The effect of the peer educational-supportive program on enhancing the resilience and self-efficacy of Hemodialysis patients 

The effect of the peer educational-supportive program on enhancing the resilience and self-efficacy of Hemodialysis patients | 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 Article The effect of the peer educational-supportive program on enhancing the resilience and self-efficacy of Hemodialysis patients Rezvan Shirali, Rahim Ali Sheikhi, Jaefar Moghaddasi, Zahra Davoudi, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6559212/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background: Hemodialysis patients often have low resilience and self-efficacy due to physical limitations, psychological pressures, and lack of social support. Nursing care must prioritize addressing these issues. Additionally, patients can be motivated and encouraged by seeing others who have successfully coped with similar challenges. Therefore, this study aims to assess the impact of peer educational-supportive programs on enhancing the resilience and self-efficacy of hemodialysis patients. Methods: The study was conducted at Hajar Hospital in Shahrekord and focused on hemodialysis patients. Patients were chosen using an available method and placed into either the intervention (32-person) or control group (34-person) based on whether they were admitted on odd or even days. Initially, five peers were selected from hemodialysis patients and underwent eight training sessions lasting 45 to 60 minutes. Afterward, the intervention group participated in a 12-week educational and support program the selected peers implemented. Data was collected using demographic and resilience questionnaires developed by Connor and Davidson and Shere’s general self-efficacy questionnaire. The analysis was conducted using SPSS version 16 software. Results: The average scores for resilience and self-efficacy in the intervention group before the intervention were 44.82 ± 7.13 and 5.02 ± 32.02, respectively. Following the intervention, these scores improved to 63.25 ± 6.63 and 55.80 ± 6.98, respectively, showing statistically significant changes (P 0.05). Conclusions : The study's results demonstrate that the educational support program implemented by peers has a positive effect on increasing the resilience and self-efficacy of hemodialysis patients. Therefore, it is suggested that including peers in educational support programs to enhance resilience and self-efficacy be seriously considered. Trial registration: No Trial sponsor: Shahrekord University of Medical Science Funding: This research is financially supported by Shahrekord University of Medical Sciences. Study status: This study has been completed. Related article: No related articles for this study have been submitted to any journal. The study's sponsor and funders had no involvement in the data's design, analysis, or interpretation. The content is entirely the authors' responsibility and does not necessarily reflect the official views of the National Institutes of Health. Health sciences/Health care Health sciences/Nephrology peer education resilience self-efficacy hemodialysis patients Figures Figure 1 Background In chronic kidney failure, irreversible damage is done to the kidney tissue, and alternative treatments for kidney function will be needed to save the patient's life ( 1 ). According to population surveys, over 15% of adults in the United States are estimated to suffer from kidney failure ( 2 ). In Iran, approximately 35,000 individuals suffer from chronic kidney failure, with 19% of them residing in Tehran. Hemodialysis remains the most prevalent treatment method for these patients, with over 50% of kidney patients in Iran undergoing this procedure ( 3 ). Hemodialysis is a stressful process that significantly impacts patients' quality of life. The belief in having an incurable disease can make it challenging to cope and reduce a person's resilience ( 4 ). Some studies showed that hemodialysis patients referred to hospitals had lower-than-average resilience ( 5 ). Resilience, the ability to handle life's challenges, is an important personality trait in health-related sciences. It is essential to focus on promoting resilience in the care of these patients. Therefore, interventions to improve resilience should be a priority in caring for these patients ( 6 ). Self-efficacy involves a person's belief in their ability to perform self-care tasks effectively, leading to improved self-care outcomes. Research indicates that self-efficacy, social support, life expectancy, and self-confidence are crucial factors in patient resilience, particularly among hemodialysis patients ( 7 ). Resilience and self-efficacy have a mutually reinforcing relationship: improving self-efficacy enhances patient resilience, further boosting the patient's self-efficacy( 8 ). A peer shares similar characteristics with another person, such as age, gender, occupation, economic-social status, and health status. Peer support involves using personal knowledge and experience to help manage one's health effectively ( 9 ). Successful peers can cheaply share their weaknesses, strengths, and experiences with patients. By discussing the stress of chronic disease and motivating them, peers encourage patients to adopt appropriate health behaviors. One method of peer support is the peer educational- support program, which helps individuals learn methods to cope with the disease and improve their quality of life ( 10 ). Previous research indicates that engaging in peer support programs positively impacts the mental health of individuals undergoing hemodialysis ( 11 ). The influence of peers on self-management skills, adherence to fluid intake, improved outcomes, and reduced hospitalization duration in hemodialysis patients has been widely studied because it can enhance their resilience and boost their self-efficacy. However, there is a lack of research on the effects of educational- support programs and peer support on resilience and self-efficacy in this patient group. Additionally, studies examining the influence of peers on the resilience of other chronic patients have produced conflicting results. For example, some studies reported no impact on the anxiety levels of patients with thalassemia ( 12 ). This study aims to investigate the effects of peer educational support programs on the resilience and self-efficacy of hemodialysis patients at Hajar Hospital in Shahrekord. Material and methods Study design and setting The present study was semi-experimental, with a control group and a pre-test-post-test design. It was conducted at Hajar Hospital in Shahrekord from October 2023 to February 2024. Study participants and sampling The study included all hemodialysis patients referred to Hajar Hospital in Shahrekord, with 79 hemodialysis patients. Among them, 41 patients visited the hemodialysis department on even days, while 38 visited on odd days. By random selection, patients referred on odd days were designated as the control group, and those referred on even days were chosen as the intervention group. Five patients from the intervention group were selected to serve as peer trainers. ( Table 1 ). These trainers conducted training and support programs for groups of 6 to 7 people. After applying the inclusion and exclusion criteria and considering some patients' refusal to participate, 32 individuals in the intervention group and 34 in the control group completed the questionnaires. Inclusion criteria required participants to be interested in the study (showing necessary cooperation and signing informed consent), aged between 20 and 65 years, have a history of hemodialysis for at least one year, and undergo at least two weekly hemodialysis sessions. Exclusion criteria included refusal to continue cooperating, incomplete questionnaire completion, non-participation in two training sessions, and simultaneous hospitalization due to another disease, poor-condition patients, and being referred on odd and even days. One patient in the intervention group and three patients in the control group refused to participate in the study. One patient was excluded from the intervention group due to severe illness, and two because of less than 1 year of hemodialysis. In the control group, one patient was ruled out because of less than 1 year of hemodialysis. Data collection tools and technique The data collection tool included questionnaires about patient’s demographic characteristics (age, gender, marital status, education, occupation, and duration of hemodialysis), Connor & Davidson's resilience, and Sherer’s questionnaire about self-efficacy. The Connor and Davidson Resilience Scale, introduced in 2003, was utilized to assess the resilience of hemodialysis patients. This questionnaire contains 25 items aimed at evaluating individuals' resilience. Respondents rate each item on a Likert scale ranging from one (completely false) to five (always true). (13)In Iran, the tool was standardized by Mohammadi in 2005, who reported a validity score of 0.82 and a reliability score of 0.79. (14) Five dimensions of Connor & Davidson's tool are the perception of individual competence, trust in individual instincts, negative emotional tolerance, positive acceptance