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Article

CKD Patients’ Emotional Well-Being: An Examination of Their Psychological Stressors and Support Factors

by
Jairo N. Fuertes
1,2,*,
Olivia B. Friedman
1,
Michael T. Moore
1 and
Sofia Rubinstein
3
1
Gordon F. Derner School of Psychology, Adelphi University, Garden City, NY 11530, USA
2
Donald and Barbara Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY 11549, USA
3
Nassau University Medical Center, East Meadow, NY 11554, USA
*
Author to whom correspondence should be addressed.
Kidney Dial. 2025, 5(2), 26; https://doi.org/10.3390/kidneydial5020026
Submission received: 15 March 2025 / Revised: 30 May 2025 / Accepted: 3 June 2025 / Published: 11 June 2025
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Abstract

:
This study examined 112 CKD patients’ adherence to and satisfaction with treatment, and their quality of life, as mediated by the level of psychological stress experienced as well as their working alliance, resilience, and social support. The patients were receiving care at a public teaching hospital in the northeast region of the U.S. The results indicated a significant moderate negative correlation between psychological distress and quality of life (r = −0.34, p < 0.01). The results also indicated significant positive moderate to strong correlations between the physician–patient working alliance and adherence (r = 0.42, p < 0.001), satisfaction (r = 0.55, p < 0.001), and quality of life (r = 0.51, p < 0.001), between social support and quality of life (r = 0.39, p < 0.001), and significant moderate positive correlations between resilience and adherence (r = 0.35, p < 0.001) and satisfaction (r = 0.26, p < 0.01). Regression analyses indicated that the following predictors were significant: patient adherence was positively predicted by the working alliance (β = 0.42, p < 0.001); patient satisfaction was positively predicted by the working alliance (β = 0.51, p < 0.001) and negatively predicted by psychological distress (β = −18, p < 0.048); and quality of life was positively predicted by the working alliance (β = 0.38, p < 0.001) and social support (β = 0.28, p < 0.016) and negatively predicted by psychological distress (β = −0.34, p < 0.002). Moderation analyses indicated that the working alliance moderated the relationship between COVID impact and adherence (R2 = 0.27, F(df1, df2) = 8.36, p < 0.001, 95% CI = 0.29–2.74), social support moderated the relationship between COVID impact and adherence (R2 = 0.19, F(df1, df2) = 5.77, p < 0.001, 95% CI = 0.47–2.77), and resilient coping moderated the relationship between COVID impact and satisfaction (R2 = 0.20, F(df1, df2) = 7.89, p < 0.001, 95% CI = 0.94–2.81). The present study provides evidence of the significant role of psychological stressors and social support in influencing CKD patients’ adherence to and satisfaction with treatment, as well as their quality of life.

