Uncovering a Silent Crisis: Psychometric Validation and Public Health Implications of Depression and Anxiety Among Caregivers of Patients Undergoing Hemodialysis in Pakistan

Uncovering a Silent Crisis: Psychometric Validation and Public Health Implications of Depression and Anxiety Among Caregivers of Patients Undergoing Hemodialysis in Pakistan | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Uncovering a Silent Crisis: Psychometric Validation and Public Health Implications of Depression and Anxiety Among Caregivers of Patients Undergoing Hemodialysis in Pakistan Talha Shabbir, Muhammad Usman, Mubariz Awan, Fizza Saleem, Minahil Iman Janjua, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7166296/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Caregivers of patients undergoing hemodialysis face considerable psychological stress, yet culturally validated tools specific for assessing depression and anxiety in this group are lacking in Pakistan. Objective: To validate the psychometric properties of the Urdu versions of the patient health questionnaire (PHQ-9) and generalized anxiety disorder (GAD-7) scales among hemodialysis caregivers in Pakistan, to measure the prevalence of generalized anxiety disorder (GAD) and major depressive disorder (MDD), and to identify demographic and caregiving-related predictors of depression and anxiety. Methods: A cross-sectional study was conducted among 362 caregivers recruited from multiple dialysis centers across Pakistan. Participants completed the pre-validated Urdu translations of PHQ-9 and GAD-7, along with sociodemographic and caregiving-related questions. Reliability and factor structure of the screening tools were evaluated, and associations between psychological scores and caregiver characteristics were analyzed using non-parametric tests and regression models. Results: The prevalence of Major Depressive Disorder was 8.0%, and Generalized Anxiety Disorder was 18.2%. Depression correlated positively with daily caregiving hours and negatively with caregiving duration. Higher levels of depression and anxiety were observed among females, urban residents, and university-educated caregivers. Regression analysis identified caregiving intensity as a significant predictor of depression (OR = 1.101), while age, gender, residence, and caregiving duration predicted anxiety (p < 0.05). Conclusion: The Urdu versions of PHQ-9 and GAD-7 demonstrated acceptable reliability and construct validity for use among hemodialysis caregivers. The findings highlight the psychological burden within this population and support the integration of routine mental health screening and tailored interventions into dialysis care programs. Hemodialysis Mental health Caregiving burden PHQ-9 GAD-7 Psychosocial stress INTRODUCTION Among hemodialysis (HD) patients and their caretakers, anxiety and depression are prevalent mental health conditions [ 1 ]. It is easy to understand why these mental health conditions are so common among caregivers, since an illness affects not only a family member but also the dynamics within the family [ 2 ]. Dialysis caregiving often imposes restrictions such as decreased physical function, fatigue, social isolation, strained relationships [ 3 ], and pervasive feelings of disappointment. These challenges are further exacerbated by advancing age, which limits caregivers' physical and emotional capacity [ 4 ]. Gender differences also play a role, with women caregivers, who often balance caregiving with family and childcare responsibilities, being particularly vulnerable to anxiety and depression [ 5 ]. In the Pakistani context, usually the family members provide care to the dialysis patients. Many patients rely on these caregivers for assistance in usual daily activities that intensifies the physical and emotional demands on caregivers. The reliance of these patients on hemodialysis highlights the multifaceted challenges caregivers face, further highlights the need to address their quality of life to mitigate the broader impact of CKD. Studies consistently show that caregivers of hemodialysis patients reported higher rates of anxiety and depression compared to the general population [ 6 ]. Research indicates that 28.8–52% of caregivers experience moderate to high levels of anxiety and depression. Key factors influencing these outcomes include caregivers’ age, education level, financial status, and perceived social support [ 1 , 3 ]. Additionally, assessments using validated tools such as the Hospital Anxiety and Depression Scale (HADS), Short Form-36 (SF-36), and Pittsburgh Sleep Quality Index (PSQI) reveal that caregivers often experience poorer sleep quality than the patients they care for [ 7 ]. Given the variability in socioeconomic conditions, cultural norms, societal roles, and language across different regions, the psychological impact of caregiving is likely to differ significantly between populations. These contextual factors influence both the manifestation of mental health symptoms and the effectiveness of assessment tools. In the Pakistani context, where caregiving responsibilities are often informal and heavily gendered, there is a notable gap in research assessing the mental health of caregivers using standardized, validated instruments. To our knowledge, no prior study in Pakistan has evaluated the prevalence of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) among caregivers of hemodialysis patients using culturally and linguistically validated screening tools. Therefore, this study aimed to fill that gap by estimating the prevalence of MDD and GAD using the Urdu versions of PHQ-9 and GAD-7, and by identifying key sociodemographic and caregiving-related predictors. Understanding these factors is essential for developing targeted interventions to mitigate caregiver burden within the local context. METHODOLOGY This study employed a cross-sectional design to assess the prevalence and associated factors of depression and anxiety among caregivers of end-stage renal disease (ESRD) patients undergoing hemodialysis. The study was conducted at multiple dialysis centers in Pakistan between December 1st, 2024, to April 30th, 2025. The study population included primary caregivers of patients receiving hemodialysis at the facilities. Caregivers aged 18 or above who had been providing care to the patient for at least three months were included. Caregivers diagnosed with psychiatric illnesses prior to caregiving or those unwilling to participate were excluded. Similarly, those having cognitive impairment that can interfere with participation, or inability to understand Urdu language were also excluded. A total of 362 caregivers were recruited using non-random convenience sampling. An initial sample size of 327 was calculated with the help of Raosoft sample size calculator, using 95% confidence level, 5% margin of error and 31.6% prevalence of depression and anxiety among caregivers of ESRD patients, based on an African study [ 8 , 9 ]. To account for potential incomplete or missing responses, sample size was increased by 10%, bringing the target to 360. However, final data collection yielded 362 valid responses, which were included in the analysis. The data were collected using a structured questionnaire that contained four sections: demographics, intensity (hours per day) and duration (number of months) of caregiving, Patient Health Questionnaire (PHQ-9) for depression, and Generalized Anxiety Disorder (GAD-7) for anxiety. Both these scales are pre-validated in various languages, including Urdu, in which the whole questionnaire was administered [ 10 , 11 ]. A total score ≥ 10 was considered indicative of at least moderate symptom severity on the PHQ-9. For a diagnosis of Major Depressive Disorder (MDD), we applied the standard PHQ-9 diagnostic criteria: the presence of five or more symptoms rated ≥ 2 (including either item 1 or 2), along with associated functional impairment. For Generalized Anxiety Disorder (GAD), a GAD-7 score ≥ 10 was used as the diagnostic cut-off. The questionnaire was administered to caregivers in dialysis centers by trained research assistants. The purpose of the study was explained to all the participants, and anonymity and confidentiality of the participants were assured. Informed written consent was obtained from all participants prior to data collection. Ethical approval was obtained from the IRB of Rahmah Foundation of Health, Islamabad, Pakistan. Psychometric properties of PHQ-9 and GAD-7 : This study assessed the psychometric properties of the Patient Health Questionnaire-9 (PHQ-9) and generalized anxiety disorder-7 (GAD-7) among caregivers of patients undergoing dialysis. Although a pre-validated Urdu translation of both scales was used, we conducted a comprehensive psychometric evaluation—including reliability testing, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA)—to ensure rigorous validation within our target population. This was done to confirm the structural validity and internal consistency of the tools in the unique sociocultural context of caregivers in dialysis settings. Data analysis was performed using Jamovi version 2.6.6 [ 12 ]. Exploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to examine the dimensional structure and construct validity of the scales, while reliability analysis was conducted to assess internal consistency. Prior to factor analysis, reliability was evaluated using Cronbach’s alpha (α) and McDonald’s omega (ω). Both total scale reliability and item-level statistics (i.e., alpha if item deleted) were calculated. For EFA, the Factor module in Jamovi was used. Factor extraction was based on the minimum residual method, and factor rotation was performed using promax rotation, a method suitable for identifying correlated factors. Sampling adequacy was confirmed using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test of sphericity. The number of factors to retain was guided by eigenvalues (> 1), scree plot inspection, and theoretical interpretability. Following EFA, CFA was conducted using the SEM (Structural Equation Modeling) module in Jamovi [ 13 , 14 , 15 ]. Variables were treated as ordered categorical, and the estimation method was set to Diagonally Weighted Least Squares (DWLS), with robust standard errors and mean-adjusted scaled and shifted χ² tests. Model parameters were estimated with 95% confidence intervals. Latent variables were standardized with the first indicator fixed to 1, and the model incorporated intercepts and mean structure. The rotation algorithm used was GPA (Generalized Procrustes Analysis) with geomin rotation and geomin epsilon = 0.001. Missing data were handled using listwise deletion, and univariate constraints were applied. Model fit was evaluated using Comparative Fit Index, Tucker-Lewis Index, Root Mean Square Error of Approximation, Standardized Root Mean Square Residual, and chi-square statistics, including both classical and scaled estimates. After psychometric validation, categorical demographic variables, individual PHQ-9 items, and GAD-7 items were summarized as frequencies and percentages. Non-normality of continuous variables (age, household income, intensity of caregiving, duration of caregiving, total depression score, and total anxiety score) was confirmed via the Kolmogorov-Smirnov test (p < 0.05); thus, medians and interquartile ranges (IQR) were computed. In inferential statistics, Spearman’s rank correlation was used to determine the correlation of depression and anxiety scores with the intensity and duration of caregiving. For group comparisons, the Mann-Whitney U test was used for binary categorical variables (e.g., gender, residence, living situation with the patient), and the Kruskal-Wallis H test was used for variables with more than two categories (e.g., marital status, education, occupation, kinship with the patient). U or H statistics, effect sizes (r for the Mann-Whitney U test and ε² for the Kruskal-Wallis H test), and asymptotic p-values were reported. Post hoc pairwise comparisons were conducted using Dunn’s test with Bonferroni correction, provided the Kruskal-Wallis H test was significant. The Chi square test was used to determine association of categorical demographic variables with major depressive disorder and generalized anxiety disorder. In multivariate analysis, two separate generalized linear models, with a negative binomial distribution and logarithmic link function, were applied using depression and anxiety scores as outcomes. Model assumptions were verified, including count-type outcome, independence of observations, linearity on the log scale for continuous predictors, absence of multicollinearity (VIF < 5), and no influential outliers, assessed by Cook’s distances and leverage values, both of which were well below 1. Only 1.7% of standardized deviance residuals exceeded |2| for the depression model. For the anxiety model, all assumptions were also met, with only 0.8% of standardized deviance residuals above the |2| threshold. For both models, the deviance/df ratio was approximately 0.6, indicating under-dispersion, which is atypical for negative binomial models. However, when the same model was re-estimated using a Poisson distribution with a log link, the deviance/df exceeded 3, and the AIC and BIC values were higher, suggesting that the negative binomial model provided a better fit to the data. To predict the presence of major depressive disorder and generalized anxiety disorder, two binary logistic regression models were applied. Assumptions of binary dependent variable, independence of observations, linearity of the logit with continuous predictors, absence of multicollinearity, and no influential outliers were met. In the anxiety model, among the three continuous predictors, two met the logit-linearity assumption, while the third—duration of caregiving—required logarithmic transformation. Outliers were evaluated using Cook’s distances and leverage values, all of which were well below 1, and only 4.7% of deviance