of change and secure relationships, control, and negative influences. The range of test scores is between 0 and 100. Higher scores indicate greater resilience of the subject (15). The Self-Efficacy Scale developed by Sherer et al. (1982) consists of 17 questions, each using a Likert scale that ranges from "strongly disagree" to "strongly agree." Each item is scored from 1 to 5 and the total score can vary from 17 to 85. (16, 17).This scale was translated and validated by Bakhtiari Barati in 1997 and its validity and reliability were proven at 79 percent (18). Patients were assigned to either the control or intervention group based on whether they visited for hemodialysis on even or odd days of the week. Demographic and resilience questionnaires by Connor and Davidson and Sherer's questionnaires were completed for both groups as a pre-test. Then, five hemodialysis patients, both men and women, were chosen based on recommendations from kidney specialists and the clinic's general practitioner. The selection process involved reviewing their medical records, including test results and evaluations from specialists such as cardiologists, ophthalmologists, and internists, to ensure they had effectively managed their hemodialysis complications. The selected individuals shared similar conditions with the research units, such as age (20 to 68 years), a history of hemodialysis for more than one year, having completed education through senior high school or higher levels, and having cultural, social, and economic similarities. They also had good social relations, the ability to manage meetings, and were interested in leadership. Furthermore, they obtained higher scores on the resilience and self-efficacy questionnaires. One peer taught and supported six or seven patients in this study, leading to the selection of five candidates. A multidisciplinary team, including a kidney specialist, a psychological consultant with a PhD degree, a nursing PhD and a master's in nursing with experience in the hemodialysis department, and an employee of the hemodialysis department, participated in training the peers. First, the research team trained peers in eight sessions lasting 45 to 60 minutes over four weeks (8 sessions). They were also trained through role-playing (Table 2). Then, they provided the necessary education to hemodialysis patients in eight group sessions of 45 to 60 minutes in the hospital's conference hall and face-to-face sessions over four weeks. Over the next eight weeks, patients in the intervention group received peer education and support. Specially trained peers, supervised by the research team, provided training, answered questions, and offered support before, during, and after each dialysis session. The peers also provided ongoing support by answering questions over the phone or in virtual spaces, offering emotional and psychological support, and showing empathy around the clock. The educating content covers kidney failure and hemodialysis knowledge, including symptoms, complications, risk factors, and treatments. It includes approved nutritional recommendations from a nutritionist, exercise suggestions, drug therapy and self-monitoring, and weight control. The education also addresses and corrects common concerns and misconceptions about treating kidney failure and hemodialysis. Furthermore, it involves practical implementation, including fistula care, weight monitoring, and interpretation and decision-making when dealing with limitations. After completing 12 weeks of education and support, the Connor and Davidson resilience questionnaire for both the control and intervention groups was completed (post-test). The data was entered into SPSS version 19 statistical software for analysis. The data were analyzed using descriptive statistics (mean, standard deviation, frequency) and inferential tests (chi-square, Fisher's exact, paired t-test, and independent t-test). Table 2 . The topics taught to the peer group by the research team first session Definition of peer support, the role and responsibility of peers, and self-awareness of one's capabilities. second session Strengthening self-esteem; effective communication to improve people's communication ability third session symptoms, complications, and risk factors of kidney failure and hemodialysis fourth session Anger management, anxiety, and stress management. Strengthening the sense of spirituality and faith. fifth session Exercise recommendations, Drug therapy, self-monitoring, fistula care sixth session establishing social relations with peers and friends - Nutritional recommendation seventh session Self-efficacy, increasing positive emotional sense, Self-belief, and genuine self-confidence. eighth session Common concerns and misconceptions about treating kidney failure, hemodialysis, and weight control. Ethical considerations All methods were performed in accordance with the relevant guidelines and regulations. Results As shown in Table 3 of the 66 patients who completed the study in both the control and intervention groups, 39 were male (59.1%) and 27 were female (40.9%). Regarding literacy levels, out of the 66 participants, 28 (42.4%) had graduated from primary school or had lower education levels. Additionally, 21 participants (31.8%) completed high school or senior high school, while 17 (25.8%) held bachelor's degrees or higher. The chi-square test indicated that the two groups were similar in gender, marital status and education (p > 0.05). Additionally, Fisher's exact test showed no statistically significant difference in occupation between the two groups (P > 0.05). The average age of the patients in the intervention group was 48.48 years with a standard deviation of 12.50, while the average age in the control group was 50.77 with a standard deviation of 11.05. According to the independent t-test, there was no statistically significant difference in the average age between the two groups (P=0.42). Additionally, the average duration of hemodialysis for intervention group patients was 28.62 months with a standard deviation of 28.10, and for control group patients, it was 32.40 months with a standard deviation of 26.97. According to the Mann-Whitney test, the two groups did not show a statistically significant difference in the average duration of hemodialysis (P=0.34) Table 3 . General information of the participants In the intervention group, the mean age of participants was 44.82 ± 7.13, while in the control group, it was 45.68 ± 6.39. The independent t-test indicated no statistically significant difference between the two groups (p=0.59). After the intervention, the mean resilience score in the intervention group increased to 63.25 ± 6.63, whereas in the control group, it reached 46.71 ± 6.15. An independent t-test showed a significant difference between the two groups (P<.001), suggesting an improvement in the intervention group's resilience. Furthermore, a paired t-test comparing resilience scores in the intervention group before and after the intervention revealed a significant difference (p<0.001), but this difference was not significant in the control group (p=0.12) (Table 4). The mean and standard deviation of the patients' self-efficacy scores before the intervention were 32.02 ± 5.02 in the intervention group and 31.37 ± 4.74 in the control group. An independent t-test (p=0.57) showed no statistically significant difference between the two groups. After the intervention, the mean and standard deviation of self-efficacy in the intervention group increased to 55.80 ± 6.97, while in the control group, it reached 32.45 ± 5.07. The independent t-test indicated a significant difference, suggesting improved self-efficacy in the intervention group (p<0.001). A paired t-test comparing the mean and standard deviation of the self-efficacy scores of the patients before and after the intervention group intervention showed a significant difference from the pre-test to the post-test time (p<0.001). However, this difference from the pre-test to the post-test was insignificant in the control group (p=0.36). In conclusion, the intervention led to a significant increase in self-efficacy. Discussion This research tested the efficacy of an education and support program delivered by peer mentorship in enhancing the resilience and self-efficacy of hemodialysis patients (Fig. 1 ). In this study, five mentors, both men and women, who were in good condition based on the opinion of an expert physician and tests, were selected as peers and trained by the research group in eight sessions of 45 to 60 minutes (Table 1 ). Peer support involves peer education and relies on volunteers to offer positive feedback, demonstrate leadership, and influence others. These volunteers are essential because they have firsthand experience with the same conditions as the patients they assist. This shared experience allows them to understand patients' psychological challenges, share similar life experiences, and provide crucial support through attentive listening and open discussions about issues ( 19 , 20 ). Choosing, training, and evaluating the right peers for medical conditions and disease control is crucial to ensure the correct transfer of information and proper patient support ( 21 ). Lack of awareness, negative