 3.2 (2.0) |
| 10 | Instability of the legs | 84 (27.5) | 8.4 (2.0) | 8.0 (2.2) | 8.2 (2.1) |
| 11 | Dull numbness or tingling in the feet | 120 (39.2) | 6.3 (2.3) | 6.1 (2.2) | 5.9 (2.3) |
| 12 | Feeling tired or losing energy | 258 (84.3) | 5.4 (2.1) | 5.4 (2.2) | 5.5 (2.3) |
| 13 | Cough | 168 (54.9) | 4.4 (2.2) | 4.2 (2.1) | 4.5 (2.5) |
| 14 | Dry mouth | 180 (58.8) | 4.8 (2.4) | 4.8 (2.3) | 5.0 (2.4) |
| 15 | Bone or joint pain | 108 (35.3) | 7.1 (2.1) | 7.1 (1.9) | 7.1 (1.8) |
| 16 | Chest pain | 66 (21.6) | 4.8 (2.4) | 4.5 (2.7) | 4.5 (2.7) |
| 17 | Headache | 120 (39.2) | 5.6 (2.8) | 5.4 (2.6) | 5.4 (2.6) |
| 18 | Muscle soreness | 114 (37.3) | 6.9 (2.2) | 6.4 (2.2) | 6.5 (2.2) |
| 19 | Difficulty concentrating | 168 (54.9) | 4.6 (2.1) | 4.5 (2.1) | 4.7 (2.0) |
| 20 | Dry skin | 174 (56.9) | 5.3 (2.5) | 5.0 (2.5) | 5.0 (2.6) |
| 21 | Itching | 162 (52.9) | 4.7 (2.7) | 4.4 (2.6) | 4.7 (2.7) |
| 22 | Anxiety | 222 (72.5) | 5.3 (2.5) | 5.2 (2.4) | 5.6 (2.5) |
| 23 | Feeling stressed | 210 (68.6) | 5.3 (2.6) | 5.2 (2.6) | 5.7 (2.6) |
| 24 | Difficulty sleeping | 192 (62.7) | 5.9 (2.4) | 6.0 (2.4) | 6.1 (2.4) |
| 25 | Difficulty staying asleep | 120 (39.2) | 7.0 (1.9) | 7.0 (1.8) | 7.0 (1.9) |
| 26 | Feeling irritable and angry | 192 (62.7) | 5.2 (2.2) | 5.3 (2.3) | 5.6 (2.5) |
| 27 | Feeling sad | 222 (72.5) | 5.1 (2.2) | 5.2 (2.3) | 5.2 (2.2) |
| 28 | Feeling agitated or uncomfortable | 198 (64.7) | 4.9 (2.3) | 5.0 (2.4) | 5.1 (2.4) |
| 29 | Depression | 174 (56.9) | 4.9 (2.4) | 4.9 (2.5) | 4.7 (2.4) |
| 30 | Lack of libido | 144 (47.1) | 4.5 (2.3) | 4.6 (2.1) | 4.8 (2.0) |
| 31 | Difficulty with sexual arousal | 138 (45.1) | 4.0 (1.7) | 3.9 (1.8) | 4.3 (1.7) |
| 32 | Frequent urination at night (during sleep) | 84 (27.5) | 3.5 (1.4) | 3.4 (1.8) | 3.3 (2.0) |
n, number; SD, standard deviation.
Self-efficacy for managing chronic disease
This study assessed patients’ self-efficacy in managing their chronic diseases via the SEMCD 6-item scale. The mean SEMCD score was 6.1 ± 1.8, reflecting a moderate level of self-efficacy in this population, on the basis of the mean distribution, as no specific cut-off values are available for this scale, as shown in Table 3.
Table 3.
Ratings of patients on the 6-item Self-Efficacy for Managing Chronic Disease Scale.
| # | SEMCD item | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | Mean (SD) |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | How confident do you feel that you can keep the fatigue caused by your disease from interfering with the things you want to do? | 18 (5.9) | 12 (3.9) | 18 (5.9) | 36 (11.8) | 66 (21.6) | 36 (11.8) | 42 (13.7) | 36 (11.8) | 36 (11.8) | 6 (2.0) | 5.7 (2.3) |
| 2 | How confident do you feel that you can keep the physical discomfort or pain of your disease from interfering with the things you want to do? | 24 (7.8) | 6 (2.0) | 6 (2.0) | 24 (7.8) | 66 (21.6) | 48 (15.7) | 42 (13.7) | 54 (17.6) | 30 (9.8) | 6 (2.0) | 6.0 (2.2) |
| 3 | How confident do you feel that you can keep the emotional distress caused by your disease from interfering with the things you want to do? | 30 (9.8) | 6 (2.0) | 24 (7.8) | 18 (5.9) | 36 (11.8) | 48 (15.7) | 48 (15.7) | 36 (11.8) | 42 (13.7) | 18 (5.9) | 6.0 (2.6) |
| 4 | How confident do you feel that you can keep any other symptoms or health problems you have from interfering with the things you want to do? | 12 (3.9) | 12 (3.9) | 6 (2.0) | 30 (9.8) | 48 (15.7) | 24 (7.8) | 54 (17.6) | 48 (15.7) | 42 (13.7) | 30 (9.8) | 6.5 (2.4) |
| 5 | How confident do you feel that you can the different tasks and activities needed to manage your health condition to reduce your need to see a doctor? | 42 (13.7) | 0 (0.0) | 12 (3.9) | 18 (5.9) | 48 (15.7) | 48 (15.7) | 36 (11.8) | 36 (11.8) | 42 (13.7) | 24 (7.8) | 6.0 (2.7) |
| 6 | How confident do you feel that you can do things other than just taking medication to reduce how much your illness affects your everyday life? | 36 (11.8) | 6 (2.0) | 0 (0.0) | 6 (2.0) | 78 (25.5) | 18 (5.9) | 36 (11.8) | 48 (15.7) | 60 (19.6) | 18 (5.9) | 6.3 (2.6) |
| SEMCD score | 6.1 (1.8) |
SEMCD: Self-Efficacy for Managing Chronic Disease Scale.
Patient quality of life
The study assessed patients’ quality of life via the EQ-5D-5L scale and EQ-VAS, as shown in Table 4. The results revealed that 56.9% reported mobility issues, 37.3% self-care issues, 52.9% difficulty performing activities, 78.4% pain/discomfort, and 82.4% anxiety/depression. The mean health rating on the EQ-VAS was 60.3 ± 18.3, suggesting that participants perceived their overall health as moderate. The mean EQ-5D-5L index score was 0.63 ± 0.3, indicating moderate QoL.
Table 4.
Quality of life reported by the patients.
| # | EQ-5D-5L item | No problems | Slight problems | Moderate problems | Severe problems | Unable to | Mean (SD) |
|---|---|---|---|---|---|---|---|
| 1 | Mobility, n (%) | 132 (43.1) | 90 (29.4) | 6 (2.0) | 24 (7.8) | 54 (17.6) | 2.3 (1.5) |
| 2 | Self-care, n (%) | 192 (62.7) | 48 (15.7) | 18 (5.9) | 6 (2.0) | 42 (13.7) | 1.9 (1.4) |
| 3 | Usual activities, n (%) | 144 (47.1) | 48 (15.7) | 42 (13.7) | 24 (7.8) | 48 (15.7) | 2.3 (1.5) |
| 4 | Pain/discomfort, n (%) | 66 (21.6) | 120 (39.2) | 72 (23.5) | 30 (9.8) | 18 (5.9) | 2.4 (1.1) |
| 5 | Anxiety/depression, n (%) | 54 (17.6) | 60 (19.6) | 132 (43.1) | 30 (9.8) | 30 (9.8) | 2.7 (1.2) |
| EQ-5D-5L index value | 0.63 (0.30) | ||||||
| VAS Qol | 60.3 (18.3) | ||||||
Correlations between the SEMCD score, EQ-5D-5L index value, and VAS score
In this study, the SEMCD score was significantly positively correlated with both the EQ-5D-5L score (r = 0.15, p = 0.013) and the VAS score (r = 0.27, p < 0.001). Furthermore, a strong positive correlation was observed between the EQ-5D-5L index value and the VAS score (r = 0.57, p < 0.001), as shown in Table 5.