residuals exceeded |2|. Based on the rule of 10 events per predictor variable, the model for major depressive disorder included only two predictors: intensity and duration of caregiving [ 16 ]. The model for generalized anxiety disorder included six predictors: gender, age, residence, kinship with the patient, intensity, and log-transformed duration of caregiving. RESULTS Exploratory and confirmatory factor analysis of PHQ-9 and GAD-7 : PHQ-9 The PHQ-9 showed strong internal consistency, with Cronbach’s α = 0.864 and McDonald’s ω = 0.864. Item-level analysis demonstrated minimal variability in reliability when any item was removed, with values of α if item deleted ranging from 0.836 to 0.872. The KMO measure of sampling adequacy was 0.893, and Bartlett’s test of sphericity was significant (χ²(36) = 1215, p < .001), supporting the factorability of the correlation matrix. EFA suggested a two-factor structure, explaining 48.51% of the variance (Factor 1 = 35.87%, Factor 2 = 12.64%). The first factor included items related to somatic-cognitive symptoms (PHQ_1 to PHQ_5, PHQ_7), while the second factor comprised affective symptoms (PHQ_6, PHQ_8, PHQ_9). Inter-factor correlation was moderately high (r = 0.635), suggesting related but distinct constructs. CFA confirmed the two-factor model with good model fit: χ²(26) = 56.86, p < .001; CFI = 0.993, TLI = 0.991, SRMR = 0.049, and RMSEA (scaled) = 0.0887 (90% CI: 0.0707–0.1075). All factor loadings were statistically significant (p < .001), ranging from 0.511 (PHQ_9) to 0.851 (PHQ_6). The two latent factors were significantly correlated (r = 0.790, p < .001), reinforcing the presence of interrelated symptom domains within depression. GAD-7 For the GAD-7, reliability analysis revealed Cronbach’s α = 0.852 and McDonald’s ω = 0.857, indicating excellent internal consistency. Item-level reliability remained stable, with α if item deleted ranging from 0.812 to 0.843. The KMO value was 0.875, and Bartlett’s test of sphericity was significant (χ² (21) = 971.6, p < .001). EFA results supported a unidimensional factor structure, accounting for 46.68% of the total variance, with item factor loadings ranging from 0.585 (GAD_6) to 0.826 (GAD_2). PCA and eigenvalue analysis further confirmed the dominance of a single latent construct. The one-factor CFA model demonstrated excellent fit: χ²(14) = 28.07, p = .014, CFI = 0.996, TLI = 0.994, SRMR = 0.038, and RMSEA (scaled) = 0.0866 (90% CI: 0.0622–0.1124). Standardized factor loadings ranged from 0.639 (GAD_6) to 0.877 (GAD_2), all statistically significant (p < .001), confirming that all items contributed meaningfully to a unidimensional anxiety construct. A detailed description of the statistical procedures, parameters, thresholds, and software settings is provided in the supplementary tables S12-S46 and supplementary figures S1 -S7. Our study included 362 caregivers, with nearly equal numbers of males and females. About three-fourths of the participants were urban residents, while the remainder were from rural areas. Over 80% were married. Secondary education was most common, followed by equal proportions of middle school and university education. Fewer were illiterate or had elementary or postgraduate education. More than half were unemployed. Two-fifths were spouses of patients, while one-fifth each were parents or children. Over 90% co-resided with patients; fewer than 10% lived separately. The demographic features of participants are presented in Table 1 and Table 2 . Table 1 Frequencies and Percentages of Categorical Demographics, and Chi square test for Association of Demographics with Major Depressive Disorder and Generalized Anxiety Disorder. Parameters Categories Total Major Depressive Disorder Generalized Anxiety Disorder Frequencies (N) Percentages (%) X2 (df) p value X2 (df) p value Gender Male 171 47.20% 3.321 (1) 0.068 6.261 (1) 0.012 Female 191 52.80% Residence Rural 98 27.10% 0.137 (1) 0.711 5.809 (1) 0.016 Urban 264 72.90% Marital Status Single 58 16.00% 10.555 (3) 0.014 8.082 (3) 0.044 Married 296 81.80% Widowed 5 1.40% Divorced 3 0.80% Education None 51 14.10% 11.276 (5) 0.046 7.186 (5) 0.207 Elementary school 43 11.90% Middle school 76 21.00% Secondary school 104 28.70% Postgraduate 12 3.30% University 76 21.00% Occupation Employed 160 44.20% 9.748 (2) 0.008 5.005 (2) 0.082 Unemployed 196 54.40% Retired 5 1.40% Kinship with the patient Children 82 22.70% 7.709 (5) 0.173 14.775 (5) 0.011 Parents 70 19.30% Spouse / Partners 148 40.90% Siblings 42 11.60% Extended Family (aunts, uncles, etc) 11 3.00% Other 9 2.50% Living situation with the patient Live with patient 334 92.30% 0.812 (1) 0.368 0.317 (1) 0.573 Live separately from patient 28 7.70% Table 2 Descriptive Statistics of Continuous Variables Parameters Median 1st quartile 3rd quartile Interquartile range Age (years) 37 30 45 15 Household income (PKR) 42,000 30,000 60,000 30,000 Intensity of caregiving (hours/day) 4 3 10 7 Duration of caregiving (months) 26 8 60 52 Total depression score 4 2 7 5 Total anxiety score 5 2.75 8 5.25 Based on PHQ-9, 41.4% had minimal depression; based on GAD-7, 44.5% had minimal anxiety. Mild depression (33.4%) and mild anxiety (37.3%) were also comparable. However, frequencies of moderate and severe levels differed, possibly due to differences in categorization. While 14.4% of participants reported moderate to severe symptoms (PHQ-9 ≥ 10), only 8% met the diagnostic criteria for Major Depressive Disorder (MDD) based on symptom pattern, presence of core symptoms, and functional impairment, as outlined in the PHQ-9 diagnostic algorithm. On the other hand, Generalized Anxiety Disorder showed a slightly higher percentage, i.e., 18.2% (N = = 66). Table 3 depicts the frequencies and percentages of depression and anxiety levels. Table 3 Frequencies and Percentages of Depression and Anxiety Levels Parameters Categories Frequencies (N) Percentages (%) PHQ-9 Symptom Severity Categories Based on Total Scores a No depression 39 10.8% Minimal depression 150 41.4% Mild depression 121 33.4% Moderate depression 30 8.3% Moderately severe depression 17 4.7% Severe depression 5 1.4% GAD-7 Symptom Severity Categories Based on Total Scores a Minimal anxiety 161 44.5% Mild anxiety 135 37.3% Moderate anxiety 53 14.6% Severe anxiety 13 3.6% Major Depressive Disorder Absent 333 92% Present 29 8% Generalized Anxiety Disorder Absent 296 81.80% Present 66 18.20% a These categories reflect symptom severity based on PHQ-9 scores. They do not indicate clinical diagnosis. A diagnosis of Major Depressive Disorder (MDD) requires meeting specific criteria using the PHQ-9 diagnostic algorithm. Chi-square test revealed a significant association of major depressive disorder with gender (χ² (1) = 3.321, p = 0.068), marital status (χ² (3) = 10.555, p = 0.014), education (χ² (5) = 11.276, p = 0.046), and occupation (χ² (2) = 9.748, p = 0.008). Generalized anxiety disorder was significantly associated with gender (χ² (1) = 6.261, p = 0.012), residence (χ² (1) = 5.809, p = 0.016), marital status (χ² (3) = 8.082, p = 0.044), and kinship with the patient (χ² (5) = 14.775, p = 0.011). The results of Chi square test are given in Table 1 . Depression and anxiety scores were strongly correlated (Spearman’s ρ = 0.622, p < 0.001). Depression was weakly positively correlated with caregiving intensity (Spearman’s ρ = 0.143, p = 0.007), and weakly negatively correlated with duration (Spearman’s ρ=-0.168, p = 0.001). Anxiety showed no significant correlation with either. Depression was significantly associated with gender (p < 0.001), with higher scores among females (r = 0.207). Association with marital status was also significant (p < 0.001), with highest scores in widowed, followed by married, divorced, and single caregivers. However, low frequencies of widowed (n = 5) and divorced (n = 3) limit interpretation. Effect size (ε²) was minimal. Education level was significantly associated (p < 0.001); scores were highest among university graduates, followed by postgraduates, secondary, elementary, middle school, and illiterate caregivers. Only university-level scores significantly differed from others. Employment status showed significant differences (p < 0.001), with lowest scores in employed, followed by unemployed and retired caregivers. Caregiver-patient relationship also showed significant association (p < 0.001), with highest depression in parents, followed by others, spouses, family, siblings, and children. Results of Mann-Whitney U test and Kruskal-Wallis H test for depression are presented in Table 4 . Table 4 Non-Parametric Analysis of Median PHQ-9 Scores by Sociodemographic and Caregiving Characteristics in Dialysis Caregivers Parameters Categories Median PHQ-9 scores Interquartile Range U or H statistics Effect sizes (|r| and epsilon squared) Asymptomatic p value Gender Male 4 6 − 1 20233.5 0.207 < 0.001 Female 5 8 − 2 Residence Rural 5 7 − 2 12391 0.033 0.536 Urban 4 7 − 2 Marital status Single 2.5 5 − 0 22.496 0.051 < 0.001 Married 5 7 − 2 Widowed 17 18 − 14 Divorced 4 5.5-3 Education None 6 10 − 3 59.052 0.13 < 0.001 Elementary school 5 7-3.5 Middle school 6 8.5-4 Secondary school 4 7 − 2 Postgraduate 2.5 6.5–1.5 University 1.5 4 − 1 Occupation Employed 3 6 − 1 29.077 0.07 < 0.001 Unemployed 5 9-2.5 Retired 7 4–7 Kinship with the patient Children 2 5 − 1 38.885 0.086 < 0.001 Parents 6 9 − 4 Spouse / Partners 5 7-2.5 Siblings 3 6 − 1 Extended Family (aunts, uncles, etc) 4 11.5–1.5 Others 7 9 − 4 Living situation with the patient Live with patient 4 7 − 2 4354 0.032 0.543 Live separately from patient 4 6 − 1 Anxiety showed similar patterns. It was significantly associated with gender (p < 0.001), with higher scores in females (r = 0.304). Marital status was significant (p < 0.001), with highest anxiety in widowed, then married, divorced, and single participants, though low subgroup frequencies again limit conclusions. Anxiety was also significantly associated with education (p < 0.001); the highest scores were in university-educated caregivers, followed by postgraduates, secondary, middle school, elementary, and illiterate. Pairwise differences were significant between university-level and lower education groups. Employment status was significantly associated (p < 0.001), with employed caregivers showing the lowest anxiety. Pairwise differences were found between employed vs. unemployed and employed vs. retired. Anxiety varied across caregiver roles (p < 0.001), highest in parents, followed by spouses, others, siblings, family, and children. Parents had significantly higher anxiety than children and siblings, but not spouses or others. No significant association was found between depression or anxiety scores and caregiver residence (urban/rural). Non-parametric tests for anxiety are present in Table 5 . Table 5 Non-Parametric Analysis of Median GAD-7 Scores by Sociodemographic and Caregiving Characteristics in Dialysis Caregivers Parameters Categories Median GAD-7 Scores Interquartile Range U or H statistics Effect sizes (r and epsilon squared) Asymptomatic p value Gender Male 4 6 − 2 22069 0.304 < 0.001 Female 6 9 − 4 Residence Rural 5 7 − 3 13634.5 0.042 0.428 Urban 5 9 − 2 Marital Status Single 3 6 − 2 16.724 0.037 < 0.001 Married 5 9 − 3 Widowed 8 14 − 7 Divorced 5 5-4.5 Education None 5 7.5–2.5 15.284 0.025 0.009 Elementary school 5 6.5-3 Middle school 6 8 − 4 Secondary school 5 9 − 3 Postgraduate 3.5 4.5-1 University 3 7 − 2 Occupation Employed 4 6 − 2 23.231 0.056 < 0.001 Unemployed 6 9 − 3 Retired 9 10 − 5 Disable Kinship with the patient Children 4 6 − 2 25.535 0.054 < 0.001 Parents 6 9 − 4 Spouse / Partners 6 9 − 3 Siblings 3.5 6 − 2 Extended Family (aunts, uncles, etc) 4 6 − 1 Others 6 8 − 3 Living situation with the patient Live with patient 5 8 − 3 4616 0.006 0.91 Live separately from patient 4.5 8.5–2.5 Generalized linear models revealed that, after adjusting for other predictors, depression was significantly higher across all education levels compared to the reference category (university education). It was also negatively associated with the duration of caregiving in months (B = -0.003, p = 0.043). In contrast, none of the predictors were significantly associated with anxiety scores in the generalized linear model. Results of generalized linear models are provided in supplementary files. Binary logistic regression found that major depressive disorder was significantly associated with caregiving intensity (OR = 1.101, p < 0.001), while generalized anxiety disorder was significantly associated with age (OR = 1.045, p = 0.001), gender (OR = 1.886, p = 0.039), residence (OR = 2.271, p = 0.032), and natural logarithm of caregiving duration (OR = 1.363, p = 0.008). Tables 8 and 9 present the results of binary logistic regression. Table 6 Binary Logistic Regression of major depressive disorder Parameters Regression Coefficient Standard Error p value Odds Ratio Intensity of caregiving (daily hours) 0.096 0.022 0.000 1.101 Duration of caregiving (months) -0.004 0.004 0.383 0.996 Constant -3.242 0.370 0.000 0.039 Table 7 Binary Logistic Regression of generalized anxiety disorder Parameters Regression Coefficient Standard Error p value Odds Ratio Age (years) 0.044 0.014 0.001 1.045 Gender 0.634 0.307 0.039 1.886 Residence 0.820 0.383 0.032 2.271 Kinship with the patients -0.056 0.134 0.677 0.946 Intensity of caregiving (daily hours) -0.013 0.021 0.532 0.987 Ln (Duration of caregiving) 0.310 0.117 0.008 1.363 Constant -6.457 1.112 0.000 0.002 DISCUSSION We confirmed prior study on psychological distress in dialysis caretakers with MDD and GAD. Our sample is unique, but 8% for MDD and 18.2% for GAD are consistent with previous patterns showing a significant mental health burden on chronically ill caregivers [ 17 , 18 ]. Alshelleh et al. (2023) evaluated sadness and anxiety in hemodialysis patients, showing the frequency of mental health concerns that can impair caretakers [ 17 ]. Our study builds on Gerogianni et al. (2021)'s hemodialysis caregiver anxiety and melancholy study [ 18 ]. Global study reveals female caregivers have more depression and anxiety [ 19 , 22 ]. According to Pacheco Barzallo et al. (2024) [ 19 ], female caregivers may perform more or diversified activities, increasing psychological strain. In addition to our gender-specific findings, Al Maqbali et al. (2025) found greater subjective stress, anxiety, and depression in female hemodialysis family caregivers [ 6 ]. This study-wide finding emphasizes gender-sensitive caregiver support. Female caregivers are susceptible due to the "double burden" of tasks and social expectations [ 19 , 21 ]. Disease awareness and performance demands may annoy university-educated caretakers. Social and financial stability safeguard jobs. Parents were most stressed by children's strong emotional bonds [ 21 ]. Our study indicated that widowed and married caregivers had better mental health, highlighting the complex interplay between social support and suffering. Social support affects caregiver well-being, although study populations and methodology prevent direct comparisons [ 20 , 25 ]. Shukri et al. showed in 2020 that strong social networks improve hemodialysis caregiver load, quality of life, anxiety, and sadness [ 20 ]. Wang et al. (2024) underlined social support and family resilience in maintenance hemodialysis patients' psychological well-being, which resonates with caretakers [ 25 ]. Our findings also show that caregiver melancholy and anxiety are highly linked to education and employment. Specifically, employed caregivers were least anxious. For all degree levels, university graduates had the most depression (median 1.5) and anxiety (median 3). These findings suggest that while socioeconomic factors and intellectual engagement may generally protect, higher disease awareness and performance demands may lead university-educated caregivers to be more attuned to and prone to expressing their mental health symptoms, contributing to their higher scores. This enhanced awareness may also increase their use of mental health resources, which could affect their scores. Ibrahim et al. (2022) are studying the effects of psychosocial and economic factors on end-stage renal disease patients and their caregivers' quality of life, which is similar to our findings on employment and education [ 27 ]. Hemodialysis caretakers' mental health suffers from emotional support and household management [ 30 ]. Kinship affects patient and caregiver mental health, with parents experiencing the highest depression and anxiety. Patient parents worry and despair most, hence caregiver-patient relationships affect mental health. Any age hemodialysis child's care is emotionally draining. Chronically ill children's parents suffer, study finds [ 29 ]. Chronically unwell children present emotional and practical concerns for parents. Indonesian hemodialysis caregivers' burden, anxiety, sadness, and quality of life were evaluated by Pio et al. (2022). While not addressing kinship, their work helps explain caregiver burden, which varies by patient connection [ 24 ]. Fu et al. (2022) demonstrated that caregiver depression is strongly linked to hemodialysis patients' depression and hospitalization, underscoring the importance of caregiver mental health, especially in parent-child relationships [ 26 ]. Our investigation found no correlation between caregiver urban/rural residence and patient living circumstances and depression and anxiety ratings. This contradicts the perception that rural caregivers are secluded or that co-residence stresses them. It reinforces studies that indicate caring burdens transcend geographical and cohabitation boundaries because the fundamental concerns remain [ 28 ]. Alnasser et al. (2025) examined hemodialysis and peritoneal dialysis caregivers' quality of life in Saudi Arabia. While not addressing residence, their data show universal caregiver stress [ 28 ]. To ensure the robustness and comparability of our findings, we estimated prevalence using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). These are thorough psychometric instruments known for their high internal consistency and well-established component structures. The two-factor structure observed for PHQ-9 (somatic-cognitive and affective symptoms) and the unidimensional structure for GAD-7 in our psychometric measurements are consistent with the widely reported properties of these instruments in the literature [ 17 , 18 , 24 ]. This consistency reinforces the validity of our measurements within this specific population, thereby enhancing the comparability of our findings with other studies that utilize these widely accepted tools [ 21 , 22 , 26 ]. The methodological rigor applied in our assessment of MDD and GAD prevalence directly supports the subsequent implications and recommendations derived from our study. Given the high prevalence of MDD and GAD among dialysis caregivers, our findings strongly advocate for the routine integration of mental health screening within nephrology care settings, utilizing validated methods such as PHQ-9 and GAD-7. These results also suggest the development of gender-specific support programs, particularly for vulnerable female caregivers [ 19 , 22 ], and tailored therapies that address caregiving intensity, age, gender, domicile, and duration characteristics for anxiety. The strong correlation observed between depression and anxiety scores further suggests that holistic mental health support, rather than standalone treatments, may be more beneficial. Recognizing that caregiver psychological discomfort directly impacts patient outcomes, hospitalization rates, and healthcare expenses, we recommend that healthcare policies prioritize the allocation of funding for support programs and the seamless integration of mental health services into dialysis centers [ 26 ]. This approach aligns with the stress-coping model and biopsychosocial frameworks for caregiver mental health in chronic disease management, which acknowledge the distinct yet overlapping risk factors for MDD and GAD. Our work sheds light on MDD and GAD in dialysis caretakers, however it has limitations. Cross-sectional research cannot prove causality, hence longitudinal studies are needed to explore temporal correlations. Our geographically constrained sample of 362 caregivers may limit generalizability to other cultures and healthcare environments. Self-reported tests (PHQ-9 and GAD-7) may be biased by social stigma, stressing the necessity for cognitive interviews by experienced psychiatrists to increase validity. Confounding variables such patients' functional state, dialysis duration, and caregivers' pre-existing diseases were not carefully examined. Finally, we did not examine caregiver-beneficial support kinds or interventions, a significant gap for tailored interventions. Prospective longitudinal studies should track caregiver mental health trajectories and identify early predictors of MDD and GAD to enable proactive intervention. Building on peer support findings by Ghenaati et al. (2024) [ 31 ], gender-specific support groups and digital mental health platforms are priorities. Understanding caregivers' lives and informing culturally relevant solutions requires qualitative research through interviews and focus groups. Comparative studies of mental health burden across renal replacement therapies (extending Alnasser et al. (2025) [ 28 ]) and economic impact assessments quantifying caregiver distress-related healthcare costs are essential for evidence-based policy frameworks. To make caregiver well-being core to chronic illness management, these studies should follow Nguyen and Vo (2025) [ 23 ] integrated care approaches. Abbreviations AIC Akaike Information Criterion B Regression Coefficient BIC Bayesian Information Criterion CFA Confirmatory Factor Analysis CKD Chronic Kidney Disease EFA Exploratory Factor Analysis ε² Epsilon Squared (Effect Size for Kruskal-Wallis test) ESRD End-Stage Renal Disease GAD Generalized Anxiety Disorder GAD-7 Generalized Anxiety Disorder – 7 item scale HADS Hospital Anxiety and Depression Scale HD Hemodialysis IRB Institutional Review Board IQR Interquartile Range KMO Kaiser-Meyer-Olkin MDD Major Depressive Disorder OR Odds Ratio p p-value (Significance level) PHQ-9 Patient Health Questionnaire – 9 item scale PKR Pakistani Rupee PSQI Pittsburgh Sleep Quality Index r Effect Size / Spearman’s Correlation Coefficient ρ Spearman’s Rank Correlation Coefficient RMSEA Root Mean Square Error of Approximation SEM Structural Equation Modeling SF-36 Short Form-36 Health Survey SRMR Standardized Root Mean Square Residual TLI Tucker-Lewis Index VIF Variance Inflation Factor χ² Chi-square Declarations Acknowledgements The authors are grateful to the participating hospitals, staff, and patients for their cooperation. Special thanks to the research assistants and data collectors for their contributions to the successful completion of this study. Funding This research received no external funding. Competing interests The authors declare no competing interests. Ethics approval and consent to participate This study was conducted after obtaining ethical approval from the Institutional Review Board of Rahmah Health Foundation, Islamabad, Pakistan (Approval No RHF-04-2024). Written informed consent was obtained from all participants before inclusion in the study. Clinical trial number Not applicable. Consent for publication This study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. Written informed consent was obtained from all participants prior to inclusion in the study. Data availability The data supporting this study's findings are available from the corresponding author upon reasonable request. Authors Contributions Conceptualization: M.U.H. Methodology: M.U.H., M.U., M.I.J., M.A., T.S., F.S., S.T, H.K, H.R, I.S, L.F Formal Analysis and Investigation: M.U.H., M.U. Writing - Original Draft Preparation: M.U.H., M.U., M.I., M.A., F.S., A,F. Writing - Review and Editing: M.U.H. References Shukri, M., et al., Burden, quality of life, anxiety, and depressive symptoms among caregivers of hemodialysis patients: The role of social support. The International Journal of Psychiatry in Medicine, 2020. 55(6): p. 397-407. Alshelleh, S., et al., Level of depression and anxiety on quality of life among patients undergoing hemodialysis. International journal of general medicine, 2023: p. 1783-1795. Gerogianni, G., et al. Factors affecting anxiety and depression in caregivers of hemodialysis patients . in GeNeDis 2020: Geriatrics . 2021. Springer. Pereira, B.d.S., et al., Beyond quality of life: a cross sectional study on the mental health of patients with chronic kidney disease undergoing dialysis and their caregivers. 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Urdu translation and validation of PHQ-9, a reliable identification, severity and treatment outcome tool for depression. J Pak Med Assoc. 2018 Aug;68(8):1166-1170. PMID: 30108380. Ahmad S, Hussain S, Shah FS, Akhtar F. Urdu translation and validation of GAD-7: A screening and rating tool for anxiety symptoms in primary health care. J Pak Med Assoc. 2017 Oct;67(10):1536-1540. PMID: 28955070.Alshelleh S, Alhawari H, Alhouri A, Abu-Hussein B, Oweis A. Level of Depression and Anxiety on Quality of Life Among Patients Undergoing Hemodialysis. Int J Gen Med. 2023 May 10;16:1783-1795. doi: 10.2147/IJGM.S406535. PMID: 37193250; PMCID: PMC10183175. The jamovi project (2024). jamovi. (Version 2.6) [Computer Software]. Retrieved from https://www.jamovi.org. Gallucci, M., Jentschke, S. (2021). SEMLj: jamovi SEM Analysis. [jamovi module]. For help please visit https://semlj.github.io/. Revelle, W. (2023). psych: Procedures for Psychological, Psychometric, and Personality Research. [R package]. Retrieved from https://cran.r-project.org/package=psych. Epskamp S. , Stuber S., Nak J., Veenman M,, Jorgensen T.D. (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages' Output. [R Package]. Retrieved from https://CRAN.R-project.org/package=semPlot. Peduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996 Dec;49(12):1373-9. doi: 10.1016/s0895-4356(96)00236-3. PMID: 8970487. Alshelleh S, Alhawari H, Alhouri A, Abu-Hussein B, Oweis A. Level of Depression and Anxiety on Quality of Life Among Patients Undergoing Hemodialysis. Int J Gen Med. 2023 May 10;16:1783-1795. doi: 10.2147/IJGM.S406535. PMID: 37193250; PMCID: PMC10183175. Gerogianni G, Polikandrioti M, Alikari V, Vasilopoulos G, Zartaloudi A, Koutelekos I, Kalafatakis F, Babatsikou F. Factors Affecting Anxiety and Depression in Caregivers of Hemodialysis Patients. Adv Exp Med Biol. 2021;1337:47-58. doi: 10.1007/978-3-030-78771-4_6. PMID: 34972890. Pacheco Barzallo D, Schnyder A, Zanini C, et al. Gender Differences in Family Caregiving. Do female caregivers do more or undertake different tasks?. BMC Health Serv Res. 2024;24:730. https://doi.org/10.1186/s12913-024-11191-w Shukri M, Mustofai MA, Md Yasin MAS, Tuan Hadi TS. Burden, quality of life, anxiety, and depressive symptoms among caregivers of hemodialysis patients: The role of social support. Int J Psychiatry Med. 2020 Nov;55(6):397-407. doi: 10.1177/0091217420913388. Epub 2020 Mar 26. PMID: 32216495. Nazir, S., Raza, H., Nisar, M., Rashid, Z., et al. (2023). Assessment of Anxiety and Burden on caregivers for haemodialysis patients in southern Punjab, Pakistan. Fabad Eczacılık Bilimler Dergisi, 48(1), 53-60. https://doi.org/10.55262/fabadeczacilik.1099539 Al Maqbali A, Al Omari O, Abu Sharour L, Al-Naamani Z, Al Khatri M, Sanad HM, Al Hashmi I, Alkhawaldeh A, Al Qadire M, Al Omari D. The perceived levels of stress, anxiety and depression among family caregivers of patients undergoing haemodialysis and their association with quality of life. BJPsych Open. 2025 May 13;11(3):e100. doi: 10.1192/bjo.2025.44. PMID: 40357747; PMCID: PMC12089806. Nguyen AM, Vo LH. Mental health and quality of life in dialysis and transplant patients in Vietnam: a call for integrated care models. Front Psychiatry. 