attitudes toward self-management, and low self-efficacy prevent hemodialysis patients from adhering to treatment. Education provided by dialysis facilities offers general guidelines on diet and adherence, but it does not help patients recognise or attribute the symptoms of uremia or intradialytic weight gain to poor self-management behaviours ( 22 – 23 ) Using context-sensitive interventions increases social support, self-efficacy, and resilience, improving adherence to dialysis treatment ( 24 – 25 ). The impact of peer-to-peer self-care training on cancer patients' resilience showed a significant improvement in the intervention group's resilience levels after the program. ( 26 ). Peer mentorship has proven effective in managing chronic diseases like diabetes, depression, and AIDS among patients undergoing dialysis ( 27 – 28 ). Also, the influence of peer groups on mothers of children with leukaemia has been established. Before the intervention, the two groups had no significant difference in average resilience levels. However, a considerable difference emerged after the intervention, showing a marked improvement in resilience among the mothers in the intervention group ( 29 ). Peer education significantly improved dialysis patients' self-efficacy ( 30 ). Peer mentor interventions enhance health-related behaviors and self-management. In patients on hemodialysis, these interventions have successfully improved care discussions, treatment adherence, and quality-of-life measures ( 31 – 32 ) The present study combined an educational and support program similar to other studies but with unique elements. During hemodialysis sessions, trained peers provided education and listened to patients' concerns. They offered guidance and support, allowing patients to discuss their problems and explore potential solutions. Additionally, outside of hemodialysis sessions, these peers were equipped to assist patients via virtual communication or phone calls when needed. The results of Wetmore's research, while similar to the current study in some ways, also differ in others. It showed that short-term interventions can enhance patients' knowledge levels but do not improve self-management abilities. In contrast, a six-month peer support program significantly enhanced self-care in hemodialysis patients ( 33 ). Although the duration of peer influence on hemodialysis patients varied across studies, all research consistently confirmed that peer support training positively impacts patient resilience and self-efficacy. Therefore, it can be concluded that peer support training programs effectively improve patient resilience. Conclusion The growing number of hemodialysis patients is presenting challenges such as inadequate self-care and emotional distress due to frequent treatment. Managing all these patients is becoming increasingly difficult for the treatment staff. Patients can support each other in managing their care and the disease in such a scenario. Peer support can effectively enhance the resilience and self-efficacy of hemodialysis patients. The critical factor in a peer support intervention is the recruitment and training of peer volunteers. Peer support is crucial in enhancing resilience and improving self-efficacy in dialysis patients by strengthening self-management, providing emotional support, and facilitating informed decision-making. Research indicates that peer support programs can enhance treatment adherence and self-efficacy among dialysis patients. These programs offer a platform for sharing experiences, which can help normalise the challenges of dialysis and encourage patients to participate actively in their care. Integrating peer support into dialysis care can enhance flexibility and improve patients' quality of life and health outcomes. Therefore, nursing managers and planners should consider leveraging the potential of peers when incorporating new educational methods in nursing. Declarations Acknowledgments We acknowledge the Vice Chancellor for Research and Technology and professors from the Faculty of Nursing at Shahrekord University of Medical Sciences for their help in executing this study. Authors’ contributions R.A. SH devised, designed, conducted the study, and wrote the manuscript. R SH assisted with study design and conduct. S.KH helped with manuscript revisions and the analysis plan and power calculation, J.M assisted with training materials and conceptual development, and ZD offered psychological support and counseling for this study. Funding Funding for this study was provided by Vince Chancellor for Research and Technology of Shahrekord University of Medical Science. Availability of data and materials The data that support the findings of this study are available from the corresponding author upon reasonable request. E-mail: [email protected] Phone number: +98-9132810140 Ethics approval and consent to participate The study received approval from the Ethics Committee of the Shahrekord University of Medical Sciences (IR.SKUMS.REC.1401.150). Patients participated in the study voluntarily and had the right to withdraw at any time. All patients provided informed consent. Confidentiality of all data and information sources was strictly maintained. All methods were performed in accordance with the relevant guidelines and regulations. Consent for publication Not Applicable. Competing interests This study had no competing interests. Author Details 1. MSc in intensive care Nursing, Department of Adults and Geriatric Nursing, School of Nursing and Midwifery Shahrekord University of Medical Sciences, Shahrekord, Iran.2.PhD in Health in Disasters and Emergencies, Community-Oriented Nursing Midwifery Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran.3.Assistant Professor of Nursing, Department of Adults and Geriatric Nursing, School of Nursing and Midwifery Shahrekord University of Medical Sciences, Shahrekord, Iran. 4.PhD in Psychology, Department of Counseling Center, Shahrekord University of Medical Sciences, Shahrekord, Iran. 5.Professor of Biostatistics, Department of Epidemiology and Biostatistics, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran References Milan M, Nasimi F, Hafizi I, Ghorbanzade M, Hosseini Y. Evaluation of the Level of Spiritual Health in Patients Undergoing Hemodialysis. Health Research Journal. 2021 Dec 10;7(1):50-8. Kritmetapak K, Pongchaiyakul C. Parathyroid hormone measurement in chronic kidney disease: from basics to clinical implications. international Journal of Nephrology. 2019;2019(1):5496710. Saber A, Tahami AN, Najafipour H, Azmandian J. Assessment of prevalence of chronic kidney disease and its predisposing factors in Kerman city. Nephro-Urology Monthly. 2017 Mar 31;9(2). Khoshkhatti N, Amiri Majd M, Bazzazian S, Yazdinezhad A. The effectiveness of mindfulness-based cognitive therapy on symptoms of anxiety, depression and stress in renal patients under hemodialysis. Iran J Nurs Res. 2020 Jan 10;14(6):9-17. Hatami A, Ghalati ZK, Badrani MR, Jahangirimehr A, Hemmatipour A. The relationship between resilience and perceived social support with hope in hemodialysis patients: a cross-sectional study. Journal of Research in Medical and Dental Science. 2019;7(3):14-20. Zeng W, Wu X, Xu Y, Wu J, Zeng Y, Shao J, Huang D, Zhu Z. The impact of general self-efficacy on psychological resilience during the COVID-19 pandemic: The mediating role of posttraumatic growth and the moderating role of deliberate rumination. Frontiers in psychology. 2021 Jun 23;12:684354. Gholami M, Tarrahi MJ, Hossein Pour AH, Valiniaei S, Bazgir Z. The relationship between health literacy and perceived self-efficacy in cardiovascular patients hospitalized in Khorramabad educational hospitals in 1396. Journal of Nursing Education. 2018 Aug 10;7(3):14-21. Song CS, Jung SY. Research on the Self-Esteem, Resilience, and Quality of life of Hemodialysis Patient. Journal of Convergence for Information Technology. 2020;10(11):77-86. Tilga H, Kalajas-Tilga H, Hein V, Raudsepp L, Koka A. Perceived autonomy support from peers, parents, and physical education teachers as predictors of physical activity and health-related quality of life among adolescents—A one-year longitudinal study. Education Sciences. 2021 Aug 24;11(9):457. Najafi L, Moghaddam Tabrizi F, Ebrahimi M. The effect of peer-based support on health-promoting behaviors in breast cancer survivors in academi hospitals and research centers in Urmia in 2015-16. Nursing And Midwifery Journal. 2018 Feb 10;15(11):795-805. Khahi AM, Mohseny M, Soleimany F, Vejdani M, Keshvardoost A, Amiri P. Relationship between self-transcendence and physically-healthy patients under hemodialysis in participating in peer-support group; a randomized clinical trial. Journal of Renal Injury Prevention. 2017 Jun 2;6(4):253-8. Sargolzaei MS, Khachian A, Seyedoshohadaee M, Haghani H. The effect of peer education on the anxiety of patients with Thalassemia major: A quasi-experimental study. Iran Journal of Nursing. 2021 Apr;34(129):39-49. Tarantino B, Earley M, Audia D, D'Adamo C, Berman B. Qualitative and quantitative evaluation of a pilot integrative coping and resiliency program for healthcare professionals. Explore. 