The Effects of an App-based Acupressure on Alleviating Fatigue, Pruritus, and Sleep Quality Among Hemodialysis Patients

Introduction Fatigue is a multidimensional construct, encompassing behavioral, emotional, sensory, and cognitive domains (Joshwa et al., 2020). Among patients receiving hemodialysis (HD), fatigue is one of the most commonly reported and debilitating symptoms (Bossola et al., 2023). This symptom profoundly affects patients' functional capacity, psychological well-being, and overall quality of life (Bossola et al., 2023).

The effectiveness of both pharmacological and non-pharmacological interventions for managing fatigue in hemodialysis patients remains inconsistent due to a lack of high-quality evidence (Natale et al., 2023). Pharmacological options, such as erythropoiesis-stimulating agents, serotonin reuptake inhibitors, beta-blockers, anabolic steroids, and glucose-enriched dialysate, have produced mixed results (Natale et al., 2023). Similarly, non-pharmacological approaches, including amino acid supplementation, music therapy, meditation, cognitive-behavioral therapy, exercise, nutritional support, and light therapy, have shown limited and inconclusive benefits (Natale et al., 2023). Other interventions, such as increasing the frequency of dialysis sessions, adjusting blood flow rates, and home blood pressure monitoring, have also been explored, but lack strong supporting evidence (Natale et al., 2023). Given the complex nature of fatigue in this population, further well-designed studies and interventions are needed to establish effective management strategies.

Acupressure, a non-invasive technique derived from traditional Chinese medicine, has been explored as a potential non-pharmacological approach for reducing fatigue across various domains, such as behavioral, emotional, sensory, and cognitive fatigue (Chang et al., 2024). Acupressure can be performed by patients themselves after appropriate training, rather than relying on a therapist. Self-administered acupressure is time-efficient, low-cost, and easy to learn. Several studies have investigated its use for managing insomnia disorder (Yeung et al., 2022), pain in patients with osteoarthritis (Guo et al., 2021; Yeung et al., 2024), cancer-related fatigue in breast cancer survivors (Zick et al., 2016), quality of life in patients with perennial allergic rhinitis (Li et al., 2023), and anxiety levels in prediabetic women (Haghighat et al., 2024). Recently, a pilot RCT demonstrated that self-acupressure is safe and feasible for preventing respiratory tract infections in patients with chronic kidney disease (CKD) (Liu et al., 2022) and for managing symptoms and improving quality of life in HD patients (Parker et al., 2024).

The rapid advancement of mobile health (mHealth) technologies has significantly enhanced both the accessibility and personalization of healthcare. Smartphone applications, in particular, have become valuable tools for promoting self-care and managing chronic conditions (Sockolow et al., 2021; Wang et al., 2021) through features such as personalized goal setting, timely reminders, social interaction, and supportive feedback (Yi et al., 2018). A systematic review indicated that app-based mHealth interventions can effectively reduce stress and enhance self-management among non-clinical and subclinical populations (Sîrbu \& David, 2024). Moreover, app-based interventions demonstrate their superiority in reducing fatigue among HD patients. A previous randomized controlled trial demonstrated that a recreational therapy app significantly reduced fatigue levels compared to standard care (Alishahi et al., 2024). The app provided a variety of content, including music, comedy, exercise, and educational materials, to help patients manage various dimensions of fatigue.

Although previous studies have shown that acupressure can effectively reduce fatigue, most studies have relied on trained therapists to administer the treatment. This limits accessibility and long-term sustainability, particularly for those who need ongoing symptom management. Although growing interest in digital health solutions, few studies have explored the use of mobile applications to guide self-administered acupressure as a convenient, cost-effective, and scalable alternative. App-based platforms can empower patients by enabling consistent practice and offering immediate, guided instruction without the need for direct clinical supervision. This approach, combining traditional therapies with modern digital tools, may enhance patient self-management and improve fatigue-related outcomes. Therefore, the primary aim of this study is to evaluate the effectiveness of an app-based self-guided acupressure intervention in alleviating fatigue among patients undergoing hemodialysis. The secondary aims are to examine its effects on pruritus and sleep quality in the same population. The hypotheses of this study are:

H1: Hemodialysis patients who receive the app-based self-guided acupressure will have greater fatigue relief compared to those receiving usual care.

H2: Hemodialysis patients who receive the app-based self-guided acupressure will have greater pruritus relief compared to those receiving usual care.

H3: Hemodialysis patients who receive the app-based self-guided acupressure will have greater improvement in sleep quality compared to those receiving usual care.

2\. Theoretical approach Bandura's Social Cognitive Theory, with a central focus on the construct of self-efficacy (Bandura, A., 1977), will be used to develop the self-guided acupressure apps (Figure 1). Self-efficacy theory explains how individuals develop and modify beliefs in their ability to perform specific behaviors, and how these beliefs influence behavioral change, performance outcomes, and personal well-being. According to Bandura, expectations of personal efficacy are derived from four principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological and emotional states (Bandura A., 1977). The self-acupressure app in this study is intentionally designed to address each of these four domains: The app encourages users to engage in regular, structured self-acupressure sessions. As participants complete these sessions, they experience successive mastery, which reinforces their confidence in managing fatigue through their own actions. Second, the app includes guided video demonstrations of self-acupressure techniques, allowing participants to observe others performing the same tasks. This modeling helps cultivate the belief that "if others can do it, so can I." Third, the app integrates motivational pop-up messages, such as "Well done!" or "Almost there-don't give up now!", to encourage continued engagement and reinforce users' belief in their ability to succeed, particularly during moments of low motivation. Finally, as acupressure helps reduce physical fatigue and promotes relaxation, users experience positive internal states. These improvements contribute to more favorable self-efficacy judgments and further motivate sustained engagement in self-care behaviors. By enhancing users' self-efficacy, the app aims to increase confidence in managing fatigue and foster long-term self-management among patients receiving hemodialysis.

