Background
Chronic kidney disease (CKD) is one of the most striking global health problems [1]. Data from 2021 Global Burden of Disease [2], report 19.94 million new cases of CKD worldwide, 673.72 million patients with CKD, 44.45 million disability-adjusted life years (DALYs) caused by CKD, and 1.53 million deaths. In China, around 120 million people suffer from CKD. End-stage renal disease (ESRD) is the final stage of CKD and involves the irreversible deterioration of kidney function, characterised by the inability of the kidneys to effectively filter waste [3]. Patients with ESRD require lifelong kidney replacement therapy to sustain vital organ functions [4, 5]. The number of people receiving kidney replacement treatment globally is estimated to exceed 5.4 million by 2030 [6]. Over 80% of patients with ESRD will undergo maintenance haemodialysis (MHD) [7].
Haemodialysis can rapidly filter small and medium-sized molecular waste or harmful substances in the blood in a short period of time, helping sustain vital functions in patients with kidney failure [8]. However, this invasive treatment that requires lifelong administration, and the patients need to visit the hospital two to three times a week at a fixed time for at least 4 h of dialysis each time. Long-term haemodialysis also exposes patients to dialysis-related complications, such as hypotension, muscle spasm, and dialysis disequilibrium syndrome [9]. These painful, uncomfortable and long-term frequent haemodialysis treatments make patients lose their ability to control work and life, and gradually decline their social adaptability [10]. Patients often experience a number of stressors, including financial constraints, sexual dysfunction, employment changes, time constraints, self-isolation, family dynamics, and functional limitations, which can lead to mental health problems [11, 12]. The most common of these stressors are depression and anxiety [13]. Poor mental health status is an independent risk factor affecting the quality of life of haemodialysis patients [14]. The compounding of various physical and psychological problems seriously reduces the quality of life of patients [11, 15, 16], which is below the normal standard [17, 18].
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Rooted in traditional Chinese familial values, declining activities of daily living among aging haemodialysis patients often heighten dependency on family caregivers. Beyond managing patients’ biomedical comorbidities, MHD caregivers experience multidimensional strain encompassing physical exhaustion, psychological distress, and socioeconomic pressures from prolonged care commitments [19]. The main family caregivers of haemodialysis patients are ‘invisible patients’ who shoulder a heavy burden of care and high psychological pressure [20]. Studies on people with other chronic diseases point to a possible relationship between caregiver burden and patient’s quality of life [21]. The daily lives of patients often create new physical, psychosocial and economic challenges for families. In response to these challenges, caregivers may put additional effort into enabling patients to maintain a good quality of life and experience difficulties and stress in the process [22]. This situation may be exacerbated by the threat of losing a partner and/or the additional burden of caring for someone who was previously able to take on family responsibilities.
Compared with those targeting only the patient or caregiver, interventions that approach the family dyadic perspective while considering the mutually supportive relationship and interaction between the caregiver and patient are expected to benefit both parties [23]. Compelling empirical evidence from chronic disease populations—particularly in cardiology—reveals that caregiver-integrated psychoeducation generates bidirectional therapeutic effects, simultaneously alleviating caregiver burden and enhancing patients’ clinical trajectories [24, 25]. Over the past few years, psychosocial interventions involving caregivers or family members have increasingly been developed as an important component of effective treatment for chronic conditions. Among these approaches, psychoeducation with relevant skill training (e.g., problem-solving and stress management) seems to benefit the psychosocial outcomes of patients and caregivers, including depression and quality of life. However, current dyadic research predominantly addresses cancer, heart failure [26] and stroke [27]. Only a few reports are available on the joint intervention of MHD patients and their caregivers. Therefore, we conducted a systematic review [5] to synthesise evidence on dyadic psychoeducational interventions in the MHD dyads. However, no high-quality randomised controlled trials of MHD dyadic intervention were retrieved, and data on the characteristics of targeted dyadic intervention were lacking. To fill this gap, we designed a dyadic psychoeducational intervention program for the MHD patient-caregiver dyads on the basis of the results of our systematic review [5]. The objective of this study was to examine the effects of the dyadic psychoeducational intervention on patients’ quality of life, caregiver burden, and psychosocial health outcomes with MHD during a 3-month follow-up.
Methods
Study design and setting
This two-arm, parallel, assessor-blinded randomised controlled trial with a repeated-measures design was registered at the ClinicalTrials (NCT06203730) on December 14, 2023. Participant recruitment was initiated on January 1, 2024, at a blood-purification center in a a top-level (3 A) hospital in Jiangsu Province, China. This study was reported following the Consolidated Standards of Reporting Trials (CONSORT) Guidelines [28].
Participants
Participants were recruited from two blood purification centres of a general hospital in Taizhou, Jiangsu Province of China from January to June 2024. This hospital is among the tertiary Grade A hospitals in China and is a comprehensive hospital that integrates medical treatment, teaching, and scientific research and provides high-quality medical services and places for our medical research.
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The principal investigator (LYZ) communicated with potential patients who meet the inclusion and exclusion criteria and recruited them after they signed the written informed consent. The inclusion criteria for patients were as follows: (i) meet the diagnostic criteria for CKD. (ii) MHD for more than 3 months. (iii) being aged ≥ 18 years and (iv) having a family caregiver as their partner in a dyad in this study. Family caregivers were included if they were: (i) being aged ≥ 18 years and (ii) responsible for the main care tasks of MHD patients. The MHD dyads were excluded if: (i) either dyad member had a serious mental, visual, or hearing impairment that prevents normal communication and (ii) accompanied by serious diseases of vital organs. withdrawal criteria for MHD dyads were as follows: (i) during the study, either dyad member did not cooperate and voluntarily withdrew from the experiment and (ii) the patient in the study developed serious dialysis complications, such as intracranial haemorrhage, thrombosis and other changes in disease, death or loss of follow-up.
Sample size calculation
The sample size calculation in this study was based on a previous literature review, which showed that psychological intervention had a significant impact on the quality of life of MHD patients, and the effect size for calculating the quality of life after the intervention was 0.64 [29]. In this present study, G-power 3.1 software [30] was used to calculate the sample size, and the effect size of Cohen’ d was set as 0.64, and the ratio between the two groups was set as 1. With significance level α = 0.05 (two-tailed) and statistical test power = 0.8, Test family select t tests, Statistical test select “Means: Difference between two independent means”, the total sample size was 62 (31 per group). With a 20% loss rate was reserved, the final sample size = 62 / (1-20%) = 77.5. The final sample size was determined to be 80, with 40 dyads in each group (i.e. 40 patients and 40 caregivers).
Randomization and allocation
Random sequencing was used for grouping. The 80 enrolled dyads were assigned numbers (1,2,3… 80). Microsoft Excel was used to generate 80 random numbers and match the dyads with these numbers. A member who was not involved in the generation of random numbers and did not know the details of the study ranked 80 random numbers, placing the first 40 patients with corresponding numbers in the intervention group and the next 40 patients with corresponding numbers in the control group. The outcome assessors were blinded by not involving them in the study design, participant recruitment and participant grouping. Owing to the characteristics of the intervention, the implementer and participant cannot be blinded.
Intervention and control conditions
The MHD patients in both groups received routine care from the blood purification centres, including medical treatment and nursing from doctors and nurses and rehabilitation services from rehabilitators. The family caregivers in the control group received health education courses on life, diet and precautions during dialysis provided by nurses for 1–2 times.