1. Introduction

Kidney diseases are a leading cause of death in the United States [1]. Chronic Kidney Disease (CKD) and End-Stage Kidney Disease (ESKD), the last stage of renal failure requiring dialysis, are highly prevalent diseases with approximately 37 million people in the U.S. having been diagnosed with CKD and 808,000 having ESKD [2]. Among ESKD patients, 69% are on dialysis and 31% have received a kidney transplant. CKD is a spectrum with varying degrees of severity and typically becomes worse over time. There are five stages of CKD, from mild damage in stage one, to kidney failure in stage five, which is also called ESKD. These stages are defined by how well the kidneys filter out waste from the blood, which is measured by the estimated glomerular filtration rate (eGFR). Although not all CKD progresses to kidney failure, when kidney failure does occur, kidney transplants and/or hemodialysis (HD) are the most common modes of treatment [3].
Common comorbidities for CKD/ESKD include diabetes, hypertension, cardiovascular disease, and obesity [4]. CKD is more common in Black adults (16%) than Latinx adults (14%), White adults (13%), and Asian adults (13%) [2]. Although CKD is slightly more prevalent among women (14%) than men (12%), men are 1.6 times more likely to develop ESKD. ESKD lifetime prevalence is also 4 times more likely to develop among Black adults, 2 times more likely among Latinx and Native American adults, and 1.4 times more likely among Asian adults than White adults [2].
There is a heavy financial burden associated with CKD and ESKD. According to the USRDS [4] expenditure analysis, spending for all CKD Medicare patients (older and younger than 66) increased to $85.4 billion in 2020, which accounts for 23.5% of total Medicare expenditures, and $50.8 billion for ESKD patients [4]. However, inflation-adjusted spending for CKD Medicare patients older than 66 decreased by 3% between 2019 and 2020, mainly due to a decrease in non-COVID hospitalizations. Even so, care for CKD patients costs approximately two times more per person than patients without CKD, regardless of insurance [4].
The current study examined patients’ perspectives on living with CKD, particularly regarding their emotional well-being, and examined the extent to which psychological distress and the impact of the COVID-19 pandemic affected them. This study also examined the extent to which these two stressors compromised their ability to adhere to treatment, diminished their satisfaction with treatment, and impacted their overall quality of life. However, to more fully examine their psychological experience, this study also evaluated the extent to which social support would allow them to adhere to and be satisfied with treatment, and improve their quality of life. The social supports examined were the quality of the relationship with their primary CKD health care provider, the amount of social support available to them, and their level of resilient coping (see Figure 1).
Due to the nature of the disease and treatment, CKD patients are especially immunocompromised. A recent meta-analysis that investigated the association between CKD and COVID-19 showed an enhanced risk of severe infection among the CKD population [5]. Prior to the pandemic, the adjusted mortality rate for both CKD and ESKD patients had decreased between 2000 and 2019. However, in 2020, the adjusted mortality rate increased by approximately 10% for CKD Medicare patients older than 66 years and was more than twice as high among Medicare patients than those without CKD. Moreover, there was a greater increase in mortality among Black individuals (23% increase) and Latinx individuals (12%) than among White individuals (9%). Regarding ESKD, the mortality rate increased by 17% for hemodialysis patients, 20% for peritoneal (home) dialysis patients, and 33% for kidney transplant patients [4]. COVID-19 was the third leading cause of death for patients treated in hemodialysis centers in 2020.
Rates of depression are generally high among ESKD patients, in the range of 20 to 30%, and higher rates of depression and psychological distress have ranged up to 45% among new hemodialysis (HD) patients starting dialysis [6,7,8,9]. Patients on HD with depression typically experience significant difficulty with adhering to the various dimensions of HD treatment [10].
The current study includes three treatment outcome indices that are central to the study and treatment of chronic disease management and CKD/ESKD in particular. Non-adherence is a problem in the health care management of chronic medical conditions, including CKD and ESKD. Non-adherence for patients on HD has been documented as 18% for missed sessions, 23% for shortened time on dialysis treatment, 80% for medication, 75% for fluid restriction, and 81% for dietary restrictions [4]. Consequently, optimizing adherence continues to be a major goal in CKD treatment. Patient satisfaction is perhaps the most cited proxy of quality of health care and has been positively associated with increased patient adherence and health care outcomes [11]. However, there is limited evidence regarding CKD and ESKD patient satisfaction in the context of the COVID-19 pandemic. Quality of life is an important index in all health care, as it encompasses the physical, psychological, social, and environmental aspects of patients’ lives that are often the target of medical care and multidisciplinary teams in health care settings. Given the high burden of the disease and treatment for CKD and ESKD patients, quality of life is a prominent concern for these patients.
Social support is an important factor in predicting the course of chronic diseases and higher levels of social support have been found to be associated with higher rates of quality of life, improved treatment prognosis, and better levels of treatment adherence [12,13,14]. For patients with ESKD, social support is viable for patients who are married, live with family members, and have social networks of support [15]. Resilient coping is defined as a person’s ability to use healthy coping skills, identify available resources, ask for help, and find ways to manage a demanding or stressful situation [16]. Research on resilient coping indicates that it is an effective stress coping response and can moderate the negative effects of anxiety and depression in health care [17]. The support received from health care providers has also been delineated as potentially more influential than the support received from family members [18]. Recent research in behavioral medicine has adopted a view of the relationship based on the concept of the working alliance, which comes from the field of psychotherapy [19,20]. The physician–patient working alliance (PPWA) has been examined with patients with chronic medical conditions and has been found to be positively associated with patient adherence and satisfaction [21]. The PPWA seems particularly relevant to HD treatment because the demands of ESKD are extensive and often take a psychological toll on patients who are heavily dependent on the care of medical staff.
Given the review of the literature, the following hypotheses were formulated: It was hypothesized that there would be negative associations between two factors, psychological distress and the impact of the COVID-19 pandemic, and three outcomes, patient adherence, satisfaction, and quality of life. Conversely, there would be positive associations between three factors, patient resilience, self-efficacy, and working alliance, and those same three outcomes (i.e., patient adherence, satisfaction, and quality of life). The third hypothesis was that patients’ resilience, social support, and ratings of the working alliance would moderate the negative association between psychological distress and COVID-19 impact and outcome (i.e., adherence, satisfaction, and quality of life).