Study design This study is a two-arm parallel randomized controlled trial (RCT). The CONSORT (Consolidated Standards of Reporting Trials) guidelines will be used to report this study. This study will be prospectively registered at ClinicalTrials.gov (https://clinicaltrials.gov/) prior to participant enrollment.

3.2 Research setting and participants The study will be conducted in the hemodialysis unit in Hoe Nhai Hospital, Hanoi, Vietnam. The patients are 18 years old or over, are able to speak and understand Vietnamese, receive hemodialysis at least three times a week for three months or longer, have a score equal to or greater than 4 on a numeric rating scale (NRS, 0-10) (Oldenmenger et al., 2013), has a smartphone or tablet, and can provide written informed consent. The patients who have advanced cancer, cognitive impairment, chronic obstructive pulmonary disease, severe edema, have already used or plan to use acupressure or acupuncture in the following 3 months, or have soft tissue or vascular disease in their lower extremities will be excluded.

Sample size will be calculated using G\*Power software version 3.1.2 (Faul et al., 2009). With a power of 0.80, a 2-sided significance level of 5%, and a medium effect size of 0.35 (Vagharseyyedin et al., 2019), it was estimated that a total sample size of 42 participants would be needed. In addition, the attrition rate of 20% will be considered. Finally, we will recruit 50 to 100 participants in this study.

3.3 Instruments The questionnaires include demographic and health-related information, Post-Dialysis Fatigue Scale, 5-D Itch, Pittsburgh Sleep Quality Index, and Hemodialysis Comfort Scale version II.

3.3.1 Demographic and health-related information questionnaire This questionnaire consists of gender, age, employment status, marital status, educational level, economic status, duration of dialysis, comorbidities, self-assessed health status, exercise frequency, BMI, Kt/V, serum phosphorus, serum potassium, serum albumin, interdialytic gain weight (IDGW), blood pressure before and after dialysis (to calculate intradialytic hypertension). The self-assessed health status was measured on a five-point scale from 1 to 5 (1 = poor, 2 = fair, 3 = good, 4 = very good, 5 = excellent). These variables will be used to analyze the differences between the two groups at the baseline.

3.3.2 Post-Dialysis Fatigue scale (PDF) PDF, developed by Hirotoshi Kodama et al. (2020), will be used to measure fatigue in this study. This scale comprises 13 self-reported items rated on a five-point Likert scale, ranging from 1 (strongly agree) to 5 (not at all). The score will be reversed for analysis, and the total score is between 13 and 65, with higher scores indicating more severe fatigue. The PDF scale is concise and can be completed in 5-10 minutes. The Vietnamese version questionnaire translated by the researchers will be used in this study. Its content validity index (CVI) is 0.99, and Cronbach's alpha is 0.90.

3.3.3 5-D Itch The 5-D Itch was developed by Elman et al. (2010) to evaluate the severity of skin itching conditions over the past 2 weeks based on five dimensions: duration, degree, direction, disability, and distribution. Itching at up to two sites receives a score of 1; three to five sites are assigned a score of 2; the score is 3 for six to ten sites; 11 to 13 sites are scored 4; and the highest score of 5 is given for 14 to 16 sites. The total scores range from 5 to 25. Higher scores indicate greater itch severity. The scale of the Vietnamese version demonstrated good content validity (CVI=1.00) and acceptable reliability with Cronbach's α of 0.80.

3.3.4 Pittsburgh Sleep Quality Index (PSQI) The PSQI was developed by Buysse et al. (1989) consists of 7 components, 3 factors, and 19 subitems, and aims to evaluate a person's sleep quality within the last month, including seven components: (1) subjective sleep quality, (2) sleep latency, (3) sleep duration, (4) habitual sleep efficiency, (5) sleep disturbances, (6) use of sleeping medication and (7) daytime dysfunction. Component scores range from 0 (no difficulty) to 3 (severe difficulty). The total score ranges from 0 to 21, with higher values indicating poor sleep quality. A score of more than 5 indicated a person had poor quality sleep. The Vietnamese version will be used in this study and has a Cronbach's alpha coefficient of 0.789, indicating an acceptable internal consistency (To, 2017).

3.4 Intervention 3.4.1 Intervention group Participants in the intervention group will be instructed to download and install the mobile application, with initial training provided by the research team to ensure correct usage. During the training session, participants will be guided through the app's features, inc

• Pruritus [Time frame: Pruritus will be assessed at the same time points for both groups (baseline (T1), 2 weeks during intervention (T2), immediately after the intervention (T3), 4 weeks follow-up after the intervention (T4), and 8 weeks follow-up after the intervention (T5))]
• Sleep quality [Time frame: Outcome will be assessed at the same time points for both groups (baseline (T1), 2 weeks during intervention (T2), immediately after the intervention (T3), 4 weeks follow-up after the intervention (T4), and 8 weeks follow-up after the intervention (T5)).]