Abstract
Objective
Patients with end-stage renal disease (ESRD) are at an increased risk for emotional issues, with depression being the most prevalent psychological concern, significantly impacting their quality of life. This study aimed to explore the mediating effect of psychological resilience on the relationship between depression and quality of life in maintenance hemodialysis (MHD) patients.
Methods
This cross-sectional study aimed to explore the mediating effect of psychological resilience on the relationship between depression and quality of life in MHD patients in Baoding, China. Conducted from January 2024 to July 2024, the study involved a questionnaire survey of 215 MHD patients across five hospitals in Baoding. Data were collected using General information questionnaire, Hemodialysis Patient Depression Scale, Psychological Resilience Scale, and Quality of Life Scale, and structural equation modeling using AMOS 21.0 was employed to analyze the mediating effect.
Results
The scores for depression, psychological resilience, and quality of life in these MHD patients were 9.37±4.6, 30.58±6.1, and 59.48±9.3, respectively. Depression had a negative correlation with quality of life, while psychological resilience had a positive correlation with quality of life (with correlation coefficients of −0.453 and 0.578, respectively, all P<0.01). Psychological resilience played a mediating role in the relationship between depression and quality of life (β=−0.13, P<0.05), with the mediating effect analysis showing a significant indirect effect of depression on quality of life. The direct and indirect effects of depression on quality of life were −0.34 and −0.13, respectively, with a total effect of −0.47. The mediating effect accounted for 27.7% of the total effect. Interpretation: PHQ-9 scores range from 0 to 27, with higher scores indicating more severe depressive symptoms. CD-RISC scores range from 0 to 100, with higher scores reflecting greater psychological resilience. SF-12 scores range from 0 to 100, with higher scores indicating a better quality of life.
Conclusion
Depression, psychological resilience, and quality of life in MHD patients were at a moderately low level. Depression in MHD patients can indirectly affect their quality of life through psychological resilience, suggesting that healthcare professionals should take measures to reduce depression levels, enhance psychological resilience, and ultimately improve the quality of life for these patients. Psychological resilience was identified as a significant mediator in this relationship, highlighting its potential as a target for interventions aimed at improving the mental well-being and quality of life of MHD patients. These results underscore the importance of integrating psychological support into the care of MHD patients.
Keywords: psychological resilience, depression, quality of life, hemodialysis
Introduction
Maintenance hemodialysis (MHD) serves as a crucial alternative therapy for patients with end-stage renal disease (ESRD), playing a vital role in slowing down disease progression and extending patient life.1 According to data from the national blood dialysis case registration system, the number of patients in China undergoing MHD treatment increased from 23.5 million in 2011 to 44.7 million in 2016, representing a 90.2% increase over five years.2 However, long-term MHD treatment can lead to physical discomfort such as pain, sleep disorders, and decreased appetite.3 In addition, the financial burden on families also increases with prolonged treatment, leading to a decrease in the quality of life and adverse psychological effects for patients, with depression being a common complication among MHD patients.4–6
Maintenance hemodialysis (MHD) is associated with a range of psychiatric comorbidities, including anxiety. A systematic review and meta-analysis by Huang et al (2021) reported that the prevalence of anxiety disorders among MHD patients is significantly higher than in the general population, with a pooled prevalence of 19% for anxiety disorders and 43% for elevated anxiety symptoms.7 This highlights the importance of considering anxiety in conjunction with depression when evaluating the mental health of MHD patients.
Much research confirms a high prevalence of depression and anxiety among patients with MHD. It is estimated that 23.7% of patients with MHD have depression. Additionally, MHD patients on dialysis are more likely to develop depression (34.5%) compared with patients not on dialysis (13.3%).8 A meta-analysis also showed that the presence of depressive symptoms was a significant predictor of mortality in dialysis patients.9
Globally, the prevalence of depression among MHD patients varies significantly, with rates ranging from 20% to 47%.10 A recent study conducted in Hodeida City, Yemen, reported a prevalence of 63%, highlighting the significant impact of depression on the quality of life of MHD patients.11 This prevalence is lower than the prevalence reported in China (73.8%)12 but higher than that reported in Jordan (48.5%),13 where both studies utilized the same scale. These variations underscore the need for a deeper understanding of the factors contributing to depression and its impact on quality of life(QoL) among MHD patients worldwide.
