Abstract

Background

Chronic Kidney Disease (CKD) is a growing global health issue with a complex symptom phenotype. It negatively impacts patients鈥� health-related quality of life and increases healthcare utilization. While digital health interventions offer promising avenues for improving symptom management in CKD, understanding their development, validation, and effectiveness is crucial for clinical application.

Objective

To comprehensively map the existing literature on digital health interventions designed to manage symptoms in patients with Chronic Kidney Disease (CKD), using the UK Medical Research Council鈥檚 complex intervention framework as a guiding lens. This scoping review aims to: (1) catalogue digital health interventions utilized in CKD symptom management; (2) detail the range of outcome measures assessing intervention effectiveness, including clinical efficacy, patient adherence, and quality of life; (3) examine the methodologies and frameworks employed in the creation of these interventions; (4) assess the pilot testing and effectiveness evaluations; and (5) categorize and analyze the barriers to implementation.

Methods

A scoping review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. Databases searched included PubMed, Scopus, Embase, and others, covering literature up to December 2023. Studies were selected based on predefined eligibility criteria for digital health interventions for CKD symptom management.

Results

The search yielded 31 studies, with a mix of development and validation studies, predominantly from developed countries. The review highlights the potential of digital interventions in enhancing symptom management, quality of life, and patient engagement in CKD care. However, gaps were identified as follows: (1) Iterative refinement cycles involving multidisciplinary stakeholders enhanced intervention acceptability and usability should be guaranteed, (2) Theory-driven and evidence-based approaches were underutilized in current intervention development, (3) Long-term implementation outcomes and process evaluations were rarely assessed. This review maps an evolving landscape where digital health interventions offer patient-centric solutions for CKD symptom management while highlighting opportunities for methodological advancements.

Conclusion

Digital health interventions hold promise for improving symptom management in CKD, yet more research is needed to overcome current limitations and fully realize their potential. Future studies should focus on patient-centred designs, comprehensive validation processes, exploring the underlying mechanism using process evaluation and the integration of these technologies into routine clinical practice.

Introduction

Chronic Kidney Disease (CKD) is a progressive condition characterized by a gradual decline in kidney function, leading to the accumulation of metabolic waste and significant health complications. The Global Burden of Disease (GBD) report reveals that the ranking of CKD in the list of causes of death continues to rise, ranking 13th in 2016 and 12th in 2017, and is predicted to become the fifth leading cause of death globally by 2040 [1, 2]. This disease presents substantial challenges due to its complex symptomatology, which adversely affects patients鈥� quality of life. Chronic Kidney Disease (CKD) presents a diverse range of symptoms due to complex underlying pathophysiology. The kidneys are crucial for filtering waste and endocrine functions. In end-stage CKD, uremic toxins accumulate, leading to systemic issues such as inflammation, immune dysfunction, and vascular disease, along with the reduced endocrine function that can cause malnutrition, anaemia, and blood pressure problems [3]. The KDIGO consensus states that while hemodialysis can sustain life, it does not necessarily alleviate symptom burden. CKD patients commonly experience symptoms like pain, fatigue, itching, and constipation, with a significant impact on health-related quality of life, hospitalization rates, and mortality [4,5,6,7]. Addressing these complex symptoms while maximizing physiological and social functioning is a critical challenge.

The KDIGO consensus conference has emphasized that symptom assessment and management are important components of high-quality care for patients with end-stage kidney disease. It specifically highlights the need to focus on symptom management strategies and their effectiveness in chronic kidney disease populations, including their impact on relevant patient outcomes such as overall symptom burden, physical function, and health-related quality of life [8]. Guidelines and consensus statements have recommended the implementation of symptom management for patients to improve their health outcomes [8,9,10,11]. Although symptom management is crucial for reducing the symptom burden of patients, there are currently barriers to clinical symptom assessment and management at both the healthcare and patient levels. On the healthcare level: Firstly, due to the lack of a standardized flow of symptom assessment [12], frequent underestimation of the range and severity of symptoms in hemodialysis patients exist commonly [13,14,15,16]. Additionally, because symptom management requires multidisciplinary collaboration, the provision of medical services is often fragmented among nephrologists, nephrology nurses, primary healthcare personnel, social workers, etc., resulting in a lack of continuity in care and difficulty for patients in accessing services [17, 18]. Lastly, due to differences in economic development levels across countries and regions, there is a variation in the number of healthcare professionals specializing in nephrology [19, 20]. This results in an insufficient number of nephrology healthcare providers in some less economically developed areas. Studies have shown that a shortage of nephrology healthcare professionals may lead to an increase in patient mortality rates [19]. On the patient level: Firstly, patients often conceal their need for symptom management due to fear, lack of knowledge, low health literacy, etc [15]. Hemodialysis patients often refrain from communicating their symptoms to healthcare personnel and adopt ineffective self-management strategies [21, 22]. Secondly, the accessibility of medical resources is also an important influencing factor. Studies have found that patients living far from kidney disease medical resources have low treatment compliance and higher mortality rates [23], which will increase mortality and other adverse outcomes.

