A Causal Model of Self-Management Behavior in Persons Receiving Hemodialysis

A Causal Model of Self-Management Behavior in Persons Receiving Hemodialysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A Causal Model of Self-Management Behavior in Persons Receiving Hemodialysis Pailin Pinthong, Orn-anong Wichaikum, Chomphoonut Srirat, Chiraporn Tachaudomdach, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8714747/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background End-stage renal disease and hemodialysis treatment were complex and impacted on the ineffective self-management behavior of hemodialysis patients. The aim of this study was to test the structural model for hemodialysis self-management behavior in Thailand. Methods This study utilized a cross-sectional design with cluster sampling based on purposive selection, involving 11 hemodialysis units and 550 patients from public hospitals in Northeast Thailand. Data collection from March to August 2024 utilized seven instruments: 1) the 14-item Health Literacy Scale (HLS-14), 2) the Patient Health Questionnaire (PHQ-9), 3) the Family State and Functioning Assessment Scale (FSFAS), 4) the Hemodialysis Knowledge Questionnaire (HDKQ), 5) the Hemodialysis Self-Management Self-Efficacy Questionnaire (HSMSEQ), 6) the Social Support Questionnaire (SSQ), and 7) the Hemodialysis Self-Management Instrument (HDSMI-18), which were analyzed using structural equation modeling. Results Indicate that the modified model successfully fits the empirical data. Health literacy, hemodialysis knowledge, social support, and depression exerted a positive direct effect on hemodialysis self-management behavior. Additionally, family function positively influenced hemodialysis self-management behavior indirectly through depression and social support, while depression negatively affected hemodialysis self-management behavior indirectly via social support. Conclusion Increasing personal skills such as health literacy and hemodialysis knowledge, including motivating family function and providing social support, especially from the healthcare team, has a positive effect on managing depression and improving hemodialysis self-management behavior. The findings show that health systems around the world can help hemodialysis patients better manage their hemodialysis self-management by creating policies in dialysis units that support health literacy and hemodialysis knowledge, improve teaching methods, regularly assess depression levels, and encourage family or friends to stay involved in long-term care. Hemodialysis self-management behavior Hemodialysis treatment Structural Equation Modelling Thailand Figures Figure 1 Figure 2 Introduction End-stage renal disease significantly affects health and is expected to be the fifth leading cause of mortality by 2040 around the world [ 1 ]. About 89% of end-stage renal disease patients use hemodialysis as treatment [ 2 ], which can help slow down the decline in renal function and stop problems from happening. In Thailand, the number of hemodialysis patients reached around 129,113 in 2023 [ 3 ]. However, hemodialysis incurs high cost is not limited to direct medical costs and burden on healthcare spending but extends to indirect societal costs, such as productivity loss by patients and caregivers [ 4 ]. Additionally, end-stage renal disease and its treatment adversely affect patients' physical and mental health and daily life, creating significant challenges [ 2 ]. Effective hemodialysis treatment necessitates patient self-management of lifestyle changes in diet, fluid, and medication, which must be maintained lifelong [ 5 ]. Success hinges on cultural factors [ 6 ], collaboration with healthcare providers, dialysis schedule [ 5 ], and family function [ 7 ]. Inappropriate management can lead to complications, such as increased intradialytic weight gain and volume overload, affecting over 70% of cardiovascular disease patients [ 8 ] and elevating morbidity and mortality risks [ 7 ]. These complications impact physical and mental health, increase hospitalization costs, and diminish quality of life and family well-being [ 2 ]. As end-stage renal disease is irreversible and necessitates lifelong dialysis, patients' self-management practices significantly influence their quality and quantity of life [ 9 ]. Factors influencing hemodialysis self-management behavior are vital for health outcomes among patients. Effective self-management, supported by personal, family, and social factors, can mitigate disease risks and complications in patients with chronic disease [ 10 ]. Research shows inconsistent hemodialysis self-management behavior levels, with moderate levels in some studies [ 11 ] and low levels in others [ 12 ]. Limited research in Thailand suggests a higher self-management behavior among older adults [ 13 ], though a comprehensive classification of hemodialysis self-management behavior in Thailand is still lacking. Moreover, we found that various factors, including knowledge [ 11 ] self-efficacy, health literacy, and social support [ 7 ], are associated with better hemodialysis self-management behavior, while anxiety and depression [ 12 , 14 ] are related to worse hemodialysis self-management behavior. In Thailand, studies in older adults showed knowledge, resilience quotient [ 13 ], and health literacy [ 15 ] significantly positively correlated with hemodialysis self-management behavior. Furthermore, a study in pre dialysis CKD patients found that knowledge, self-efficacy, and social support can promote self-management behaviors [ 15 ]. Previous research indicates that hemodialysis self-management levels are generally moderate or low, potentially because studies have focused on individual factors instead of all dimensions that explain self-management behavior. Other contributing elements include healthcare providers, family, and friends, who are crucial for managing complex diseases and long-term therapy. Furthermore, many studies were conducted abroad in different economic and social contexts, with varied patient demographics, suggesting that initial research may not adequately explain hemodialysis self-management behavior in Thailand. Additionally, nursing policies often lack adequate evidence to support the self-management needs of end-stage renal disease patients, particularly regarding family involvement in dialysis services. To resolve this, it is crucial to improve the nursing policy framework to encourage nurse-led, family-centered care models that can lead to equitable health outcomes. The researcher aims to test a structural model of hemodialysis self-management behavior among Thai patients, integrating personal, social, and family factors to inform future nursing policy development. The outcome could assist in developing tailored strategies and educational interventions that promote self-management in hemodialysis patients. Theorical framework Researchers developed a model for hemodialysis self-management behaviors derived from Individual and Family Self-Management Theory and a literature review of hemodialysis and chronic kidney disease patients. IFSMT defines self-management as a multifaceted construction, including context, process, and outcomes [ 17 ]. The context dimension identifies risk and protective factors in three areas: specific health conditions, environmental aspects, and individual/family influences. Process dimensions pertain to self-regulation skills for managing risk, categorized as knowledge, skills, and social support. The study primarily addresses proximal outcomes related to self-management behaviors. This study examines how context and process impact self-management behaviors in individuals undergoing hemodialysis treatment. Key factors include individual and family characteristics, such as age and comorbidity, which influence cognitive functions and overall health [ 17 ]. Health literacy, defined as the ability to use knowledge to improve health, is also affected by contextual elements [ 18 ]. Additionally, depression, which impacts mood and activity levels [ 14 ] and family functioning can significantly affect self-management in hemodialysis patients [ 7 ]. The self-management process in hemodialysis is characterized by knowledge, self-efficacy, and social support. Ryan et al. [ 17 ] defines knowledge as factual information about end-stage renal disease, influenced by a person's intelligence and abilities. Bandura [ 19 ] emphasizes self-efficacy as the confidence individuals have in managing their end-stage renal disease and reducing complications. Song and Zhang [ 20 ] stated that social support is a complex and multidimensional concept that has been researched, and they found that receiving assistance is more important than providing it. Thus, social support receives from personal and professional networks that can help patients navigate their condition. Effective hemodialysis self-management behavior includes participation in treatment, diet, fluid, and medication management and requires support from family and guidance from healthcare providers for daily living adaptation. Methods Design A cross-sectional, predictive correlation design was used to