The MHD dyads allocated to the intervention group underwent the dyadic psychoeducational interventions. The programme was based on the double ABC-X model, which consists of five key elements: stress pile-up (aA), family resources (bB), family perception (cC), coping (BC), and family adaptation (xX) [31]. This model is used to explain the coping and adaptation process of family members in the face of crisis and emphasise the importance of family adaptation to stress pile-up, a complex interactive process between resources and cognition. In this process, families respond directly to the broad needs of stressors and become aware of the need for systemic changes within the family unit to facilitate effective responses to stressful events that improve family satisfaction and well-being [32]. The programme was designed to enhance the MHD dyads’ perceptions and resources through four key components—information provision, social support, coping strategies, and relaxation techniques—as identified in our previous systematic review [5]. These components are expected to enhance their coping strategies and improve their functioning and psychosocial health outcomes. The programme uses a joint format of face-to-face interventions with MHD dyads, including Chinese health education booklets, individuals and small groups (6–10 MHD dyads). It has four main topics, each with 1–3 short lessons. Over the course of the 4-week intervention, one topic is presented each week. The practitioners of the programme are specialised nurses and doctors of the blood purification centres and psychotherapists. The details of the program are presented in Table 1.
Table 1
The dyadic psychoeducational interventions programme
Topics | Lessons | Contents | Setting | Delivery |
|---|---|---|---|---|
Dyadic coping with “first acquaintance” | 1. Establish relationship | Researchers introduce themselves | bedside | Face-to-face/individual |
Patient and caregiver self-introduction | ||||
Instructing patients and caregivers to join the WeChat hemodialysis communication group and suggesting that they can ask questions in the group at any time. There will be a professional medical staff in the hemodialysis center to give a guided response. Guiding them to pay attention to the blood purification center Subscription Account, dynamic understanding of disease-related information. | ||||
2.Programme overview | Introducing aims and procedures of this programme for patients and caregivers and distributing the booklets. | |||
3.Problem assessment and group discussion | Inviting Patients and caregivers to describe their current physical and mental state, difficulties encountered during dialysis, current care needs and/or self-care needs, and to lead discussions between patients and their family caregivers. | Demonstration classroom | Face-to-face/group | |
4. Introduction of dyadic coping | Explaining what dyadic coping is and its purpose, and emphasizing the importance of patient and caregiver participation. | |||
5. Health education | Introduction to maintenance hemodialysis: principles, advantages, precautions. | |||
6. Sum up | Summarizing this intervention session and inform the timing and content of the next intervention session. | |||
Dyadic coping with “deep understanding” | 1. Warm greetings | Warm up the field before intervention start, to promote familiarity. | Demonstration classroom | Face-to-face/group |
2. Review of last week | ||||
3. Positive copping | Guiding patients and their family caregivers to discuss maintenance hemodialysis related distress and its causes, and to conduct group communication. | |||
Explaining the double ABC-X model, explaining the causes of distress and its impact on caregiving burden and quality of life. | ||||
Exploring the coping strategy-positive coping | ||||
4. Health education | Maintenance hemodialysis related knowledge: explaining vascular access management, drug management, diet management, exercise management and health management. | |||
5. Sum up | Summarizing this intervention session and inform the timing and content of the next intervention session. | |||
Dyadic coping with “co-solution” | 1. Warm greetings | Demonstration classroom | Face-to-face/group | |
2. Review of last week | ||||
3. Problem solving | Example: How to use the 7 steps of problem solving to solve daily life problems. | |||
4. Social support | Dyadic support: Encourage the expression of both emotions | |||
Social support: encourage them to increase social interaction and find social support, such as peer support, family support, etc. | ||||
Assign homework: Take your partner’s place and do one of the chores he or she usually does for the family. | ||||
5. Health education | Explaining the prevention and treatment of complications of maintenance hemodialysis. | |||
6. Sum up | Summarizing this intervention session and inform the timing and content of the next intervention session. | |||
Dyadic coping with “co-experience” | 1. Warm greetings | Demonstration classroom | Face-to-face/group | |
2. Review of last week | ||||
3. Family support | Homework share from the last lesson: “What I did for each other” | |||
Guiding both patients and caregivers to recall happy moments in their lives, encouraging them to tap into their contributions to the family, and helping strengthen their relationship commitment. | ||||
Encouraging both of them to find simple and easy hobbies, participate together, and find fun. | ||||
4. Relaxation technique | Explaining the types, methods, functions and effects of relaxation techniques. | |||
Teaching patients and caregivers to cooperate with music and using relaxation techniques to help relieve negative emotions. | ||||
Patients and their caregivers demonstrate abdominal breathing exercises | ||||
5. Sum up | Summarizing this intervention programme. |
Data collection
Data were collected at baseline (T0) and immediately (T1), 1 month (T2) and 3 months after intervention (T3) by six trained research assistants blinded to the group allocation. To ensure inter-rater reliability among the six assessors prior to baseline (T0) measurements, a standardized training program was implemented. This involved a pilot assessment protocol where each assessor independently evaluated six MHD patients using the study questionnaires. Statistical analyses were conducted in R (version 4.2.1, R Foundation for Statistical Computing) to compute Fleiss’ kappa coefficients for multi-rater agreement assessment. This approach ensured objectivity in evaluating measurement consistency across six blinded assessors. Inter-rater reliability was quantified through Fleiss’ kappa to assess agreement among six independent raters evaluating randomly selected dyads. κ values were interpreted per Landis & Koch’s criteria: <0.20 poor, 0.21–0.40 fair, 0.41–0.60 moderate, 0.61–0.80 substantial, > 0.81 near-perfect [33]. These assessors’ Fleiss’ kappa coefficients ranging from 0.64 to 0.84. These results demonstrate substantial agreement in outcome measurements across assessors.
Measurement
Socio-demographic and clinical profile
Socio-demographic information, including gender, age, education level, marital status, place of residence, employment and financial status, was also collected from the dyads. Clinical information on patients, including medical payment methods, years of dialysis and comorbidities, was collected by reviewing the patients’ medical records at study hospitals (with patient consent). Information about the family caregiver’s relationship with the patient, such as the length of care, was also gathered.
The primary outcomes
The Chinese version of KDQOL-36™ was downloaded from RAND Corporation website (https://www.rand.org/health-care/surveys_tools/kdqol.html), imported by Amgen and translated by the MAPI Institute. It can be subdivided into five subscales, namely, SF-12 Physical Health Composite (SF-12 PC), the SF-12 Mental Health Composite (SF-12 MC), the Kidney Disease Symptoms/Problems (SP), the Burden of Kidney Disease (BKD) and the Effects of Kidney Disease (EKD). Each subscale focuses on a different aspect of the patient’s life. In the KDQOL-36TM scale, the first two subscales are common to the SF-12 scale and cover a wide range of health-related quality of life areas. The last three subscales are specific to kidney disease. Each item is set to 5–6 different response levels, and patients make choices according to their actual situation. Each dimension is scored on a scale of 0–100, with high scores indicating good quality of life. The Chinese version of KDQOL-36™ has good reliability and validity, with the Cronbach’s alpha coefficient of each dimension ranging from 0.69 to 0.78 [34].