2. Methods

2.1. Participants and Procedures

A power analysis indicated that between 107 and 112 participants would be needed in order to have sufficient statistical power (0.80) to detect the medium effect anticipated between the variables of interest using a conventional alpha level (0.05) [22]. After receiving full IRB approval (#010921), data were collected from 112 participants in the dialysis (n = 70) and CKD clinics (n = 42) at a public teaching hospital in the northeast region of the U.S. The participants were 40 (35.7%) females and 72 (64.3%) males, with an average age of 57.35 (SD = 14.93, range = 23 to 86 years). Overall, 51 reported being Black/African American (45.5%), 29 Hispanic/Latino/a (26%), 13 White (11.6%), 8 other (7.1%), and 3 Asian or Pacific Islander (2.7%), and 8 did not provide their race/ethnicity (7.1%). A total of 78 of the respondents spoke English (70%) and 34 spoke Spanish (30%) and completed the survey in their language. In terms of education, 41 (36.6%) participants reported completing high school, 9 (8.0%) college, 16 (9.7%) some college, 33 reported completing eighth grade (29.6%), 2 (1.8%) graduate school, and 11 (14.3%) did not complete this item. In terms of their state of health, 58 (51.8%) reported “Fair”, 43 (38.4%) “Good”, 5 (4.5%) “Excellent”, 2 (1.8%) “Bad”, and 4 (3.6%) “Poor”. Lastly, 85 (75.6%) of the participants reported an annual household income under $39,999, 11 (9.8%) did not respond to this item, and the remaining 16 (14.6%) reported an income between $40,000 and $70,000.

2.2. Brief Symptom Inventory (BSI) [23]

The 53-item BSI assesses the symptoms of psychopathology in the following areas: somatization, obsession–compulsion, interpersonal sensitivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism. Three global indices of distress, global severity index, positive symptom distress index, and positive symptom, are also assessed.
Total rankings characterize the intensity of distress during the previous seven days. The items are rated on a 5-point Likert scale ranging from 0 not at all to 4 extremely. Derogatis [23] reports good internal consistency, ranging from α = 0.71 to 0.81, which is comparable to what was found in the present study (α = 0.95). In the current study, the overall global severity index, comprising all 53 items, is reported as a general measure of psychological distress.

2.3. COVID Impact Scale (CIS) [24]

This 10-item novel measure was developed to assess the impact of the COVID-19 pandemic on a range of areas of individuals’ lives, such as their finances, well-being, and hopefulness. Items are measured on a scale from 1 (it is much improved) to 7 (it is much worse). The scale is constructed with both the potential negative and positive effects of the pandemic in mind. Internal consistency for the scale was excellent in the present study (α = 0.91) with item eight removed.