2025 May 6;16:1570138. doi: 10.3389/fpsyt.2025.1570138. PMID: 40395465; PMCID: PMC12089989. Pio TMT, Prihanto JB, Jahan Y, Hirose N, Kazawa K, Moriyama M. Assessing Burden, Anxiety, Depression, and Quality of Life among Caregivers of Hemodialysis Patients in Indonesia: A Cross-Sectional Study. Int J Environ Res Public Health. 2022 Apr 9;19(8):4544. doi: 10.3390/ijerph19084544. PMID: 35457412; PMCID: PMC9032362. Wang Y, Qiu Y, Ren L, Jiang H, Chen M, Dong C. Social support, family resilience and psychological resilience among maintenance hemodialysis patients: a longitudinal study. BMC Psychiatry. 2024 Jan 26;24(1):76. doi: 10.1186/s12888-024-05526-4. PMID: 38279114; PMCID: PMC10811847. Fu L, Wu Y, Zhu A, Wang Z, Qi H. Depression of caregivers is significantly associated with depression and hospitalization of hemodialysis patients. Hemodial Int. 2022 Jan;26(1):108-113. doi: 10.1111/hdi.12967. Epub 2021 Jul 5. PMID: 34227223. Ibrahim N, Chu SY, Siau CS, Amit N, Ismail R, Abdul Gafor AH. The effects of psychosocial and economic factors on the quality of life of patients with end-stage renal disease and their caregivers in Klang Valley, Malaysia: protocol for a mixed-methods study. BMJ Open. 2022 Jun 3;12(6):e059305. doi: 10.1136/bmjopen-2021-059305. PMID: 36691236; PMCID: PMC9171257. Alnasser HA, BinMuneif YA, Alrsheed SF, Alqahtani SA, Alhaisoni FE, Algadheb HA, Alateeq NM. Quality of Life Among Caregivers of Patients Undergoing Hemodialysis Versus Peritoneal Dialysis in Saudi Arabia: A Cross-Sectional Study. Cureus. 2025 Jan 22;17(1):e77834. doi: 10.7759/cureus.77834. PMID: 39991350; PMCID: PMC11844773. Azeez A, Ambatipudi S. Caregiver burden and quality of life among family caregivers of hemodialysis patients from South India. J Educ Health Promot. 2024 Dec 28;13:486. doi: 10.4103/jehp.jehp_273_24. PMID: 39850309; PMCID: PMC11756677. Wu HHL, Dhaygude AP, Mitra S, Tennankore KK. Home dialysis in older adults: challenges and solutions. Clin Kidney J. 2022 Oct 7;16(3):422-431. doi: 10.1093/ckj/sfac220. PMID: 36865019; PMCID: PMC9972827. Ghenaati N, Zendehtalab HR, Namazinia M, Zare M. Peer support groups and care burden in hemodialysis caregivers: a RCT in an Iranian healthcare setting. BMC Nephrol. 2024 Oct 21;25(1):371. doi: 10.1186/s12882-024-03811-8. PMID: 39433988; PMCID: PMC11495059. Additional Declarations No competing interests reported. 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19:38:05","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7166296/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7166296/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":91732776,"identity":"58b73c35-a56a-4761-9a08-e9bd66a7b56e","added_by":"auto","created_at":"2025-09-19 16:31:42","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1589098,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7166296/v1/c3daa037-dbb4-4e6c-894f-19f8ae3ac45a.pdf"},{"id":90112438,"identity":"7263f5da-0bed-4415-b2a2-999a98543977","added_by":"auto","created_at":"2025-08-28 15:26:42","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":370249,"visible":true,"origin":"","legend":"","description":"","filename":"NephroGADMDDSupplementaryFile19725.docx","url":"https://assets-eu.researchsquare.com/files/rs-7166296/v1/c522b6585a8636811de39c5e.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Uncovering a Silent Crisis: Psychometric Validation and Public Health Implications of Depression and Anxiety Among Caregivers of Patients Undergoing Hemodialysis in Pakistan","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAmong hemodialysis (HD) patients and their caretakers, anxiety and depression are prevalent mental health conditions [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. It is easy to understand why these mental health conditions are so common among caregivers, since an illness affects not only a family member but also the dynamics within the family [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Dialysis caregiving often imposes restrictions such as decreased physical function, fatigue, social isolation, strained relationships [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e], and pervasive feelings of disappointment. These challenges are further exacerbated by advancing age, which limits caregivers' physical and emotional capacity [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Gender differences also play a role, with women caregivers, who often balance caregiving with family and childcare responsibilities, being particularly vulnerable to anxiety and depression [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the Pakistani context, usually the family members provide care to the dialysis patients.\u003c/p\u003e\u003cp\u003eMany patients rely on these caregivers for assistance in usual daily activities that intensifies the physical and emotional demands on caregivers. The reliance of these patients on hemodialysis highlights the multifaceted challenges caregivers face, further highlights the need to address their quality of life to mitigate the broader impact of CKD.\u003c/p\u003e\u003cp\u003eStudies consistently show that caregivers of hemodialysis patients reported higher rates of anxiety and depression compared to the general population [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Research indicates that 28.8–52% of caregivers experience moderate to high levels of anxiety and depression. Key factors influencing these outcomes include caregivers’ age, education level, financial status, and perceived social support [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, assessments using validated tools such as the Hospital Anxiety and Depression Scale (HADS), Short Form-36 (SF-36), and Pittsburgh Sleep Quality Index (PSQI) reveal that caregivers often experience poorer sleep quality than the patients they care for [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGiven the variability in socioeconomic conditions, cultural norms, societal roles, and language across different regions, the psychological impact of caregiving is likely to differ significantly between populations. These contextual factors influence both the manifestation of mental health symptoms and the effectiveness of assessment tools. In the Pakistani context, where caregiving responsibilities are often informal and heavily gendered, there is a notable gap in research assessing the mental health of caregivers using standardized, validated instruments.\u003c/p\u003e\u003cp\u003eTo our knowledge, no prior study in Pakistan has evaluated the prevalence of Major Depressive Disorder (MDD) and Generalized Anxiety Disorder (GAD) among caregivers of hemodialysis patients using culturally and linguistically validated screening tools. Therefore, this study aimed to fill that gap by estimating the prevalence of MDD and GAD using the Urdu versions of PHQ-9 and GAD-7, and by identifying key sociodemographic and caregiving-related predictors. Understanding these factors is essential for developing targeted interventions to mitigate caregiver burden within the local context.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003eThis study employed a cross-sectional design to assess the prevalence and associated factors of depression and anxiety among caregivers of end-stage renal disease (ESRD) patients undergoing hemodialysis. The study was conducted at multiple dialysis centers in Pakistan between December 1st, 2024, to April 30th, 2025. The study population included primary caregivers of patients receiving hemodialysis at the facilities. Caregivers aged 18 or above who had been providing care to the patient for at least three months were included. Caregivers diagnosed with psychiatric illnesses prior to caregiving or those unwilling to participate were excluded. Similarly, those having cognitive impairment that can interfere with participation, or inability to understand Urdu language were also excluded. A total of 362 caregivers were recruited using non-random convenience sampling. An initial sample size of 327 was calculated with the help of Raosoft sample size calculator, using 95% confidence level, 5% margin of error and 31.6% prevalence of depression and anxiety among caregivers of ESRD patients, based on an African study [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. To account for potential incomplete or missing responses, sample size was increased by 10%, bringing the target to 360. However, final data collection yielded 362 valid responses, which were included in the analysis.\u003c/p\u003e\u003cp\u003eThe data were collected using a structured questionnaire that contained four sections: demographics, intensity (hours per day) and duration (number of months) of caregiving, Patient Health Questionnaire (PHQ-9) for depression, and Generalized Anxiety Disorder (GAD-7) for anxiety. Both these scales are pre-validated in various languages, including Urdu, in which the whole questionnaire was administered [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. A total score ≥ 10 was considered indicative of at least moderate symptom severity on the PHQ-9. For a diagnosis of Major Depressive Disorder (MDD), we applied the standard PHQ-9 diagnostic criteria: the presence of five or more symptoms rated ≥ 2 (including either item 1 or 2), along with associated functional impairment. For Generalized Anxiety Disorder (GAD), a GAD-7 score ≥ 10 was used as the diagnostic cut-off.\u003c/p\u003e\u003cp\u003eThe questionnaire was administered to caregivers in dialysis centers by trained research assistants. The purpose of the study was explained to all the participants, and anonymity and confidentiality of the participants were assured. Informed written consent was obtained from all participants prior to data collection. Ethical approval was obtained from the IRB of Rahmah Foundation of Health, Islamabad, Pakistan.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePsychometric properties of PHQ-9 and GAD-7\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThis study assessed the psychometric properties of the Patient Health Questionnaire-9 (PHQ-9) and generalized anxiety disorder-7 (GAD-7) among caregivers of patients undergoing dialysis. Although a pre-validated Urdu translation of both scales was used, we conducted a comprehensive psychometric evaluation—including reliability testing, exploratory factor analysis (EFA), and confirmatory factor analysis (CFA)—to ensure rigorous validation within our target population. This was done to confirm the structural validity and internal consistency of the tools in the unique sociocultural context of caregivers in dialysis settings. Data analysis was performed using Jamovi version 2.6.6 [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eExploratory Factor Analysis (EFA) and Confirmatory Factor Analysis (CFA) were employed to examine the dimensional structure and construct validity of the scales, while reliability analysis was conducted to assess internal consistency.\u003c/p\u003e\u003cp\u003ePrior to factor analysis, reliability was evaluated using Cronbach’s alpha (α) and McDonald’s omega (ω). Both total scale reliability and item-level statistics (i.e., alpha if item deleted) were calculated. For EFA, the Factor module in Jamovi was used. Factor extraction was based on the minimum residual method, and factor rotation was performed using promax rotation, a method suitable for identifying correlated factors. Sampling adequacy was confirmed using the Kaiser-Meyer-Olkin (KMO) measure and Bartlett’s test of sphericity. The number of factors to retain was guided by eigenvalues (\u0026gt; 1), scree plot inspection, and theoretical interpretability.\u003c/p\u003e\u003cp\u003eFollowing EFA, CFA was conducted using the SEM (Structural Equation Modeling) module in Jamovi [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. Variables were treated as ordered categorical, and the estimation method was set to Diagonally Weighted Least Squares (DWLS), with robust standard errors and mean-adjusted scaled and shifted χ² tests. Model parameters were estimated with 95% confidence intervals. Latent variables were standardized with the first indicator fixed to 1, and the model incorporated intercepts and mean structure. The rotation algorithm used was GPA (Generalized Procrustes Analysis) with geomin rotation and geomin epsilon = 0.001. Missing data were handled using listwise deletion, and univariate constraints were applied. Model fit was evaluated using Comparative Fit Index, Tucker-Lewis Index, Root Mean Square Error of Approximation, Standardized Root Mean Square Residual, and chi-square statistics, including both classical and scaled estimates.\u003c/p\u003e\u003cp\u003eAfter psychometric validation, categorical demographic variables, individual PHQ-9 items, and GAD-7 items were summarized as frequencies and percentages. Non-normality of continuous variables (age, household income, intensity of caregiving, duration of caregiving, total depression score, and total anxiety score) was confirmed via the Kolmogorov-Smirnov test (p \u0026lt; 0.05); thus, medians and interquartile ranges (IQR) were computed.\u003c/p\u003e\u003cp\u003eIn inferential statistics, Spearman’s rank correlation was used to determine the correlation of depression and anxiety scores with the intensity and duration of caregiving. For group comparisons, the Mann-Whitney U test was used for binary categorical variables (e.g., gender, residence, living situation with the patient), and the Kruskal-Wallis H test was used for variables with more than two categories (e.g., marital status, education, occupation, kinship with the patient). U or H statistics, effect sizes (r for the Mann-Whitney U test and ε² for the Kruskal-Wallis H test), and asymptotic p-values were reported. Post hoc pairwise comparisons were conducted using Dunn’s test with Bonferroni correction, provided the Kruskal-Wallis H test was significant. The Chi square test was used to determine association of categorical demographic variables with major depressive disorder and generalized anxiety disorder.