The ZBI was originally developed by Zarit’s team in 1980 [35] and was sinicised by Wang Lie’s team of China Medical University in 2005 [36]. It is the most used tool to assess caregiver burden and has been revised and improved to form a 22-item ZBI scale, which is divided into two dimensions: personal burden and responsibility burden. Each entry is rated on a scale of 0–4 points (i.e. total score 0–88). Burden is divided into four levels according to the total score: 0–20 is rated as no or slight burden, 21–40 is rated as light to moderate burden, 41–60 is rated as moderate to heavy burden and 61–88 is rated as heavy burden. The Chinese version of ZBI has good reliability and validity, with Cronbach’s alpha coefficient of 0.87 [37].
The secondary outcomes
The Medical Outcomes Study Social Support Survey (MOS-SSS), adapted into Chinese by Doris’ team [38], consists of a total of 20 items categorized into four dimensions. These dimensions are Tangible Support, Informational and Emotional Support, Positive Social Interaction, and Affectionate Support. Among the 20 items, Item 1 is a subjective question aimed at measuring the size of the patient’s support network and is not scored. The remaining items are objective questions scored based on the frequency or degree of occurrence. Each item employs a Likert-5 point scoring system, ranging from “1” representing “None of the time” to “5” representing “All of the time.” Higher scores indicate better medical social support. The Cronbach alpha coefficient for this scale is 0.79.
The Brief COPE Scale (BCS), originally developed by Carver [39], distinguishes between adaptive coping and maladaptive coping strategies. It encompasses 14 dimensions with a total of 28 items. Each item uses a Likert-4 point scoring system, ranging from “1” representing “Never” to “4” representing “Almost Always.” Higher scores indicate a greater tendency to use that coping strategy. The Cronbach alpha coefficient for this scale is 0.83.
The Hospital Anxiety and Depression Scale (HADS) was translated by the Leung team at The Chinese University of Hong Kong [40]. It comprises a total of 14 items, divided into two subscales: HADS-A (Anxiety) and HADS-D (Depression), with each subscale containing 7 items. The scale employs a 4-point scoring system, ranging from 0 to 3 points per item, for a total possible score of 0–21 points per subscale. Higher scores indicate more severe levels of anxiety or depression. The Cronbach’s alphas ranging from 0.68 to 0.93 for the HADS-A and from 0.67 to 0.90 for the HADS-D [41].
Data analysis
All data were statistically analysed using IBM SPSS software (version 29.0, International Business Machines Corp, NY, USA) with a significance level set at 5% (two-tailed). Descriptive statistics were used to summarise the study variables and describe the characteristics of the intervention and control groups at baseline. The normality of continuous variables was evaluated using Q-Q plots, and measurements conforming to normal distributions were described by means and standard deviations. Data that do not conform to normal distribution were described by median and interquartile intervals. Count data were described using rate and percentage. As appropriate, an independent T-test or chi-square was applied to assess homogeneity between the intervention and control groups at baseline.
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The Generalized Estimated Equation (GEE) model with autoregressive correlation structure was used to examine the effect of dyadic psychoeducational intervention from T0 to T3 time points on the primary outcomes (patients’ quality of life and caregiver burden) and secondary outcomes (i.e., dyads’ coping, depression and anxiety symptoms, and social support) [28, 42]. GEE was fitted separately for each outcome variable to avoid cross-outcome confounding. With the participants as the subject variable, the time point as the intra-subject variable and the outcome measure as the dependent variable, the variables with p values < 0.1 and < 0.05 in the comparison between the baseline data groups were chosen as potential covariates (reducing the possibility of making Type II errors) [43] to analyse the interaction effects between the groups and the time point. A pairwise comparison of the estimated marginal mean was then performed [44]. Cohen’s d statistic was used to estimate the effect size of individual findings based on the change in mean score differences between groups before and after the intervention, and cutoff points were set at 0.2 (small), 0.5 (medium) and 0.8 (large) [45]. All analyses were based on intention-to-treat (ITT) analysis, all participants were analyzed per original allocation. Missing data were imputed via predictive mean matching. ITT reflects the daily clinical practice, preserves the balancing of risk factors between the study arms at baseline and maintains unchanged the study power because no participants is excluded from the analysis [46, 47].
Results
Participants
A total of 200 MHD dyads were screened for eligibility, 9 of whom were excluded because they did not meet the inclusion criteria and 111 declined to participate because of time conflicts or lack of interest. Ultimately, 80 dyads participated in this study. Over the course of the study, the loss of follow-up rate was 2.5% for patients (i.e. 2 losses /80 baseline) and 3.7% for caregivers (i.e. 3 losses /80 baseline). Although these loss of follow-up cases are inevitable, we still try our best to reduce their impact through effective follow-up strategies and communication mechanisms and ensure the accuracy and reliability of research data. The study maintained a relatively high completion rate and data quality, providing a solid foundation for our subsequent data analysis and interpretation of the results. The details are shown in Fig. 1.
Fig. 1
CONSORT-Flow diagram of the study
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Baseline characteristics
The patients’ age ranged from 25 years to 80 years, with an average age of 52.11 ± 12.68 years. About half of them were male (48.8%) and received less than high school education (58.8%). Among the patients, 21.3% had no spouse and 37.5% were unemployed. Half of them earned less than 1,000 yuan (50%) and relied on family members, relatives and friends and the government for relief supplies (46.3%). Most of the patients used medical insurance or agricultural insurance to pay for their medical expenses (98.8%). A large proportion of the patients (61.3%) had dialysis duration of 2–10 years. The age of caregivers ranged from 18 years to 76 years, with an average age of 51.45 ± 13.47 years. About half of them were female (53.8%) and had received less than high school education (56.3%). Most of the caregivers were married with spouse status (87.5%), had stable financial resources (73.8%) and lived in urban areas (68.8%). Among the caregivers, 62.5% were the spouse of the patient. No statistical comparisons were made between groups at baseline, as per randomized trial reporting standards. A detailed description is provided in Table 2.