Research has reported a depression prevalence rate of 21.7% to 55.1% among MHD patients in China.14 A meta-analysis revealed that in China, the prevalence of depression among MHD patients over the past decade ranges from 33.8% to 46.0%.15 While there have been no studies for direct comparison during the same period, when compared to the global and domestic overall rates of depression among MHD patients of 20%-47% and 21.7% to 55.1% respectively, it indirectly suggests that the prevalence of depression among MHD patients in China has been relatively high in the past 10 years.10 This could be attributed to the increasing number of ESRD patients in the country, leading to a corresponding rise in the number of patients receiving MHD treatment.16
Psychological resilience is considered a potential protective factor in reducing levels of depression.17 It is a good coping ability when faced with adversity, and also a self-protective potential.18 Good psychological resilience can improve depressive emotions, alleviate the adverse effects of negative emotions. In addition, research has also shown that psychological resilience can effectively alleviate the impact of physical problems such as poor sleep quality on mental health. Currently, there is a lack of research on the relationship between these three factors.19
This study aims to investigate the current status of depression, psychological resilience, and quality of life in MHD patients. It will analyze the mediating effect of psychological resilience on the relationship between depression and quality of life. The findings of this study will provide important insights and guidance for improving the quality of life for these patients.
Methods
Study Design and Participants
Convenient sampling was used to select 215 MHD patients treated at Baoding five hospitals (two tertiary hospitals, two secondary hospitals, and one privately-owned hemodialysis center) from January 2024 to July 2024. All patients included in the study received a formalized psychiatric diagnosis by a psychiatrist before their inclusion in the study. Inclusion criteria were: 1) receiving hemodialysis treatment for ≥3 months; 2) age ≥18 years; 3) normal cognitive, communication, and understanding abilities; 4) informed consent and voluntary participation in the study. Exclusion criteria were: 1) concurrent peritoneal dialysis; 2) patients with other serious illnesses or acute diseases (defined as conditions that are life-threatening or significantly impact the patient’s ability to participate in the study due to their severity or acute nature, such as severe cardiac events, recent stroke, or active cancer treatment);20 3) individuals with hearing or visual impairments, or severe psychological cognitive disruptions that hinder participation in the study.
According to Kendall’s rough sample size estimation algorithm,21 the sample size should be 5–10 times the number of independent variables. This study includes general information on 10 items, the Depression Scale for hemodialysis Patients on 1 dimension, the Psychological Resilience Scale on 3 dimensions, and the Quality of Life Scale on 2 dimensions, totaling 16 independent variables. The calculated total sample size is 80–160 cases. Taking into account a 15% dropout rate, the sample size is 92–184 cases. Ultimately, this study includes a total of 215 participants. The study employed a cross-sectional design to assess the relationship between depression, psychological resilience, and quality of life in MHD patients. This design was chosen for its efficiency in capturing the prevalence of depressive symptoms and their impact on quality of life within a short period. The study has been approved by the Ethics Committee of Baoding No.1 Central Hospital (Ethics number: 2023052),) and adhered strictly to the guidelines and principles outlined in the Declaration of Helsinki. The participants were informed that the data will be anonymized. To protect participants’ privacy and confidentiality, data were anonymized, and questionnaires and data storage were secured on a password-protected server.22
Study Tools
General Information Questionnaire
Designed by the researcher according to the research objectives and significance, this questionnaire included demographic data such as age, gender, marital status, education level, frequency of dialysis, complications, payment methods, average monthly household income, hemodialysis session, and hemodialysis access.