2013 Jan 1;9(1):44-7 Shojaee S, Beh-Pajooh A. The effectiveness of resilience training on resilience and its component in siblings of children with Down syndrome. Journal of Exceptional Children. 2015 Sep 10;15(2):5-18 Connor KM, Davidson JR. Development of a new resilience scale: The Connor‐Davidson resilience scale (CD‐RISC). Depression and anxiety. 2003 Sep;18(2):76-82. Noghani F, Ghadirian F, Sharifnia SH, Fereydooni Sarijjeh P. The study of hope and self-efficacy in hemodialysis patients. Military Caring Sciences. 2020 Nov 10;7(3):234-42. Farani MM, Rejeh N, Heravi-Karimooi M, Davood S. The effect of self-management program based of self-empowerment on the Self-Efficacy in Elderly patients undergoing hemodialysis. Iran J Nurs Res (IJNR) Original Article. 2020 Jun;15(2) Gorji AM, Ahmadinia F, Baladehi NR, Sari I. Examining the Relationship between Spiritual Health and Self-efficacy of Medical Interns of Mazandaran University of Medical Sciences. Simmons D, Cohn S, Bunn C, Birch K, Donald S, Paddison C, Ward C, Robins P, Prevost AT, Graffy J. Testing a peer support intervention for people with type 2 diabetes: a pilot for a randomised controlled trial. BMC family practice. 2013 Dec;14:1-0. Chen X, Hua L, Zhang C, Xu Z, Cao X, Cai Y. Effect of peer support on improving self-management ability in peritoneal dialysis patients—a randomized controlled trial. Annals of Palliative Medicine. 2021 Mar;10(3):3028038-3038. Li H, Jiang YF, Lin CC. Factors associated with self-management by people undergoing hemodialysis: a descriptive study. Int J Nurs Stud.2014;51(2):208–16. Cabrera VJ, Hansson J, Kliger AS, Finkelstein FO. Symptom Management of the Patient with CKD: the role of Dialysis. Clin J Am Soc Nephrol. 2017;12(4):687–93. Cabrera C, Brunelli SM, Rosenbaum D, et al. A retrospective, longitudinal study estimating the association between interdialytic weight gain and cardiovascular events and death in hemodialysis patients. BMC Nephrol.2015;16:113 Sharp J, Wild MR, Gumley AI. A systematic review of psychological interventions to treat nonadherence to fluid-intake restrictions in people receiving hemodialysis. Am J Kidney Dis. 2005;45(1):15–27. Irajpour A, Hashemi MS, Abazari P, Shahidi S. The effects of peer education on treatment adherence among patients receiving hemodialysis: a randomized controlled trial. Iranian Journal of Nursing and Midwifery Research. 2024 Jan 1;29(1):46-55. Mollaei Z, Rahemi Z, Izadi Avanji FS, Sarvizadeh M, Hosseinian M, Akbari H. The effect of self-care training by peer group on the resilience of patients with cancer: a randomized clinical trial. Journal of Client-Centered Nursing Care. 2022 Jan 10;8(1):41-50. Heisler M, Vijan S, Makki F, Piette JD. Diabetes control with reciprocal peer support versus nurse care management: a randomized trial. Ann Intern Med. 2010;153(8):507–15. Heisler M. Different models to mobilize peer support to improve diabetes self-management and clinical outcomes: evidence, logistics, evaluation considerations and needs for future research. Fam Pract. 2010;27(Suppl1):i23–32 Jamali A, Ghaljaei F, Keikhaei A, Jalalodini A. Effect of peer education on the resilience of mothers of children with leukemia: A clinical trial. Medical-Surgical Nursing Journal. 2019 May 31;8(2). Heydarzadeh N, Rezaee M, Habibzadeh HO. Effect of peer education on self-efficacy of dialysis patients referring to educational-medical centers in Urmia in 2019. Journal of Clinical Nursing and Midwifery. 2020 Jan 1;9(3):719-27. Tang TS, Funnell M, Sinco B, et al. Comparative effectiveness of peer leaders and community health workers in diabetes self-management support: results of a randomized controlled trial. Diabetes Care.2014;37(6):1525–34. Webel AR, Okonsky J, Trompeta J, Holzemer WL. A systematic review of the effectiveness of peer-based interventions on health-related behaviors in adults. Am J Public Health. 2010;100(2):247–53 Wetmore JB, Gilbertson DT, Liu J, Collins AJ. Improving outcomes in patients receiving dialysis: the peer kidney care initiative. Clinical Journal of the American Society of Nephrology. 2016 Jul 1;11(7):1297-304. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 24 Sep, 2025 Reviewers agreed at journal 15 Sep, 2025 Reviewers invited by journal 07 Aug, 2025 Editor assigned by journal 06 Aug, 2025 Editor invited by journal 14 May, 2025 Submission checks completed at journal 13 May, 2025 First submitted to journal 29 Apr, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6559212","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":497286828,"identity":"d35982c0-828a-4a74-9b6f-a85777a88fea","order_by":0,"name":"Rezvan Shirali","email":"","orcid":"","institution":"Shahrekord University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Rezvan","middleName":"","lastName":"Shirali","suffix":""},{"id":497286829,"identity":"d7ae377c-bf02-424d-8985-2c1f2457cfed","order_by":1,"name":"Rahim Ali Sheikhi","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABFklEQVRIiWNgGAWjYBAC+wYehgNAOoGBgY2NIaGCTQ4keuABHi0GB1C0nOEzBmtJIKCFAa6FsU0usQHKxa3l+NmDh24w1OXxz0hLe/CwzSx9ftjhh0Bb7OR0G3D4pScv4XAOw+FiiRtpxw0SzqXlbrydZgDUkmxsdgC7FjuGHAOglgOJDTfS2yQSyo7lbpydANJyIHEbDi3G/G9AWuoS54O1sP1PN5yd/gGvFsMZYFuYEzfcSDsmkdDGliAvnYPfFoMbIFsMDiduPPMsTSLhDJvhBumcggMJBrj9YnA+x/hzTkVd4rzjaWaSPyrY5OVnp2/+8KHCTg6XFqhGIBZIgLIPwEQIAn6oofINxKgeBaNgFIyCkQQAiNxsQO9HwFcAAAAASUVORK5CYII=","orcid":"","institution":"Shahrekord University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Rahim","middleName":"Ali","lastName":"Sheikhi","suffix":""},{"id":497286830,"identity":"43000444-0b9c-4fee-8254-e74d44084d57","order_by":2,"name":"Jaefar Moghaddasi","email":"","orcid":"","institution":"Shahrekord University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Jaefar","middleName":"","lastName":"Moghaddasi","suffix":""},{"id":497286831,"identity":"57647cee-1408-4072-9e46-db0396cb9354","order_by":3,"name":"Zahra Davoudi","email":"","orcid":"","institution":"Shahrekord University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Zahra","middleName":"","lastName":"Davoudi","suffix":""},{"id":497286832,"identity":"02983ff9-4702-414c-9759-fd3f7af858e5","order_by":4,"name":"Soleiman kheiri","email":"","orcid":"","institution":"Shahrekord University of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Soleiman","middleName":"","lastName":"kheiri","suffix":""}],"badges":[],"createdAt":"2025-04-29 19:53:04","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6559212/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6559212/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":88951880,"identity":"eb455ef2-0f01-4b6a-b384-000e05510679","added_by":"auto","created_at":"2025-08-13 05:55:49","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":134766,"visible":true,"origin":"","legend":"\u003cp\u003eThe semi trial design of the study\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6559212/v1/1cd3eda23d48f52829429dac.jpg"},{"id":88952228,"identity":"add17434-944a-4368-8bff-8d9af32f2f47","added_by":"auto","created_at":"2025-08-13 06:03:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":843745,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6559212/v1/2d5dc20f-52d4-42de-93bd-ea6d58a4152e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"The effect of the peer educational-supportive program on enhancing the resilience and self-efficacy of Hemodialysis patients ","fulltext":[{"header":"Background","content":"\u003cp\u003eIn chronic kidney failure, irreversible damage is done to the kidney tissue, and alternative treatments for kidney function will be needed to save the patient's life (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). According to population surveys, over 15% of adults in the United States are estimated to suffer from kidney failure (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In Iran, approximately 35,000 individuals suffer from chronic kidney failure, with 19% of them residing in Tehran. Hemodialysis remains the most prevalent treatment method for these patients, with over 50% of kidney patients in Iran undergoing this procedure (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eHemodialysis is a stressful process that significantly impacts patients' quality of life. The belief in having an incurable disease can make it challenging to cope and reduce a person's resilience (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Some studies showed that hemodialysis patients referred to hospitals had lower-than-average resilience (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Resilience, the ability to handle life's challenges, is an important personality trait in health-related sciences. It is essential to focus on promoting resilience in the care of these patients. Therefore, interventions to improve resilience should be a priority in caring for these patients (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Self-efficacy involves a person's belief in their ability to perform self-care tasks effectively, leading to improved self-care outcomes. Research indicates that self-efficacy, social support, life expectancy, and self-confidence are crucial factors in patient resilience, particularly among hemodialysis patients (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e). Resilience and self-efficacy have a mutually reinforcing relationship: improving self-efficacy