Table 5.
Correlations between the SEMCD score, EQ-5D-5L index value, and VAS score.
| SEMCD score | EQ-5D-5L index value | VAS Qol | ||
|---|---|---|---|---|
| SEMCD score | Pearson’s r | – | 0.15 | 0.27 |
| p value | 0.013 | < 0.001 | ||
| EQ-5D-5L index value | Pearson’s r | 0.15 | – | 0.57 |
| p value | 0.013 | < 0.001 | ||
| VAS Qol | Pearson’s r | 0.27 | 0.57 | – |
| p value | < 0.001 | < 0.001 | ||
Predictors of self-efficacy in managing chronic disease
Multiple linear regression analysis identified several significant predictors of self-efficacy in managing chronic disease (SEMCD score), adjusting for confounders, as shown in Table 6. Higher self-efficacy was significantly associated with many factors, such as living with family (β = 0.72, p = 0.001), having a higher educational level (β = 0.66, p < 0.001), and having fewer mobility problems (β = 0.69, p < 0.001). Conversely, lower self-efficacy was predicted by, for example, being unmarried (β = − 0.49, p = 0.006), living in urban areas (β = − 0.59, p < 0.001), having a lower BMI (β = − 0.08, p < 0.001), having chest pain (β = − 1.65, p < 0.001), and having constipation (β = − 0.58, p < 0.001). This regression model explained 83.9% of the variance in the SEMCD self-efficacy scores (R2 = 0.839, p < 0.001).
Table 6.
Factors predicting self-efficacy in managing chronic disease.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| BMI | − 0.08 | 0.01 | − 0.22 | − 5.44 | < 0.001 |
| Place of residence | − 0.59 | 0.09 | − 0.24 | − 6.26 | < 0.001 |
| Living conditions | 0.72 | 0.22 | 0.15 | 3.29 | 0.001 |
| Educational level | 0.66 | 0.13 | 0.23 | 5.27 | < 0.001 |
| Marital status | − 0.49 | 0.18 | − 0.12 | − 2.79 | 0.006 |
| Diabetes mellitus | 0.73 | 0.16 | 0.20 | 4.43 | < 0.001 |
| Hypertension | 0.39 | 0.22 | 0.10 | 1.81 | 0.071 |
| Constipation | − 0.58 | 0.16 | − 0.16 | − 3.70 | < 0.001 |
| Vomiting | 0.04 | 0.17 | 0.01 | 0.23 | 0.822 |
| Muscle cramp | − 0.02 | 0.17 | 0.00 | − 0.11 | 0.914 |
| Cough | 1.60 | 0.14 | 0.44 | 11.14 | < 0.001 |
| Chest pain | − 1.65 | 0.25 | − 0.38 | − 6.68 | < 0.001 |
| Dry skin | 0.42 | 0.14 | 0.12 | 2.98 | 0.003 |
| Itching | 0.17 | 0.14 | 0.05 | 1.18 | 0.240 |
| Feeling stressed | − 0.44 | 0.17 | -0.11 | − 2.61 | 0.010 |
| Difficulty sleeping | 0.38 | 0.13 | 0.10 | 2.82 | 0.005 |
| Feeling sad | 0.20 | 0.21 | 0.05 | 0.94 | 0.347 |
| Feeling agitated or uncomfortable | − 0.34 | 0.19 | − 0.09 | − 1.81 | 0.071 |
| Depression | 1.01 | 0.18 | 0.28 | 5.59 | < 0.001 |
| Lack of libido | 0.32 | 0.19 | 0.09 | 1.66 | 0.098 |
| Difficulty with sexual arousal | − 1.17 | 0.21 | − 0.32 | − 5.56 | < 0.001 |
| Frequent urination at night (during sleep) | 0.11 | 0.16 | 0.03 | 0.65 | 0.519 |
| Number of hemodialysis sessions per week | − 2.92 | 0.29 | − 0.38 | − 10.05 | < 0.001 |
| Length of hemodialysis session (hours) | 0.60 | 0.18 | 0.13 | 3.31 | 0.001 |
| Mobility | 0.69 | 0.11 | 0.58 | 6.49 | < 0.001 |
| Self− care | − 0.98 | 0.13 | − 0.77 | − 7.55 | < 0.001 |
| Usual activities | 0.12 | 0.14 | 0.10 | 0.91 | 0.364 |
| Pain/discomfort | 0.03 | 0.11 | 0.02 | 0.29 | 0.769 |
| Anxiety/depression | 0.51 | 0.09 | 0.33 | 6.01 | < 0.001 |
| VAS Qol | 0.02 | 0.00 | 0.16 | 3.41 | 0.001 |
R2 = 0.839, p < 0.001.
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale; BMI, Body Mass Index.
Significant values are in bold
Predictors of mobility problems
As shown in Table 7, significant predictors of mobility problems included being female (β = 1.15, p < 0.001), unemployment (β = 0.85, p < 0.001), and diabetes (β = 0.20, p = 0.004). Difficulty in independently managing medications (β = 1.46, p < 0.001) and symptoms such as nausea (β = 0.60, p < 0.001) were additional contributing factors. Older age (β = 0.04, p < 0.001) and lower VAS QoL scores (β = − 0.03, p < 0.001) were associated with reduced mobility. Other significant predictors are listed in Table 7. The multiple linear regression model explained 98.7% of the variance in the mobility problems (R2 = 0.987, p < 0.001).
Table 7.