\u003c/p\u003e\u003cp\u003eIn multivariate analysis, two separate generalized linear models, with a negative binomial distribution and logarithmic link function, were applied using depression and anxiety scores as outcomes. Model assumptions were verified, including count-type outcome, independence of observations, linearity on the log scale for continuous predictors, absence of multicollinearity (VIF \u0026lt; 5), and no influential outliers, assessed by Cook’s distances and leverage values, both of which were well below 1. Only 1.7% of standardized deviance residuals exceeded |2| for the depression model. For the anxiety model, all assumptions were also met, with only 0.8% of standardized deviance residuals above the |2| threshold.\u003c/p\u003e\u003cp\u003eFor both models, the deviance/df ratio was approximately 0.6, indicating under-dispersion, which is atypical for negative binomial models. However, when the same model was re-estimated using a Poisson distribution with a log link, the deviance/df exceeded 3, and the AIC and BIC values were higher, suggesting that the negative binomial model provided a better fit to the data.\u003c/p\u003e\u003cp\u003eTo predict the presence of major depressive disorder and generalized anxiety disorder, two binary logistic regression models were applied. Assumptions of binary dependent variable, independence of observations, linearity of the logit with continuous predictors, absence of multicollinearity, and no influential outliers were met. In the anxiety model, among the three continuous predictors, two met the logit-linearity assumption, while the third—duration of caregiving—required logarithmic transformation. Outliers were evaluated using Cook’s distances and leverage values, all of which were well below 1, and only 4.7% of deviance residuals exceeded |2|.\u003c/p\u003e\u003cp\u003eBased on the rule of 10 events per predictor variable, the model for major depressive disorder included only two predictors: intensity and duration of caregiving [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The model for generalized anxiety disorder included six predictors: gender, age, residence, kinship with the patient, intensity, and log-transformed duration of caregiving.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cb\u003eExploratory and confirmatory factor analysis of PHQ-9 and GAD-7\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e\u003cb\u003ePHQ-9\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe PHQ-9 showed strong internal consistency, with Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.864 and McDonald\u0026rsquo;s ω\u0026thinsp;=\u0026thinsp;0.864. Item-level analysis demonstrated minimal variability in reliability when any item was removed, with values of α if item deleted ranging from 0.836 to 0.872. The KMO measure of sampling adequacy was 0.893, and Bartlett\u0026rsquo;s test of sphericity was significant (χ\u0026sup2;(36)\u0026thinsp;=\u0026thinsp;1215, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), supporting the factorability of the correlation matrix.\u003c/p\u003e\u003cp\u003eEFA suggested a two-factor structure, explaining 48.51% of the variance (Factor 1\u0026thinsp;=\u0026thinsp;35.87%, Factor 2\u0026thinsp;=\u0026thinsp;12.64%). The first factor included items related to somatic-cognitive symptoms (PHQ_1 to PHQ_5, PHQ_7), while the second factor comprised affective symptoms (PHQ_6, PHQ_8, PHQ_9). Inter-factor correlation was moderately high (r\u0026thinsp;=\u0026thinsp;0.635), suggesting related but distinct constructs.\u003c/p\u003e\u003cp\u003eCFA confirmed the two-factor model with good model fit: χ\u0026sup2;(26)\u0026thinsp;=\u0026thinsp;56.86, p\u0026thinsp;\u0026lt;\u0026thinsp;.001; CFI\u0026thinsp;=\u0026thinsp;0.993, TLI\u0026thinsp;=\u0026thinsp;0.991, SRMR\u0026thinsp;=\u0026thinsp;0.049, and RMSEA (scaled)\u0026thinsp;=\u0026thinsp;0.0887 (90% CI: 0.0707\u0026ndash;0.1075). All factor loadings were statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), ranging from 0.511 (PHQ_9) to 0.851 (PHQ_6). The two latent factors were significantly correlated (r\u0026thinsp;=\u0026thinsp;0.790, p\u0026thinsp;\u0026lt;\u0026thinsp;.001), reinforcing the presence of interrelated symptom domains within depression.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGAD-7\u003c/b\u003e\u003c/p\u003e\u003cp\u003eFor the GAD-7, reliability analysis revealed Cronbach\u0026rsquo;s α\u0026thinsp;=\u0026thinsp;0.852 and McDonald\u0026rsquo;s ω\u0026thinsp;=\u0026thinsp;0.857, indicating excellent internal consistency. Item-level reliability remained stable, with α if item deleted ranging from 0.812 to 0.843. The KMO value was 0.875, and Bartlett\u0026rsquo;s test of sphericity was significant (χ\u0026sup2; (21)\u0026thinsp;=\u0026thinsp;971.6, p\u0026thinsp;\u0026lt;\u0026thinsp;.001).\u003c/p\u003e\u003cp\u003eEFA results supported a unidimensional factor structure, accounting for 46.68% of the total variance, with item factor loadings ranging from 0.585 (GAD_6) to 0.826 (GAD_2). PCA and eigenvalue analysis further confirmed the dominance of a single latent construct.\u003c/p\u003e\u003cp\u003eThe one-factor CFA model demonstrated excellent fit: χ\u0026sup2;(14)\u0026thinsp;=\u0026thinsp;28.07, p\u0026thinsp;=\u0026thinsp;.014, CFI\u0026thinsp;=\u0026thinsp;0.996, TLI\u0026thinsp;=\u0026thinsp;0.994, SRMR\u0026thinsp;=\u0026thinsp;0.038, and RMSEA (scaled)\u0026thinsp;=\u0026thinsp;0.0866 (90% CI: 0.0622\u0026ndash;0.1124). Standardized factor loadings ranged from 0.639 (GAD_6) to 0.877 (GAD_2), all statistically significant (p\u0026thinsp;\u0026lt;\u0026thinsp;.001), confirming that all items contributed meaningfully to a unidimensional anxiety construct.\u003c/p\u003e\u003cp\u003eA detailed description of the statistical procedures, parameters, thresholds, and software settings is provided in the supplementary tables S12-S46 and supplementary figures \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e-S7.\u003c/p\u003e\u003cp\u003e Our study included 362 caregivers, with nearly equal numbers of males and females. About three-fourths of the participants were urban residents, while the remainder were from rural areas. Over 80% were married. Secondary education was most common, followed by equal proportions of middle school and university education. Fewer were illiterate or had elementary or postgraduate education. More than half were unemployed. Two-fifths were spouses of patients, while one-fifth each were parents or children. Over 90% co-resided with patients; fewer than 10% lived separately. The demographic features of participants are presented in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Table \u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequencies and Percentages of Categorical Demographics, and Chi square test for Association of Demographics with Major Depressive Disorder and Generalized Anxiety Disorder.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c6\" namest=\"c5\"\u003e\u003cp\u003eMajor Depressive Disorder\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c8\" namest=\"c7\"\u003e\u003cp\u003eGeneralized Anxiety Disorder\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequencies (N)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentages (%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eX2 (df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003eX2 (df)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e171\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e47.20%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e3.321 (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.068\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e6.261 (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.012\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e52.80%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.137 (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e5.809 (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e264\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e72.90%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e58\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e16.00%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e10.555 (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e8.082 (3)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.80%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.40%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.80%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.10%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e11.276 (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.046\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e7.186 (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.207\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElementary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.90%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e104\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.70%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.30%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e21.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e160\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.20%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e9.748 (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e5.005 (2)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e196\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e54.40%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.40%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eKinship with the patient\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChildren\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.70%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e7.709 (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.173\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e14.775 (5)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19.30%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpouse / Partners\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e148\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e40.90%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSiblings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.60%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExtended Family (aunts, uncles, etc)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.00%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOther\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.50%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eLiving situation with the patient\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLive with patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e334\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92.30%\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.812 (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.368\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.317 (1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.573\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLive separately from patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.70%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive Statistics of Continuous Variables\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedian\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1st quartile\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3rd quartile\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eInterquartile range\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e15\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eHousehold income (PKR)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e42,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e30,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e60,000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30,000\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIntensity of caregiving (hours/day)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration of caregiving (months)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e26\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e52\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal depression score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eTotal anxiety score\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.25\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eBased on PHQ-9, 41.4% had minimal depression; based on GAD-7, 44.5% had minimal anxiety. Mild depression (33.4%) and mild anxiety (37.3%) were also comparable. However, frequencies of moderate and severe levels differed, possibly due to differences in categorization. While 14.4% of participants reported moderate to severe symptoms (PHQ-9\u0026thinsp;\u0026ge;\u0026thinsp;10), only 8% met the diagnostic criteria for Major Depressive Disorder (MDD) based on symptom pattern, presence of core symptoms, and functional impairment, as outlined in the PHQ-9 diagnostic algorithm. On the other hand, Generalized Anxiety Disorder showed a slightly higher percentage, i.e., 18.2% (N\u0026thinsp;=\u0026thinsp;=\u0026thinsp;66). Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e depicts the frequencies and percentages of depression and anxiety levels.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eFrequencies and Percentages of Depression and Anxiety Levels\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"4\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eFrequencies (N)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ePercentages (%)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003ePHQ-9 Symptom Severity Categories Based on Total Scores\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinimal depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e150\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e121\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e33.