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Table 2
Socio-demographic and clinical characteristics and self-reported outcomes between the intervention and control groups at baseline
Characteristics | Intervention (n = 40 dyads) | Control (n = 40 dyads) | Intervention (n = 40 dyads) | Control (n = 40 dyads) | |
|---|---|---|---|---|---|
MHD patients | Caregivers | ||||
Age | 52.58 ± 13.28 | 51.65 ± 12.21 | Age | 55.05 ± 12.40 | 47.85 ± 13.68 |
Sex | Sex | ||||
Men | 20 (50.0%) | 19 (47.5%) | Men | 18 (45.0%) | 19 (47.5%) |
Women | 20 (50.0%) | 21 (52.5%) | Women | 22 (55.0%) | 21 (52.5%) |
Education level | Education level | ||||
Primary school or less | 12 (30.0%) | 5 (12.5%) | Primary school or less | 9 (22.5%) | 5 (12.5%) |
Junior High School | 10 (25.0%) | 20 (50.0%) | Junior High School | 11 (27.5%) | 20 (50.0%) |
High school | 11 (27.5%) | 12 (30.0%) | High school | 11 (27.5%) | 7 (17.5%) |
College degree or above | 7 (17.5%) | 3 (7.5%) | College degree or above | 9 (22.5%) | 8 (20.0%) |
Marital status | Marital status | ||||
Unmarried | 6 (15.0%) | 3 (7.5%) | Unmarried | 4 (10.0%) | 2 (5.0%) |
Married | 29 (72.5%) | 34 (85.0%) | Married | 33 (82.5%) | 37 (92.5%) |
Divorced | 4 (10.0%) | 2 (5.0%) | Divorced | 3 (7.5%) | 0 |
Widowhood | 1 (2.5%) | 1 (2.5%) | Widowhood | 0 | 1 (2.5%) |
Employment | Employment | ||||
Employed | 5 (12.5%) | 4 (10.0%) | Employed | 14 (35.0%) | 20 (50.0%) |
Unemployed | 17 (42.5%) | 13 (32.5%) | Unemployed | 5 (12.5%) | 2 (5.0%) |
Retirement | 13 (32.5%) | 11 (27.5%) | Retirement | 13 (32.5%) | 9 (22.5%) |
Freelancer | 1 (2.5%) | 5 (12.5%) | Freelancer | 4 (10.0%) | 4 (10.0%) |
Farming | 4 (10.0%) | 7 (17.5%) | Farming | 4 (10.0%) | 5 (12.5%) |
Monthly income | Monthly income | ||||
Less than 1000 RMB | 19 (47.5%) | 21 (52.5%) | Less than 1000 RMB | 10 (25.0%) | 8 (20.0%) |
1000–3000 RMB | 9 (22.5%) | 7 (17.5%) | 1000–3000 RMB | 12 (30.0%) | 10 (25.0%) |
3000–5000 RMB | 5 (12.5%) | 7 (17.5%) | 3000–5000 RMB | 9 (22.5%) | 13 (32.5%) |
More than 5000 RMB | 7 (17.5%) | 5 (12.5%) | More than 5000 RMB | 9 (22.5%) | 9 (22.5%) |
Financial source | Financial source | ||||
Salary/pension | 17 (42.5%) | 17 (42.5%) | Salary/pension | 29 (72.5%) | 30 (75.0%) |
Saving | 0 | 1 (2.5%) | Saving | 0 | 1 (2.5%) |
Supply of family members | 14 (13.5%) | 13 (32.5%) | Supply of family members | 5 (12.5%) | 4 (10.0%) |
Relatives/friends supply | 3 (7.5%) | 0 | Relatives/friends supply | 2 (5.0%) | 0 |
Government assistance | 2 (5.0%) | 5 (12.5%) | Government assistance | 0 | 0 |
Farming | 4 (10.0%) | 4 (10.0%) | Farming | 4 (10.0%) | 5 (12.5%) |
Place of Residence | Place of Residence | ||||
Towns | 28 (70.0%) | 23 (57.5%) | Towns | 30 (75.0%) | 25 (62.5%) |
Village | 12 (30.0%) | 17 (42.5%) | Village | 10 (25.0%) | 15 (37.5%) |
Medical payment method | Relationship with patients | ||||
Rural medical insurance | 8 (20.0%) | 6 (15.0%) | Children | 9 (22.5%) | 11 (27.5%) |
Social medical insurance | 32 (80.0%) | 33 (82.5%) | Spouse | 26 (65.0%) | 24 (60.0%) |
Self-financing | 0 | 1 (2.5%) | Parent | 5 (12.5%) | 4 (10.0%) |
Dialysis time | Others | 0 | 1 (2.5%) | ||
Less than 2 years | 6 (15.0%) | 9 (22.5%) | Care time | 2.75 ± 1.15 | 2.57 ± 1.53 |
2–4 years | 13 (32.5%) | 8 (20.0%) | |||
4 to 10 years | 11 (27.5%) | 17 (42.5%) | |||
More than 10 years | 10 (25.0%) | 6 (15.0%) | |||
Complicated chronic disease | |||||
None | 26 (65.0%) | 28 (70.0%) | |||
Yes | 14 (35.0%) | 12 (30.0%) | |||
Quality of life (KDQOL-36™) | Caregiver burden (ZBI) | ||||
Total points | 61.37 ± 17.29 | 59.40 ± 14.68 | Total points | 32.35 ± 11.37 | 31.08 ± 13.45 |
SF-12 PC | 47.00 ± 27.54 | 45.00 ± 23.48 | Personal burden | 17.50 ± 5.60 | 17.08 ± 6.73 |
SF-12 MC | 56.21 ± 21.96 | 55.21 ± 19.63 | Liability burden | 8.70 ± 4.11 | 8.68 ± 4.98 |
SP | 77.45 ± 18.98 | 76.03 ± 17.24 | |||
BKD | 35.94 ± 18.49 | 34.69 ± 21.13 | |||
EKD | 58.67 ± 18.80 | 59.38 ± 20.25 | |||
Anxiety (HADS) | 9.55 ± 4.39 | 9.63 ± 4.24 | Anxiety (HADS) | 10.73 ± 4.23 | 10.38 ± 5.22 |
Depression (HADS) | 9.70 ± 4.16 | 9.60 ± 3.97 | Depression (HADS) | 7.43 ± 3.11 | 7.70 ± 3.31 |
Social support (MOS-SSS) | 62.35 ± 18.20 | 56.45 ± 19.12 | Social support (MOS-SSS) | 67.88 ± 14.35 | 69.00 ± 13.04 |
Adaptive coping (BCS) | 2.36 ± 0.52 | 2.34 ± 0.35 | Adaptive coping (BCS) | 2.44 ± 0.40 | 2.47 ± 0.41 |
Maladaptive coping (BCS) | 2.08 ± 0.48 | 2.02 ± 0.42 | Maladaptive coping (BCS) | 1.93 ± 0.38 | 1.96 ± 0.39 |
Effects of the dyadic psychoeducational intervention on study outcomes
Effects on the primary outcomes
The GEE model revealed a statistically significant group * time interaction effect on quality of life of MHD patients (Table 3). Pairwise comparisons indicated that the means scores between groups were significant at T1, T2 or T3. Significant improvement was observed during the follow-up. Among the five domains, statistically significant group * time effects were observed in mental health, kidney disease burden and kidney disease impact. Pairwise comparisons showed statistically significant differences in mean scores in mental health domains at T1 and T2 with effect sizes of 0.9 and 0.49, respectively, kidney disease burden domains at T2 and T3 with effect sizes of 0.97 and 1, respectively and kidney disease impact domains at T1, T2 and T3 with effect sizes of 0.80, 0.97 and 0.98, respectively. However, no significant group * time interaction effect was observed in the domains of physical health and kidney disease symptoms and problems.