Factors predicting mobility problems.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Sex | 1.15 | 0.07 | 0.38 | 15.87 | < 0.001 |
| Educational level | − 0.34 | 0.06 | − 0.14 | − 5.68 | < 0.001 |
| Marital status | − 0.43 | 0.05 | − 0.13 | − 8.22 | < 0.001 |
| Employment status | 0.85 | 0.10 | 0.26 | 8.42 | < 0.001 |
| Income level | 0.09 | 0.09 | 0.03 | 1.07 | 0.287 |
| Diabetes mellitus | 0.20 | 0.07 | 0.07 | 2.87 | 0.004 |
| Hypertension | -0.09 | 0.07 | − 0.03 | − 1.27 | 0.205 |
| Arthritis | − 0.16 | 0.13 | − 0.04 | − 1.19 | 0.237 |
| Angina | 0.69 | 0.11 | 0.16 | 6.10 | < 0.001 |
| Heart failure | − 0.31 | 0.08 | − 0.09 | − 4.03 | < 0.001 |
| Other diseases | − 1.64 | 0.23 | − 0.29 | − 7.19 | < 0.001 |
| Do you take medications by yourself | 1.46 | 0.09 | 0.38 | 16.66 | < 0.001 |
| Constipation | − 0.64 | 0.05 | − 0.21 | -12.98 | < 0.001 |
| Nausea | 0.60 | 0.10 | 0.18 | 5.77 | < 0.001 |
| Vomiting | − 0.91 | 0.09 | − 0.19 | − 10.22 | < 0.001 |
| Diarrhea | 0.66 | 0.08 | 0.21 | 8.23 | < 0.001 |
| Muscle cramp | 0.26 | 0.09 | 0.08 | 2.82 | 0.005 |
| Swelling in the legs | − 0.37 | 0.07 | − 0.11 | − 5.23 | < 0.001 |
| Shortness of breath | 0.38 | 0.08 | 0.12 | 4.67 | < 0.001 |
| Instability of the legs | 0.63 | 0.06 | 0.19 | 9.80 | < 0.001 |
| Dull numbness or tingling in the feet | − 0.94 | 0.10 | − 0.30 | − 9.38 | < 0.001 |
| Feeling tired or losing energy | 1.16 | 0.16 | 0.28 | 7.28 | < 0.001 |
| Cough | − 0.02 | 0.08 | − 0.01 | − 0.19 | 0.850 |
| Dry mouth | − 1.04 | 0.07 | − 0.34 | − 15.81 | < 0.001 |
| Bone or joint pain | 0.32 | 0.18 | 0.10 | 1.79 | 0.074 |
| Chest pain | 0.76 | 0.13 | 0.21 | 5.82 | < 0.001 |
| Headache | 0.15 | 0.06 | 0.05 | 2.37 | 0.018 |
| Muscle soreness | − 0.28 | 0.17 | − 0.09 | − 1.69 | 0.092 |
| Difficulty concentrating | − 0.47 | 0.05 | − 0.16 | − 8.82 | < 0.001 |
| Difficulty sleeping | − 0.41 | 0.05 | − 0.13 | − 8.22 | < 0.001 |
| Difficulty staying asleep | 1.33 | 0.13 | 0.43 | 10.56 | < 0.001 |
| Feeling sad | − 0.75 | 0.11 | − 0.22 | − 6.57 | < 0.001 |
| Feeling agitated or uncomfortable | 0.46 | 0.06 | 0.15 | 7.46 | < 0.001 |
| Lack of libido | 0.59 | 0.12 | 0.19 | 5.04 | < 0.001 |
| Difficulty with sexual arousal | − 0.22 | 0.13 | − 0.07 | − 1.66 | 0.097 |
| SEMCD score | 0.18 | 0.02 | 0.22 | 9.74 | < 0.001 |
| Age (year) | 0.04 | 0.00 | 0.39 | 11.09 | < 0.001 |
| Number of hemodialysis sessions per week | 0.52 | 0.18 | 0.08 | 2.84 | 0.005 |
| Length of hemodialysis session (hours) | − 0.54 | 0.09 | − 0.14 | − 5.69 | < 0.001 |
| Self− care | 0.11 | 0.04 | 0.10 | 2.98 | 0.003 |
| Usual activities | − 0.01 | 0.04 | − 0.01 | − 0.16 | 0.870 |
| Pain/discomfort | − 0.06 | 0.06 | − 0.05 | − 1.11 | 0.269 |
| Anxiety/depression | − 0.03 | 0.06 | − 0.02 | − 0.46 | 0.649 |
| VAS Qol | − 0.03 | 0.00 | − 0.36 | − 11.77 | < 0.001 |
R2 = 0.987, p < 0.001.
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale.
Significant values are in bold
Predictors of problems performing usual activities
Problems with usual activities were significantly associated with living alone (β = 2.9, p < 0.001), low income (β = − 3.2, p < 0.001), and unemployment (β = 5.3, p < 0.001), as shown in Table 8. Health-related contributors included stroke (β = 2.0, p < 0.001), hypertension (β = 1.5, p < 0.001), and arthritis (β = 0.7, p < 0.001). Additional contributors were symptoms such as muscle soreness (β = 5.9, p < 0.001) and fatigue (β = 3.7, p < 0.001). Additional predictors are given in Table 8. The multiple linear regression model explained 98.7% of the variance in problems performing usual activities (R2 = 0.987, p < 0.001).
Table 8.
Factors predicting problems in performing usual activities.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Place of residence | − 0.9 | 0.0 | − 0.4 | − 24.3 | 0.000 |
| Living conditions | 2.9 | 0.1 | 0.7 | 37.6 | 0.000 |
| Educational level | − 1.8 | 0.1 | − 0.7 | − 31.8 | 0.000 |
| Marital status | − 2.6 | 0.1 | − 0.8 | − 33.3 | 0.000 |
| Employment status | 5.3 | 0.1 | 1.7 | 37.2 | 0.000 |
| Income level | − 3.2 | 0.1 | − 1.0 | − 40.0 | 0.000 |
| Diabetes mellitus | 0.3 | 0.1 | 0.1 | 3.8 | 0.000 |
| Hypertension | 1.5 | 0.1 | 0.4 | 24.3 | 0.000 |
| Arthritis | 0.7 | 0.1 | 0.2 | 9.6 | 0.000 |
| Angina | − 2.6 | 0.1 | − 0.6 | − 31.2 | 0.000 |
| Stroke | 2.0 | 0.1 | 0.4 | 20.7 | 0.000 |
| Heart failure | − 1.4 | 0.1 | − 0.4 | − 28.2 | 0.000 |
| Other diseases | − 6.5 | 0.2 | − 1.2 | − 42.1 | 0.000 |
| Do you take medications by yourself | 3.3 | 0.1 | 0.9 | 33.1 | 0.000 |
| Constipation | − 0.1 | 0.0 | 0.0 | − 3.3 | 0.001 |
| Nausea | 0.7 | 0.1 | 0.2 | 10.8 | 0.000 |
| Loss of appetite | − 0.3 | 0.0 | − 0.1 | − 7.5 | 0.000 |
| Muscle cramp | − 0.8 | 0.1 | − 0.3 | − 12.0 | 0.000 |
| Swelling in the legs | − 0.8 | 0.1 | − 0.2 | − 16.1 | 0.000 |
| Shortness of breath | − 1.9 | 0.1 | − 0.6 | − 27.7 | 0.000 |
| Vertigo/dizziness | 2.2 | 0.1 | 0.8 | 34.9 | 0.000 |
| Instability of the legs | − 2.7 | 0.1 | − 0.8 | − 33.6 | 0.000 |
| Dull numbness or tingling in the feet | − 2.7 | 0.1 | − 0.9 | − 25.6 | 0.000 |
| Feeling tired or losing energy | 3.7 | 0.1 | 0.9 | 36.8 | 0.000 |
| Cough | 1.0 | 0.1 | 0.3 | 12.3 | 0.000 |
| Dry mouth | − 3.1 | 0.1 | − 1.0 | − 31.9 | 0.000 |
| Bone or joint pain | − 2.0 | 0.1 | − 0.6 | − 21.5 | 0.000 |
| Chest pain | 0.0 | 0.1 | 0.0 | 0.4 | 0.686 |
| Headache | − 1.5 | 0.1 | − 0.5 | − 18.9 | 0.000 |
| Muscle soreness | 5.9 | 0.1 | 1.9 | 50.4 | 0.000 |
| Difficulty concentrating | 0.6 | 0.0 | 0.2 | 17.2 | 0.000 |
| Dry skin | − 0.4 | 0.1 | − 0.1 | − 8.2 | 0.000 |
| Difficulty sleeping | 0.0 | 0.0 | 0.0 | − 0.7 | 0.468 |
| Difficulty staying asleep | 4.6 | 0.2 | 1.5 | 28.1 | 0.000 |
| Feeling irritable and angry | − 1.6 | 0.1 | − 0.5 | − 32.6 | 0.000 |
| Lack of libido | − 2.3 | 0.1 | − 0.8 | − 26.9 | 0.000 |
| Difficulty with sexual arousal | 2.8 | 0.1 | 0.9 | 28.7 | 0.000 |
| SEMCD score | 0.2 | 0.0 | 0.2 | 11.3 | 0.000 |
| Age (year) | 0.1 | 0.0 | 1.0 | 23.5 | 0.000 |
| Number of hemodialysis sessions per week | 2.2 | 0.1 | 0.3 | 17.5 | 0.000 |
| Length of hemodialysis session (hours) | − 2.0 | 0.1 | − 0.5 | − 23.5 | 0.000 |
| Mobility | − 0.5 | 0.0 | − 0.5 | − 18.1 | 0.000 |
| Self-care | 0.1 | 0.0 | 0.1 | 4.7 | 0.000 |
| Pain/discomfort | 1.4 | 0.0 | 1.0 | 35.2 | 0.000 |
| Anxiety/depression | − 2.3 | 0.1 | − 1.8 | − 38.9 | 0.000 |
| VAS Qol | 0.0 | 0.0 | 0.1 | 5.1 | 0.000 |
R2 = 0.978, p < 0.001
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale.