examine the hypothesized causal model of hemodialysis self-management behavior of persons receiving hemodialysis. Sample and Setting The hypothesized model in this study encompasses 100 estimated parameters (Fig. 1 ), requiring a sample size of 550 Thai hemodialysis patients, derived from a sample-to-variable ratio method of 5:1 [ 21 ]. This sample was collected from 11 outpatient hemodialysis units in northeastern Thailand, utilizing purposive sampling of either female or male patients aged 20–69 who had undergone hemodialysis for at least six months. Patients who are 60 years old or more were screened for normal cognitive function using the Thai version of the 6-item Cognitive Impairment Test (6CIT) [ 22 ], with scores between 0 and 7 indicating normal cognitive status. Ethical considerations The institutional review boards at Chiang Mai University initially approved this study (study code: 2566-EXP116). Subsequently, the study received approval from the institutional review boards of eleven participating hospitals, with eight committees granting new approvals. The remaining three hospitals followed the ethical guidelines set by the Faculty of Nursing, Chiang Mai University. Instruments The selection of eight instruments was based on theoretical concepts used to measure data from hemodialysis and chronic kidney disease patients in prior research. A license was obtained from the authors for using and translating the questionnaires when required. 1. Personal information questionnaire The personal information questionnaire developed by the researcher consists of a clinical information recording form to collect patient histories, including age, comorbidity (such as diabetes, hypertension, heart disease, stroke, etc.), gender, current job, income, cause of end-stage renal disease, dialysis start date, frequency of dialysis per week, medications taken, and average weight gain between dialysis sessions over four weeks. 2. The 14-item Health Literacy Scale (HLS-14)—Thai-version The 14-item Health Literacy Scale assesses health literacy through knowledge, motivation, and competence in handling health information. It consists of 14 items across three domains, with scores ranging from 14 to 70, where higher scores indicate better health literacy. The instrument was translated into Thai with permission [ 23 ], achieving a Cronbach’s alpha of 0.89, and confirmatory factor analysis supported a three-factor model aligned with its original design. 3. The Patient Health Questionnaire (PHQ-9)— Thai-version The Patient Health Questionnaire evaluates depression severity over the past two weeks with a scale from 0 to 3 for each of its 9 items, yielding a subscale score from 0 to 27. Scores categorize severity as minimal (1–4), mild (5–9), moderate (10–14), moderately severe (15–19), and severe (20–27) [ 24 ]. The questionnaire was translated into Thai, with permissions obtained for use in the study [ 25 ]. The total data collected revealed a Cronbach’s alpha of 0.78, confirming the two-factor model aligned with its original design. 4. The Family State and Functioning Assessment Scale (FSFAS)—Thai-version The Family State and Functioning Assessment Scale evaluates family function through an individual's perception of family issues with 25 items across five domains. Respondents indicate their agreement on a four-point Likert scale, and the total score ranges from 0 to 75, with higher scores reflecting better family state and function. Scores are categorized as excellent, fairly good, slightly good, and not good. The FSFAS was translated into Thai and used in a study [ 26 ], demonstrating a Cronbach’s alpha of 0.71 and confirming a two-factor model through factor analysis. 5. The Hemodialysis Knowledge Questionnaire (HDKQ)—English-version The Hemodialysis Knowledge Questionnaire assesses knowledge related to end-stage renal disease and hemodialysis treatment, comprising 25 true or false questions [ 27 ]. Responses are scored from 0 to 25, with higher scores reflecting better knowledge. The researcher employed the back-translation technique [ 28 ]. Content validity was evaluated by three hemodialysis specialists and yielded an item-content validity index (I-CVI) and scale- content validity index (S-CVI) of 1.00. Reliability, indicated by a Kuder-Richardson 20 coefficient of 0.82, and confirmatory factor analysis confirmed a five-factor model aligned with the original design. 6. The Hemodialysis Self-Management Self-Efficacy Questionnaire (HSMSEQ)—Thai-version The Hemodialysis Self-Management Self-Efficacy Questionnaire, translated into the Thai language with added medication management items, assesses hemodialysis self-efficacy [ 29 ]. It consists of three domains and 15 items rated on a 10-point scale (0-150) to classify self-efficacy as high (101–150), moderate (51–100), or low (0–50). A higher score means better self-efficacy. The Cronbach's alpha is 0.92, and a confirmatory factor analysis backs up a three-factor model that fits with the original design. 7. The Social Support Questionnaire (SSQ)—Thai-version The Social Support Questionnaire was utilized for self-reports of social support, translated into the Thai language with permission from Methakanjanasak [ 29 ]. It comprises five domains with 12 items assessed on a five-point scale from "strongly agree (5)" to "strongly disagree (1). " The total score ranges from 12 to 60, categorized into high (45–60), moderate (29–44), and low (12–28) levels of social support, where a higher score indicates more support. The Cronbach’s alpha for the collected data was 0.77, and confirmatory factor analysis revised the model from five factors to four for this study. 8. The Hemodialysis Self-Management Instrument (HDSMI-18)—English-version The Hemodialysis Self-Management Instrument, developed from the hemodialysis self-management concept by Curtin et al. [ 27 ], consists of four domains and 18 items, with scores ranging from 18 to 72, where higher scores reflect better self-management in hemodialysis patients [ 30 ]. The researcher employed the back-translation technique [ 28 ]. Content validity was evaluated by three hemodialysis specialists and yielded an item-content validity index (I-CVI) and scale- content validity index (S-CVI) of 1.00. Reliability was confirmed with Cronbach’s alpha for the collected data was 0.72, and confirmatory factor analysis supported a four-factor model consistent with its original design. Data collection After obtaining permission, in a pilot study conducted at one hospital with 45 hemodialysis patients meeting the study criteria, various reliability coefficients were measured: Cronbach’s alpha was 0.83 for HLS-14, 0.80 for PHQ-9, 0.70 for FSFAS, 0.91 for HSMSEQ, 0.76 for SSQ, and 0.70 for HDSMI-18, while the Kuder-Richardson 20 reliability coefficient was 0.81 for HDKQ. The researcher prepared research assistants for the study procedures and called for volunteers across eleven hospitals. Interested participants were assessed for qualifications based on inclusion criteria, after which study objectives and procedures were explained. Participants who consented were given seven questionnaires to complete before hemodialysis sessions or took them home. Completion was verified by researchers or research assistants, and personal and demographic information was gathered from dialysis records. Data analysis Descriptive statistics were applied to assess the sample's demographic traits and identify outliers. Statistical prerequisites for structural equation modeling (SEM) were evaluated, revealing the data's non-normal distribution. The hypothesized model was analyzed using the Mplus program version 8.6, applying the MLR-estimated technique due to the data's distribution. Model fit was determined through various indices: chi-square statistics (χ²) indicating p values above 0.05 [ 31 ], χ²/df under two, RMSEA below 0.05, CFI and TLI over 0.90 [ 32 ], and SRMR under 0.05 [ 33 ]. Characteristics of the study variables The characteristics of the study variables as divided by IFSMT are shown in Table 1 as follows. Results In this study of 550 samples, the average age was 57.50 years, primarily consisting of men (58.73%). The majority (41.09%) were in the age range of 61–69 and had completed primary school (47.09%). A significant portion were involved in agriculture (37.45%) or were unemployed (21.82%). Most people had universal health insurance (55.27%), and their incomes ranged from 100 to 10,000 baht (38.36%) or none at all (34.90%). Common underlying conditions included hypertension (47.27%) and diabetes alongside hypertension (18.36%), often diagnosed ten years prior (68.18%). Hemodialysis began most frequently between 2018 and 2022 (52.55%), typically occurring three times weekly (61.45%), with most patients undergoing dialysis for 2–5 years. Participants also experienced intradialytic weight gain of 1.1–2.5 kg per session (59.45%) and had at least one comorbidity (52.71%), with a daily intake of 6–10 medications (58.73%). Descriptive statistics for the samples are outlined in terms of the range, median, and IQR of the variables' scores and are presented in Table 1 . Model testing The structural equation modeling analysis