Patient Health Questionnaire (PHQ-9)
The Patient Health Questionnaire-9 (PHQ-9) is a health questionnaire developed by American psychiatrist Spitze in the Diagnostic and Statistical Manual of Mental Disorders (DSM-V) to screen and assess the severity of depressive symptoms in patients over the past 2 decades.23 In 2009, Chinese scholars Bian Cuidong and others translated and validated the questionnaire, with a Cronbach’s α coefficient of 0.833, content validity of 0.934, and split-half reliability of 0.732 for the Chinese version of the scale. This study used the questionnaire to assess depressive symptoms in the research subjects, which includes 9 items such as loss of interest, low mood, sleep disturbances, fatigue, appetite changes, feelings of worthlessness, difficulty concentrating, psychomotor retardation, and suicidal thoughts. Each item is scored on a 4-point scale, with a total score ranging from 0 to 27. A score of 5 is considered the threshold for depressive symptoms, while a score of 10 indicates a tendency towards depression. Scores equal to or greater than 5 suggest the presence of depressive symptoms, with scores of 5–9 indicating mild depression, 10–14 indicating moderate depression, 15–19 indicating moderately severe depression, and 20–27 indicating severe depression. In this study, the Cronbach’s α coefficient for this scale was 0.755.
Connor-Davidson Resilience Scale (CD-RISC)
Connor-Davidson Resilience Scale (CD-RISC): It utilizes a Likert 5-point scaling from 0 (“Not true at all”) to 4 (“True nearly all the time”), with a scoring method that totals 100 points. The scores are positively correlated with levels of psychological resilience; scores below 60 indicate poor psychological resilience, scores between 61–69 indicate average psychological resilience, scores between 70–79 indicate good psychological resilience, and scores of 80 or higher indicate excellent psychological resilience. The CD-RISC consists of 3 dimensions (self-reliance, optimism, resilience) with a total of 25 items.24 These factors are derived from the scale’s items, which are scored and categorized accordingly. The reference for this categorization can be found in the original publication by Connor and Davidson, where they describe the development of the scale and its psychometric properties.25 Besides, A study confirmed that the Connor-Davidson Resilience Scale (CD-RISC) has been validated in various populations, including those with chronic illnesses.26 The reliability of the CD-RISC in the study was assessed using Cronbach’s α, which was found to be 0.873.
SF-12 Quality of Life Scale
The SF-12 is a simplified version of the Health Survey (SF-36) developed by the Boston Medical Center in the United States.27 It is used to assess an individual’s physical and mental health, consisting of a total of 12 items that cover both the physical health aspect and the mental health aspect, across 2 dimensions. Scores for each dimension need to be converted to standard scores, with scores ranging from 0 to 100. The total score is obtained by adding the scores of the 2 dimensions together, with higher scores indicating a better quality of life. This scale has been widely used in Chinese populations,28 with a Cronbach’s α coefficient of 0.72.
Data Collection Methods
The researcher utilized uniform instructions to clearly explain the purpose and contents of the investigation to the participants. After obtaining consent, one-on-one interviews were conducted, recording information truthfully and objectively. Following the completion of the survey, timely checks were conducted to ensure the completeness and accuracy of the data. A total of 234 questionnaires were distributed for this study, with 215 valid responses received, resulting in an effective response rate of 91.88%. Ultimately, a total of 215 samples were included in the study.
Statistical Analysis
This study utilized SPSS 26.0 for statistical analysis, employing x ± s to describe metric data that followed a normal distribution. Group comparisons were made using t-tests, while multiple group comparisons utilized one-way analysis of variance. Pearson correlation analysis was used to explore the relationship between depression, psychological resilience, and quality of life. The AMOS 21.0 was employed for mediation analysis, with statistical significance indicated by P < 0.05.
Results
Univariate Analysis of the Quality of Life in These MHD Patients with Different Characteristics
Univariate analysis of the quality of life in these MHD patients with different characteristics Among 215 patients with MHD, 55.4% were male and 44.6% were female. 60% of these patients underwent HD three times a week, while 40% twice a week. 55.4% of these patients had more than 3 complications, and 46.9% of them had a monthly household income of less than 3000 yuan RMB. Our study found significant differences in quality of life of these MHD patients among different genders, hemodialysis session, complications, and average monthly household income (p<0.05), while there were no significant differences in age, marital status, education level, dialysis frequency, hemodialysis access, and payment methods (p>0.05). Please refer to Table 1 for specific details.
Table 1.