Significant values are in bold
Predictors of problems in self-care
A lower level of self-care ability was significantly associated with a lower educational level (β = − 0.38, p < 0.001), unemployment (β = 1.00, p < 0.001), and comorbid conditions such as diabetes (β = 0.36, p < 0.001) and stroke (β = 0.70, p < 0.001). Psychological symptoms such as sadness (β = − 0.93, p < 0.001) and depression (β = 0.99, p < 0.001), as well as lower self-efficacy (β = − 0.06, p < 0.001), were also significant predictors. Additional significant factors are detailed in Table 9. The multiple linear regression model explained 97.6% of the variance in problems in self care (R2 = 0.976, p < 0.001).
Table 9.
Factors predicting problems in self-care.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Living conditions | − 0.09 | 0.09 | − 0.03 | − 0.99 | 0.321 |
| Educational level | − 0.38 | 0.06 | − 0.17 | − 6.23 | 0.000 |
| Employment status | 1.00 | 0.14 | 0.33 | 7.23 | 0.000 |
| Income level | − 0.08 | 0.11 | − 0.03 | − 0.73 | 0.468 |
| Diabetes mellitus | 0.36 | 0.09 | 0.13 | 4.06 | 0.000 |
| Hypertension | 0.16 | 0.09 | 0.05 | 1.69 | 0.092 |
| Arthritis | − 0.19 | 0.24 | − 0.05 | − 0.80 | 0.422 |
| Angina | 0.09 | 0.10 | 0.02 | 0.92 | 0.359 |
| Stroke | 0.70 | 0.17 | 0.15 | 4.06 | 0.000 |
| Heart failure | 0.02 | 0.12 | 0.01 | 0.15 | 0.879 |
| Other diseases | 0.87 | 0.18 | 0.17 | 4.96 | 0.000 |
| Do you take medications by yourself | 0.71 | 0.09 | 0.20 | 7.93 | 0.000 |
| Constipation | − 0.52 | 0.06 | − 0.18 | − 8.18 | 0.000 |
| Nausea | − 0.58 | 0.12 | − 0.18 | − 5.01 | 0.000 |
| Loss of appetite | 0.00 | 0.06 | 0.00 | − 0.09 | 0.931 |
| Muscle cramp | 0.43 | 0.09 | 0.15 | 4.80 | 0.000 |
| Swelling in the legs | 0.44 | 0.10 | 0.14 | 4.55 | 0.000 |
| Shortness of breath | − 0.48 | 0.09 | − 0.16 | − 5.58 | 0.000 |
| Instability of the legs | 0.17 | 0.12 | 0.05 | 1.45 | 0.149 |
| Dull numbness or tingling in the feet | − 0.46 | 0.08 | − 0.16 | − 5.53 | 0.000 |
| Cough | − 0.34 | 0.07 | − 0.12 | − 4.91 | 0.000 |
| Dry mouth | − 0.07 | 0.07 | − 0.03 | − 0.99 | 0.322 |
| Bone or joint pain | 0.34 | 0.20 | 0.11 | 1.65 | 0.101 |
| Chest pain | 0.26 | 0.09 | 0.07 | 2.70 | 0.007 |
| Headache | − 0.52 | 0.09 | − 0.18 | − 5.81 | 0.000 |
| Muscle soreness | 0.17 | 0.17 | 0.06 | 1.01 | 0.316 |
| Difficulty concentrating | − 0.28 | 0.06 | − 0.10 | − 5.01 | 0.000 |
| Dry skin | 0.42 | 0.07 | 0.15 | 6.35 | 0.000 |
| Feeling stressed | − 0.73 | 0.07 | − 0.24 | − 11.13 | 0.000 |
| Difficulty sleeping | 0.02 | 0.07 | 0.01 | 0.32 | 0.746 |
| Difficulty staying asleep | 0.91 | 0.15 | 0.31 | 5.89 | 0.000 |
| Feeling sad | − 0.93 | 0.10 | − 0.29 | − 9.26 | 0.000 |
| Feeling agitated or uncomfortable | 0.30 | 0.07 | 0.10 | 4.28 | 0.000 |
| Depression | 0.99 | 0.07 | 0.35 | 14.34 | 0.000 |
| Lack of libido | − 0.34 | 0.12 | − 0.12 | − 2.82 | 0.005 |
| Difficulty with sexual arousal | 0.48 | 0.10 | 0.17 | 4.81 | 0.000 |
| SEMCD score | − 0.06 | 0.02 | − 0.08 | − 3.68 | 0.000 |
| Age (year) | 0.03 | 0.00 | 0.33 | 7.52 | 0.000 |
| Length of hemodialysis session (hours) | − 0.27 | 0.10 | − 0.07 | − 2.70 | 0.007 |
| Mobility | 0.04 | 0.05 | 0.04 | 0.75 | 0.456 |
| Usual activities | 0.86 | 0.04 | 0.91 | 20.64 | 0.000 |
| Pain/discomfort | − 0.44 | 0.05 | − 0.34 | − 8.71 | 0.000 |
| Anxiety/depression | 0.20 | 0.05 | 0.16 | 3.70 | 0.000 |
| VAS Qol | − 0.01 | 0.00 | − 0.14 | − 4.74 | 0.000 |
R2 = 0.976, p < 0.001.
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale.
Significant values are in bold
Predictors of pain/discomfort
Pain and discomfort were significantly predicted by higher educational level (β = 0.6, p < 0.001), diabetes (β = 0.8, p < 0.001), and shortness of breath (β = 1.1, p < 0.001). Psychological and physical symptoms such as anxiety (β = 0.9, p < 0.001) and muscle soreness (β = − 3.4, p < 0.001) were also important contributors. Additional predictors are given in Table 10. The multiple linear regression model explained 97.6% of the variance in the pain discomfort (R2 = 0.976, p < 0.001).
Table 10.