revealed that the initial hypothesized model did not fit the empirical data well. Modifications were made based on theoretical reasoning and modification indices, resulting in a revised model that significantly improved fit, indicated by p-value = 0.000, χ2 = 639.452, χ2/df = 1.943, RMSEA = 0.041, SRMR = 0.063, CFI = 0.920, and TLI = 0.902 (Fig. 2 ). This modified model explained 58.7% of the variance in hemodialysis self-management behavior. Key direct effects included health literacy, hemodialysis knowledge, social support, and depression. Indirect effects showed depression had a negative impact on self-management behavior through social support, while family function positively influenced via depression and social support. Discussion The results supported the IFSMT concept regarding personal self-management behavior, emphasizing the role of individuals and family units [ 17 ]. Effective health management, including adherence to healthy activities with family support, is essential to mitigate disease progression and complications. The study confirmed linear relationships among model components, with each factor being influenced by its antecedents, establishing interdependencies among them. Health literacy significantly influences hemodialysis self-management behavior (HD-SMB), with past studies confirming this positive correlation among older hemodialysis patients in Thailand [ 15 ]. A literature review also supports that enhanced health literacy is linked to improved self-management in chronic kidney disease patients [ 34 ], while research on Korean hemodialysis patients further affirms this relationship [ 7 ]. Patients with higher health literacy can effectively access and understand health information, engage with healthcare providers, and utilize critical thinking skills. The sample's average age of 57.50 suggests peak cognitive abilities, enabling effective communication with health teams, which can augment health literacy skills and improve HD-SMB [ 35 ], consistent with the IFSMT framework. Hemodialysis knowledge significantly influences self-management behavior, supported by findings from Thailand and Iran [ 13 , 11 ]. However, this study included many participants with only primary education who exhibited high knowledge scores, unlike previous studies that focused on more educated samples; this is likely due to strong social support from family and friends. This support may mediate knowledge's impact on self-management behavior [ 16 ]. The research highlights the importance of hemodialysis knowledge, encompassing renal function and treatment, for effective self-management in ESRD patients. It reaffirms that factual health knowledge is crucial for enhancing decision-making and health behavior adherence [ 17 ], emphasizing the role of social support in improving hemodialysis self-management behaviors. Social support significantly enhances hemodialysis self-management behavior, consistent with prior findings among Taiwanese and Korea patients [ 9 , 7 ]. Defined as interpersonal assistance, social support encompasses physical and emotional help [ 36 ], facilitating health management through collaboration with families and healthcare professionals [ 17 ]. Self-care knowledge, depression levels, self-efficacy were the strongest factors influencing self-management [ 37 ]. However, this study moderate information support from healthcare providers may reduce self-management effectiveness, indicating that improved communication and teaching by hemodialysis nurses and nephrologists is essential for patient outcomes. This study revealed the significant effects of depression on hemodialysis self-management behavior. It finds that patients who have low levels of education, are unemployed, or are having trouble with money are more likely to be depressed [ 14 , 38 ]. Patients undergoing dialysis, especially those with treatment durations of less than five years [ 39 ], endure increased psychological and physical burdens, negatively affecting mental health and self-management practices. These factors collectively exacerbate depression, which, in turn, affects patient survival behaviors. In examining the indirect effect of depression on hemodialysis self-management behavior, the text supports a conceptual framework where increased depression diminishes self-management via social support. The IFSMT theory posits that social support positively influences self-management. Sufficient perceived social support can alleviate depression and promote better self-management behaviors [ 36 , 16 ], which is crucial for patients facing end-stage renal disease challenges. Studies, including one by [ 36 ], highlight the efficacy of combining psychological therapy with social support to reduce anxiety and enhance quality of life. Additionally, increased support from friends can drastically lower anxiety levels [ 38 ], correlating with improved self-management behaviors in hemodialysis patients. Healthcare professionals should assess depression levels and support resources to foster better self-management behavior. Family function significantly impacts hemodialysis self-management behavior. While research in Bangkok showed no relationship [ 13 ], studies in Korea indicated a positive correlation [ 7 ]. Effective family support enhances self-management and reduces depression, especially in crises like unemployment. A study on female hemodialysis patients confirmed better family functioning leads to lower depression [ 40 ]. The current study noted minimal depression and good family functioning, reinforcing the need for hemodialysis nurses to involve family members in care for improved physical and mental health support, addressing crucial factors affecting patients' well-being. Conclusion and recommendations These findings highlight the importance of health literacy, knowledge of hemodialysis treatment, and social support, particularly from family and friends, in managing depression and enhancing hemodialysis self-management behavior. Hemodialysis specialists and nurses should assess depression levels and identify social support to promote health educational strategies that enhance individual skills related to these areas in long-term care. Implications for nursing and health policies Careful monitoring of the outcomes of patients on HD is essential to develop effective strategies worldwide for risk reduction. Thus, to enhance self-management behaviors in hemodialysis patients, it is essential to inform policymakers in planning sustainable and affordable renal care. Policymakers should implement educational techniques that improve health literacy, particularly for those receiving treatment for less than two years. Regular monitoring of depression levels is essential, and educating family members about end-stage renal disease and treatment options is crucial for effective support. Dialysis units should also create nurse-led care guidelines that focus on structured health education, regular depression screening, and encouraging family involvement to improve support for long-term self-management. Intervention programs should be developed to boost health literacy, hemodialysis knowledge, family function, and social support. By building these personal skills, nurses can help reduce patient depression and empower them to master self-management behaviors through supportive approach. Limitations In this study, the sample consisted of hemodialysis patients from a public hospital, which may limit the generalizability of the research findings to other healthcare settings. Declarations Ethics approval and consent to participate. Ethical approval was obtained from the Research Ethics Committee, Faculty of Nursing, Chiang Mai University (study code: 2566-EXP116). Furthermore, formal ethical clearance was obtained from the institutional review boards of all participating hospitals involved in the research. The study was conducted according to the ethical standards outlined in the Declaration of Helsinki. Information consent was obtained from all participants after they received information about the study’s aim and objectives. Participants were informed that their participation was voluntary and that they could withdraw from the study at any time without giving any explanation. The participants’ identities were kept confidential, and personal or identifying information was not disclosed. Consent for publication. Not applicable to this study. Availability of data and materials. Not applicable. Competing interests. The authors declare no competing interests. Funding. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors. Author contributions. Study design: PP, OW, CS, CT. Data collection: PP. Data analysis: PP, OW. Study supervision: OW, CS, CT. Manuscript writing: PP, OW, CS, CT, AS. Acknowledgement. The authors are grateful to the study participants for their contributions. Recognition is also extended to the Faculty of Nursing, Chiang Mai University, Thailand for their support during the first author’ s doctoral study. Authors’ information. Pailin Pinthong, RN, PhD (Candidate) 1 Faculty of Nursing, Ubon Ratchathani University, Ubon Ratchathani province, Thailand Email: [email protected] and [email protected] Corresponding author : Orn-Anong Wichaikhum, RN, PhD, Assistant Professor 2 Faculty of Nursing, Chiang Mai University, Chiang Mai province, Thailand Email: [email protected] Chomphoonut Srirat, RN, PhD, Assistant Professor 2 Faculty of Nursing, Chiang Mai University, Chiang Mai province, Thailand Email: [email protected] Chiraporn Tachaudomdach, RN, PhD, Associate Professor 2 Faculty of Nursing, Chiang Mai University, Chiang Mai province, Thailand Email: [email protected] Allison P Squires, RN, PhD, Professor 3 NYU Rory Meyers College of Nursing, New York University, New York, NY, USA. 