Table 3
Comparison of outcome variables between groups and effect size of the intervention over the study period for MHD dyads
Patients’ outcomes | Intervention group (N = 40) | Control group (N = 40) | Between-group p value | Effect size (Cohen’s d) | Caregivers’ outcomes | Intervention group (N = 40) | Control group (N = 40) | Between-group p value | Effect size (Cohen’s d) | ||
|---|---|---|---|---|---|---|---|---|---|---|---|
Quality of life (KDQOL-36™) | Caregiver burden (ZBI) | ||||||||||
T0 Baseline | 61.37 ± 17.29 | 59.40 ± 14.68 | 0.583 | - | T0 Baseline | 31.08 ± 13.45 | 32.35 ± 11.37 | 0.648 | - | ||
T1 follow-up | 70.74 ± 8.73 | 61.39 ± 14.33 | <0.001 | 0.79 | T1 follow-up | 25.78 ± 11.07 | 32.15 ± 11.08 | 0.055 | 0.58 | ||
T2 follow-up | 71.46 ± 10.05 | 61.10 ± 12.64 | <0.001 | 0.91 | T2 follow-up | 23.92 ± 10.70 | 32.15 ± 11.57 | 0.007 | 0.74 | ||
T3 follow-up | 71.98 ± 10.24 | 61.88 ± 14.14 | <0.001 | 0.82 | T3 follow-up | 24.61 ± 11.53 | 32.21 ± 11.27 | 0.008 | 0.67 | ||
Physical Health Composite | Personal burden | ||||||||||
T0 Baseline | 47.00 ± 27.54 | 45.00 ± 23.48 | 0.728 | - | T0 Baseline | 17.08 ± 6.73 | 17.50 ± 5.60 | 0.760 | - | ||
T1 follow-up | 49.48 ± 26.88 | 47.13 ± 24.83 | 0.921 | 0.09 | T1 follow-up | 14.65 ± 6.92 | 17.38 ± 5.57 | 0.097 | 0.43 | ||
T2 follow-up | 50.55 ± 25.97 | 48.85 ± 25.12 | 0.707 | 0.07 | T2 follow-up | 13.79 ± 6.03 | 17.41 ± 5.60 | 0.036 | 0.62 | ||
T3 follow-up | 51.67 ± 26.74 | 49.62 ± 25.99 | 0.828 | 0.08 | T3 follow-up | 14.05 ± 6.20 | 17.49 ± 5.62 | 0.033 | 0.58 | ||
Mental Health Composite | Liability burden | ||||||||||
T0 Baseline | 56.21 ± 21.96 | 55.21 ± 19.63 | 0.831 | - | T0 Baseline | 8.68 ± 4.98 | 8.70 ± 4.11 | 0.981 | - | ||
T1 follow-up | 75.86 ± 17.19 | 59.20 ± 19.87 | 0.002 | 0.90 | T1 follow-up | 6.48 ± 3.26 | 8.73 ± 3.96 | 0.009 | 0.62 | ||
T2 follow-up | 66.95 ± 19.86 | 57.38 ± 19.19 | 0.002 | 0.49 | T2 follow-up | 6.08 ± 3.77 | 8.67 ± 4.23 | 0.003 | 0.65 | ||
T3 follow-up | 64.71 ± 20.81 | 58.07 ± 20.09 | 0.317 | 0.32 | T3 follow-up | 6.21 ± 3.84 | 8.56 ± 4.07 | 0.006 | 0.59 | ||
Kidney Disease Symptoms/Problems | Anxiety (HADS) | ||||||||||
T0 Baseline | 77.45 ± 18.98 | 76.03 ± 17.24 | 0.778 | - | T0 Baseline | 10.38 ± 5.22 | 10.73 ± 4.23 | 0.743 | - | ||
T1 follow-up | 84.86 ± 11.07 | 78.13 ± 15.17 | 0.025 | 0.51 | T1 follow-up | 9.58 ± 4.57 | 9.75 ± 4.28 | 0.786 | 0.04 | ||
T2 follow-up | 85.52 ± 10.76 | 77.99 ± 14.38 | 0.031 | 0.59 | T2 follow-up | 8.79 ± 4.29 | 10.79 ± 3.83 | 0.012 | 0.49 | ||
T3 follow-up | 86.06 ± 9.77 | 79.32 ± 14.00 | 0.077 | 0.56 | T3 follow-up | 7.24 ± 3.82 | 10.23 ± 3.25 | 0.004 | 0.84 | ||
Burden of Kidney Disease | Depression (HADS) | ||||||||||
T0 Baseline | 35.94 ± 18.49 | 34.69 ± 21.13 | 0.779 | - | T0 Baseline | 7.70 ± 3.31 | 7.43 ± 3.11 | 0.703 | - | ||
T1 follow-up | 42.19 ± 18.17 | 36.25 ± 22.43 | 0.210 | 0.29 | T1 follow-up | 7.53 ± 3.31 | 7.53 ± 2.83 | 0.757 | 0.00 | ||
T2 follow-up | 59.22 ± 20.85 | 38.14 ± 22.71 | <0.001 | 0.97 | T2 follow-up | 7.26 ± 2.27 | 9.00 ± 2.84 | 0.015 | 0.68 | ||
T3 follow-up | 62.98 ± 20.29 | 39.26 ± 22.94 | <0.001 | 1.00 | T3 follow-up | 6.66 ± 2.32 | 8.23 ± 2.15 | 0.015 | 0.70 | ||
Effects of Kidney Disease | Social support (MOS-SSS) | ||||||||||
T0 Baseline | 58.67 ± 18.80 | 59.38 ± 20.25 | 0.873 | - | T0 Baseline | 69.00 ± 13.04 | 67.88 ± 14.35 | 0.715 | - | ||
T1 follow-up | 72.50 ± 15.46 | 59.69 ± 16.55 | <0.001 | 0.80 | T1 follow-up | 69.80 ± 11.79 | 67.58 ± 13.75 | 0.594 | 0.17 | ||
T2 follow-up | 73.52 ± 14.29 | 58.18 ± 17.07 | <0.001 | 0.97 | T2 follow-up | 71.44 ± 11.91 | 66.90 ± 13.68 | 0.131 | 0.35 | ||
T3 follow-up | 74.44 ± 14.74 | 58.02 ± 18.49 | <0.001 | 0.98 | T3 follow-up | 73.87 ± 12.64 | 66.00 ± 14.58 | 0.019 | 0.58 | ||
Anxiety (HADS) | Adaptive coping (BCS) | ||||||||||
T0 Baseline | 9.55 ± 4.39 | 9.63 ± 4.24 | 0.938 | - | T0 Baseline | 2.47 ± 0.41 | 2.44 ± 0.40 | 0.699 | - | ||
T1 follow-up | 6.95 ± 3.11 | 9.38 ± 3.11 | 0.022 | 0.78 | T1 follow-up | 2.57 ± 0.34 | 2.48 ± 0.33 | 0.442 | 0.27 | ||
T2 follow-up | 6.40 ± 2.71 | 9.33 ± 3.21 | 0.002 | 0.99 | T2 follow-up | 2.75 ± 0.39 | 2.35 ± 0.37 | <0.001 | 1.05 | ||
T3 follow-up | 5.87 ± 2.44 | 8.82 ± 2.77 | 0.001 | 0.90 | T3 follow-up | 2.71 ± 0.41 | 2.30 ± 0.33 | <0.001 | 1.10 | ||
Depression (HADS) | Maladaptive coping (BCS) | ||||||||||
T0 Baseline | 9.70 ± 4.16 | 9.60 ± 3.97 | 0.913 | - | T0 Baseline | 1.96 ± 0.39 | 1.93 ± 0.38 | 0.697 | - | ||
T1 follow-up | 8.05 ± 3.66 | 9.33 ± 3.08 | 0.180 | 0.38 | T1 follow-up | 1.92 ± 0.43 | 1.98 ± 0.41 | 0.199 | 0.14 | ||
T2 follow-up | 7.33 ± 3.56 | 9.64 ± 3.26 | 0.017 | 0.68 | T2 follow-up | 1.76 ± 0.41 | 2.00 ± 0.39 | 0.002 | 0.60 | ||
T3 follow-up | 6.51 ± 3.17 | 9.18 ± 2.65 | 0.006 | 0.91 | T3 follow-up | 1.67 ± 0.51 | 2.06 ± 0.32 | <0.001 | 0.92 | ||
Social support (MOS-SSS) | |||||||||||
T0 Baseline | 62.35 ± 18.20 | 56.45 ± 19.12 | 0.161 | - | |||||||
T1 follow-up | 69.13 ± 10.10 | 63.60 ± 15.05 | 0.024 | 0.43 | |||||||
T2 follow-up | 68.48 ± 8.56 | 62.31 ± 12.90 | 0.017 | 0.54 | |||||||
T3 follow-up | 68.15 ± 8.74 | 64.26 ± 12.54 | 0.116 | 0.36 | |||||||
Adaptive coping (BCS) | |||||||||||
T0 Baseline | 2.36 ± 0.52 | 2.34 ± 0.35 | 0.795 | - | |||||||
T1 follow-up | 2.53 ± 0.46 | 2.35 ± 0.33 | 0.009 | 0.45 | |||||||
T2 follow-up | 2.63 ± 0.45 | 2.31 ± 0.37 | <0.001 | 0.78 | |||||||
T3 follow-up | 2.56 ± 0.50 | 2.35 ± 0.40 | 0.020 | 0.46 | |||||||
Maladaptive coping (BCS) | |||||||||||
T0 Baseline | 2.08 ± 0.48 | 2.02 ± 0.42 | 0.256 | - | |||||||
T1 follow-up | 1.90 ± 0.50 | 2.00 ± 0.44 | 0.019 | 0.21 | |||||||
T2 follow-up | 1.90 ± 0.50 | 2.11 ± 0.44 | <0.001 | 0.45 | |||||||
T3 follow-up | 1.98 ± 0.51 | 2.16 ± 0.36 | 0.002 | 0.41 | |||||||
The GEE model revealed statistically significant group * time interaction effects on caregiver burden, and pairwise comparisons indicated significant between groups difference of means scores at T2 and T3 with medium-to- large effect sizes of 0.74 and 0.67, respectively (Table 4). Among the two domains, statistically significant group * time interaction effects were observed for liability burden domains. Pairwise comparisons revealed statistically significant different mean scores in liability burden at T1, T2 and T3 with medium effect sizes of 0.62, 0.65 and 0.59, respectively.