Quality of Life Comparison Among Maintenance Hemodialysis Patients
| Variables | Total (n = 215) | Mean±SD | P |
|---|---|---|---|
| Gender, n(%) | |||
| Male | 119 (55.35) | 58.12± 8.94 | 0.009 |
| Female | 96 (44.65) | 61.53± 10.04 | |
| Age (Years), n(%) | 0.786 | ||
| <45 | 95 (44.19) | 60.07± 9.67 | |
| 45–60 | 81 (37.67) | 59.07± 9.26 | |
| >60 | 39 (18.14) | 59.78± 10.18 | 0.689 |
| Marital status, n(%) | |||
| Married | 146 (67.91) | 59.82± 9.34 | |
| Divorce or widowhood | 69 (32.09) | 59.26± 10.01 | |
| Education Level,(%) | 0.685 | ||
| Junior high school and below | 88 (40.93) | 60.06± 10.02 | |
| High school/vocational school, | 91 (42.33) | 58.98± 9.08 | |
| College and above | 36 (16.74) | 60.29± 90.86 | 0.671 |
| Hemodialysis frequency/Week, n(%) | |||
| Three times | 129 (60.00) | 59.41± 9.30 | |
| Twice | 86 (40.00) | 59.98± 10.03 | |
| Hemodialysis session/Years, n(%) | <0.001 | ||
| <1 | 73 (33.95) | 61.78± 9.70 | |
| 1–3 | 99 (46.05) | 60.85± 9.54 | |
| >3 | 43 (20.00) | 53.23± 6.32 | |
| Hemodialysis access, n(%) | 0.155 | ||
| Autogenous arteriovenous fistula | 141 (65.58) | 60.46± 9.60 | |
| Semi-permanent hemodialysis catheter | 66 (30.70) | 57.75± 9.00 | |
| Arteriovenous graft | 8 (3.72) | 60.90± 12.59 | <0.001 |
| Complications, n(%) | |||
| ≤3 | 96 (44.65) | 63.99± 9.30 | |
| >3 | 119 (55.35) | 56.13± 8.31 | |
| Payment methods, n(%) | 0.852 | ||
| Health insurance | 100 (46.51) | 59.24± 9.53 | |
| New Rural Cooperative Medical Care | 103 (47.91) | 60.00± 9.87 | |
| Others | 12 (5.58) | 59.92± 7.76 | |
| Average monthly household income (Renminbi), n(%) | <0.001 | ||
| <3000 | 101 (46.98) | 56.73± 9.06 | |
| 3000–5000 | 71 (33.02) | 61.92± 9.84 | |
| >5000 | 42 (19.53) | 65.69± 8.56 |
Notes: Complications: the number of comorbid health issues, including but not limited to anemia, bone disease, and cardiovascular diseases, which are common in patients with end-stage renal disease undergoing hemodialysis. Bold values indicate significant differences. (P<0.05).
The Levels of Depression, Psychological Resilience, and Quality of Life in These MHD Patients
The mean depression score for these MHD patients was 9.37 ± 4.60, the psychological resilience score was 30.58 ± 6.05. The resilience score was 17.45 ± 3.12, accounting for 30.3% of the total score of psychological resilience, the self-reliance score was 25.36 ± 5.78, representing 40.0% of the total, and the optimism score was 17.12 ± 2.46, making up 29.7% of the total. The quality of life score was 59.48 ± 9.30. The score for physical health was 27.32 ± 4.72, representing 45.3% of the total score of quality of life, while the score for mental health was 34.65 ± 7.14, accounting for 54.7%. These scores all fell within the moderate to low range, as detailed in Table 2.
Table 2.
The Scores of Depression, Psychological Resilience, and Quality of Life in These Hemodialysis Patients
| Variables | Depression | Psychological Resilience | Resilience | Self-Reliance | Optimism | Quality of Life | Physical Health | Mental Health |
|---|---|---|---|---|---|---|---|---|
| Score range | 0–27 | 0–100 | 0–30 | 0–40 | 0–30 | 0–100 | 0–50 | 0–50 |
| Score (Mean ± SD) | 9.37 ± 4.60 | 57.58 ± 6.05 | 17.45 ± 3.12 | 25.36 ± 5.78 | 17.12 ± 2.46 | 59.48 ± 9.30 | 27.32 ± 4.72 | 34.65± 7.14 |
Correlation Analysis of Depression, Psychological Resilience, and Quality of Life in These MHD Patients
The results of this study demonstrated a negative correlation between depression and psychological resilience, as well as depression and quality of life (P<0.05). Additionally, a positive correlation was found between psychological resilience and quality of life (P <0.05). For detailed information, please refer to Table 3.