2.4. The Physician–Patient Working Alliance Inventory (PPWAI) [20]

The PPWAI is adapted from the Working Alliance Inventory used in psychotherapy research [25]. The PPWAI is similar but aligns with areas related to medical care relationships. The twelve-item measure contains three subscales: emotional bond, agreement on treatment goals, and agreement on treatment tasks. Items are rated on a Likert scale from 1 (strongly disagree) to 7 (strongly agree). Fuertes et al. [20] demonstrated that the overall scale has excellent internal consistency (α = 0.93). In the present study, the scale had excellent internal consistency (α = 0.91) when item eight was removed. The measure has been validated in populations with an array of chronic conditions [21,26].

2.5. Social Support (MOS) [12]

This 19-item measure evaluates individuals’ perceived access to social support rated on a Likert scale from 1 (none of the time) to 5 (all of the time). The scale includes four dimensions: emotional/informative support, tangible support, affection, and positive social interaction. The scale has been shown to have excellent internal consistency (α = 0.91) [12]. Reyes et al. [26] also found the scale to have excellent internal consistency (α = 0.97) among hemodialysis patients, as did the present study (α = 0.95).

2.6. Resilient Coping Measure (RCM) [27]

This 4-item scale measures the extent to which individuals cope with stress adaptively. The scale focuses on the tendency to effectively use coping strategies in flexible, committed ways to actively solve problems despite stressful circumstances. The scale has demonstrated adequate internal consistency (α = 0.69) in previous studies and good internal consistency in the present study (α = 0.86). Coping was assessed on a 5-point Likert scale of 1 (does not describe me at all) to 5 (describes me very well).

2.7. General Adherence Measure (GAM) [28]

This 5-item measure is a subset of the General Adherence measure of the Medical Outcomes Study. Reyes et al. [26] showed acceptable internal consistency (α = 0.72), while the present study exceeded this value (α = 0.75) when item one was removed. Patients are asked to identify whether they feel they act in accordance with their physician’s treatment plans on a 6-point Likert scale from 1 (strongly disagree) to 6 (strongly agree).

2.8. Medical Patient Satisfaction Questionnaire (MPSQ) [20]

This 6-item measure assesses patients’ overall satisfaction with medical treatment on a scale from 1 (strongly disagree) to 5 (strongly agree). The original validation study found excellent internal consistency (α = 0.91) and Reyes et al. [26] showed similar results, with a global internal consistency (α = 0.93) [20]. Internal consistency for the scale in the present study was also excellent (α = 0.95) with item 4 removed.

2.9. The World Health Organization Quality of Life-BREF (WHOQOL-BREF) [29]

This 26-item measure is based on the World Health Organization Quality of Life-100 (WHOQOL-100). The scale includes four domains: physical health, psychological, social relationships, and environment. Participants rate these areas of their life on a scale from 1 (very poor or very dissatisfied) to 5 (very good or very satisfied). The scale has been shown to be valid and reliable [29]. Reyes et al. [26] found excellent internal consistency (α = 0.94) as did the present study (α = 0.90). In the current study, a global index of QOL was assessed by summing the scores of the four domains.

3. Results

3.1. Hypothesis 1: Intercorrelations Among All Variables

The first hypothesis was that there would be negative associations between the two factors, psychological distress and the impact of the COVID-19 pandemic, and the three outcomes (i.e., patient adherence, satisfaction, and quality of life). As evident from Table 1, this hypothesis is partially supported by the significant moderate negative correlation between psychological distress and quality of life, but is contradicted by the significant moderate positive correlation between COVID impact and patient satisfaction. The second hypothesis was that there would be positive associations between the three support factors, working alliance, social support, and patient resiliency, and the three outcomes (i.e., patient adherence, satisfaction, and quality of life). As evident from Table 1, this hypothesis is largely supported by the significant positive moderate to strong correlations between working alliance and adherence and satisfaction and quality of life, the significant moderate positive correlation between social support and quality of life, and the significant moderate positive correlations between resilience and adherence and satisfaction.