Table 4
GEE models for the comparison of outcome variables over the study period for MHD dyads
Outcome variables | Group - difference | Time1- difference | Time2- difference | Time3- difference | Group * Time1 - difference | Group * Time2 - difference | Group * Time2 - difference | |||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
b (95%CI) | p | b (95%CI) | p | b (95%CI) | p | b (95%CI) | p | b (95%CI) | p | b (95%CI) | p | b (95%CI) | p | |
PATIENTS | ||||||||||||||
Quality of life (KDQOL-36™) | ||||||||||||||
0.84 (-5.71, 7.38) | 0.802 | 1.92 (-1.06, 4.90) | 0.207 | 2.13 (-0.81, 5.06) | 0.155 | 2.79 (-0.38, 5.96) | 0.084 | 8.51 (4.12, 12.91) | <0.001 | 9.03 (4.12, 13.65) | <0.001 | 8.82 (3.62, 14.02) | <0.001 | |
Physical Health Composite | ||||||||||||||
2.00 (-9.08, 13.08) | 0.723 | 2.13 (-4.26, 8.51) | 0.514 | 4.89 (-1.55, 11.33) | 0.137 | 5.50 (-1.09, 13.08) | 0.103 | 0.35 (-6.54, 7.24) | 0.921 | -1.34 (-8.34, 5.66) | 0.707 | -0.85 (-8.49, 6.79) | 0.828 | |
Mental Health Composite | ||||||||||||||
1.00 (-8.01, 10.01) | 0.828 | 3.98 (-1.59, 9.55) | 0.161 | 2,53 (-3.17, 8.24) | 0.758 | 3.07 (-2.90, 9.05) | 0.313 | 15.66 (5.58, 25.74) | 0.002 | 8.20 (-0.74, 17.14) | 0.002 | 5.23 (-5.02, 15.48) | 0.317 | |
Kidney Disease Symptoms/Problems | ||||||||||||||
1.15 (-6.70, 8.99) | 0.775 | 1.82(-1.01, 4.65) | 0.207 | 1.4 (-0.88, 4.76) | 0.178 | 3.19 (-0.21, 6.60) | 0.066 | 5.68 (0.73, 10.65) | 0.025 | 6.13 (0.57, 11.69) | 0.031 | 5.61 (-0.62, 11.83) | 0.077 | |
Burden of Kidney Disease | ||||||||||||||
1.25 (-7.34, 9.84) | 0.776 | 1.56 (-2.21, 5.33) | 0.417 | 3.94 (-0.05, 7.92) | 0.053 | 4.92 (-0.47, 10.31) | 0.073 | 4.69 (-2.63, 12.01) | 0.210 | 19.35 (9.81, 28.88) | <0.001 | 22.30 (13.01, 31.58) | <0.001 | |
Effects of Kidney Disease | ||||||||||||||
-0.70 (-9.12, 7.75) | 0.871 | 0.31 (-3.73, 4.00) | 0.868 | -0.70 (-4.94, 3.55) | 0.748 | -0.96 (-5.29, 3.73) | 0.664 | 13.52 (8.42, 18.62) | <0.001 | 15.54 (9.33, 21.75) | <0.001 | 16.25 (9.74, 22.76) | <0.001 | |
Anxiety (HADS) | ||||||||||||||
-0.08 (-1.94, 1.79) | 0.937 | -0.25 (-1.60, 1.10) | 0.716 | -3.1 (-1.66. 1.04) | 0.650 | -0.81 (-1.89, 0.27) | 0.140 | -2.35 (-4.38, -0.34) | 0.022 | -2.84 (-4.67, -1.00) | 0.002 | -2.85 (-4.60, -1.10) | 0.001 | |
Depression (HADS) | ||||||||||||||
0.10 (-1.66, 1.86) | 0.911 | -0.28 (-1.50, 0.95) | 0.661 | 0.02 (-1.31, 1.35) | 0.98 | -0.43 (-1.74, 0.88) | 0.519 | -1.38 (-3.38, 0.63) | 0.180 | -2.39 (-4.35, -0.43) | 0.017 | -2.71 (-4.63, -0.78) | 0.006 | |
Social support (MOS-SSS) | ||||||||||||||
0.08 (-6.05, 0.01) | 0.981 | 2.50 (-0.71, 5.71) | 0.127 | 1.65 (-1.36, 4.66) | 0.282 | 2.96 (-0.37, 6.29) | 0.081 | 5.45 (0.73, 10.17) | 0.024 | 5.65 (1.00, 10.29) | 0.017 | 3.82 (-0.95, 8.59) | 0.116 | |
Adaptive coping (BCS) | ||||||||||||||
0.03 (-0.08, 0.12) | 0.792 | 0.01 (-0.04, 0.06) | 0.681 | -0.02 (-0.12, 0.06) | 0.613 | 0.02 (-0.09, 0.12) | 0.759 | 0.16 (0.04, 0.28) | 0.009 | 0.29 (0.15, 0.43) | <0.001 | 0.20 (0.03, 0.37) | 0.020 | |
Maladaptive coping (BCS) | ||||||||||||||
0.07 (-0.13, 0.26) | 0.505 | -0.02 (-0.12, 0.09) | 0.769 | 0.09 (-0.02, 0.20) | 0.108 | 0.14 (0.03, 0.26) | 0.018 | -0.17 (-0.32, -0.03) | 0.019 | -0.27 (-0.42, -0.13) | <0.001 | -0.25 (-0.40, -0.09) | 0.002 | |
CAREGIVERS | ||||||||||||||
Caregiver burden (ZBI) | ||||||||||||||
-1,28 (-6.66, 4.11) | 0.643 | -0.20 (-0.71, 0.31) | 0.442 | -0.25 (-0.62, 0.11) | 0.176 | -0.18 (-0.57, 0.22) | 0.38 | -5.10 (-10.32, 0.12) | 0.055 | -6.95 (-12.02, -1.89) | 0.007 | -6.34 (-11.01, -1.66) | 0.008 | |
Personal burden | ||||||||||||||
-0.58 (2.99, 1.84) | 0.641 | -0.13 (-0.32, 0.07) | 0.217 | -0.13 (-0.30, 0.05) | 0.148 | -0.01 (-0.20, 0.20) | 0.993 | -2.23 (-4.86, 0.41) | 0.097 | -2.67 (-5.17, -0.17) | 0.036 | -2.46 (-4.72, -0.19) | 0.033 | |
Liability burden | ||||||||||||||
-0.03 (-2.00, 1.95) | 0.980 | 0.03 (-0.21, 0.26) | 0.835 | -0.01 (-0.25, 0.22) | 0.906 | -0.05 (-0.32, 0.23) | 0.748 | -2.23 (-3.89, -0.56) | 0.009 | -2.55 (-4.20, -0.89) | 0.003 | -2.37 (-4.04, -0.69) | 0.006 | |
Anxiety (HADS) | ||||||||||||||
-0.35 (-2.41, 1.71) | 0.793 | -0.98 (-1.81, -0.14) | 0.022 | 0.16 (-0.63, 0.94) | 0.70 | -0.43 (-1.42, 0.57) | 0.399 | 0.18 (-1.09, 1.44) | 0.786 | -1.67 (-1.09, -0.37) | 0.012 | -2.57 (-4.32, -0.82) | 0.004 | |
Depression (HADS) | ||||||||||||||
0.28 (-1.12, 1.67) | 0.698 | 0.10 (-0.95, 1.15) | 0.852 | 1.57 (0.45, 2.69) | 0.006 | 0.81 (-0.17, 1.78) | 0.106 | -0.28 (-2.02, 1.47) | 0.757 | -2.01 (-3.63, -0.39) | 0.015 | -1.85 (-3.33, -0.36) | 0.015 | |
Social support (MOS-SSS) | ||||||||||||||
1.13 (-4.81, 7.06) | 0.710 | -0.30 (-3.63, 3.03) | 0.860 | -0.68 (-3.47, 2.11) | 0.634 | -1.63 (-4.60, 1.33) | 0.280 | 1.10 (-2.95, 5.15) | 0.594 | 2.89 (-0.86, 6.64) | 0.131 | 5.99 (1.01, 10.98) | 0.019 | |
Adaptive coping (BCS) | ||||||||||||||
0.04 (-0.14, 0.21) | 0.695 | 0.04 (-0.03, 0.11) | 0.209 | -0.08 (-0.19, 0.03) | 0.136 | -0.13 (-0.24, -0.03) | 0.017 | 0.06 (-0.09, 0.20) | 0.442 | 0.36 (0.20, 0.52) | <0.001 | 0.38 (0.22, 0.54) | <0.001 | |
Maladaptive coping (BCS) | ||||||||||||||
0.03 (-0.13, 0.20) | 0.692 | 0.06 -0.01, 0.13) | 0.119 | 0.09 (-0.02, 0.19) | 0.104 | 0.14 (0.02, 0.27) | 0.019 | -0.10 (-0.25, 0.05) | 0.199 | -0.29 (-0.46, -0.12) | 0.002 | -0.44 (-0.65, -0.23) | <0.001 | |
Effects on the secondary outcomes
The GEE models revealed statistically significant group * time interaction effects on anxiety, depression adaptive coping and maladaptive coping among MHD patients (Table 3). Although the interaction effect on social support was non-significant, statistical differences were still observed between groups at T1 and T2. Pairwise comparisons revealed statistically significant differences in anxiety between groups at T1, T2 and T3 (effect sizes of 0.78, 0.99 and 0.90, respectively), depression at T2 and T3 (effect sizes of 0.68 and 0.91, respectively), adaptive coping at T1, T2 and T3 (effect sizes of 0.45, 0.78 and 0.46, respectively) and maladaptive coping at T1, T2 and T3 (effect sizes of 0.21, 0.45 and 0.41, respectively).