Factors predicting pain/discomfort.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Living conditions | − 0.1 | 0.1 | 0.0 | − 0.7 | 0.480 |
| Educational level | 0.6 | 0.1 | 0.3 | 11.6 | 0.000 |
| Employment status | − 0.6 | 0.1 | − 0.2 | − 5.7 | 0.000 |
| Income level | 0.5 | 0.1 | 0.2 | 5.3 | 0.000 |
| Diabetes mellitus | 0.8 | 0.1 | 0.4 | 11.1 | 0.000 |
| Hypertension | − 0.6 | 0.1 | − 0.3 | − 9.5 | 0.000 |
| Arthritis | 0.3 | 0.1 | 0.1 | 3.0 | 0.003 |
| Angina | 0.5 | 0.1 | 0.2 | 6.3 | 0.000 |
| Stroke | − 2.1 | 0.2 | − 0.6 | − 13.3 | 0.000 |
| Heart failure | 0.0 | 0.1 | 0.0 | − 0.2 | 0.871 |
| Other diseases | − 1.6 | 0.2 | − 0.4 | − 10.0 | 0.000 |
| Do you take medications by yourself | 0.2 | 0.1 | 0.1 | 2.5 | 0.012 |
| Constipation | − 0.3 | 0.1 | − 0.2 | − 6.8 | 0.000 |
| Nausea | 0.1 | 0.1 | 0.0 | 0.8 | 0.408 |
| Diarrhea | 0.3 | 0.1 | 0.1 | 4.2 | 0.000 |
| Loss of appetite | 0.0 | 0.0 | 0.0 | − 0.4 | 0.660 |
| Muscle cramp | − 0.5 | 0.1 | − 0.2 | − 6.3 | 0.000 |
| Swelling in the legs | − 0.1 | 0.1 | 0.0 | − 1.4 | 0.172 |
| Shortness of breath | 1.1 | 0.1 | 0.5 | 14.1 | 0.000 |
| Vertigo/dizziness | − 0.8 | 0.1 | − 0.4 | − 11.2 | 0.000 |
| Instability of the legs | 0.5 | 0.1 | 0.2 | 5.4 | 0.000 |
| Dull numbness or tingling in the feet | − 0.5 | 0.1 | − 0.2 | − 6.9 | 0.000 |
| Cough | 0.2 | 0.1 | 0.1 | 3.5 | 0.001 |
| Dry mouth | 0.1 | 0.1 | 0.0 | 0.8 | 0.425 |
| Bone or joint pain | 3.4 | 0.1 | 1.5 | 26.4 | 0.000 |
| Chest pain | − 0.3 | 0.1 | − 0.1 | − 2.7 | 0.007 |
| Headache | 1.0 | 0.1 | 0.5 | 10.3 | 0.000 |
| Muscle soreness | − 3.4 | 0.2 | − 1.5 | − 20.4 | 0.000 |
| Difficulty concentrating | − 0.6 | 0.1 | − 0.3 | − 9.5 | 0.000 |
| Dry skin | 0.1 | 0.1 | 0.0 | 0.9 | 0.369 |
| Anxiety | 0.9 | 0.1 | 0.4 | 12.4 | 0.000 |
| Difficulty sleeping | − 1.0 | 0.1 | − 0.4 | − 18.9 | 0.000 |
| Difficulty staying asleep | − 0.3 | 0.1 | − 0.1 | − 2.4 | 0.019 |
| Feeling irritable and angry | − 0.1 | 0.1 | 0.0 | − 0.9 | 0.350 |
| Feeling agitated or uncomfortable | 0.5 | 0.1 | 0.2 | 8.5 | 0.000 |
| Lack of libido | 1.1 | 0.1 | 0.5 | 10.9 | 0.000 |
| Difficulty with sexual arousal | − 1.3 | 0.1 | − 0.6 | − 11.9 | 0.000 |
| Frequent urination at night (during sleep) | 0.6 | 0.0 | 0.2 | 8.0 | 0.000 |
| Age (year) | 0.0 | 0.0 | 0.3 | 6.9 | 0.000 |
| Time elapsed since receiving hemodialysis (years) | − 0.1 | 0.1 | − 0.2 | − 9.1 | 0.000 |
| Length of hemodialysis session (hours) | 1.0 | 0.0 | 0.4 | 11.0 | 0.000 |
| Mobility | − 0.3 | 0.1 | − 0.4 | − 7.2 | 0.000 |
| Self− care | 0.1 | 0.0 | 0.2 | 2.8 | 0.006 |
| Usual activities | 0.1 | 0.0 | 0.2 | 3.4 | 0.001 |
| Anxiety/depression | 0.6 | 0.0 | 0.6 | 19.7 | 0.000 |
| VAS Qol | 0.0 | 0.0 | − 0.3 | − 12.9 | 0.000 |
R2 = 0.976, p < 0.001.
Abbreviations: UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale.
Significant values are in bold
Predictors of anxiety/depression
Significant predictors of anxiety/depression included living in refugee camps (β = − 0.52, p < 0.001), having a lower level of education (β = − 0.36, p < 0.001), and being unable to manage medications independently (β = − 0.75, p < 0.001). Emotional and somatic symptoms, including stress (β = 1.48, p < 0.001) and sadness (β = 1.23, p < 0.001), were also associated. Additional predictors are listed in Table 11. The multiple linear regression model explained 91.9% of the variance in anxiety/depression (R2 = 0.919, p < 0.001).
Table 11.
Factors predicting anxiety/depression.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Place of residence | − 0.52 | 0.06 | − 0.33 | − 9.29 | 0.000 |
| Educational level | − 0.36 | 0.07 | − 0.20 | − 5.16 | 0.000 |
| Employment status | 0.03 | 0.13 | 0.01 | 0.19 | 0.850 |
| Income level | 0.26 | 0.13 | 0.11 | 1.95 | 0.052 |
| Diabetes mellitus | − 0.07 | 0.12 | -0.03 | − 0.61 | 0.543 |
| Hypertension | − 0.16 | 0.13 | − 0.06 | − 1.20 | 0.232 |
| Arthritis | − 0.93 | 0.15 | − 0.28 | − 6.14 | 0.000 |
| Angina | 0.15 | 0.12 | 0.05 | 1.28 | 0.200 |
| Stroke | − 0.43 | 0.23 | − 0.11 | − 1.85 | 0.065 |
| Heart failure | 0.07 | 0.10 | 0.03 | 0.71 | 0.476 |
| Do you take medications by yourself | − 0.75 | 0.10 | − 0.26 | − 7.24 | 0.000 |
| Constipation | 0.08 | 0.08 | 0.03 | 0.97 | 0.334 |
| Nausea | 0.29 | 0.11 | 0.11 | 2.56 | 0.011 |
| Vomiting | − 0.66 | 0.13 | − 0.19 | − 5.20 | 0.000 |
| Diarrhea | 0.41 | 0.10 | 0.17 | 3.99 | 0.000 |
| Loss of appetite | 0.07 | 0.06 | 0.03 | 1.17 | 0.243 |
| Shortness of breath | 0.47 | 0.15 | 0.19 | 3.07 | 0.002 |
| Vertigo/dizziness | 0.35 | 0.08 | 0.15 | 4.16 | 0.000 |
| Cough | 1.41 | 0.11 | 0.61 | 12.47 | 0.000 |
| Dry mouth | − 0.87 | 0.09 | − 0.37 | − 9.26 | 0.000 |
| Bone or joint pain | − 1.93 | 0.23 | − 0.80 | − 8.35 | 0.000 |
| Chest pain | − 0.11 | 0.12 | − 0.04 | − 0.92 | 0.356 |
| Headache | − 0.91 | 0.10 | − 0.39 | − 9.20 | 0.000 |
| Muscle soreness | 0.42 | 0.28 | 0.17 | 1.46 | 0.145 |
| Difficulty concentrating | 0.39 | 0.09 | 0.17 | 4.42 | 0.000 |
| Dry skin | − 0.06 | 0.07 | − 0.03 | − 0.93 | 0.353 |
| Anxiety | 0.09 | 0.11 | 0.04 | 0.81 | 0.421 |
| Feeling stressed | 1.48 | 0.13 | 0.60 | 11.44 | 0.000 |
| Difficulty sleeping | 0.68 | 0.07 | 0.29 | 9.14 | 0.000 |
| Difficulty staying asleep | 0.01 | 0.15 | 0.00 | 0.04 | 0.968 |
| Feeling irritable and angry | − 0.38 | 0.09 | − 0.16 | − 4.35 | 0.000 |
| Feeling sad | 1.23 | 0.15 | 0.48 | 8.40 | 0.000 |
| Feeling agitated or uncomfortable | − 0.64 | 0.10 | − 0.27 | − 6.64 | 0.000 |
| Depression | − 0.33 | 0.09 | − 0.14 | − 3.51 | 0.001 |
| Lack of libido | − 0.02 | 0.08 | − 0.01 | − 0.24 | 0.812 |
| Difficulty with sexual arousal | − 0.52 | 0.13 | − 0.23 | − 4.15 | 0.000 |
| Frequent urination at night (during sleep) | − 0.80 | 0.12 | − 0.31 | − 6.46 | 0.000 |
| SEMCD score | − 0.12 | 0.02 | − 0.19 | − 4.92 | 0.000 |
| Age (year) | − 0.01 | 0.00 | − 0.11 | − 2.14 | 0.033 |
| Length of hemodialysis session (hours) | 0.67 | 0.13 | 0.22 | 5.25 | 0.000 |
| Mobility | − 0.05 | 0.06 | − 0.06 | − 0.88 | 0.379 |
| Self− care | 0.80 | 0.06 | 0.98 | 13.02 | 0.000 |
| Usual activities | − 0.66 | 0.05 | − 0.86 | − 12.46 | 0.000 |
| Pain/discomfort | 1.26 | 0.05 | 1.20 | 22.86 | 0.000 |
| VAS Qol | 0.02 | 0.00 | 0.27 | 6.18 | 0.000 |
R2 = 0.919, p < 0.001.