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Tables Table 1 Characteristics of the study variables by context, process and outcome (n = 550) Study variables Possible score Actually score Median IQR Level Context Health Literacy 14-70 22-70 58 17 High Depression 0-27 0-27 3 4 Minimal depression Family Function Process 0-75 0-66 47 7 Moderately good Hemodialysis Knowledge 0-25 1-24 17 5 High Self-efficacy 0-150 47-150 133 24 High Social support Proximal outcome HD-SMB 12-60 18-72 20-60 21-72 48 47 7 10 High Moderate Note: Interquartile range (IQR), hemodialysis self-management behavior (HD-SMB) Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted 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. 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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-8714747","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":582943588,"identity":"c86d41ba-a995-4505-bc5b-d2e237b79f18","order_by":0,"name":"Pailin Pinthong","email":"","orcid":"","institution":"Faculty of Nursing Ubon Ratchathani University","correspondingAuthor":false,"prefix":"","firstName":"Pailin","middleName":"","lastName":"Pinthong","suffix":""},{"id":582943589,"identity":"1858781b-d760-4b3b-829d-70c604cd820d","order_by":1,"name":"Orn-anong Wichaikum","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA10lEQVRIiWNgGAWjYJADxgcwFjOxWpgNYHqbidXCJkGUFn7pswcYfu6wyZN34DGr+JlzmIG//QD74wI8WiT78hIYe8+kFRse4DG72bvtMIPEmQTG5hl4tBic4TH/wdt2OHFjA++224xALQw3gA7jwa/FgPEvVEsxSIs8MVqYQbbMZ+DdxgzSYkBIi2QPUItsW1riBmb+z5K929J5DM8kNs7Gp4WfB+iwt202ifPb2xI//NxmLSd3/PCBz/i0IFx4GEIDFTM2EKOBgUGeSHWjYBSMglEwAgEAefVF9oebk2AAAAAASUVORK5CYII=","orcid":"","institution":"Faculty of Nursing Chiang Mai University","correspondingAuthor":true,"prefix":"","firstName":"Orn-anong","middleName":"","lastName":"Wichaikum","suffix":""},{"id":582943590,"identity":"6bd30c41-309c-4034-9bde-dd2c171f9b8c","order_by":2,"name":"Chomphoonut Srirat","email":"","orcid":"","institution":"Faculty of Nursing Chiang Mai University","correspondingAuthor":false,"prefix":"","firstName":"Chomphoonut","middleName":"","lastName":"Srirat","suffix":""},{"id":582943591,"identity":"1b50a84d-513e-444e-9a5d-400659f86c09","order_by":3,"name":"Chiraporn Tachaudomdach","email":"","orcid":"","institution":"Faculty of Nursing Chiang Mai University","correspondingAuthor":false,"prefix":"","firstName":"Chiraporn","middleName":"","lastName":"Tachaudomdach","suffix":""},{"id":582943592,"identity":"df5e9362-0755-4d88-9f42-11e12f097ca4","order_by":4,"name":"Allison P Squires","email":"","orcid":"","institution":"NYU Rory Meyers College of Nursing, New York University","correspondingAuthor":false,"prefix":"","firstName":"Allison","middleName":"P","lastName":"Squires","suffix":""}],"badges":[],"createdAt":"2026-01-27 23:08:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8714747/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8714747/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":101792404,"identity":"a269ff00-8fac-491d-b906-aea1dbfbb3c6","added_by":"auto","created_at":"2026-02-03 16:12:23","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":287163,"visible":true,"origin":"","legend":"\u003cp\u003ethe hypothesized model of hemodialysis self-management behavior in persons receiving hemodialysis\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8714747/v1/9e70b8830fa8e4c3b7d21e9f.png"},{"id":101792441,"identity":"d1ec27b5-6a93-41a2-bd7c-8249dd2fba19","added_by":"auto","created_at":"2026-02-03 16:12:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":344534,"visible":true,"origin":"","legend":"\u003cp\u003eThe final model of self-management behaviors in persons receiving hemodialysis\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8714747/v1/72f001e1e40c770824386008.png"},{"id":101792591,"identity":"cf6e69a8-c01c-4134-b7eb-766bc9bb65d4","added_by":"auto","created_at":"2026-02-03 16:12:52","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1140357,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8714747/v1/9c10acfb-ceb5-4390-8640-367e86b1325d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Causal Model of Self-Management Behavior in Persons Receiving Hemodialysis\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eEnd-stage renal disease significantly affects health and is expected to be the fifth leading cause of mortality by 2040 around the world [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. About 89% of end-stage renal disease patients use hemodialysis as treatment [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e], which can help slow down the decline in renal function and stop problems from happening. In Thailand, the number of hemodialysis patients reached around 129,113 in 2023 [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. However, hemodialysis incurs high cost is not limited to direct medical costs and burden on healthcare spending but extends to indirect societal costs, such as productivity loss by patients and caregivers [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Additionally, end-stage renal disease and its treatment adversely affect patients' physical and mental health and daily life, creating significant challenges [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eEffective hemodialysis treatment necessitates patient self-management of lifestyle changes in diet, fluid, and medication, which must be maintained lifelong [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Success hinges on cultural factors [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], collaboration with healthcare providers, dialysis schedule [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e], and family function [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Inappropriate management can lead to complications, such as increased intradialytic weight gain and volume overload, affecting over 70% of cardiovascular disease patients [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e] and elevating morbidity and mortality risks [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These complications impact physical and mental health, increase hospitalization costs, and diminish quality of life and family well-being [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. As end-stage renal disease is irreversible and necessitates lifelong dialysis, patients' self-management practices significantly influence their quality and quantity of life [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eFactors influencing hemodialysis self-management behavior are vital for health outcomes among patients. Effective self-management, supported by personal, family, and social factors, can mitigate disease risks and complications in patients with chronic disease [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. Research shows inconsistent hemodialysis self-management behavior levels, with moderate levels in some studies [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] and low levels in others [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Limited research in Thailand suggests a higher self-management behavior among older adults [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], though a comprehensive classification of hemodialysis self-management behavior in Thailand is still lacking.\u003c/p\u003e \u003cp\u003eMoreover, we found that various factors, including knowledge [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e] self-efficacy, health literacy, and social support [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], are associated with better hemodialysis self-management behavior, while anxiety and depression [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] are related to worse hemodialysis self-management behavior. In Thailand, studies in older adults showed knowledge, resilience quotient [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], and health literacy [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] significantly positively correlated with hemodialysis self-management behavior. Furthermore, a study in pre dialysis CKD patients found that knowledge, self-efficacy, and social support can promote self-management behaviors [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePrevious research indicates that hemodialysis self-management levels are generally moderate or low, potentially because studies have focused on individual factors instead of all dimensions that explain self-management behavior. Other contributing elements include healthcare providers, family, and friends, who are crucial for managing complex diseases and long-term therapy. Furthermore, many studies were conducted abroad in different economic and social contexts, with varied patient demographics, suggesting that initial research may not adequately explain hemodialysis self-management behavior in Thailand.