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerately severe depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.7%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere depression\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.4%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eGAD-7 Symptom Severity Categories Based on Total Scores\u003c/b\u003e\u003csup\u003e\u003cb\u003ea\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMinimal anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e161\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e44.5%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMild anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e135\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e37.3%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eModerate anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSevere anxiety\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e3.6%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eMajor Depressive Disorder\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e333\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e92%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGeneralized Anxiety Disorder\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAbsent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e296\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81.80%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePresent\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.20%\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003csup\u003ea\u003c/sup\u003eThese categories reflect symptom severity based on PHQ-9 scores. They do not indicate clinical diagnosis. A diagnosis of Major Depressive Disorder (MDD) requires meeting specific criteria using the PHQ-9 diagnostic algorithm.\u003c/p\u003e\u003cp\u003eChi-square test revealed a significant association of major depressive disorder with gender (χ\u0026sup2; (1)\u0026thinsp;=\u0026thinsp;3.321, p\u0026thinsp;=\u0026thinsp;0.068), marital status (χ\u0026sup2; (3)\u0026thinsp;=\u0026thinsp;10.555, p\u0026thinsp;=\u0026thinsp;0.014), education (χ\u0026sup2; (5)\u0026thinsp;=\u0026thinsp;11.276, p\u0026thinsp;=\u0026thinsp;0.046), and occupation (χ\u0026sup2; (2)\u0026thinsp;=\u0026thinsp;9.748, p\u0026thinsp;=\u0026thinsp;0.008). Generalized anxiety disorder was significantly associated with gender (χ\u0026sup2; (1)\u0026thinsp;=\u0026thinsp;6.261, p\u0026thinsp;=\u0026thinsp;0.012), residence (χ\u0026sup2; (1)\u0026thinsp;=\u0026thinsp;5.809, p\u0026thinsp;=\u0026thinsp;0.016), marital status (χ\u0026sup2; (3)\u0026thinsp;=\u0026thinsp;8.082, p\u0026thinsp;=\u0026thinsp;0.044), and kinship with the patient (χ\u0026sup2; (5)\u0026thinsp;=\u0026thinsp;14.775, p\u0026thinsp;=\u0026thinsp;0.011). The results of Chi square test are given in Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003eDepression and anxiety scores were strongly correlated (Spearman\u0026rsquo;s ρ\u0026thinsp;=\u0026thinsp;0.622, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Depression was weakly positively correlated with caregiving intensity (Spearman\u0026rsquo;s ρ\u0026thinsp;=\u0026thinsp;0.143, p\u0026thinsp;=\u0026thinsp;0.007), and weakly negatively correlated with duration (Spearman\u0026rsquo;s ρ=-0.168, p\u0026thinsp;=\u0026thinsp;0.001). Anxiety showed no significant correlation with either.\u003c/p\u003e\u003cp\u003eDepression was significantly associated with gender (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with higher scores among females (r\u0026thinsp;=\u0026thinsp;0.207). Association with marital status was also significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with highest scores in widowed, followed by married, divorced, and single caregivers. However, low frequencies of widowed (n\u0026thinsp;=\u0026thinsp;5) and divorced (n\u0026thinsp;=\u0026thinsp;3) limit interpretation. Effect size (ε\u0026sup2;) was minimal. Education level was significantly associated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); scores were highest among university graduates, followed by postgraduates, secondary, elementary, middle school, and illiterate caregivers. Only university-level scores significantly differed from others. Employment status showed significant differences (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with lowest scores in employed, followed by unemployed and retired caregivers. Caregiver-patient relationship also showed significant association (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with highest depression in parents, followed by others, spouses, family, siblings, and children. Results of Mann-Whitney U test and Kruskal-Wallis H test for depression are presented in Table \u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNon-Parametric Analysis of Median PHQ-9 Scores by Sociodemographic and Caregiving Characteristics in Dialysis Caregivers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedian PHQ-9 scores\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eU or H statistics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEffect sizes (|r| and epsilon squared)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAsymptomatic p value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e20233.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.207\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e12391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.033\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.536\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eMarital status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e22.496\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18\u0026thinsp;\u0026minus;\u0026thinsp;14\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.5-3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e59.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElementary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7-3.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.5-4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.5\u0026ndash;1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e29.077\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e0.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9-2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4\u0026ndash;7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eKinship with the patient\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChildren\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e38.885\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.086\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpouse / Partners\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7-2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSiblings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExtended Family (aunts, uncles, etc)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e11.5\u0026ndash;1.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eLiving situation with the patient\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLive with patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4354\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.543\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLive separately from patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eAnxiety showed similar patterns. It was significantly associated with gender (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with higher scores in females (r\u0026thinsp;=\u0026thinsp;0.304). Marital status was significant (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with highest anxiety in widowed, then married, divorced, and single participants, though low subgroup frequencies again limit conclusions. Anxiety was also significantly associated with education (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001); the highest scores were in university-educated caregivers, followed by postgraduates, secondary, middle school, elementary, and illiterate. Pairwise differences were significant between university-level and lower education groups. Employment status was significantly associated (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), with employed caregivers showing the lowest anxiety. Pairwise differences were found between employed vs. unemployed and employed vs. retired. Anxiety varied across caregiver roles (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), highest in parents, followed by spouses, others, siblings, family, and children. Parents had significantly higher anxiety than children and siblings, but not spouses or others. No significant association was found between depression or anxiety scores and caregiver residence (urban/rural). Non-parametric tests for anxiety are present in Table \u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eNon-Parametric Analysis of Median GAD-7 Scores by Sociodemographic and Caregiving Characteristics in Dialysis Caregivers\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eCategories\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eMedian GAD-7 Scores\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eInterquartile Range\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eU or H statistics\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eEffect sizes (r and epsilon squared)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eAsymptomatic p value\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e22069\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.304\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFemale\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRural\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e13634.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.042\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.428\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUrban\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eMarital Status\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e16.724\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.037\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eWidowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14\u0026thinsp;\u0026minus;\u0026thinsp;7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDivorced\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5-4.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eEducation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNone\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.5\u0026ndash;2.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e15.284\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.009\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eElementary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.5-3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMiddle school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u0026thinsp;\u0026minus;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSecondary school\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePostgraduate\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.5-1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUniversity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u003cb\u003eOccupation\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e23.231\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRetired\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10\u0026thinsp;\u0026minus;\u0026thinsp;5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDisable\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u003cb\u003eKinship with the patient\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eChildren\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e25.535\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e0.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"5\" rowspan=\"6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eParents\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSpouse / Partners\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e9\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eSiblings\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e3.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eExtended Family (aunts, uncles, etc)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6\u0026thinsp;\u0026minus;\u0026thinsp;1\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOthers\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e\u003cb\u003eLiving situation with the patient\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLive with patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8\u0026thinsp;\u0026minus;\u0026thinsp;3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e4616\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003e0.91\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eLive separately from patient\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.5\u0026ndash;2.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eGeneralized linear models revealed that, after adjusting for other predictors, depression was significantly higher across all education levels compared to the reference category (university education). It was also negatively associated with the duration of caregiving in months (B = -0.003, p\u0026thinsp;=\u0026thinsp;0.043). In contrast, none of the predictors were significantly associated with anxiety scores in the generalized linear model. Results of generalized linear models are provided in supplementary files.\u003c/p\u003e\u003cp\u003eBinary logistic regression found that major depressive disorder was significantly associated with caregiving intensity (OR\u0026thinsp;=\u0026thinsp;1.101, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), while generalized anxiety disorder was significantly associated with age (OR\u0026thinsp;=\u0026thinsp;1.045, p\u0026thinsp;=\u0026thinsp;0.001), gender (OR\u0026thinsp;=\u0026thinsp;1.886, p\u0026thinsp;=\u0026thinsp;0.039), residence (OR\u0026thinsp;=\u0026thinsp;2.271, p\u0026thinsp;=\u0026thinsp;0.032), and natural logarithm of caregiving duration (OR\u0026thinsp;=\u0026thinsp;1.363, p\u0026thinsp;=\u0026thinsp;0.008). Tables\u0026nbsp;8 and 9 present the results of binary logistic regression.