Table 3.
Correlation Analysis Between Depression, Psychological Resilience, and Quality of Life in These Maintenance Hemodialysis Patients (r Value)
| Parameters | Depression | Psychological Resilience | Resilience | Self-Reliance | Optimism | Quality of Life | Physical Health | Mental Health |
|---|---|---|---|---|---|---|---|---|
| Depression | 1.000 | |||||||
| Psychological Resilience | −0.456 | 1.000 | ||||||
| Resilience | −0.478 | 0.796 | 1.000 | |||||
| Self-reliance | −0.546 | 0.679 | 0.712 | 1.000 | ||||
| Optimism | −0.436 | 0.776 | 0.643 | 0.578 | 1.000 | |||
| Quality of Life | −0.453 | 0.578 | 0.725 | 0.251 | 0.649 | 1.000 | ||
| Physical Health | −0.384 | 0.721 | 0.462 | 0.376 | 0.589 | 0.386 | 1.000 | |
| Mental Health | −0.296 | 0.437 | 0.513 | 0.279 | 0.752 | 0.596 | 0.531 | 1.000 |
Note: all p<0.05.
The Analysis of the Mediating Effect of Psychological Resilience Between Depression and Quality of Life in These MHD Patients
Using AMOS 21.0, a structural equation model was established with quality of life as the dependent variable, psychological resilience as a parallel mediating variable, and depression as the independent variable. The model was modified, fitted, and hypotheses were tested using the maximum likelihood method. The results of model fit indicated that χ2 /df = 1.958, the root mean square error of approximation (RMSEA) = 0.071, goodness of fit index (GFI) = 0.964 (>0.9), adjusted goodness of fit index (AGFI) = 0.912 (>0.9), normed fit index (NFI) = 0.931 (>0.9), incremental fit index (IFI) = 0.954 (>0.9), and comparative fit index (CFI) = 0.964 (>0.9). These values suggest that the model fits well, and all path coefficients are statistically significant (P<0.05), indicating the feasibility of testing for mediating effects. Initial fit indices showed that all fit indices were above acceptable levels. After model modification, no significant improvement in model fit was observed. Therefore, the structural equation model established in this analysis reached a stable level and no further model adjustments will be made. The structural equation model of the mediating effect of psychological resilience between depression and quality of life is shown in Figure 1. The model indicated that Psychological resilience played a mediating role in the relationship between depression and quality of life (β=−0.13, P<0.05), with the mediating effect analysis showing a significant indirect effect of depression on quality of life. The direct and indirect effects of depression on quality of life were −0.34 and −0.13, respectively, with a total effect of −0.47. The mediating effect accounted for 27.7% (−0.13 / −0.47) * 100% ≈ 27.7%) of the total effect. Interactions between variables can be found in Table 4.
Figure 1.
Model of the mediating effect of psychological resilience in the relationship between depression and quality of life in these MHD patients.
Table 4.