enhances patient resilience, further boosting the patient's self-efficacy(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eA peer shares similar characteristics with another person, such as age, gender, occupation, economic-social status, and health status. Peer support involves using personal knowledge and experience to help manage one's health effectively (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Successful peers can cheaply share their weaknesses, strengths, and experiences with patients. By discussing the stress of chronic disease and motivating them, peers encourage patients to adopt appropriate health behaviors. One method of peer support is the peer educational- support program, which helps individuals learn methods to cope with the disease and improve their quality of life (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Previous research indicates that engaging in peer support programs positively impacts the mental health of individuals undergoing hemodialysis (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eThe influence of peers on self-management skills, adherence to fluid intake, improved outcomes, and reduced hospitalization duration in hemodialysis patients has been widely studied because it can enhance their resilience and boost their self-efficacy. However, there is a lack of research on the effects of educational- support programs and peer support on resilience and self-efficacy in this patient group. Additionally, studies examining the influence of peers on the resilience of other chronic patients have produced conflicting results. For example, some studies reported no impact on the anxiety levels of patients with thalassemia (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). This study aims to investigate the effects of peer educational support programs on the resilience and self-efficacy of hemodialysis patients at Hajar Hospital in Shahrekord.\u003c/p\u003e"},{"header":"Material and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eStudy design and setting\u003c/h2\u003e\u003cp\u003eThe present study was semi-experimental, with a control group and a pre-test-post-test design. It was conducted at Hajar Hospital in Shahrekord from October 2023 to February 2024.\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eStudy participants and sampling\u003c/h3\u003e\n\u003cp\u003eThe study included all hemodialysis patients referred to Hajar Hospital in Shahrekord, with 79 hemodialysis patients. Among them, 41 patients visited the hemodialysis department on even days, while 38 visited on odd days. By random selection, patients referred on odd days were designated as the control group, and those referred on even days were chosen as the intervention group. Five patients from the intervention group were selected to serve as peer trainers. ( Table \u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). These trainers conducted training and support programs for groups of 6 to 7 people. After applying the inclusion and exclusion criteria and considering some patients' refusal to participate, 32 individuals in the intervention group and 34 in the control group completed the questionnaires.\u003c/p\u003e\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"387\" height=\"577\"\u003e\u003c/p\u003e\n\u003cp\u003eInclusion criteria required participants to be interested in the study (showing necessary cooperation and signing informed consent), aged between 20 and 65 years, have a history of hemodialysis for at least one year, and undergo at least two weekly hemodialysis sessions. Exclusion criteria included refusal to continue cooperating, incomplete questionnaire completion, non-participation in two training sessions, and simultaneous hospitalization due to another disease, poor-condition patients, and being referred on odd and even days. One patient in the intervention group and three patients in the control group refused to participate in the study. One patient was excluded from the intervention group due to severe illness, and two because of less than 1 year of hemodialysis. In the control group, one patient was ruled out because of less than 1 year of hemodialysis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection tools and technique\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data collection tool included questionnaires about patient\u0026rsquo;s demographic characteristics (age, gender, marital status, education, occupation, and duration of hemodialysis), Connor \u0026amp; Davidson\u0026apos;s resilience, and Sherer\u0026rsquo;s questionnaire about self-efficacy.\u0026nbsp;The Connor and Davidson Resilience Scale, introduced in 2003, was utilized to assess the resilience of hemodialysis patients. This questionnaire contains 25 items aimed at evaluating individuals\u0026apos; resilience. Respondents rate each item on a Likert scale ranging from one (completely false) to five (always true). (13)In Iran, the tool was standardized by Mohammadi in 2005, who reported a validity score of 0.82 and a reliability score of 0.79.\u0026nbsp;(14)\u0026nbsp;Five dimensions of Connor \u0026amp; Davidson\u0026apos;s tool are the perception of individual competence, trust in individual instincts, negative emotional tolerance, positive acceptance of change and secure relationships, control, and negative influences. The range of test scores is between 0 and 100. Higher scores indicate greater resilience of the subject (15).\u0026nbsp;The Self-Efficacy Scale developed by Sherer et al. (1982) consists of 17 questions, each using a Likert scale that ranges from \u0026quot;strongly disagree\u0026quot; to \u0026quot;strongly agree.\u0026quot; Each item is scored from 1 to 5 and\u0026nbsp;the total score can vary from 17 to 85.\u0026nbsp;\u0026nbsp;(16, 17).This scale was translated and validated by Bakhtiari Barati in 1997 and its validity and reliability were proven at 79 percent (18).\u003c/p\u003e\n\u003cp\u003ePatients were assigned to either the control or intervention group based on whether they visited for hemodialysis on even or odd days of the week. Demographic and resilience questionnaires by Connor and Davidson and Sherer\u0026apos;s questionnaires were completed for both groups as a pre-test. Then, five hemodialysis patients, both men and women, were chosen based on recommendations from kidney specialists and the clinic\u0026apos;s general practitioner. The selection process involved reviewing their medical records, including test results and evaluations from specialists such as cardiologists, ophthalmologists, and internists, to ensure they had effectively managed their hemodialysis complications. The selected individuals shared similar conditions with the research units, such as age (20 to 68 years), a history of hemodialysis for more than one year, having completed education through senior high school or higher levels, and having cultural, social, and economic similarities. They also had good social relations, the ability to manage meetings, and were interested in leadership. Furthermore, they obtained higher scores on the resilience and self-efficacy questionnaires.\u003c/p\u003e\n\u003cp\u003eOne peer taught and supported six or seven patients in this study, leading to the selection of five candidates. A multidisciplinary team, including a kidney specialist, a psychological consultant with a PhD degree, a nursing PhD and a master\u0026apos;s in nursing with experience in the hemodialysis department, and an employee of the hemodialysis department, participated in training the peers.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFirst, the research team trained peers in eight sessions lasting 45 to 60 minutes over four weeks (8 sessions). They were also trained through role-playing (Table 2). Then, they provided the necessary education to hemodialysis patients in eight group sessions of 45 to 60 minutes in the hospital\u0026apos;s conference hall and face-to-face sessions over four weeks.\u0026nbsp;Over the next eight weeks, patients in the intervention group received peer education and support. Specially trained peers, supervised by the research team, provided training, answered questions, and offered support before, during, and after each dialysis session. The peers also provided ongoing support by answering questions over the phone or in virtual spaces, offering emotional and psychological support, and showing empathy around the clock.\u003c/p\u003e\n\u003cp\u003eThe educating content covers kidney failure and hemodialysis knowledge, including symptoms, complications, risk factors, and treatments. It includes approved nutritional recommendations from a nutritionist, exercise suggestions, drug therapy and self-monitoring, and weight control. The education also addresses and corrects common concerns and misconceptions about treating kidney failure and hemodialysis. Furthermore, it involves practical implementation, including fistula care, weight monitoring, and interpretation and decision-making when dealing with limitations.\u003c/p\u003e\n\u003cp\u003eAfter completing 12 weeks of education and support, the Connor and Davidson resilience questionnaire for both the control and intervention groups was completed (post-test). The data was entered into SPSS version 19 statistical software for analysis. The data were analyzed using descriptive statistics (mean, standard deviation, frequency) and inferential tests (chi-square, Fisher\u0026apos;s exact, paired t-test, and independent t-test).