\u003c/p\u003e \u003cp\u003eAdditionally, nursing policies often lack adequate evidence to support the self-management needs of end-stage renal disease patients, particularly regarding family involvement in dialysis services. To resolve this, it is crucial to improve the nursing policy framework to encourage nurse-led, family-centered care models that can lead to equitable health outcomes. The researcher aims to test a structural model of hemodialysis self-management behavior among Thai patients, integrating personal, social, and family factors to inform future nursing policy development. The outcome could assist in developing tailored strategies and educational interventions that promote self-management in hemodialysis patients.\u003c/p\u003e\n\u003ch3\u003eTheorical framework\u003c/h3\u003e\n\u003cp\u003eResearchers developed a model for hemodialysis self-management behaviors derived from Individual and Family Self-Management Theory and a literature review of hemodialysis and chronic kidney disease patients. IFSMT defines self-management as a multifaceted construction, including context, process, and outcomes [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. The context dimension identifies risk and protective factors in three areas: specific health conditions, environmental aspects, and individual/family influences. Process dimensions pertain to self-regulation skills for managing risk, categorized as knowledge, skills, and social support. The study primarily addresses proximal outcomes related to self-management behaviors.\u003c/p\u003e \u003cp\u003eThis study examines how context and process impact self-management behaviors in individuals undergoing hemodialysis treatment. Key factors include individual and family characteristics, such as age and comorbidity, which influence cognitive functions and overall health [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Health literacy, defined as the ability to use knowledge to improve health, is also affected by contextual elements [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Additionally, depression, which impacts mood and activity levels [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e] and family functioning can significantly affect self-management in hemodialysis patients [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe self-management process in hemodialysis is characterized by knowledge, self-efficacy, and social support. Ryan et al. [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] defines knowledge as factual information about end-stage renal disease, influenced by a person's intelligence and abilities. Bandura [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] emphasizes self-efficacy as the confidence individuals have in managing their end-stage renal disease and reducing complications. Song and Zhang [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e] stated that social support is a complex and multidimensional concept that has been researched, and they found that receiving assistance is more important than providing it. Thus, social support receives from personal and professional networks that can help patients navigate their condition. Effective hemodialysis self-management behavior includes participation in treatment, diet, fluid, and medication management and requires support from family and guidance from healthcare providers for daily living adaptation.\u003c/p\u003e \u003c/div\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003cdiv id=\"Sec4\" class=\"Section3\"\u003e \u003ch2\u003eDesign\u003c/h2\u003e \u003cp\u003eA cross-sectional, predictive correlation design was used to examine the hypothesized causal model of hemodialysis self-management behavior of persons receiving hemodialysis.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSample and Setting\u003c/h3\u003e\n\u003cp\u003eThe hypothesized model in this study encompasses 100 estimated parameters (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), requiring a sample size of 550 Thai hemodialysis patients, derived from a sample-to-variable ratio method of 5:1 [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This sample was collected from 11 outpatient hemodialysis units in northeastern Thailand, utilizing purposive sampling of either female or male patients aged 20\u0026ndash;69 who had undergone hemodialysis for at least six months. Patients who are 60 years old or more were screened for normal cognitive function using the Thai version of the 6-item Cognitive Impairment Test (6CIT) [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e], with scores between 0 and 7 indicating normal cognitive status.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eEthical considerations\u003c/h3\u003e\n\u003cp\u003e The institutional review boards at Chiang Mai University initially approved this study (study code: 2566-EXP116). Subsequently, the study received approval from the institutional review boards of eleven participating hospitals, with eight committees granting new approvals. The remaining three hospitals followed the ethical guidelines set by the Faculty of Nursing, Chiang Mai University.\u003c/p\u003e\n\u003ch3\u003eInstruments\u003c/h3\u003e\n\u003cp\u003eThe selection of eight instruments was based on theoretical concepts used to measure data from hemodialysis and chronic kidney disease patients in prior research. A license was obtained from the authors for using and translating the questionnaires when required.\u003c/p\u003e \u003cp\u003e \u003cem\u003e1. Personal information questionnaire\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe personal information questionnaire developed by the researcher consists of a clinical information recording form to collect patient histories, including age, comorbidity (such as diabetes, hypertension, heart disease, stroke, etc.), gender, current job, income, cause of end-stage renal disease, dialysis start date, frequency of dialysis per week, medications taken, and average weight gain between dialysis sessions over four weeks.\u003c/p\u003e \u003cp\u003e \u003cem\u003e2. The 14-item Health Literacy Scale (HLS-14)\u0026mdash;Thai-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe 14-item Health Literacy Scale assesses health literacy through knowledge, motivation, and competence in handling health information. It consists of 14 items across three domains, with scores ranging from 14 to 70, where higher scores indicate better health literacy. The instrument was translated into Thai with permission [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e], achieving a Cronbach\u0026rsquo;s alpha of 0.89, and confirmatory factor analysis supported a three-factor model aligned with its original design.\u003c/p\u003e \u003cp\u003e \u003cem\u003e3. The Patient Health Questionnaire (PHQ-9)\u0026mdash; Thai-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Patient Health Questionnaire evaluates depression severity over the past two weeks with a scale from 0 to 3 for each of its 9 items, yielding a subscale score from 0 to 27. Scores categorize severity as minimal (1\u0026ndash;4), mild (5\u0026ndash;9), moderate (10\u0026ndash;14), moderately severe (15\u0026ndash;19), and severe (20\u0026ndash;27) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. The questionnaire was translated into Thai, with permissions obtained for use in the study [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. The total data collected revealed a Cronbach\u0026rsquo;s alpha of 0.78, confirming the two-factor model aligned with its original design.\u003c/p\u003e \u003cp\u003e \u003cem\u003e4. The Family State and Functioning Assessment Scale (FSFAS)\u0026mdash;Thai-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Family State and Functioning Assessment Scale evaluates family function through an individual's perception of family issues with 25 items across five domains. Respondents indicate their agreement on a four-point Likert scale, and the total score ranges from 0 to 75, with higher scores reflecting better family state and function. Scores are categorized as excellent, fairly good, slightly good, and not good. The FSFAS was translated into Thai and used in a study [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e], demonstrating a Cronbach\u0026rsquo;s alpha of 0.71 and confirming a two-factor model through factor analysis.\u003c/p\u003e \u003cp\u003e \u003cem\u003e5. The Hemodialysis Knowledge Questionnaire (HDKQ)\u0026mdash;English-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Hemodialysis Knowledge Questionnaire assesses knowledge related to end-stage renal disease and hemodialysis treatment, comprising 25 true or false questions [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Responses are scored from 0 to 25, with higher scores reflecting better knowledge. The researcher employed the back-translation technique [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Content validity was evaluated by three hemodialysis specialists and yielded an item-content validity index (I-CVI) and scale- content validity index (S-CVI) of 1.00. Reliability, indicated by a Kuder-Richardson 20 coefficient of 0.82, and confirmatory factor analysis confirmed a five-factor model aligned with the original design.