Analysis of the Mediating Effect of Psychological Resilience Between Depression and Quality of Life in These Maintenance Hemodialysis Patients
| Path | Effect Size | Standard Error | 95% CI | Effect Size Ratio | P |
|---|---|---|---|---|---|
| Indirect Effect | −0.13 | 0.042 | 〔-0.27,-0.09〕 | 27.7% | <0.001 |
| Direct Effect | −0.34 | 0.076 | 〔-0.45,-0.18〕 | 72.3% | 0.014 |
| Total Effect | −0.47 | 0.058 | 〔-0.68,-0.21〕 | 100% | 0.003 |
Discussion
ESRD has a high mortality rate, and hemodialysis is currently an effective treatment method in clinical practice for this disease. This method helps maintain electrolyte balance, acid-base balance, and overall kidney system balance in the body. However, during the process of hemodialysis, it inevitably disrupts the quality of life for patients.29 In this study, the quality of life score was found to be 59.48 ± 9.30, indicating a below-average level, suggesting that there is room for improvement in the quality of life for these patients. The research confirms that the quality of life of patients is influenced by factors such as anxiety and depression, psychological resilience, social support, and the duration of the illness. This highlights the need for medical staff to pay close attention to the quality of life of such patients and provide targeted interventions based on these influencing factors. A study conducted by Togay et al revealed that the quality of life for individuals undergoing dialysis was notably subpar, and various demographic factors and disease-related data were found to have differing impacts on the quality of life of these patients.30
According to research, the risk of depression in MHD patients is four times higher than the general population.31 The main contributing factors include inflammation and nutritional imbalances. The decline in kidney function during the ESRD stage leads to reduced ability to excrete inflammatory factors, resulting in prolonged high expression of inflammatory cytokines such as tumor necrosis factor alpha, interleukin-6, and interleukin-1.32 Additionally, nutrient loss during dialysis accelerates muscle protein breakdown, increases metabolism, decreases synthesis, and most MHD patients suffer from malnutrition, which can lead to reduced activity and increased negative emotions.33 Furthermore, MHD patients are prone to complications such as pain, fatigue, and sleep disorders, increasing the risk of depression.34 Our study revealed that the mean total depression score of these MHD patients was 9.37 ± 4.60, indicating a moderate to low level of depression. A cross-sectional study conducted through interviews with patients at the dialysis unit of Jordan University Hospital revealed that 92.4% of the patients experienced symptoms of depression and the female patients exhibited significantly higher depression scores compared to their male counterparts.35 Additionally, there was a positive correlation between age and depression scores among the patients.
Psychological resilience is the ability and capacity of an individual to cope with stress or pressure, playing a protective role in promoting the individual’s mental health. ESRD is a challenging condition with various complications and a poor prognosis. Due to the physical limitations imposed by this disease, patients’ psychological well-being is disrupted, leading to a decrease in their level of psychological resilience. The constraints of this illness impede the patients’ ability to fulfill their responsibilities and obligations, necessitating care from family members. Consequently, feelings of guilt and helplessness significantly increase, giving rise to negative emotions, and causing a decline in their physical and mental health, ultimately leading to a noticeable reduction in their quality of life. This study determined that the overall psychological resilience score of the group of MHD patients was 57.58 ± 6.05, indicating a slightly below average level of resilience. A cross-sectional study conducted in China discovered that increased social support and family resilience, coupled with the passage of time, were associated with enhanced psychological resilience among these patients.36 Their discovery underscores the critical importance of recognizing and utilizing social and familial support systems that can positively influence an individual’s growth and development.
The results of this study indicate a significant negative correlation between depression and psychological resilience, and quality of life. The more pronounced the symptoms of depression, the lower the level of psychological resilience, leading to a decline in quality of life. Some researchers have pointed out that assessing a patient’s depression symptoms can better reflect their quality of life compared to measuring clinical objective indicators.37 The mediating role of psychological resilience in the relationship between depression and quality of life has been previously reported in international studies. For example, González-Flores CJ.et al found that higher resilience was associated with better mental health outcomes in MHD patients.38 Similarly, van Rijn MM.et al reported that resilience moderated the impact of depression on quality of life in MHD patients.39 Besides, A study suggest that psychological interventions, specifically resilience training, can have a positive impact on the psychological well-being and quality of life of patients undergoing hemodialysis.40 Effective management of depression is necessary in clinical work, conducting dynamic assessments of the causes and timing of depression occurrences can facilitate timely interventions. Additionally, poor psychological resilience in patients is associated with more severe depression, lower levels of quality of life.41 The close association between psychological resilience and depression is consistent with previous research findings.42–44 This suggests that healthcare professionals should prioritize the mental health of individuals with Mental Health Disorders, through conducting psychological workshops, encouraging patients to express their feelings, and organizing activities for emotional support among peers to help them cultivate a positive mindset and ultimately enhance their quality of life. Research has shown that improving psychological resilience contributes to an increase in the quality of life for MHD patients, indicating a positive correlation between psychological resilience and quality of life, which aligns with the conclusions of our study.45
The findings of this study suggest that psychological resilience partially mediates the relationship between depression and quality of life. Specifically, a decrease in psychological resilience among patients with mental health disorders increases the risk of depression and reduces quality of life. Therefore, healthcare providers should not only focus on improving patients’ depression but also closely monitor their psychological resilience. By enhancing patients’ psychological resilience, it is possible to partially reduce their levels of depression, maintain homeostasis, sustain good mental energy and quality of life. Stable and comprehensive family environments, economic conditions, and social support are key factors in improving psychological resilience. Therefore, nursing staff need to assess the ability of mental health disorder patients to cope with stress and adversity, and intervene promptly with effective measures such as mindfulness stress reduction and music therapy based on their psychological changes. This will help enhance their ability to adapt to changes and promote the recovery of their physical and mental health. By leveraging the resources around the patients and tapping into the support of their families and society, patients can clearly feel the understanding and support from their loved ones and the community.