\u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"474\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"2\" valign=\"top\" style=\"width: 474px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e. The topics taught to the peer group by the research team\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003efirst session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003e\u0026nbsp;Definition of peer support, the role and responsibility of peers, and self-awareness of one\u0026apos;s capabilities.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003esecond session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003eStrengthening self-esteem; effective communication to improve people\u0026apos;s communication ability\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003ethird session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003esymptoms, complications, and risk factors of kidney failure and hemodialysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003efourth session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003eAnger management, anxiety, and stress management. Strengthening the sense of spirituality and faith.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003efifth session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003e\u0026nbsp;Exercise recommendations, Drug therapy, self-monitoring, fistula care\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003esixth session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003eestablishing social relations with peers and friends - Nutritional recommendation\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eseventh session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003eSelf-efficacy, increasing positive emotional sense, Self-belief, and genuine self-confidence.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 78px;\"\u003e\n \u003cp\u003eeighth session\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 396px;\"\u003e\n \u003cp\u003eCommon concerns and misconceptions about treating kidney failure, hemodialysis, and weight control.\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eEthical considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eAs shown in Table 3\u003cspan dir=\"RTL\"\u003e\u0026nbsp;of the 66 patients who completed the study in both the control and intervention groups, 39 were male (59.1%) and 27 were female (40.9%). Regarding literacy levels, out of the 66 participants, 28 (42.4%) had graduated from primary school or had lower education levels. Additionally, 21 participants (31.8%) completed high school or senior high school, while 17 (25.8%) held bachelor\u0026apos;s degrees or higher. The chi-square test indicated that the two groups were similar in gender, marital status and education (p \u0026gt; 0.05). Additionally, Fisher\u0026apos;s exact test showed no statistically significant difference in occupation between the two groups (P \u0026gt; 0.05).\u0026nbsp;\u003c/span\u003e\u003c/p\u003e\n\u003cp\u003eThe average age of the patients in the intervention group was 48.48 years with a standard deviation of 12.50, while the average age in the control group was 50.77 with a standard deviation of 11.05. According to the independent t-test, there was no statistically significant difference in the average age between the two groups (P=0.42). Additionally, the average duration of hemodialysis for intervention group patients was 28.62 months with a standard deviation of 28.10, and for control group patients, it was 32.40 months with a standard deviation of 26.97. According to the Mann-Whitney test, the two groups did not show a statistically significant difference in the average duration of hemodialysis (P=0.34)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e. General information of the participants\u003c/p\u003e\n\u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"670\" height=\"754\"\u003e\u003c/p\u003e\n\u003cp\u003eIn the intervention group, the mean age of participants was 44.82 \u0026plusmn; 7.13, while in the control group, it was 45.68 \u0026plusmn; 6.39. The independent t-test indicated no statistically significant difference between the two groups (p=0.59). After the intervention, the mean resilience score in the intervention group increased to 63.25 \u0026plusmn; 6.63, whereas in the control group, it reached 46.71 \u0026plusmn; 6.15. An independent t-test showed a significant difference between the two groups (P\u0026lt;.001), suggesting an improvement in the intervention group\u0026apos;s resilience. Furthermore, a paired t-test comparing resilience scores in the intervention group before and after the intervention revealed a significant difference (p\u0026lt;0.001), but this difference was not significant in the control group (p=0.12) \u003cstrong\u003e(Table 4).\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"746\" height=\"472\"\u003e\u003c/strong\u003e\u003cbr\u003e\u003c/p\u003e\n\u003cp\u003eThe mean and standard deviation of the patients\u0026apos; self-efficacy scores before the intervention were 32.02 \u0026plusmn; 5.02 in the intervention group and 31.37 \u0026plusmn; 4.74 in the control group. An independent t-test (p=0.57) showed no statistically significant difference between the two groups. After the intervention, the mean and standard deviation of self-efficacy in the intervention group increased to 55.80 \u0026plusmn; 6.97, while in the control group, it reached 32.45 \u0026plusmn; 5.07. The independent t-test indicated a significant difference, suggesting improved self-efficacy in the intervention group (p\u0026lt;0.001). A paired t-test comparing the mean and standard deviation of the self-efficacy scores of the patients before and after the intervention group intervention showed a significant difference from the pre-test to the post-test time (p\u0026lt;0.001). However, this difference from the pre-test to the post-test was insignificant in the control group (p=0.36). In conclusion, the intervention led to a significant increase in self-efficacy.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis research tested the efficacy of an education and support program delivered by peer mentorship in enhancing the resilience and self-efficacy of hemodialysis patients (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). In this study, five mentors, both men and women, who were in good condition based on the opinion of an expert physician and tests, were selected as peers and trained by the research group in eight sessions of 45 to 60 minutes (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Peer support involves peer education and relies on volunteers to offer positive feedback, demonstrate leadership, and influence others. These volunteers are essential because they have firsthand experience with the same conditions as the patients they assist. This shared experience allows them to understand patients' psychological challenges, share similar life experiences, and provide crucial support through attentive listening and open discussions about issues (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). Choosing, training, and evaluating the right peers for medical conditions and disease control is crucial to ensure the correct transfer of information and proper patient support (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e\u003cp\u003eLack of awareness, negative attitudes toward self-management, and low self-efficacy prevent hemodialysis patients from adhering to treatment. Education provided by dialysis facilities offers general guidelines on diet and adherence, but it does not help patients recognise or attribute the symptoms of uremia or intradialytic weight gain to poor self-management behaviours (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eUsing context-sensitive interventions increases social support, self-efficacy, and resilience, improving adherence to dialysis treatment (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e). The impact of peer-to-peer self-care training on cancer patients' resilience showed a significant improvement in the intervention group's resilience levels after the program. (\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePeer mentorship has proven effective in managing chronic diseases like diabetes, depression, and AIDS among patients undergoing dialysis (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Also, the influence of peer groups on mothers of children with leukaemia has been established. Before the intervention, the two groups had no significant difference in average resilience levels. However, a considerable difference emerged after the intervention, showing a marked improvement in resilience among the mothers in the intervention group (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePeer education significantly improved dialysis patients' self-efficacy (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Peer mentor interventions enhance health-related behaviors and self-management. In patients on hemodialysis, these interventions have successfully improved care discussions, treatment adherence, and quality-of-life measures (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eThe present study combined an educational and support program similar to other studies but with unique elements. During hemodialysis sessions, trained peers provided education and listened to patients' concerns. They offered guidance and support, allowing patients to discuss their problems and explore potential solutions. Additionally, outside of hemodialysis sessions, these peers were equipped to assist patients via virtual communication or phone calls when needed.