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab6\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 6\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBinary Logistic Regression of major depressive disorder\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegression Coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIntensity of caregiving (daily hours)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.096\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.022\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.101\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eDuration of caregiving (months)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.383\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.996\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConstant\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-3.242\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.370\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab7\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 7\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBinary Logistic Regression of generalized anxiety disorder\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eParameters\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRegression Coefficient\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eStandard Error\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003ep value\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOdds Ratio\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eAge (years)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.044\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.045\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.634\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.307\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.039\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.886\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eResidence\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.820\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.383\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.032\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e2.271\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eKinship with the patients\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.056\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.134\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.677\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.946\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eIntensity of caregiving (daily hours)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.532\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.987\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eLn (Duration of caregiving)\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e0.310\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e0.117\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.008\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e1.363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e\u003cb\u003eConstant\u003c/b\u003e\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e-6.457\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e1.112\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e\u003cp\u003e0.000\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c5\"\u003e\u003cp\u003e0.002\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eWe confirmed prior study on psychological distress in dialysis caretakers with MDD and GAD. Our sample is unique, but 8% for MDD and 18.2% for GAD are consistent with previous patterns showing a significant mental health burden on chronically ill caregivers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Alshelleh et al. (2023) evaluated sadness and anxiety in hemodialysis patients, showing the frequency of mental health concerns that can impair caretakers [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Our study builds on Gerogianni et al. (2021)'s hemodialysis caregiver anxiety and melancholy study [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eGlobal study reveals female caregivers have more depression and anxiety [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. According to Pacheco Barzallo et al. (2024) [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], female caregivers may perform more or diversified activities, increasing psychological strain. In addition to our gender-specific findings, Al Maqbali et al. (2025) found greater subjective stress, anxiety, and depression in female hemodialysis family caregivers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This study-wide finding emphasizes gender-sensitive caregiver support. Female caregivers are susceptible due to the \"double burden\" of tasks and social expectations [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Disease awareness and performance demands may annoy university-educated caretakers. Social and financial stability safeguard jobs. Parents were most stressed by children's strong emotional bonds [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur study indicated that widowed and married caregivers had better mental health, highlighting the complex interplay between social support and suffering. Social support affects caregiver well-being, although study populations and methodology prevent direct comparisons [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. Shukri et al. showed in 2020 that strong social networks improve hemodialysis caregiver load, quality of life, anxiety, and sadness [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Wang et al. (2024) underlined social support and family resilience in maintenance hemodialysis patients' psychological well-being, which resonates with caretakers [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur findings also show that caregiver melancholy and anxiety are highly linked to education and employment. Specifically, employed caregivers were least anxious. For all degree levels, university graduates had the most depression (median 1.5) and anxiety (median 3). These findings suggest that while socioeconomic factors and intellectual engagement may generally protect, higher disease awareness and performance demands may lead university-educated caregivers to be more attuned to and prone to expressing their mental health symptoms, contributing to their higher scores. This enhanced awareness may also increase their use of mental health resources, which could affect their scores. Ibrahim et al. (2022) are studying the effects of psychosocial and economic factors on end-stage renal disease patients and their caregivers' quality of life, which is similar to our findings on employment and education [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Hemodialysis caretakers' mental health suffers from emotional support and household management [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eKinship affects patient and caregiver mental health, with parents experiencing the highest depression and anxiety. Patient parents worry and despair most, hence caregiver-patient relationships affect mental health. Any age hemodialysis child's care is emotionally draining. Chronically ill children's parents suffer, study finds [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. Chronically unwell children present emotional and practical concerns for parents. Indonesian hemodialysis caregivers' burden, anxiety, sadness, and quality of life were evaluated by Pio et al. (2022). While not addressing kinship, their work helps explain caregiver burden, which varies by patient connection [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Fu et al. (2022) demonstrated that caregiver depression is strongly linked to hemodialysis patients' depression and hospitalization, underscoring the importance of caregiver mental health, especially in parent-child relationships [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eOur investigation found no correlation between caregiver urban/rural residence and patient living circumstances and depression and anxiety ratings. This contradicts the perception that rural caregivers are secluded or that co-residence stresses them. It reinforces studies that indicate caring burdens transcend geographical and cohabitation boundaries because the fundamental concerns remain [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Alnasser et al. (2025) examined hemodialysis and peritoneal dialysis caregivers' quality of life in Saudi Arabia. While not addressing residence, their data show universal caregiver stress [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eTo ensure the robustness and comparability of our findings, we estimated prevalence using the Patient Health Questionnaire-9 (PHQ-9) and Generalized Anxiety Disorder-7 (GAD-7). These are thorough psychometric instruments known for their high internal consistency and well-established component structures. The two-factor structure observed for PHQ-9 (somatic-cognitive and affective symptoms) and the unidimensional structure for GAD-7 in our psychometric measurements are consistent with the widely reported properties of these instruments in the literature [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. This consistency reinforces the validity of our measurements within this specific population, thereby enhancing the comparability of our findings with other studies that utilize these widely accepted tools [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. The methodological rigor applied in our assessment of MDD and GAD prevalence directly supports the subsequent implications and recommendations derived from our study.\u003c/p\u003e\u003cp\u003eGiven the high prevalence of MDD and GAD among dialysis caregivers, our findings strongly advocate for the routine integration of mental health screening within nephrology care settings, utilizing validated methods such as PHQ-9 and GAD-7. These results also suggest the development of gender-specific support programs, particularly for vulnerable female caregivers [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], and tailored therapies that address caregiving intensity, age, gender, domicile, and duration characteristics for anxiety. The strong correlation observed between depression and anxiety scores further suggests that holistic mental health support, rather than standalone treatments, may be more beneficial. Recognizing that caregiver psychological discomfort directly impacts patient outcomes, hospitalization rates, and healthcare expenses, we recommend that healthcare policies prioritize the allocation of funding for support programs and the seamless integration of mental health services into dialysis centers [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]. This approach aligns with the stress-coping model and biopsychosocial frameworks for caregiver mental health in chronic disease management, which acknowledge the distinct yet overlapping risk factors for MDD and GAD.\u003c/p\u003e\u003cp\u003eOur work sheds light on MDD and GAD in dialysis caretakers, however it has limitations. Cross-sectional research cannot prove causality, hence longitudinal studies are needed to explore temporal correlations. Our geographically constrained sample of 362 caregivers may limit generalizability to other cultures and healthcare environments. Self-reported tests (PHQ-9 and GAD-7) may be biased by social stigma, stressing the necessity for cognitive interviews by experienced psychiatrists to increase validity. Confounding variables such patients' functional state, dialysis duration, and caregivers' pre-existing diseases were not carefully examined. Finally, we did not examine caregiver-beneficial support kinds or interventions, a significant gap for tailored interventions.\u003c/p\u003e\u003cp\u003eProspective longitudinal studies should track caregiver mental health trajectories and identify early predictors of MDD and GAD to enable proactive intervention. Building on peer support findings by Ghenaati et al. (2024) [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], gender-specific support groups and digital mental health platforms are priorities. Understanding caregivers' lives and informing culturally relevant solutions requires qualitative research through interviews and focus groups. Comparative studies of mental health burden across renal replacement therapies (extending Alnasser et al. (2025) [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]) and economic impact assessments quantifying caregiver distress-related healthcare costs are essential for evidence-based policy frameworks. To make caregiver well-being core to chronic illness management, these studies should follow Nguyen and Vo (2025) [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e] integrated care approaches.