3.2. Hypothesis 2: Regression Analyses Results

To better understand the interplay between the zero-order correlations among the stress and support variables, and as a secondary test of hypotheses one and two above, we ran three separate simultaneous linear regressions. In each regression model, patient adherence, patient satisfaction, and quality of life were the dependent variable, and psychological distress, COVID impact, patient resilience, social support, and the working alliance were predictors. As evident from Table 2, all three regression models were significant, with the following predictors being significant: patient adherence was positively predicted by the working alliance, patient satisfaction was positively predicted by the working alliance and negatively predicted by psychological distress, and quality of life was positively predicted by the working alliance and social support and negatively predicted by psychological distress.

3.3. Hypothesis 3: Moderation Analyses Results

To test our third hypothesis of whether working alliance, social support, and resilient coping moderated the negative relationship between psychological distress, COVID impact, and the three outcomes measures (i.e., treatment adherence, satisfaction, and quality of life), a bias-corrected bootstrapping procedure was used to construct 95% confidence intervals in PROCESS v4.2 according to the recommendations of Preacher and Hayes [30]. A total of 18 moderations were run using the eight variables in our model. Three of the eighteen moderation analyses were significant, indicating partial support for the moderation hypotheses, and all three involved COVID impact (see Figure 2). The PPWA moderated the relationship between COVID impact and adherence (R2 = 0.27, F(df1, df2) = 8.36, p < 0.001, 95% CI = 0.29–2.74). To decompose this interaction, the relationship between COVID impact and treatment adherence was examined at three levels of the moderator (the PPWA): +1SD PPWA (i.e., high working alliance), mean PPWA, and −1SD PPWA (i.e., low working alliance) (see Figure 2). Results found higher COVID impact scores to be associated with worse treatment adherence for those with low working alliance, and higher COVID impact scores to be associated with better treatment adherence for those with high working alliance. Social support also moderated the relationship between COVID impact and adherence (R2 = 0.19, F(df1, df2) = 5.77, p < 0.001, 95% CI = 0.47–2.77; see Figure 2). Similar decomposition (i.e., +1SD (i.e., high social support), mean, and −1SD (i.e., low social support) of this effect found that COVID impact was not significantly associated with treatment adherence for those with low social support. However, higher COVID impact scores were associated with more treatment adherence for those high in social support. Resilient coping moderated the relationship between COVID impact and satisfaction (R2 = 0.20, F(df1, df2) = 7.89, p < 0.001, 95% CI = 0.94–2.81; see Figure 2). Similar decomposition of this effect (+1SD) (i.e., resilient coping), mean, and −1SD (i.e., low resilient coping) found that COVID impact was not significantly associated with treatment satisfaction for those low in resilient coping. However, higher COVID impact scores were associated with more treatment satisfaction for those high in resilient coping.