Our research findings unveiled the significant moderating impact of psychological resilience on the connection between depression and quality of life. This study stands as a pioneering exploration into the role of psychological resilience as a moderator in the correlation between depression and quality of life among MHD individuals. A pertinent qualitative analysis demonstrated that engaging in physical activity post-adversity boosts psychological resilience as a protective element. Furthermore, numerous prior studies have delved into the shielding effects of psychological resilience on depressive symptoms across various demographic groups.46–48 In alignment with the interaction model of psychological resilience, moderating factors can modify the impact of risk elements on psycho-social well-being. Within this investigation, robust psychological resilience exhibited a dampening effect on the depression-quality of life relationship. Conversely, in the low psychological resilience cohort, depression displayed a negative association with quality of life. These outcomes underscore the importance of interventions targeting psychological resilience to bolster its protective prowess against the deleterious impacts of depression on the quality of life in MHD patients.
The similarities in our findings with international studies may be due to the universal challenges faced by MHD patients. However, differences may arise from variations in healthcare systems, cultural contexts, and the specific measures used to assess resilience and quality of life. Kang et al reported higher resilience scores in South Korea, attributing this to cultural differences in the perception of and response to adversity.
We acknowledge that our study has limitations due to the inclusion of only a subset of demographical data, which may not fully capture the complexity of the factors influencing depression and quality of life in MHD patients. Future research should aim to include a more comprehensive set of variables to provide a more nuanced understanding of these relationships.
This study is constrained by its cross-sectional design and reliance on convenience sampling. The participants were exclusively recruited from a single location, potentially limiting the sample size and the generalizability of the findings. Future research should aim to further validate the results in different regions and populations. In future studies, it is recommended to utilize longitudinal data in order to enhance understanding of the causal direction. Additionally, similar to prior research, this study relied on self-reporting which may introduce recall bias. Therefore, conducting further experimental research with improved methods for psychological resilience, as well as depression and quality of life, is necessary.
Conclusions
In light of our findings, we conclude that among maintenance hemodialysis (MHD) patients, depression is prevalent and significantly impacts their quality of life. Psychological resilience was identified as a mediator in the relationship between depression and quality of life, with a significant indirect effect of depression on quality of life through resilience (β=−0.13, P<0.05). The direct effect of depression on quality of life was also significant (β=−0.34, P<0.05), accounting for 72.3% of the total effect, while the mediating effect of psychological resilience accounted for 27.7% of the total effect. These results underscore the importance of addressing depression and enhancing psychological resilience in MHD patients to improve their quality of life. Future research should explore additional potential mediators to further understand the complex relationship between depression, psychological resilience, and quality of life in MHD patients.42–44
Acknowledgment
The author acknowledges the contributions of the colleagues in Baoding No 1 Central Hospital that aided the efforts.
Funding Statement
This research was supported by Baoding Science and Technology Plan Self-finiancing Project.
Abbreviation
MHD, maintenance hemodialysis; ESRD, end-stage renal disease; PHQ-9, Patient Health Questionnaire; DSM-V, Diagnostic and Statistical Manual of Mental Disorders; CD-RISC, Connor-Davidson Resilience Scale.
Data Sharing Statement
The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author.
Ethics Approval and Consent to Participate
The study has been approved by the Ethics Committee of Baoding No.1 Central Hospital (Ethics number: 2023052),) and adhered strictly to the guidelines and principles outlined in the Declaration of Helsinki. The participants were informed that the data will be anonymized.
Consent for Publication
Written informed consent was obtained from the patients for publication of this study.
Disclosure
The author declares there are no competing interests.
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