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale.
Significant values are in bold
Predictors of the EQ-5D-5L index value and VAS score
As shown in Table 12, higher EQ-5D-5L index scores were significantly associated with higher income (β = 0.25, p < 0.001) and the absence of arthritis (β = − 0.18, p = 0.001), as were fewer symptoms such as pain (β = − 0.26, p < 0.001) and bone/joint issues (β = − 0.22, p < 0.001). The positive contributors also included the absence of agitation (β = − 0.08, p < 0.001) and better skin conditions (β = 0.10, p < 0.001). Additional predictors are detailed in Table 12. The multiple linear regression model explained 85.7% of the variance in the EQ-5D-5L index scores (R2 = 0.857, p < 0.001).
Table 12.
Factors predicting the EQ-5D-5L index score.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Employment status | − 0.16 | 0.04 | − 0.24 | − 4.06 | < 0.001 |
| Income level | 0.25 | 0.04 | 0.39 | 5.91 | < 0.001 |
| Diabetes mellitus | 0.05 | 0.02 | 0.08 | 2.07 | 0.039 |
| Hypertension | − 0.04 | 0.04 | − 0.06 | − 1.03 | 0.303 |
| Arthritis | − 0.18 | 0.05 | − 0.21 | − 3.49 | 0.001 |
| Angina | − 0.01 | 0.04 | − 0.01 | − 0.29 | 0.775 |
| Stroke | 0.13 | 0.04 | 0.13 | 3.57 | < 0.001 |
| Heart failure | 0.06 | 0.03 | 0.08 | 1.74 | 0.083 |
| Constipation | 0.00 | 0.02 | 0.00 | 0.09 | 0.927 |
| Nausea | 0.09 | 0.04 | 0.13 | 2.37 | 0.019 |
| Appetite | − 0.09 | 0.02 | − 0.15 | − 4.06 | < 0.001 |
| Muscle | − 0.06 | 0.03 | − 0.09 | − 1.65 | 0.100 |
| Swelling | 0.17 | 0.03 | 0.27 | 6.07 | < 0.001 |
| Instability | 0.09 | 0.03 | 0.14 | 2.98 | 0.003 |
| Energy | 0.03 | 0.03 | 0.04 | 1.00 | 0.318 |
| Dry | 0.01 | 0.02 | 0.02 | 0.58 | 0.562 |
| Bone | − 0.22 | 0.05 | − 0.35 | − 4.51 | < 0.001 |
| Pain | − 0.26 | 0.03 | − 0.36 | − 9.33 | < 0.001 |
| Headache | 0.00 | 0.03 | 0.00 | 0.06 | 0.949 |
| Soreness | − 0.12 | 0.05 | − 0.19 | − 2.40 | 0.017 |
| Concentrating | − 0.05 | 0.02 | − 0.08 | − 2.48 | 0.014 |
| Skin | 0.10 | 0.02 | 0.17 | 4.60 | < 0.001 |
| Stressed | − 0.02 | 0.03 | − 0.03 | − 0.71 | 0.479 |
| Staying asleep | − 0.08 | 0.04 | − 0.13 | − 2.02 | 0.044 |
| Agitated | − 0.08 | 0.02 | − 0.13 | − 3.59 | < 0.001 |
| Libido | 0.16 | 0.04 | 0.27 | 4.25 | < 0.001 |
| Sexual | 0.05 | 0.03 | 0.09 | 1.49 | 0.138 |
| Number of hemodialysis sessions per week | − 0.13 | 0.04 | − 0.10 | − 2.95 | 0.003 |
| SEMCD score | 0.01 | 0.01 | 0.06 | 1.45 | 0.149 |
| VAS Qol | 0.00 | 0.00 | 0.25 | 5.16 | < 0.001 |
R2 = 0.857, p < 0.001.
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale.
For the VAS QoL score (Table 13), higher values were significantly predictive of being female (β = 9.60, p = 0.003), living in urban areas (β = 5.67, p < 0.001), and having received a kidney transplant (β = 26.01, p < 0.001). Greater scores were also associated with fewer physical symptoms, such as muscle soreness (β = − 35.17, p < 0.001) and pain/discomfort (β = − 13.25, p < 0.001), as well as younger age (β = − 0.53, p = 0.036). A higher SEMCD score also predicted better QoL (β = 1.22, p = 0.046). Other predictors are presented in Table 13. The multiple linear regression model explained 97.1% of the variance in the EQ-VAS scores (R2 = 0.971, p < 0.001).
Table 13.
Factors predicting VAS QoL.
| Variable | UC | SE | SC | t | p value |
|---|---|---|---|---|---|
| Sex | 9.60 | 3.21 | 0.26 | 2.99 | 0.003 |
| BMI categories | − 4.15 | 4.39 | − 0.11 | − 0.95 | 0.345 |
| Place of residence | 5.67 | 1.12 | 0.23 | 5.06 | 0.000 |
| Educational level | 4.84 | 1.10 | 0.17 | 4.41 | 0.000 |
| Employment status | − 4.50 | 5.50 | − 0.11 | − 0.82 | 0.414 |
| Income level | − 8.18 | 4.01 | − 0.21 | − 2.04 | 0.042 |
| Received a kidney transplantation | 26.01 | 6.90 | 0.38 | 3.77 | 0.000 |
| Diabetes mellitus | − 7.86 | 4.47 | − 0.21 | − 1.76 | 0.080 |
| Hypertension | − 4.01 | 1.84 | − 0.10 | − 2.18 | 0.030 |
| Arthritis | 28.46 | 3.24 | 0.54 | 8.79 | 0.000 |
| Angina | 18.81 | 2.05 | 0.35 | 9.20 | 0.000 |
| Stroke | − 15.21 | 4.07 | − 0.25 | − 3.74 | 0.000 |
| Heart failure | − 8.67 | 2.49 | − 0.21 | − 3.48 | 0.001 |
| Other diseases | 17.86 | 13.06 | 0.26 | 1.37 | 0.173 |
| Do you take medications by yourself | − 4.75 | 7.06 | − 0.10 | − 0.67 | 0.502 |
| Smoker | − 0.24 | 1.48 | − 0.01 | − 0.16 | 0.872 |
| Constipation | − 3.39 | 2.28 | − 0.09 | − 1.49 | 0.138 |
| Nausea | 10.01 | 3.96 | 0.24 | 2.53 | 0.012 |
| Diarrhea | 6.24 | 2.67 | 0.16 | 2.34 | 0.020 |
| Muscle cramp | 8.19 | 2.41 | 0.21 | 3.39 | 0.001 |
| Swelling in the legs | − 6.42 | 2.69 | − 0.16 | − 2.39 | 0.018 |
| Shortness of breath | 13.42 | 1.74 | 0.35 | 7.73 | 0.000 |
| Instability of the legs | − 20.65 | 4.97 | − 0.50 | − 4.15 | 0.000 |
| Dull numbness or tingling in the feet | 9.38 | 4.25 | 0.25 | 2.21 | 0.028 |
| Feeling tired or losing energy | − 17.39 | 4.82 | − 0.35 | − 3.61 | 0.000 |
| Dry mouth | − 0.48 | 3.24 | − 0.01 | − 0.15 | 0.883 |
| Bone or joint pain | 25.33 | 6.97 | 0.66 | 3.64 | 0.000 |
| Chest pain | 19.75 | 3.84 | 0.44 | 5.15 | 0.000 |
| Headache | 8.14 | 2.26 | 0.22 | 3.61 | 0.000 |
| Muscle soreness | − 35.17 | 4.68 | − 0.93 | − 7.51 | 0.000 |
| Difficulty concentrating | − 4.37 | 1.76 | − 0.12 | − 2.48 | 0.014 |
| Dry skin | − 2.30 | 2.10 | − 0.06 | − 1.10 | 0.274 |
| Itching | − 9.82 | 1.65 | − 0.27 | − 5.97 | 0.000 |
| Difficulty sleeping | 3.75 | 3.63 | 0.10 | 1.03 | 0.303 |
| Difficulty staying asleep | − 13.82 | 4.77 | − 0.37 | − 2.90 | 0.004 |
| Feeling agitated or uncomfortable | − 0.66 | 1.31 | − 0.02 | − 0.51 | 0.614 |
| Depression | 4.96 | 1.34 | 0.13 | 3.71 | 0.000 |
| Difficulty with sexual arousal | − 8.07 | 1.47 | − 0.22 | − 5.51 | 0.000 |
| SEMCD score | 1.22 | 0.61 | 0.12 | 2.01 | 0.046 |
| Age (year) | − 0.53 | 0.25 | − 0.38 | − 2.11 | 0.036 |
| Time elapsed since receiving hemodialysis (years) | − 0.32 | 0.15 | − 0.08 | − 2.14 | 0.033 |
| Number of hemodialysis sessions per week | − 14.89 | 3.86 | − 0.19 | − 3.86 | 0.000 |
| Mobility | − 0.38 | 2.78 | − 0.03 | − 0.14 | 0.893 |
| Self-care | − 3.07 | 1.63 | − 0.24 | − 1.88 | 0.061 |
| Usual activities | 2.99 | 1.50 | 0.25 | 1.99 | 0.047 |
| Pain/discomfort | − 13.25 | 1.28 | − 0.80 | − 10.39 | 0.000 |
| Anxiety/depression | 6.87 | 1.51 | 0.43 | 4.56 | 0.000 |
R2 = 0.971, p < 0.001.