4. Discussion

The zero-order correlations show large effects in the associations between working alliance and quality of life, working alliance and treatment satisfaction, and satisfaction and treatment adherence. There is a prominent main effect between these variables, and while directionality cannot be ascertained between them, their close association is noteworthy. Working alliance and adherence are more moderately related, as was the correlation between treatment satisfaction and quality of life. These bivariate correlations are consistent with previous findings that link support, working alliance with CKD patient adherence, satisfaction, and quality of life [21]. Regression analyses further elucidated the significant role of the working alliance in predicting CKD patients’ treatment adherence, satisfaction, and quality of life. These results are consistent with previous findings that have shown that the working alliance is an important factor for patients undergoing care for a variety of chronic medical conditions; the working alliance has been found in several empirical studies to predict treatment adherence, treatment satisfaction, and quality of life [21]. Another positive predictor identified through regression was social support, which proved to be a significant predictor of quality of life for CKD patients. In terms of significant negative prediction, the regression analyses showed the deleterious effect of psychological distress on treatment satisfaction and quality of life. This last result is consistent with previous findings from research with CKD patients, whose functional impairment limited social activity, and increases in depression were observed [31,32,33].
The more complex analyses of moderation implicate the significant role of the COVID pandemic and its impact on CKD patients’ treatment adherence and satisfaction with treatment. The results further indicate that the working alliance has a significant moderating effect on the negative relationship between COVID impact and adherence such that when the working alliance between a patient and the medical provider is strong, the deleterious effect of COVID impact on adherence decreases; conversely, when the working alliance is less strong, COVID impact is associated with decreased adherence. In other words, CKD patients who reported high impact from the COVID pandemic had more difficulty adhering to their treatment regimen; however, the negative influence of COVID impact on adherence can be neutralized by a sound working relationship with their health care providers. The second significant result indicates that social support has a significant moderating effect on the otherwise negative relationship between COVID impact and adherence, such that as social support increases, adherence increases. Just like with the working alliance, the negative influence of COVID impact on treatment adherence can be neutralized by the social support available to CKD patients. The third significant result indicates that resilient coping has a significant moderating effect on the negative relationship between COVID impact and treatment satisfaction. When the patient reported higher levels of resilient coping, higher treatment satisfaction was evident despite COVID impact.
In summary, the results reveal a close association between CKD patients’ emotional well-being and their outcomes in treatment. Social support, resilient coping, and the working alliance with their providers seems to have a large and positive influence on these patients. Furthermore, the results showed that the COVID pandemic has had a significant and deleterious effect on CKD patients’ experience of treatment, particularly their adherence to and satisfaction with treatment. A clinical implication from these findings is that medical care professionals should assess the role of the COVID pandemic with their CKD patients, and actively work to develop a strong working alliance with them. That would mean establishing agreement communication, perhaps by contracting with their patients about the goals of treatment and the tasks that the patient will follow to meet those agreed-upon goals. A strong working alliance would also mean that the health care provider would actively work to establish a sense of trust and interpersonal liking with their CKD patients. Another clinical implication from the findings is that CKD patients benefit from social support. Therefore, medical care professionals ought to continue promoting programs and activities that promote social interaction and interpersonal caring for their patients, such as support group meetings and social activities within clinics and in patients’ communities. The CKD patients may be poised to receive such help as most still rely on hemodialysis for several hours, three times a week. During these long sessions, the patient can participate socially with others, or watch psychoeducational interventions on their electronic device. A third clinical implication involves interventions that can help CKD patients develop skills of resilient coping; these can take place in person or online through psychoeducational programs led by nephrologists, residents, and/or mental health professionals. Resilient coping skills include a patient’s ability to solve problems during difficult situations, to maintain a certain amount of control in the face of challenges, believe they can grow from difficult situations, and find ways to replace losses.

5. Conclusions

The present study provides evidence of the significant role of psychological stressors and social support in influencing CKD patients’ adherence to and satisfaction with treatment, as well as their quality of life. There are possibilities for developing interventions including psychoeducational programs that can help these patients alleviate emotional challenges and make optimal use of the medical treatment that is being provided to them.

Author Contributions

Conceptualization: J.N.F. and O.B.F.; Methodology: J.N.F., O.B.F., M.T.M., and S.R.; Software: J.N.F. and M.T.M.; Methodology: M.T.M.; Formal analysis: M.T.M.; Investigation: J.N.F., O.B.F., and S.R.; Resources: J.N.F. and S.R.; Data curation: S.R.; Writing—J.N.F. and O.B.F.; Writing—O.B.F. and J.N.F.; Review and editing: J.N.F., O.B.F., M.T.M., and S.R.; Project administration: J.N.F. and S.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki, and approved by the Institutional Review Board of ADELPHI UNIVERSITY (#010921. 11 January 2023).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author due to privacy and ethical considerations.