The GEE model revealed statistically significant group * time interaction effects on anxiety, depression, adaptive coping and maladaptive coping among caregivers and a non-significant interaction effect on social support (Table 4). Pairwise comparisons revealed statistically significant differences at T2 and T3 between groups for anxiety (effect sizes of 0.49 and 0.84, respectively), depression at (effect sizes of 0.68 and 0.70, respectively), adaptive coping (effect sizes of 1.05 and 1.10, respectively) and maladaptive coping (effect sizes of 0.60 and 0.492, respectively).
Discussion
This randomised controlled trial is the first study to examine the effectiveness of the dyadic psychoeducation intervention for MHD patients and their family caregivers in a Chinese population. We used a rigorous randomised controlled trial designed based on the most current and best available evidence. We found that the dyadic psychoeducational intervention had significantly positive effects on patients’ quality of life, caregiver burden and patients and caregivers’ anxiety, depression and coping ability. These findings support the potential integration of dyads and commonly accepted psychoeducational approaches to routine MHD management.
The attrition rate of MHD patients in this study was 2.5%, and the loss rate of caregivers was 3.8%, which was lower than the attrition rate of previous intervention studies of MHD patients and caregivers (8.3–19.7%) [48]. On the one hand, the undertaking hospital of this study is a third-class A hospital with a superior geographical location and a large blood purification centre. The participants have a fixed schedule to go to the hospital for haemodialysis three times a week, and the intervention time is selected during the patients’ bed dialysis and before or after haemodialysis, which is acceptable to patients and their caregivers. On the other hand, the patients and caregivers participate together in the intervention program and have interaction opportunities. Family members’ emotional expression in the traditional cultural background of our country is relatively implicit. Several of the interventions in this study have created a vivid and interesting expression environment for patients and caregivers, making them willing to participate in such interventions and preventing sample loss. This finding is similar to the results of previous studies on dyadic interventions in patients with heart failure [26].
Regarding the quality of life of MHD patients, the quality-of-life scores in the intervention group were all higher than before the intervention and were better than those of the control group in the three follow–up stages. This finding indicates that the intervention effect of the dyadic psychoeducational intervention is immediate and has a certain continuity. This feature is particularly important for patients who require long-term haemodialysis treatment. The continuous improvement in quality of life helps them cope with the challenges of disease and treatment, which is similar to the findings of several recent trials of dyadic interventions for chronic diseases [26, 49]. The dyadic psychoeducation also showed a significant effect on the dimensions, particularly the psychological dimension related to self-perception (i.e. mental health, kidney disease burden and kidney disease impact). This trend is consistent with the observed significant improvement in anxiety and depression in patients and shows that the dyadic psychoeducational intervention mainly focuses on improving the psychological dimension of patients. The possible reasons are as follows: firstly, the intervention program adopts a coping strategy intervention. According to psychologist Lazarus [50], coping strategies are behaviours that help individuals deal with problems and stress. The intervention in this study can guide patients to calmly face the disease and solve problems from a positive perspective, reducing their negative psychological experience. Secondly, the joint participation of patients and caregivers and the simultaneous participation of peers increase the interaction and communication opportunities. The patients feel the support from their caregivers and peers, thereby relieving their negative emotions and helping them maintain their mental health. Thirdly, Hobfoll’s resource conservation theory holds that people with resources are rarely in stressful environments that have a negative impact on their mental health [51]. The intervention program includes the use of medical resources provided to patients, the provision of disease counselling channels and measures to promote family and social resources. Hence, patients can effectively use the surrounding resources to reduce stress. However, this study found no improvement in physical health and kidney disease symptoms and problems among the MHD patients. This finding indicates that the dyadic psychoeducational intervention is insensitive to patients’ somatic related health, which is consistent with previous studies [26, 52]. Improvements in the physical function or symptoms of patients are likely to be achieved by clinical drugs or treatment changes and other medical measures and are difficult to obtain using psychosocial or educational interventions alone [44, 53]. However, this study found that the dyadic psychoeducational intervention has a certain promoting effect on the patients’ anxiety, depression and other psychological distress. In view of the limitations of dyadic psychoeducational intervention in improving physical function, future studies can explore comprehensive intervention strategies and combine psychological intervention with physical treatment to improve patients’ health in a comprehensive way.