UC, Unstandardized Coefficient; SE, Standard Error; SC, Standardized Coefficient; SEMCD, Self-Efficacy for Managing Chronic Disease; EQ-VAS, EuroQol Visual Analogue Scale; BMI, Body Mass Index.
Significant values are in bold
Discussion
This study aimed to assess how physical and psychological symptoms affect self-efficacy and quality of life among patients undergoing hemodialysis in Palestine. Our findings demonstrate that higher education, healthy weight, and family support positively predict self-efficacy and quality of life, whereas comorbidities such as diabetes and depression, as well as symptom burden, pain, and sleep problems, negatively impact these outcomes. These results contribute to the growing literature emphasizing the role of both clinical and psychosocial factors in the wellbeing of hemodialysis patients in low-resource settings.
Associations between healthy weight, higher education, and social support and higher self-efficacy
Patients with higher education, a healthy weight, and good social support were more confident in controlling their condition. Patients with high educational levels exhibit self-efficacy, which leads to improved quality of life and better control of their health conditions. This could be interpreted from the perspective that education helps patients understand their health status and treatment procedures, enhancing their compliance with therapy17,19. Higher education may improve patients’ understanding of dialysis and their chronic condition, enabling better adherence and confidence in self-care. This suggests the need to tailor educational interventions for patients with lower literacy levels. Social support helps in stress management and promotes improved quality of life. Family members of chronic patients, including those on hemodialysis, can offer psychosocial support to improve quality of life and reduce stress26,27. This finding is consistent with those of previous studies demonstrating that social support and education have positive effects on health outcomes in patients undergoing hemodialysis and other conditions10,17,28–30.
In addition to education and social support, maintaining a healthy weight was also associated with higher self-efficacy in our study. This relationship may reflect patients’ engagement in positive health behaviors, such as diet management and physical activity, which require a level of self-regulation and confidence in managing their condition. A healthy weight may thus be both a consequence and an indicator of self-efficacy. This finding is consistent with prior studies reporting that patients with healthier lifestyles tend to exhibit higher levels of self-efficacy, which in turn supports better disease management and overall quality of life31.
Healthcare providers should tailor educational materials and sessions on the basis of educational and social support levels. Increased family involvement can increase patients’ confidence in managing their health conditions. Future research should explore structured educational programs to improve self-efficacy and promote weight management among patients undergoing hemodialysis.
Associations between comorbid diabetes mellitus or depression or more hemodialysis sessions and low self-efficacy
The presence of diabetes and depression was associated with lower self-efficacy, which aligns with previous studies indicating that self-care is implicated in patients with psychiatric comorbidities15,29,32. Depression is a known barrier to effective chronic disease care because of its effects on motivation and cognition33. Patients who had frequent and lengthy dialysis treatments reported reduced self-efficacy due to increased physical and emotional stress, similar to the findings of previous studies34,35. Long sessions add to treatment fatigue and might cause feelings of helplessness and reliance33. Switching patients to peritoneal dialysis when clinically appropriate can enhance their sense of control and improve self-efficacy36, whereas research on the impact of session length on patient outcomes is crucial to produce effective and protective dialysis prescriptions that address both physical and psychological well-being.
Furthermore, frequent and extended dialysis sessions are associated with greater fatigue and decreased self-efficacy11,29,32.
This highlights the importance of managing both the mental and medical conditions of patients undergoing hemodialysis in Palestine. Healthcare providers should adopt a holistic approach and include mental health and patient support services to increase self-efficacy among patients undergoing hemodialysis.
Associations between symptom burden and the impact on self-efficacy and quality of life
This study revealed that symptoms such as constipation, pain, difficulty sleeping, and chest pain can predict low self-efficacy and poor quality of life in patients undergoing hemodialysis. Symptoms such as constipation, chest pain, and difficulty sleeping significantly predicted lower self-efficacy and quality of life in our sample. These results are consistent with those of Son et al. and Agarwal et al., who reported that multiple concurrent symptoms reduce coping ability and functioning37,38. Our findings emphasize that not only symptom presence but also perceived discomfort negatively affects self-management. Individualized symptom management strategies are therefore essential, particularly in resource-limited settings.
The negative effects of symptoms on quality of life and the increased psychological stress they cause have been reported in various settings in many studies37–41. Multiple health impacts patients experience compound physical and mental changes, worsening their overall condition.
A patient-centered approach may help in symptom management, and future research to further explore the effects of multidisciplinary interventions on decreasing symptom burden is needed.
Association between low self-efficacy and mobility problems
Patients undergoing hemodialysis with mobility-limiting impairments, such as numbness, muscle cramps, and leg planting, experience a significant decrease in self-efficacy, a finding that is consistent with those of previous studies11,32,42,43. These findings suggest that functional disability poses a significant barrier to self-care among patients with chronic diseases, as it hinders their ability to perform routine daily activities.
This study suggests that restoring possession can improve disease management, emphasizing the importance of strengthening exercise in physical rehabilitation programs for patients undergoing hemodialysis. Strengthening mobility through exercise-focused rehabilitation programs is essential, as it supports independence, reduces treatment-related fatigue, and facilitates active participation in self-care. Future research could explore ways to improve mobility and self-efficacy through physical therapy and assistive devices.
Association between low self-efficacy and older age
This study revealed that older haemodialysis patients demonstrated lower self-efficacy than younger patients did, which is consistent with previous research11,32,42,43. This may be attributed to age-related declines in physical and cognitive function, as well as the presence of multiple comorbidities. These findings suggest that older adults may face greater challenges in managing complex treatments such as hemodialysis and may have lower adherence to treatment regimens.
The study emphasized the need for tailored interventions for the elderly population, including special instructional materials and self-management support. Future research should assess the effectiveness of these interventions and explore potential techniques to address age-related decreases in self-efficacy in older patients.
Association between challenges performing usual activities and low self-efficacy
This study revealed that limited engagement in daily activities significantly lowers the self-efficacy of hemodialysis patients. This decline in self-efficacy can lead to poor health outcomes, as indicated by previous studies10,16,30,32,33,38,40. The extent to which routine activities are disrupted by limitations not only affects patients’ health status but also contributes to feelings of despair and further decreases in self-efficacy.