\u003c/p\u003e \u003cp\u003e \u003cem\u003e6. The Hemodialysis Self-Management Self-Efficacy Questionnaire (HSMSEQ)\u0026mdash;Thai-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Hemodialysis Self-Management Self-Efficacy Questionnaire, translated into the Thai language with added medication management items, assesses hemodialysis self-efficacy [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It consists of three domains and 15 items rated on a 10-point scale (0-150) to classify self-efficacy as high (101\u0026ndash;150), moderate (51\u0026ndash;100), or low (0\u0026ndash;50). A higher score means better self-efficacy. The Cronbach's alpha is 0.92, and a confirmatory factor analysis backs up a three-factor model that fits with the original design.\u003c/p\u003e \u003cp\u003e \u003cem\u003e7. The Social Support Questionnaire (SSQ)\u0026mdash;Thai-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Social Support Questionnaire was utilized for self-reports of social support, translated into the Thai language with permission from Methakanjanasak [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]. It comprises five domains with 12 items assessed on a five-point scale from \"strongly agree (5)\" to \"strongly disagree (1). \" The total score ranges from 12 to 60, categorized into high (45\u0026ndash;60), moderate (29\u0026ndash;44), and low (12\u0026ndash;28) levels of social support, where a higher score indicates more support. The Cronbach\u0026rsquo;s alpha for the collected data was 0.77, and confirmatory factor analysis revised the model from five factors to four for this study.\u003c/p\u003e \u003cp\u003e \u003cem\u003e8. The Hemodialysis Self-Management Instrument (HDSMI-18)\u0026mdash;English-version\u003c/em\u003e \u003c/p\u003e \u003cp\u003eThe Hemodialysis Self-Management Instrument, developed from the hemodialysis self-management concept by Curtin et al. [\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], consists of four domains and 18 items, with scores ranging from 18 to 72, where higher scores reflect better self-management in hemodialysis patients [\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]. The researcher employed the back-translation technique [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. Content validity was evaluated by three hemodialysis specialists and yielded an item-content validity index (I-CVI) and scale- content validity index (S-CVI) of 1.00. Reliability was confirmed with Cronbach\u0026rsquo;s alpha for the collected data was 0.72, and confirmatory factor analysis supported a four-factor model consistent with its original design.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eData collection\u003c/h2\u003e \u003cp\u003eAfter obtaining permission, in a pilot study conducted at one hospital with 45 hemodialysis patients meeting the study criteria, various reliability coefficients were measured: Cronbach\u0026rsquo;s alpha was 0.83 for HLS-14, 0.80 for PHQ-9, 0.70 for FSFAS, 0.91 for HSMSEQ, 0.76 for SSQ, and 0.70 for HDSMI-18, while the Kuder-Richardson 20 reliability coefficient was 0.81 for HDKQ. The researcher prepared research assistants for the study procedures and called for volunteers across eleven hospitals. Interested participants were assessed for qualifications based on inclusion criteria, after which study objectives and procedures were explained. Participants who consented were given seven questionnaires to complete before hemodialysis sessions or took them home. Completion was verified by researchers or research assistants, and personal and demographic information was gathered from dialysis records.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eData analysis\u003c/h2\u003e \u003cp\u003eDescriptive statistics were applied to assess the sample's demographic traits and identify outliers. Statistical prerequisites for structural equation modeling (SEM) were evaluated, revealing the data's non-normal distribution. The hypothesized model was analyzed using the Mplus program version 8.6, applying the MLR-estimated technique due to the data's distribution. Model fit was determined through various indices: chi-square statistics (χ\u0026sup2;) indicating p values above 0.05 [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e], χ\u0026sup2;/df under two, RMSEA below 0.05, CFI and TLI over 0.90 [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e], and SRMR under 0.05 [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e].\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eCharacteristics of the study variables\u003c/h3\u003e\n\u003cp\u003eThe characteristics of the study variables as divided by IFSMT are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e as follows.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eIn this study of 550 samples, the average age was 57.50 years, primarily consisting of men (58.73%). The majority (41.09%) were in the age range of 61\u0026ndash;69 and had completed primary school (47.09%). A significant portion were involved in agriculture (37.45%) or were unemployed (21.82%). Most people had universal health insurance (55.27%), and their incomes ranged from 100 to 10,000 baht (38.36%) or none at all (34.90%). Common underlying conditions included hypertension (47.27%) and diabetes alongside hypertension (18.36%), often diagnosed ten years prior (68.18%). Hemodialysis began most frequently between 2018 and 2022 (52.55%), typically occurring three times weekly (61.45%), with most patients undergoing dialysis for 2\u0026ndash;5 years. Participants also experienced intradialytic weight gain of 1.1\u0026ndash;2.5 kg per session (59.45%) and had at least one comorbidity (52.71%), with a daily intake of 6\u0026ndash;10 medications (58.73%). Descriptive statistics for the samples are outlined in terms of the range, median, and IQR of the variables' scores and are presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eModel testing\u003c/h2\u003e \u003cp\u003eThe structural equation modeling analysis revealed that the initial hypothesized model did not fit the empirical data well. Modifications were made based on theoretical reasoning and modification indices, resulting in a revised model that significantly improved fit, indicated by p-value\u0026thinsp;=\u0026thinsp;0.000, χ2\u0026thinsp;=\u0026thinsp;639.452, χ2/df\u0026thinsp;=\u0026thinsp;1.943, RMSEA\u0026thinsp;=\u0026thinsp;0.041, SRMR\u0026thinsp;=\u0026thinsp;0.063, CFI\u0026thinsp;=\u0026thinsp;0.920, and TLI\u0026thinsp;=\u0026thinsp;0.902 (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e2\u003c/span\u003e). This modified model explained 58.7% of the variance in hemodialysis self-management behavior. Key direct effects included health literacy, hemodialysis knowledge, social support, and depression. Indirect effects showed depression had a negative impact on self-management behavior through social support, while family function positively influenced via depression and social support.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe results supported the IFSMT concept regarding personal self-management behavior, emphasizing the role of individuals and family units [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Effective health management, including adherence to healthy activities with family support, is essential to mitigate disease progression and complications. The study confirmed linear relationships among model components, with each factor being influenced by its antecedents, establishing interdependencies among them.\u003c/p\u003e \u003cp\u003eHealth literacy significantly influences hemodialysis self-management behavior (HD-SMB), with past studies confirming this positive correlation among older hemodialysis patients in Thailand [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. A literature review also supports that enhanced health literacy is linked to improved self-management in chronic kidney disease patients [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e], while research on Korean hemodialysis patients further affirms this relationship [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Patients with higher health literacy can effectively access and understand health information, engage with healthcare providers, and utilize critical thinking skills. The sample's average age of 57.50 suggests peak cognitive abilities, enabling effective communication with health teams, which can augment health literacy skills and improve HD-SMB [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e], consistent with the IFSMT framework.