Anzeige
Significant effects on caregiver burden were observed after the implementation of the dyadic psychoeducational intervention, suggesting that the caregivers of MHD patients can benefit from dyadic psychoeducational intervention. The effect of the intervention manifested on the second follow-up (T2). Despite the delay, the intervention program could effectively reduce the burden of caregivers, which is consistent with the results of recent studies on psychoeducational intervention in patients with stroke [44, 54], cancer [55] and cardiovascular disease [56]. A meta-analysis showed that psychosocial interventions conducted in multidisciplinary groups had the greatest impact on caregiver burden, inducing a moderate improvement in this aspect [57]. In this study, the intervention program formulation and implementation team consisted of professional researchers, nephrophysicians, blood purification nurses and psychologists. The intervention can solve the problems of disease treatment and care, provide emotional and psychological support and promote the caregiver’s perception of a high level of social support to minimise their burden. The program provides an opportunity for caregivers to express their emotions, and caregivers and patients give each other comfort and support, increasing confidence in the face of illness or difficulty. Both are encouraged to work towards a common goal while jointly addressing unmet needs and concerns. With the support of patients, caregivers can achieve an optimal balance between necessary care tasks and their own lives and family relationships, thereby reducing the caregiver burden caused by caregiving behaviours and activities [27]. Additionally, education and skill training related to the caregiver role can enhance the caregiver’s competence and increase his/her confidence in managing new life situations [58‐60], potentially decreasing the caregiver burden.
Regarding secondary outcomes for patients, the dyadic psychoeducational intervention also showed significant effects on coping, anxiety and depression in T1, T2 and T3. Although the effects on social support were not significant, the intervention group still had better social support in T1 and T2 than the control group. Several recent studies of psychosocial and educational interventions with family members have also shown significant improvements in coping for patients with cancer [61] and stroke [62], which matched the current results for anxiety and depression. The dyadic psychoeducational intervention has a positive effect on alleviating anxiety and depression in MHD patients, and this improvement has been continuously reflected at different time points after the intervention. It provides knowledge of coping with emotional distress and related psychotherapy strategies, enhances family and peer communication and helps patients access support resources to manage their negative emotions. Several studies on stroke [44] and cancer [63] also confirmed significant improvements in psychological distress and depressive symptoms in patients who received dyadic psychological interventions. Additionally, the patient is able to apply the knowledge and skills acquired during the intervention to cope with problems in daily life, thereby improving his/her psychological state.
Regarding secondary outcomes for caregivers, the improvements in coping, anxiety and depression in caregivers were more delayed than those in patients and were observed at 1 month after intervention (T1). Relevant studies have shown an interdependent relationship between the emotional distress of patients and caregivers, and their anxiety and depression affect each other [64, 65]. T In the current work, the effects on caregivers appeared late, possibly because they did not have enough time to practice their recently acquired coping skills [66]. Patients and caregivers need to be treated as a dyad nursing unit, and joint dyadic psychological intervention can improve the anxiety and depression of patients and caregivers. No effect on caregiver social support was observed, which is consistent with previous findings [67, 68]. Firstly, family caregivers often consider the patient’s care needs to be the top priority, followed by the caregiver’s own needs. Although we tend to provide support throughout the program, this phenomenon may be due to the short duration of the intervention and the caregiver not yet feeling the support he/she has received [69]. Secondly, only one caregiver participated in the intervention, which did not change the other family members’ care issues and emotional support for the caregiver, resulting in limited improvement in the caregiver’s social support [44, 70]. Therefore, future research should focus on the psychosocial outcomes of family caregivers and provide long-term psychosocial support to meet their individual needs during care.
This study verified the effect of the dyadic psychoeducational intervention in MHD patients. The program can significantly improve the negative emotions, coping ability and positive behaviours of MHD patients and caregivers, thereby improving the patient quality of life and caregiver burden and their mental health. However, the persistence of the intervention effect needs further investigation. This work explored the great potential and application value of the dyadic psychoeducational intervention, which provides an efficient psychological intervention means for this special group. The results support the inclusion of the dyadic psychoeducational intervention in the routine nursing and clinical practice of MHD to ensure the sustainability of the intervention effect. However, the current problem of human resources for health care personnel may hinder this process. Future studies should further optimise the intervention regimen so that it can be effectively integrated into clinical practice.
Limitations
This study had several limitations. Firstly, this research is a single-centre study with a small sample size, and the extrapolation of the results is still uncertain. In the future, the sample size will be expanded, multi-centre research will be carried out and the extrapolation of research results will be increased. Second, due to the time problem, the follow-up was only conducted for 3 months after the end of the intervention. Hence, determining the long-term effect of the dyadic psychoeducational intervention on MHD dyads is impossible. The intervention period and follow-up time will be extended in future studies to observe the long-term impact of the intervention. In addition, multiple hypothesis testing was conducted in the study, which increases the risk of committing a Type I error (i.e., falsely rejecting a true null hypothesis). In future studies, we will consider adopting stricter methods for multiple comparison correction to further reduce the risk of Type I errors. Finally, the longer time that healthcare providers spent with the intervention group compared to the control group resulted in differences in the perceived social support between the two groups. In future studies, we will consider employing more objective assessment methods to quantify the level of social support and explore other approaches to further balance and mitigate this potential bias.
Conclusions
The dyadic psychoeducational intervention is an effective way to improve the quality of life of the patients and burden of their caregivers in the context of MHD care. This study provides a basis for the inclusion of family caregivers in blood purification care procedures. Given the uncertainty of the effect of the dyadic psychoeducational intervention on improving physical function and social support, future studies should explore integrated intervention strategies, add training strategies for patients’ physical function and focus on the psychosocial outcomes of family caregivers during long-term follow-up.
Acknowledgements
The authors would like to thank the participated in this study，and also thank the data collectors and implementers of this program.
Declarations
Ethics approval and consent to participate
The study design and procedures followed the Declaration of Helsinki and were approved by the Ethics Committee of Taizhou People’s Hospital, Jiangsu Province, China (KY2023-184-01). Written informed consent was obtained from each participant who agreed to participate in the study. The participants have the right to withdraw from the study at any time without any negative impact on their usual treatment, care, and other service.
Consent for publication
Not applicable.
Competing interests
The authors declare no competing interests.
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