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAIC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Akaike Information Criterion\u003c/p\u003e\n\u003cp\u003eB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Regression Coefficient\u003c/p\u003e\n\u003cp\u003eBIC\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Bayesian Information Criterion\u003c/p\u003e\n\u003cp\u003eCFA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Confirmatory Factor Analysis\u003c/p\u003e\n\u003cp\u003eCKD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Chronic Kidney Disease\u003c/p\u003e\n\u003cp\u003eEFA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Exploratory Factor Analysis\u003c/p\u003e\n\u003cp\u003e\u0026epsilon;\u0026sup2;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Epsilon Squared (Effect Size for Kruskal-Wallis test)\u003c/p\u003e\n\u003cp\u003eESRD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;End-Stage Renal Disease\u003c/p\u003e\n\u003cp\u003eGAD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Generalized Anxiety Disorder\u003c/p\u003e\n\u003cp\u003eGAD-7\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Generalized Anxiety Disorder \u0026ndash; 7 item scale\u003c/p\u003e\n\u003cp\u003eHADS\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Hospital Anxiety and Depression Scale\u003c/p\u003e\n\u003cp\u003eHD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Hemodialysis\u003c/p\u003e\n\u003cp\u003eIRB\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Institutional Review Board\u003c/p\u003e\n\u003cp\u003eIQR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Interquartile Range\u003c/p\u003e\n\u003cp\u003eKMO\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Kaiser-Meyer-Olkin\u003c/p\u003e\n\u003cp\u003eMDD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Major Depressive Disorder\u003c/p\u003e\n\u003cp\u003eOR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Odds Ratio\u003c/p\u003e\n\u003cp\u003ep\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;p-value (Significance level)\u003c/p\u003e\n\u003cp\u003ePHQ-9\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Patient Health Questionnaire \u0026ndash; 9 item scale\u003c/p\u003e\n\u003cp\u003ePKR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Pakistani Rupee\u003c/p\u003e\n\u003cp\u003ePSQI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Pittsburgh Sleep Quality Index\u003c/p\u003e\n\u003cp\u003er\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Effect Size / Spearman\u0026rsquo;s Correlation Coefficient\u003c/p\u003e\n\u003cp\u003e\u0026rho; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Spearman\u0026rsquo;s Rank Correlation Coefficient\u003c/p\u003e\n\u003cp\u003eRMSEA\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Root Mean Square Error of Approximation\u003c/p\u003e\n\u003cp\u003eSEM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Structural Equation Modeling\u003c/p\u003e\n\u003cp\u003eSF-36\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Short Form-36 Health Survey\u003c/p\u003e\n\u003cp\u003eSRMR\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standardized Root Mean Square Residual\u003c/p\u003e\n\u003cp\u003eTLI\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Tucker-Lewis Index\u003c/p\u003e\n\u003cp\u003eVIF\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Variance Inflation Factor\u003c/p\u003e\n\u003cp\u003e\u0026chi;\u0026sup2; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Chi-square\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the participating hospitals, staff, and patients for their cooperation. Special thanks to the research assistants and data collectors for their contributions to the successful completion of this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no external funding.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted after obtaining ethical approval from the Institutional Review Board of Rahmah Health Foundation, Islamabad, Pakistan (Approval No RHF-04-2024). Written informed consent was obtained from all participants before inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical trial number \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the ethical principles outlined in the Declaration of Helsinki. \u0026nbsp;Written informed consent was obtained from all participants prior to inclusion in the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data supporting this study\u0026apos;s findings are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConceptualization: M.U.H.\u003c/p\u003e\n\u003cp\u003eMethodology: M.U.H., M.U., M.I.J., M.A., T.S., F.S., S.T, H.K, H.R, I.S, L.F\u003c/p\u003e\n\u003cp\u003eFormal Analysis and Investigation: M.U.H., M.U.\u003c/p\u003e\n\u003cp\u003eWriting - Original Draft Preparation: M.U.H., M.U., M.I., M.A., F.S., A,F.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWriting - Review and Editing: M.U.H.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eShukri, M., et al., \u003cem\u003eBurden, quality of life, anxiety, and depressive symptoms among caregivers of hemodialysis patients: The role of social support.\u003c/em\u003e The International Journal of Psychiatry in Medicine, 2020. 55(6): p. 397-407.\u003c/li\u003e\n\u003cli\u003eAlshelleh, S., et al., \u003cem\u003eLevel of depression and anxiety on quality of life among patients undergoing hemodialysis.\u003c/em\u003e International journal of general medicine, 2023: p. 1783-1795.\u003c/li\u003e\n\u003cli\u003eGerogianni, G., et al. \u003cem\u003eFactors affecting anxiety and depression in caregivers of hemodialysis patients\u003c/em\u003e. in \u003cem\u003eGeNeDis 2020: Geriatrics\u003c/em\u003e. 2021. 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PMID: 30108380.\u003c/li\u003e\n\u003cli\u003eAhmad S, Hussain S, Shah FS, Akhtar F. Urdu translation and validation of GAD-7: A screening and rating tool for anxiety symptoms in primary health care. J Pak Med Assoc. 2017 Oct;67(10):1536-1540. PMID: 28955070.Alshelleh S, Alhawari H, Alhouri A, Abu-Hussein B, Oweis A. Level of Depression and Anxiety on Quality of Life Among Patients Undergoing Hemodialysis. Int J Gen Med. 2023 May 10;16:1783-1795. doi: 10.2147/IJGM.S406535. PMID: 37193250; PMCID: PMC10183175.\u003c/li\u003e\n\u003cli\u003eThe jamovi project (2024). jamovi. (Version 2.6) [Computer Software]. Retrieved from https://www.jamovi.org.\u003c/li\u003e\n\u003cli\u003eGallucci, M., Jentschke, S. (2021). SEMLj: jamovi SEM Analysis. [jamovi module]. For help please visit https://semlj.github.io/.\u003c/li\u003e\n\u003cli\u003eRevelle, W. (2023). psych: Procedures for Psychological, Psychometric, and Personality Research. [R package]. Retrieved from https://cran.r-project.org/package=psych.\u003c/li\u003e\n\u003cli\u003eEpskamp S. , Stuber S., Nak J., Veenman M,, Jorgensen T.D. (2019). semPlot: Path Diagrams and Visual Analysis of Various SEM Packages\u0026apos; Output. [R Package]. Retrieved from https://CRAN.R-project.org/package=semPlot.\u003c/li\u003e\n\u003cli\u003ePeduzzi P, Concato J, Kemper E, Holford TR, Feinstein AR. A simulation study of the number of events per variable in logistic regression analysis. J Clin Epidemiol. 1996 Dec;49(12):1373-9. doi: 10.1016/s0895-4356(96)00236-3. PMID: 8970487.\u003c/li\u003e\n\u003cli\u003eAlshelleh S, Alhawari H, Alhouri A, Abu-Hussein B, Oweis A. Level of Depression and Anxiety on Quality of Life Among Patients Undergoing Hemodialysis. Int J Gen Med. 2023 May 10;16:1783-1795. doi: 10.2147/IJGM.S406535. PMID: 37193250; PMCID: PMC10183175.\u003c/li\u003e\n\u003cli\u003eGerogianni G, Polikandrioti M, Alikari V, Vasilopoulos G, Zartaloudi A, Koutelekos I, Kalafatakis F, Babatsikou F. Factors Affecting Anxiety and Depression in Caregivers of Hemodialysis Patients. Adv Exp Med Biol. 2021;1337:47-58. doi: 10.1007/978-3-030-78771-4_6. PMID: 34972890.\u003c/li\u003e\n\u003cli\u003ePacheco Barzallo D, Schnyder A, Zanini C, et al. Gender Differences in Family Caregiving. Do female caregivers do more or undertake different tasks?. BMC Health Serv Res. 2024;24:730. https://doi.org/10.1186/s12913-024-11191-w\u003c/li\u003e\n\u003cli\u003eShukri M, Mustofai MA, Md Yasin MAS, Tuan Hadi TS. Burden, quality of life, anxiety, and depressive symptoms among caregivers of hemodialysis patients: The role of social support. Int J Psychiatry Med. 2020 Nov;55(6):397-407. doi: 10.1177/0091217420913388. Epub 2020 Mar 26. PMID: 32216495.\u003c/li\u003e\n\u003cli\u003eNazir, S., Raza, H., Nisar, M., Rashid, Z., et al. (2023). Assessment of Anxiety and Burden on caregivers for haemodialysis patients in southern Punjab, Pakistan. Fabad Eczacılık Bilimler Dergisi, 48(1), 53-60. https://doi.org/10.55262/fabadeczacilik.1099539\u003c/li\u003e\n\u003cli\u003eAl Maqbali A, Al Omari O, Abu Sharour L, Al-Naamani Z, Al Khatri M, Sanad HM, Al Hashmi I, Alkhawaldeh A, Al Qadire M, Al Omari D. The perceived levels of stress, anxiety and depression among family caregivers of patients undergoing haemodialysis and their association with quality of life. BJPsych Open. 2025 May 13;11(3):e100. doi: 10.1192/bjo.2025.44. PMID: 40357747; PMCID: PMC12089806.\u003c/li\u003e\n\u003cli\u003eNguyen AM, Vo LH. Mental health and quality of life in dialysis and transplant patients in Vietnam: a call for integrated care models. Front Psychiatry. 2025 May 6;16:1570138. doi: 10.3389/fpsyt.2025.1570138. PMID: 40395465; PMCID: PMC12089989.\u003c/li\u003e\n\u003cli\u003ePio TMT, Prihanto JB, Jahan Y, Hirose N, Kazawa K, Moriyama M. Assessing Burden, Anxiety, Depression, and Quality of Life among Caregivers of Hemodialysis Patients in Indonesia: A Cross-Sectional Study. Int J Environ Res Public Health. 2022 Apr 9;19(8):4544. doi: 10.3390/ijerph19084544. PMID: 35457412; PMCID: PMC9032362.\u003c/li\u003e\n\u003cli\u003eWang Y, Qiu Y, Ren L, Jiang H, Chen M, Dong C. Social support, family resilience and psychological resilience among maintenance hemodialysis patients: a longitudinal study. BMC Psychiatry. 2024 Jan 26;24(1):76. doi: 10.1186/s12888-024-05526-4. PMID: 38279114; PMCID: PMC10811847.\u003c/li\u003e\n\u003cli\u003eFu L, Wu Y, Zhu A, Wang Z, Qi H. Depression of caregivers is significantly associated with depression and hospitalization of hemodialysis patients. Hemodial Int. 2022 Jan;26(1):108-113. doi: 10.1111/hdi.12967. Epub 2021 Jul 5. PMID: 34227223.\u003c/li\u003e\n\u003cli\u003eIbrahim N, Chu SY, Siau CS, Amit N, Ismail R, Abdul Gafor AH. The effects of psychosocial and economic factors on the quality of life of patients with end-stage renal disease and their caregivers in Klang Valley, Malaysia: protocol for a mixed-methods study. BMJ Open. 2022 Jun 3;12(6):e059305. doi: 10.1136/bmjopen-2021-059305. PMID: 36691236; PMCID: PMC9171257.\u003c/li\u003e\n\u003cli\u003eAlnasser HA, BinMuneif YA, Alrsheed SF, Alqahtani SA, Alhaisoni FE, Algadheb HA, Alateeq NM. Quality of Life Among Caregivers of Patients Undergoing Hemodialysis Versus Peritoneal Dialysis in Saudi Arabia: A Cross-Sectional Study. Cureus. 2025 Jan 22;17(1):e77834. doi: 10.7759/cureus.77834. PMID: 39991350; PMCID: PMC11844773.\u003c/li\u003e\n\u003cli\u003eAzeez A, Ambatipudi S. Caregiver burden and quality of life among family caregivers of hemodialysis patients from South India. J Educ Health Promot. 2024 Dec 28;13:486. doi: 10.4103/jehp.jehp_273_24. PMID: 39850309; PMCID: PMC11756677.\u003c/li\u003e\n\u003cli\u003eWu HHL, Dhaygude AP, Mitra S, Tennankore KK. Home dialysis in older adults: challenges and solutions. Clin Kidney J. 2022 Oct 7;16(3):422-431. doi: 10.1093/ckj/sfac220. PMID: 36865019; PMCID: PMC9972827.\u003c/li\u003e\n\u003cli\u003eGhenaati N, Zendehtalab HR, Namazinia M, Zare M. Peer support groups and care burden in hemodialysis caregivers: a RCT in an Iranian healthcare setting. BMC Nephrol. 2024 Oct 21;25(1):371. doi: 10.1186/s12882-024-03811-8. PMID: 39433988; PMCID: PMC11495059.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hemodialysis, Mental health, Caregiving burden, PHQ-9, GAD-7, Psychosocial stress","lastPublishedDoi":"10.21203/rs.3.rs-7166296/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7166296/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCaregivers of patients undergoing hemodialysis face considerable psychological stress, yet culturally validated tools specific for assessing depression and anxiety in this group are lacking in Pakistan.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo validate the psychometric properties of the Urdu versions of the patient health questionnaire (PHQ-9) and generalized anxiety disorder (GAD-7) scales among hemodialysis caregivers in Pakistan, to measure the prevalence of generalized anxiety disorder (GAD) and major depressive disorder (MDD), and to identify demographic and caregiving-related predictors of depression and anxiety.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional study was conducted among 362 caregivers recruited from multiple dialysis centers across Pakistan. Participants completed the pre-validated Urdu translations of PHQ-9 and GAD-7, along with sociodemographic and caregiving-related questions. Reliability and factor structure of the screening tools were evaluated, and associations between psychological scores and caregiver characteristics were analyzed using non-parametric tests and regression models.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of Major Depressive Disorder was 8.0%, and Generalized Anxiety Disorder was 18.2%. Depression correlated positively with daily caregiving hours and negatively with caregiving duration. Higher levels of depression and anxiety were observed among females, urban residents, and university-educated caregivers. Regression analysis identified caregiving intensity as a significant predictor of depression (OR = 1.101), while age, gender, residence, and caregiving duration predicted anxiety (p \u0026lt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Urdu versions of PHQ-9 and GAD-7 demonstrated acceptable reliability and construct validity for use among hemodialysis caregivers. The findings highlight the psychological burden within this population and support the integration of routine mental health screening and tailored interventions into dialysis care programs.\u003c/p\u003e","manuscriptTitle":"Uncovering a Silent Crisis: Psychometric Validation and Public Health Implications of Depression and Anxiety Among Caregivers of Patients Undergoing Hemodialysis in Pakistan","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-28 15:26:37","doi":"10.21203/rs.3.rs-7166296/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"2ed05494-ef6e-4396-96c3-0ffd10341f51","owner":[],"postedDate":"August 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-09-19T16:23:24+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-28 15:26:37","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7166296","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7166296","identity":"rs-7166296","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}