\u003c/p\u003e \u003cp\u003eHemodialysis knowledge significantly influences self-management behavior, supported by findings from Thailand and Iran [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. However, this study included many participants with only primary education who exhibited high knowledge scores, unlike previous studies that focused on more educated samples; this is likely due to strong social support from family and friends. This support may mediate knowledge's impact on self-management behavior [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. The research highlights the importance of hemodialysis knowledge, encompassing renal function and treatment, for effective self-management in ESRD patients. It reaffirms that factual health knowledge is crucial for enhancing decision-making and health behavior adherence [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], emphasizing the role of social support in improving hemodialysis self-management behaviors.\u003c/p\u003e \u003cp\u003eSocial support significantly enhances hemodialysis self-management behavior, consistent with prior findings among Taiwanese and Korea patients [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Defined as interpersonal assistance, social support encompasses physical and emotional help [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], facilitating health management through collaboration with families and healthcare professionals [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Self-care knowledge, depression levels, self-efficacy were the strongest factors influencing self-management [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. However, this study moderate information support from healthcare providers may reduce self-management effectiveness, indicating that improved communication and teaching by hemodialysis nurses and nephrologists is essential for patient outcomes.\u003c/p\u003e \u003cp\u003eThis study revealed the significant effects of depression on hemodialysis self-management behavior. It finds that patients who have low levels of education, are unemployed, or are having trouble with money are more likely to be depressed [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Patients undergoing dialysis, especially those with treatment durations of less than five years [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e], endure increased psychological and physical burdens, negatively affecting mental health and self-management practices. These factors collectively exacerbate depression, which, in turn, affects patient survival behaviors.\u003c/p\u003e \u003cp\u003eIn examining the indirect effect of depression on hemodialysis self-management behavior, the text supports a conceptual framework where increased depression diminishes self-management via social support. The IFSMT theory posits that social support positively influences self-management. Sufficient perceived social support can alleviate depression and promote better self-management behaviors [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e], which is crucial for patients facing end-stage renal disease challenges. Studies, including one by [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], highlight the efficacy of combining psychological therapy with social support to reduce anxiety and enhance quality of life. Additionally, increased support from friends can drastically lower anxiety levels [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e], correlating with improved self-management behaviors in hemodialysis patients. Healthcare professionals should assess depression levels and support resources to foster better self-management behavior.\u003c/p\u003e \u003cp\u003eFamily function significantly impacts hemodialysis self-management behavior. While research in Bangkok showed no relationship [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], studies in Korea indicated a positive correlation [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. Effective family support enhances self-management and reduces depression, especially in crises like unemployment. A study on female hemodialysis patients confirmed better family functioning leads to lower depression [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]. The current study noted minimal depression and good family functioning, reinforcing the need for hemodialysis nurses to involve family members in care for improved physical and mental health support, addressing crucial factors affecting patients' well-being.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion and recommendations","content":"\u003cp\u003eThese findings highlight the importance of health literacy, knowledge of hemodialysis treatment, and social support, particularly from family and friends, in managing depression and enhancing hemodialysis self-management behavior. Hemodialysis specialists and nurses should assess depression levels and identify social support to promote health educational strategies that enhance individual skills related to these areas in long-term care.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eImplications for nursing and health policies\u003c/h2\u003e \u003cp\u003eCareful monitoring of the outcomes of patients on HD is essential to develop effective strategies worldwide for risk reduction. Thus, to enhance self-management behaviors in hemodialysis patients, it is essential to inform policymakers in planning sustainable and affordable renal care. Policymakers should implement educational techniques that improve health literacy, particularly for those receiving treatment for less than two years. Regular monitoring of depression levels is essential, and educating family members about end-stage renal disease and treatment options is crucial for effective support. Dialysis units should also create nurse-led care guidelines that focus on structured health education, regular depression screening, and encouraging family involvement to improve support for long-term self-management. Intervention programs should be developed to boost health literacy, hemodialysis knowledge, family function, and social support. By building these personal skills, nurses can help reduce patient depression and empower them to master self-management behaviors through supportive approach.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eLimitations\u003c/h2\u003e \u003cp\u003eIn this study, the sample consisted of hemodialysis patients from a public hospital, which may limit the generalizability of the research findings to other healthcare settings.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003eEthics approval and consent to participate.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Research Ethics Committee, Faculty of Nursing, Chiang Mai University (study code: 2566-EXP116). Furthermore, formal ethical clearance was obtained from the institutional review boards of all participating hospitals involved in the research. The study was conducted according to the ethical standards outlined in the Declaration of Helsinki. Information consent was obtained from all participants after they received information about the study\u0026rsquo;s aim and objectives. \u0026nbsp;Participants were informed that their participation was voluntary and that they could withdraw from the study at any time without giving any explanation. The participants\u0026rsquo; identities were kept confidential, and personal or identifying information was not disclosed.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eConsent for publication.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable to this study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAvailability of data and materials.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eCompeting interests.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eFunding.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThis research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor contributions.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eStudy design: PP, OW, CS, CT. Data collection: PP. Data analysis: PP, OW. Study supervision: OW, CS, CT. Manuscript writing: PP, OW, CS, CT, AS.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAcknowledgement.\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors are grateful to the study participants for their contributions. Recognition is also extended to the Faculty of Nursing, Chiang Mai University, Thailand for their support during the first author\u0026rsquo; s doctoral study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthors\u0026rsquo; information.