Conflicts of Interest

The authors declare no conflicts of interest.

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Figure 1. Prediction of patient adherence, treatment satisfaction, and quality of life based on symptoms of psychopathology, impact of the COVID-19 pandemic, and their interactions with the physician–patient working alliance, patient social support, and resilience. Note: PPWAI = physician–patient working alliance inventory.
Figure 1. Prediction of patient adherence, treatment satisfaction, and quality of life based on symptoms of psychopathology, impact of the COVID-19 pandemic, and their interactions with the physician–patient working alliance, patient social support, and resilience. Note: PPWAI = physician–patient working alliance inventory.
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Kidneydial 05 00026 g002aKidneydial 05 00026 g002b
Figure 2. Graphs of three significant moderation analyses.
Figure 2. Graphs of three significant moderation analyses.
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Table 1. Means, standard deviations, internal consistencies, and Pearson’s correlation matrix.
Table 1. Means, standard deviations, internal consistencies, and Pearson’s correlation matrix.
MeasureNMeanS.D.Alpha12345678
1.PPWA9263.6110.180.91
2.BSI9714.8220.400.95−0.07
3.C19A10134.369.510.910.15−0.11
4.QOL8093.3014.320.900.51 **−0.34 *−0.09
5.SOS10366.9624.000.950.21−0.220.070.39 **
6.RES11013.754.010.860.23−0.02−0.020.230.18
7.GAM9418.944.730.750.42 **−0.220.140.36 **0.120.35 **
8.PSQ11021.404.080.950.55 **−0.210.24 *0.41 **0.200.26 *0.49 **
Note. Physician–patient working alliance (PPWA); Brief Symptom Inventory (BSI); COVID-19 impact assessment (C19A); quality of life inventory (QOL); social support (SOS); resilience scale (RES); General Adherence Measure (GAM); Patient Satisfaction Questionnaire (PSQ). * Correlation is significant at the 0.01 level (2-tailed); ** Correlation is significant at the 0.001 level (2-tailed).
Table 2. Significant results for simultaneous regression analyses.
Table 2. Significant results for simultaneous regression analyses.
PredictorβtαVIF
PPWA0.4203.460.0011.16
a. Dependent Variable: Adherence. Adj R2 0.217, p < 0.002.
PPWA0.5155.340.0011.08
BSI−0.18−2.010.0481.01
b. Dependent Variable: Satisfaction: Adherence. Adj R2 0.348, p < 0.001.
PPWA0.3893.490.0011.15
SOS0.2802.490.0161.18
BIS−0.348−3.260.0021.06
c. Dependent Variable: Quality of Life: Adherence. Adj R2 0.348, p < 0.001.
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Fuertes, J.N.; Friedman, O.B.; Moore, M.T.; Rubinstein, S. CKD Patients’ Emotional Well-Being: An Examination of Their Psychological Stressors and Support Factors. Kidney Dial. 2025, 5, 26. https://doi.org/10.3390/kidneydial5020026

AMA Style

Fuertes JN, Friedman OB, Moore MT, Rubinstein S. CKD Patients’ Emotional Well-Being: An Examination of Their Psychological Stressors and Support Factors. Kidney and Dialysis. 2025; 5(2):26. https://doi.org/10.3390/kidneydial5020026

Chicago/Turabian Style

Fuertes, Jairo N., Olivia B. Friedman, Michael T. Moore, and Sofia Rubinstein. 2025. "CKD Patients’ Emotional Well-Being: An Examination of Their Psychological Stressors and Support Factors" Kidney and Dialysis 5, no. 2: 26. https://doi.org/10.3390/kidneydial5020026

APA Style

Fuertes, J. N., Friedman, O. B., Moore, M. T., & Rubinstein, S. (2025). CKD Patients’ Emotional Well-Being: An Examination of Their Psychological Stressors and Support Factors. Kidney and Dialysis, 5(2), 26. https://doi.org/10.3390/kidneydial5020026

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