\u003c/p\u003e\u003cp\u003eThe results of Wetmore's research, while similar to the current study in some ways, also differ in others. It showed that short-term interventions can enhance patients' knowledge levels but do not improve self-management abilities. In contrast, a six-month peer support program significantly enhanced self-care in hemodialysis patients (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e). Although the duration of peer influence on hemodialysis patients varied across studies, all research consistently confirmed that peer support training positively impacts patient resilience and self-efficacy. Therefore, it can be concluded that peer support training programs effectively improve patient resilience.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe growing number of hemodialysis patients is presenting challenges such as inadequate self-care and emotional distress due to frequent treatment. Managing all these patients is becoming increasingly difficult for the treatment staff. Patients can support each other in managing their care and the disease in such a scenario. Peer support can effectively enhance the resilience and self-efficacy of hemodialysis patients. The critical factor in a peer support intervention is the recruitment and training of peer volunteers. Peer support is crucial in enhancing resilience and improving self-efficacy in dialysis patients by strengthening self-management, providing emotional support, and facilitating informed decision-making. Research indicates that peer support programs can enhance treatment adherence and self-efficacy among dialysis patients. These programs offer a platform for sharing experiences, which can help normalise the challenges of dialysis and encourage patients to participate actively in their care. Integrating peer support into dialysis care can enhance flexibility and improve patients' quality of life and health outcomes. Therefore, nursing managers and planners should consider leveraging the potential of peers when incorporating new educational methods in nursing.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge the Vice Chancellor for Research and Technology and professors from the Faculty of Nursing at Shahrekord University of Medical Sciences\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003efor their help in executing this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026rsquo; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eR.A. SH devised, designed, conducted the study, and wrote the manuscript. R SH assisted with study design and conduct. S.KH helped with manuscript revisions and the analysis plan and power calculation, J.M assisted with training materials and conceptual development,\u003cspan dir=\"RTL\"\u003e\u0026nbsp;\u003c/span\u003eand ZD offered psychological support and counseling for this study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding for this study was provided by Vince Chancellor for Research and Technology of Shahrekord University of Medical Science.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of data and materials\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the findings of this study are available from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eE-mail:[email protected]\u003c/li\u003e\n \u003cli\u003ePhone number: +98-9132810140\u003c/li\u003e\n\u003c/ul\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study received approval from the Ethics Committee of the Shahrekord University of Medical Sciences (IR.SKUMS.REC.1401.150). Patients participated in the study voluntarily and had the right to withdraw at any time. All patients provided informed consent. Confidentiality of all data and information sources was strictly maintained. All methods were performed in accordance with the relevant guidelines and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot Applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study had no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e1.\u003c/strong\u003eMSc in intensive care Nursing, Department of Adults and Geriatric Nursing, School of Nursing and Midwifery Shahrekord University of Medical Sciences, Shahrekord, Iran.2.PhD in Health in Disasters and Emergencies, Community-Oriented Nursing Midwifery Research Center, Shahrekord University of Medical Sciences, Shahrekord, Iran.3.Assistant Professor of Nursing, Department of Adults and Geriatric Nursing, School of \u0026nbsp; \u0026nbsp; Nursing and Midwifery Shahrekord University of Medical Sciences, Shahrekord, Iran. 4.PhD in Psychology, Department of Counseling Center, Shahrekord University of Medical Sciences, Shahrekord, Iran. 5.Professor of Biostatistics, Department of Epidemiology and Biostatistics, School of Health, Shahrekord University of Medical Sciences, Shahrekord, Iran\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMilan M, Nasimi F, Hafizi I, Ghorbanzade M, Hosseini Y. Evaluation of the Level of Spiritual Health in Patients Undergoing Hemodialysis. Health Research Journal. 2021 Dec 10;7(1):50-8.\u003c/li\u003e\n\u003cli\u003eKritmetapak K, Pongchaiyakul C. Parathyroid hormone measurement in chronic kidney disease: from basics to clinical implications. international Journal of Nephrology. 2019;2019(1):5496710.\u003c/li\u003e\n\u003cli\u003eSaber A, Tahami AN, Najafipour H, Azmandian J. Assessment of prevalence of chronic kidney disease and its predisposing factors in Kerman city. Nephro-Urology Monthly. 2017 Mar 31;9(2).\u003c/li\u003e\n\u003cli\u003eKhoshkhatti N, Amiri Majd M, Bazzazian S, Yazdinezhad A. The effectiveness of mindfulness-based cognitive therapy on symptoms of anxiety, depression and stress in renal patients under hemodialysis. Iran J Nurs Res. 2020 Jan 10;14(6):9-17.\u003c/li\u003e\n\u003cli\u003eHatami A, Ghalati ZK, Badrani MR, Jahangirimehr A, Hemmatipour A. The relationship between resilience and perceived social support with hope in hemodialysis patients: a cross-sectional study. Journal of Research in Medical and Dental Science. 2019;7(3):14-20.\u003c/li\u003e\n\u003cli\u003eZeng W, Wu X, Xu Y, Wu J, Zeng Y, Shao J, Huang D, Zhu Z. The impact of general self-efficacy on psychological resilience during the COVID-19 pandemic: The mediating role of posttraumatic growth and the moderating role of deliberate rumination. Frontiers in psychology. 2021 Jun 23;12:684354.\u003c/li\u003e\n\u003cli\u003eGholami M, Tarrahi MJ, Hossein Pour AH, Valiniaei S, Bazgir Z. The relationship between health literacy and perceived self-efficacy in cardiovascular patients hospitalized in Khorramabad educational hospitals in 1396. Journal of Nursing Education. 2018 Aug 10;7(3):14-21.\u003c/li\u003e\n\u003cli\u003eSong CS, Jung SY. Research on the Self-Esteem, Resilience, and Quality of life of Hemodialysis Patient. Journal of Convergence for Information Technology. 2020;10(11):77-86.\u003c/li\u003e\n\u003cli\u003eTilga H, Kalajas-Tilga H, Hein V, Raudsepp L, Koka A. Perceived autonomy support from peers, parents, and physical education teachers as predictors of physical activity and health-related quality of life among adolescents\u0026mdash;A one-year longitudinal study. Education Sciences. 2021 Aug 24;11(9):457.\u003c/li\u003e\n\u003cli\u003eNajafi L, Moghaddam Tabrizi F, Ebrahimi M. The effect of peer-based support on health-promoting behaviors in breast cancer survivors in academi hospitals and research centers in Urmia in 2015-16. Nursing And Midwifery Journal. 2018 Feb 10;15(11):795-805.\u003c/li\u003e\n\u003cli\u003eKhahi AM, Mohseny M, Soleimany F, Vejdani M, Keshvardoost A, Amiri P. Relationship between self-transcendence and physically-healthy patients under hemodialysis in participating in peer-support group; a randomized clinical trial. Journal of Renal Injury Prevention. 2017 Jun 2;6(4):253-8.\u003c/li\u003e\n\u003cli\u003eSargolzaei MS, Khachian A, Seyedoshohadaee M, Haghani H. The effect of peer education on the anxiety of patients with Thalassemia major: A quasi-experimental study. Iran Journal of Nursing. 2021 Apr;34(129):39-49.\u003c/li\u003e\n\u003cli\u003eTarantino B, Earley M, Audia D, D\u0026apos;Adamo C, Berman B. Qualitative and quantitative evaluation of a pilot integrative coping and resiliency program for healthcare professionals. Explore. 2013 Jan 1;9(1):44-7\u003c/li\u003e\n\u003cli\u003eShojaee S, Beh-Pajooh A. The effectiveness of resilience training on resilience and its component in siblings of children with Down syndrome. Journal of Exceptional Children. 2015 Sep 10;15(2):5-18 \u003c/li\u003e\n\u003cli\u003eConnor KM, Davidson JR. Development of a new resilience scale: The Connor‐Davidson resilience scale (CD‐RISC). Depression and anxiety. 