\u003c/em\u003e\u003c/p\u003e\n\u003col\u003e\n \u003cli\u003ePailin Pinthong, RN, PhD (Candidate) \u003cstrong\u003e\u003csup\u003e1\u003c/sup\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFaculty of Nursing, Ubon Ratchathani University, Ubon Ratchathani province, Thailand\u003c/p\u003e\n\u003cp\u003eEmail: [email protected] and [email protected]\u003c/p\u003e\n\u003col start=\"2\"\u003e\n \u003cli\u003e\u003cstrong\u003eCorresponding author\u003c/strong\u003e: Orn-Anong Wichaikhum, RN, PhD, Assistant Professor\u003csup\u003e\u0026nbsp;\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFaculty of Nursing, Chiang Mai University,\u0026nbsp;Chiang Mai province, Thailand\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003col start=\"3\"\u003e\n \u003cli\u003eChomphoonut Srirat, RN, PhD, Assistant Professor\u003csup\u003e\u0026nbsp;\u003cstrong\u003e2\u003c/strong\u003e\u003c/sup\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFaculty of Nursing, Chiang Mai University,\u0026nbsp;Chiang Mai province, Thailand\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003col start=\"4\"\u003e\n \u003cli\u003eChiraporn Tachaudomdach, RN, PhD, Associate Professor \u003cstrong\u003e\u003csup\u003e2\u003c/sup\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eFaculty of Nursing, Chiang Mai University,\u0026nbsp;Chiang Mai province, Thailand\u003c/p\u003e\n\u003cp\u003eEmail: [email protected]\u003c/p\u003e\n\u003col start=\"5\"\u003e\n \u003cli\u003eAllison P Squires, RN, PhD, Professor\u003cstrong\u003e\u0026nbsp;\u003csup\u003e3\u003c/sup\u003e\u003c/strong\u003e\u003c/li\u003e\n\u003c/ol\u003e\n\u003cp\u003eNYU Rory Meyers College of Nursing, New York University, New York, NY, USA.\u003c/p\u003e\n\u003cp\u003eE-mail: [email protected]\u003c/p\u003e\n\u003cp\u003e\u003cem\u003eAuthor details\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e1\u003c/sup\u003e Faculty of Nursing, Ubon Ratchathani University, Ubon Ratchathani, Thailand\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e2\u003c/sup\u003e Faculty of Nursing, Chiang Mai University, Chiang Mai, Thailand\u003c/p\u003e\n\u003cp\u003e\u003csup\u003e3\u003c/sup\u003e NYU Rory Meyers College of Nursing, New York University, USA\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eFrancis A, et al. 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Associations of health literacy with self-management behaviours and health outcomes in chronic kidney disease: a systematic review. J Nephrol. 2023;36:1267\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChow BC, et al. Health literacy mediates the relationships of cognitive and physical functions with health-related quality of life in older adults. Front Public Health. 2024;12:1355392.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFan M, et al. Effects of psychology therapy and social support on anxiety, depression, and social function in patients receiving uremic hemodialysis. Arch Clin Psychiatry. 2022;49(5):70\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWu S-FV, et al. Differences in self-care knowledge, self-efficacy, psychological distress and self-management between patients with early-and end-stage chronic kidney disease. J Clin Nurs. 2022;31(15/16):2287\u0026ndash;95.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePinyo S, Jinawin S. Effects of the self-management program on volume overload in end stage renal disease patients receiving hemodialysis. Phrae Med J Clin Sci. 2023;31(2):48\u0026ndash;59.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMazharulhaq, et al. Prevalence of depression in patients on hemodialysis. Int J Health Sci. 2023;7(S1):41\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKim O, Yeom EY, Jeon HO. Relationships between depression, family function, physical symptom, and illness uncertainty in female patients with chronic kidney disease. Nurs Health Sci. 2020;22:543\u0026ndash;46.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Characteristics of the study variables by context, process and outcome (n = 550)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"100%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003evariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePossible\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003escore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eActually\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003escore\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedian\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eIQR\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLevel\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003e\u003cstrong\u003eContext\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eHealth\u0026nbsp;Literacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14-70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e22-70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e58\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e0-27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e0-27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eMinimal depression\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003eFamily\u0026nbsp;Function\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProcess\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e0-75\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e0-66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eModerately\u0026nbsp;good\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003eHemodialysis Knowledge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e0-25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e1-24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e17\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003eSelf-efficacy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e0-150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e47-150\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e133\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 29.9679%;\"\u003e\n \u003cp\u003eSocial\u0026nbsp;support\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eProximal outcome\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eHD-SMB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e12-60\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e18-72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 15.0641%;\"\u003e\n \u003cp\u003e20-60\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e21-72\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 13.3013%;\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 11.6987%;\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16.6667%;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cem\u003eNote:\u003c/em\u003e Interquartile range (IQR), hemodialysis self-management behavior (HD-SMB)\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Hemodialysis self-management behavior, Hemodialysis treatment, Structural Equation Modelling, Thailand","lastPublishedDoi":"10.21203/rs.3.rs-8714747/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8714747/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eEnd-stage renal disease and hemodialysis treatment were complex and impacted on the ineffective self-management behavior of hemodialysis patients. The aim of this study was to test the structural model for hemodialysis self-management behavior in Thailand.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eThis study utilized a cross-sectional design with cluster sampling based on purposive selection, involving 11 hemodialysis units and 550 patients from public hospitals in Northeast Thailand. Data collection from March to August 2024 utilized seven instruments: 1) the 14-item Health Literacy Scale (HLS-14), 2) the Patient Health Questionnaire (PHQ-9), 3) the Family State and Functioning Assessment Scale (FSFAS), 4) the Hemodialysis Knowledge Questionnaire (HDKQ), 5) the Hemodialysis Self-Management Self-Efficacy Questionnaire (HSMSEQ), 6) the Social Support Questionnaire (SSQ), and 7) the Hemodialysis Self-Management Instrument (HDSMI-18), which were analyzed using structural equation modeling.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIndicate that the modified model successfully fits the empirical data. Health literacy, hemodialysis knowledge, social support, and depression exerted a positive direct effect on hemodialysis self-management behavior. Additionally, family function positively influenced hemodialysis self-management behavior indirectly through depression and social support, while depression negatively affected hemodialysis self-management behavior indirectly via social support.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eIncreasing personal skills such as health literacy and hemodialysis knowledge, including motivating family function and providing social support, especially from the healthcare team, has a positive effect on managing depression and improving hemodialysis self-management behavior. The findings show that health systems around the world can help hemodialysis patients better manage their hemodialysis self-management by creating policies in dialysis units that support health literacy and hemodialysis knowledge, improve teaching methods, regularly assess depression levels, and encourage family or friends to stay involved in long-term care.\u003c/p\u003e","manuscriptTitle":"A Causal Model of Self-Management Behavior in Persons Receiving Hemodialysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-03 16:09:53","doi":"10.21203/rs.3.rs-8714747/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"3a18a141-03a1-4667-a867-fc15869493c3","owner":[],"postedDate":"February 3rd, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-02-03T16:11:10+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-03 16:09:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8714747","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8714747","identity":"rs-8714747","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}