Improved capacity and regular activity participation can increase self-efficacy in patients undergoing hemodialysis. Healthcare professionals should incorporate functional restoration and assessments into everyday practice. Customized help and effective plans can help patients control their health. Future research should evaluate rehabilitation approaches and assistive devices.
Association between self-care difficulties and their relationship with self-efficacy
The challenges faced by hemodialysis patients in self-care are closely linked to low self-efficacy, which is influenced by factors such as physical limitations, mental health issues, and a lack of supportive networks1,15,19,27,34,37–39,44–46. These difficulties can hinder their ability to manage chronic conditions and perform self-care activities effectively. This emphasizes the importance of healthcare providers in enhancing self-care practices, including patient education, providing assistive devices, and enhancing confidence in self-care capabilities.
Association between pain and discomfort and self-efficacy
Pain and discomfort were significant predictors of lower self-efficacy in our study. This finding is supported by a body of literature that highlights the negative impact of pain on self-management abilities32,43,47. Persistent pain can be debilitating, reducing patients’ ability to engage in self-care activities and manage their treatment effectively.
Effective pain management is crucial for patients’ self-efficacy, and clinicians should prioritize pain assessment and management as integral components of care, using personalized strategies.
Future research should focus on developing integrated protocols, exploring their impact on self-efficacy and quality of life, and combining pain management with supportive interventions.
Association between anxiety and depression as predictors of lower self-efficacy
Anxiety and depression were found to significantly predict lower self-efficacy among patients. This aligns with substantial evidence indicating that mental health issues are closely linked to diminished self-management abilities and overall health outcomes11,32,42,48. The presence of anxiety and depression can exacerbate the challenges of managing chronic diseases, further undermining patients’ confidence in their ability to cope with their condition.
The study emphasized the importance of integrated mental health support in chronic disease management, recommended that healthcare providers address mental health concerns alongside physical health issues, and recommended the use of counselling, cognitive‒behavioral therapy, and stress management techniques. Further research could enhance targeted treatment approaches.
Association between overall health rating and self-efficacy
The study revealed that higher overall health scores are correlated with greater self-efficacy, similar to studies that indicated a positive relationship between health status and self-management ability15,32,33,37,38,40–43,45. Enhancing overall health may lead to increased self-efficacy, highlighting the potential of interventions that address both physical and mental well-being to improve self-management. Future studies should investigate the effectiveness of such comprehensive programs and identify which specific health factors are most impactful for targeted intervention.
Predictors of quality of life: Clinical and functional insights
The regression models (Tables 12 and 13) identified several clinical and demographic predictors of QoL among patients undergoing hemodialysis. Higher EQ-5D index scores were significantly associated with higher income, the absence of arthritis, lower pain levels, the absence of agitation, and better skin conditions. These results emphasize the critical role of both physical symptoms and comorbidities in shaping patients’ perceived health status.
For the EQ-VAS scores, female sex, urban residence, kidney transplant history, and higher self-efficacy scores were linked to better perceived health. These findings suggest that psychosocial and contextual factors, including access to resources and perceived control, may also influence how patients assess their own health. The strong association between self-efficacy and QoL further supports the importance of integrated care models that address both symptom relief and patient empowerment. These insights reinforce the need for individualized care plans that address the broader determinants of health in this population.
Recommendations and limitations
This study sheds light on how physical, psychological, and mental health problems affect self-efficacy and quality of life among Palestinian haemodialysis patients. The findings identify critical areas for change and emphasize the importance of comprehensive patient care. The findings highlight the need to integrate psychosocial support and tailored education in dialysis care programs, which may improve self-efficacy and overall health outcomes.
From a clinical perspective, these results emphasize the need for a multidimensional approach in hemodialysis care—integrating symptom screening, psychological assessment, and social support services. Given the clear association between self-efficacy and health-related QoL, incorporating self-management training into routine dialysis sessions may enhance outcomes. Furthermore, policy makers should consider embedding mental health services within renal care programs, especially in low-resource settings such as Palestine.
Although this study identified several clinical and demographic factors associated with self-efficacy in hemodialysis patients, it is important to acknowledge that other relevant psychological and contextual variables have not been explored in depth. For example, factors such as patient beliefs, coping strategies, cultural norms, health literacy, and the availability of social support systems may also significantly shape patients’ perceptions of their ability to manage chronic illness. Future research is encouraged to integrate these psychosocial dimensions for a more comprehensive understanding of self-efficacy in the dialysis population.
Although this study has valuable insights, it has several limitations. First, it was conducted in a cross-sectional design, limiting the ability to establish causal relationships. Second, the data were self-reported, which introduces the possibility of recall bias, which can affect the reliability and accuracy of the study. Furthermore, while this study provides useful insights into the Palestinian setting, its findings may not be applicable to communities with various sociodemographic and healthcare features. Finally, while adjustments were made for key demographic and clinical variables, unmeasured confounders may still have influenced the results. Despite its limitations, this study presents significant data that can guide multidisciplinary healthcare interventions to improve self-efficacy and QoL. Our findings contribute to a deeper understanding of symptom burden and psychosocial dynamics in the context of dialysis care, particularly in low- to middle-income countries, where patient-centered strategies are urgently needed.
Conclusions
This research provides insight into how symptom burden affects self-efficacy and overall quality of life among patients undergoing hemodialysis in Palestine. The findings showed that greater symptom burden was significantly associated with lower self-efficacy and poorer QoL. Factors such as pain, emotional distress, and functional limitations were among the strongest predictors. These results underscore the need for integrated interventions that target symptom relief while enhancing patients’ self-management capacity. Future studies should consider longitudinal or interventional designs to test the effectiveness of symptom-based self-management programs.
Acknowledgements
We express gratitude to An-Najah National University and its faculty for their provision of essential resources and an enabling research environment. We extend special thanks to An-Najah National University Hospital and Al-Hussein Government Hospital for their invaluable assistance and support.
Abbreviations
- ANOVA
Analysis of variance
- ESRD
End-stage renal disease
- EQ-5D-5L
EuroQol-5 Dimension
- EQ-VAS
EQ visual analogue scale
- QoL
Health related quality of life
- SEMCD
Self-efficacy for managing chronic disease
- SD
Standard deviation
- SPSS
Statistical package for social sciences
Author contributions
SHZ and SWA contributed to the conception of the study. They also planned the study, designed the methodology, and critically reviewed and finalized the manuscript. ASA was responsible for data collection and analysis. ASA and DA drafted the initial manuscript under the supervision of SHZ. All authors reviewed, revised, and approved the final version of the manuscript for submission.
Funding
Not available.
Data availability
The datasets used and/or analysed during the current study are available from the corresponding author upon request.
Declarations
Competing interests
The authors declare no competing interests.
Ethics approval and consent to participate
The study received approval from the Institutional Review Board Committee of An-Najah National University [IRB Reference #: Mas. Oct. 2021/37]. Written informed consent was obtained from all participants prior to their inclusion in the study. The consent process included providing both written and verbal explanations of the study objectives, procedures, and potential implications. Participants were assured that their information would be kept strictly confidential and used only for scientific purposes. They were informed of their full right to refuse participation or to withdraw from the study at any stage without providing reasons and without any harm or consequences. Participants were also given the opportunity to ask questions before agreeing to participate, ensuring that their decision was fully voluntary and based on adequate understanding. Permissions were granted from the hospitals involved. All methodologies adhered to ethical standards set by institutional and national research committees, following the principles outlined in the 1964 Helsinki Declaration and its subsequent revisions or equivalent ethical guidelines.
Footnotes
Publisher’s note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Contributor Information
Samah W. Al-Jabi, Email: samahjabi@yahoo.com
Sa’ed H. Zyoud, Email: saedzyoud@yahoo.com
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Data Availability Statement
The datasets used and/or analysed during the current study are available from the corresponding author upon request.