2003 Sep;18(2):76-82.\u003c/li\u003e\n\u003cli\u003eNoghani F, Ghadirian F, Sharifnia SH, Fereydooni Sarijjeh P. The study of hope and self-efficacy in hemodialysis patients. Military Caring Sciences. 2020 Nov 10;7(3):234-42.\u003c/li\u003e\n\u003cli\u003eFarani MM, Rejeh N, Heravi-Karimooi M, Davood S. The effect of self-management program based of self-empowerment on the Self-Efficacy in Elderly patients undergoing hemodialysis. Iran J Nurs Res (IJNR) Original Article. 2020 Jun;15(2)\u003c/li\u003e\n\u003cli\u003eGorji AM, Ahmadinia F, Baladehi NR, Sari I. Examining the Relationship between Spiritual Health and Self-efficacy of Medical Interns of Mazandaran University of Medical Sciences.\u003c/li\u003e\n\u003cli\u003eSimmons D, Cohn S, Bunn C, Birch K, Donald S, Paddison C, Ward C, Robins P, Prevost AT, Graffy J. Testing a peer support intervention for people with type 2 diabetes: a pilot for a randomised controlled trial. BMC family practice. 2013 Dec;14:1-0.\u003c/li\u003e\n\u003cli\u003eChen X, Hua L, Zhang C, Xu Z, Cao X, Cai Y. Effect of peer support on improving self-management ability in peritoneal dialysis patients\u0026mdash;a randomized controlled trial. Annals of Palliative Medicine. 2021 Mar;10(3):3028038-3038.\u003c/li\u003e\n\u003cli\u003eLi H, Jiang YF, Lin CC. Factors associated with self-management by people undergoing hemodialysis: a descriptive study. Int J Nurs Stud.2014;51(2):208\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eCabrera VJ, Hansson J, Kliger AS, Finkelstein FO. Symptom Management of the Patient with CKD: the role of Dialysis. Clin J Am Soc Nephrol. 2017;12(4):687\u0026ndash;93.\u003c/li\u003e\n\u003cli\u003eCabrera C, Brunelli SM, Rosenbaum D, et al. A retrospective, longitudinal study estimating the association between interdialytic weight gain and cardiovascular events and death in hemodialysis patients. BMC Nephrol.2015;16:113 \u003c/li\u003e\n\u003cli\u003eSharp J, Wild MR, Gumley AI. A systematic review of psychological interventions to treat nonadherence to fluid-intake restrictions in people receiving hemodialysis. Am J Kidney Dis. 2005;45(1):15\u0026ndash;27.\u003c/li\u003e\n\u003cli\u003eIrajpour A, Hashemi MS, Abazari P, Shahidi S. The effects of peer education on treatment adherence among patients receiving hemodialysis: a randomized controlled trial. Iranian Journal of Nursing and Midwifery Research. 2024 Jan 1;29(1):46-55.\u003c/li\u003e\n\u003cli\u003eMollaei Z, Rahemi Z, Izadi Avanji FS, Sarvizadeh M, Hosseinian M, Akbari H. The effect of self-care training by peer group on the resilience of patients with cancer: a randomized clinical trial. Journal of Client-Centered Nursing Care. 2022 Jan 10;8(1):41-50.\u003c/li\u003e\n\u003cli\u003eHeisler M, Vijan S, Makki F, Piette JD. Diabetes control with reciprocal peer support versus nurse care management: a randomized trial. Ann Intern Med. 2010;153(8):507\u0026ndash;15.\u003c/li\u003e\n\u003cli\u003eHeisler M. Different models to mobilize peer support to improve diabetes self-management and clinical outcomes: evidence, logistics, evaluation considerations and needs for future research. Fam Pract. 2010;27(Suppl1):i23\u0026ndash;32\u003c/li\u003e\n\u003cli\u003eJamali A, Ghaljaei F, Keikhaei A, Jalalodini A. Effect of peer education on the resilience of mothers of children with leukemia: A clinical trial. Medical-Surgical Nursing Journal. 2019 May 31;8(2).\u003c/li\u003e\n\u003cli\u003eHeydarzadeh N, Rezaee M, Habibzadeh HO. Effect of peer education on self-efficacy of dialysis patients referring to educational-medical centers in Urmia in 2019. Journal of Clinical Nursing and Midwifery. 2020 Jan 1;9(3):719-27.\u003c/li\u003e\n\u003cli\u003eTang TS, Funnell M, Sinco B, et al. Comparative effectiveness of peer leaders and community health workers in diabetes self-management support: results of a randomized controlled trial. Diabetes Care.2014;37(6):1525\u0026ndash;34.\u003c/li\u003e\n\u003cli\u003eWebel AR, Okonsky J, Trompeta J, Holzemer WL. A systematic review of the effectiveness of peer-based interventions on health-related behaviors in adults. Am J Public Health. 2010;100(2):247\u0026ndash;53\u003c/li\u003e\n\u003cli\u003eWetmore JB, Gilbertson DT, Liu J, Collins AJ. Improving outcomes in patients receiving dialysis: the peer kidney care initiative. Clinical Journal of the American Society of Nephrology. 2016 Jul 1;11(7):1297-304.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"peer education, resilience, self-efficacy, hemodialysis patients","lastPublishedDoi":"10.21203/rs.3.rs-6559212/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6559212/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u0026nbsp;\u003c/strong\u003eHemodialysis patients often have low resilience\u0026nbsp;and self-efficacy due to physical limitations, psychological pressures, and lack of social support. Nursing care must prioritize addressing these issues. Additionally, patients can be motivated and encouraged by seeing others who have successfully coped with similar challenges. Therefore, this study aims to assess the impact of peer educational-supportive programs on enhancing the resilience\u0026nbsp;and self-efficacy of hemodialysis patients.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e The study was conducted at Hajar Hospital in Shahrekord and focused on hemodialysis patients. Patients were chosen using an available method and placed into either the intervention (32-person) or control group (34-person) based on whether they were admitted on odd or even days. Initially, five peers were selected from hemodialysis patients and underwent eight training sessions lasting 45 to 60 minutes. Afterward, the intervention group participated in a 12-week educational and support program the selected peers implemented. Data was collected using demographic and resilience questionnaires developed by Connor and Davidson and Shere’s general self-efficacy questionnaire. The analysis was conducted using SPSS version 16 software.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e The average scores for resilience and self-efficacy in the intervention group before the intervention were 44.82 ± 7.13 and 5.02 ± 32.02, respectively. Following the intervention, these scores improved to 63.25 ± 6.63 and 55.80 ± 6.98, respectively, showing statistically significant changes (P \u0026lt; 0.001). In contrast, there were no significant differences in resilience and self-efficacy scores within the control group before and after the intervention (P \u0026gt; 0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions\u003c/strong\u003e: The study's results demonstrate that the educational support program implemented by peers has a positive effect on increasing the resilience and self-efficacy of hemodialysis patients. Therefore, it is suggested that including peers in educational support programs to enhance resilience and self-efficacy be seriously considered.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial registration:\u003c/strong\u003e No\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTrial sponsor:\u0026nbsp;\u003c/strong\u003eShahrekord University of Medical Science\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding:\u003c/strong\u003e This research is financially supported by Shahrekord University of Medical\u003cstrong\u003e\u0026nbsp;Sciences.\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy status:\u0026nbsp;\u003c/strong\u003eThis study has been completed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelated article:\u0026nbsp;\u003c/strong\u003eNo related articles for this study have been submitted to any journal. The study's sponsor and funders had no involvement in the data's design, analysis, or interpretation. The content is entirely the authors' responsibility and does not necessarily reflect the official views of the National Institutes of Health.\u003c/p\u003e","manuscriptTitle":"The effect of the peer educational-supportive program on enhancing the resilience and self-efficacy of Hemodialysis patients ","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-13 05:47:44","doi":"10.21203/rs.3.rs-6559212/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-09-24T11:35:11+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"73614740571563764936212087167480405854","date":"2025-09-15T04:26:35+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-08-07T10:16:03+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-08-06T05:36:27+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-05-14T07:01:42+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-05-13T06:54:20+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2025-04-29T19:37:51+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"de0b64ac-152f-41b2-8bad-8f09c9bd0630","owner":[],"postedDate":"August 13th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":52827554,"name":"Health sciences/Health care"},{"id":52827555,"name":"Health sciences/Nephrology"}],"tags":[],"updatedAt":"2025-08-13T05:47:44+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-13 05:47:44","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6559212","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6559212","identity":"rs-6559212","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}