Given the significant barriers identified in effective symptom management for hemodialysis patients, digital health interventions emerge as a pivotal solution. By leveraging advanced technologies, these interventions can profoundly transform care delivery, addressing both healthcare and patient-level challenges. Firstly, digital health platforms can standardize symptom assessment processes. By utilizing regular and algorithm-driven prompts for symptom reporting, these platforms ensure consistent and accurate tracking of symptom severity, which mitigates the common issue of symptom underestimation in hemodialysis patients [24]. Moreover, digital tools facilitate enhanced multidisciplinary collaboration [25]. Integrated health systems allow for real-time sharing of patient data among healthcare teams, including nephrologists, nurses, and social workers. Such connectivity fosters improved communication and coordination, ensuring that all team members are informed and aligned in their care strategies, thus improving the continuity of care for patients. On the patient side, digital interventions empower individuals by enhancing their knowledge and self-management capabilities [26, 27]. Additionally, digital health interventions significantly enhance access to specialized nephrology care, especially in underserved regions. Through telemedicine, patients in remote areas can connect with nephrology specialists, effectively overcoming geographical barriers that limit access to expert care [23, 28,29,30]. This is particularly vital in regions with a shortage of healthcare professionals, potentially reducing mortality rates associated with inadequate care. Worldwide, scholars have also developed digital applications for interventions targeting symptom monitoring and symptom management issues faced by chronic kidney disease patients.

Although digital interventions show promising prospects for symptom management in Chronic Kidney Disease (CKD), there is currently a significant lack of comprehensive descriptions of digital interventions across the entire research cycle of CKD. To ensure a rigorous and structured approach to developing and evaluating digital health interventions for Chronic Kidney Disease (CKD) symptom management, this study employs the Medical Research Council鈥檚 (MRC) framework. The framework guides the systematic progression of the interventions through four phases: Development, Feasibility/Piloting, Evaluation, and Implementation, ensuring comprehensive oversight and structured analysis. While there is substantial research in this field, reviews that comprehensively describe the digital interventions for symptom management in CKD throughout the entire research cycle are lacking. As a complex intervention, it remains unclear what components are included in digital interventions for symptom management in CKD patients. Additionally, the development of interventions is generally considered the beginning of the research cycle for complex interventions, where the MRC framework emphasizes that development should be based on evidence-based medicine and involve stakeholders in its inception. It remains unclear whether these studies on developing interventions have a sufficient evidence base, involved relevant stakeholders, used specific program theories to guide the development phase, or refined the interventions post-development. In the phases of feasibility and effectiveness testing of the interventions, it is not clear what types of study designs were used, whether they adequately demonstrate the effectiveness of digital health interventions, or what specific subpopulations of CKD (chronic kidney disease, dialysis, or pre-transplant) the interventions target. Moreover, what outcome measures were studied, and what specific issues they address under what circumstances remain unspecified. Nevertheless, the landscape of digital health interventions for symptom management in CKD is in a phase of continual evolution, necessitating a comprehensive understanding of the current state of research in this domain. Medical Research Council鈥檚 complex intervention framework is a rigorous framework for researchers to develop, validate and implement a complex intervention [31]. Therefore, conducting a scoping review to chart the existing literature on the development of digital health interventions for symptom management in CKD is imperative. Such a review will aid in identifying gaps, challenges, and prospects in this area, thereby informing future research endeavours and clinical practice guidelines.

Objectives

The primary aim of this scoping review is to explore and map the range of digital health interventions for chronic kidney disease (CKD), thereby identifying gaps in the current research and potential areas for future investigation [32]. The specific objectives are structured to dissect the complexity and breadth of this rapidly evolving field: (1) Catalogue digital health interventions used in CKD symptom management; (2) Evaluate Outcome Measures: Detail the range of outcomes used to assess the effectiveness and impact of these interventions, including clinical efficacy, patient adherence, and quality of life, (3) Examine the methodologies and frameworks utilized in the creation of digital health interventions, (4) Identify and assess the pilot testing and effectiveness evaluations, (5) Identify, assess and category the barriers of the implementation.

Method

Methodology & reporting guidelines

We chose to conduct a scoping review to provide a broad and inclusive overview of the diverse and rapidly evolving field of digital health interventions in Chronic Kidney Disease. This approach allowed us to explore a wide spectrum of interventions, methodologies, and outcomes, incorporating both grey literature and various study designs to fully capture the interdisciplinary and multifaceted nature of this domain. The flexibility of the scoping review framework was crucial for mapping out the existing landscape, identifying gaps in the literature, and outlining potential areas for future systematic reviews [33, 34]. Furthermore, the insights derived from this review are instrumental in guiding future research directions and shaping policy and practice by clearly delineating the current state and gaps in research and clinical practice [33, 34].

We used the Arksey & O鈥橫alley as our research framework [35]. This scoping review was conducted based on the guidelines and principles of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) Checklist [36]. The scoping review was registered on the OSF (Open Science Framework) and the registration DOI is . Although pre-registering a scoping review can help reduce bias, researchers need to make adjustments based on the actual circumstances of the study. In this study, we followed the pre-registered protocol for conducting the scoping review as closely as possible. However, during the formal conduct of the scoping review, the following adjustments were made: further refinement and improvement of the search expression (including the addition of symptom-related search terms). The RISMA-ScR Checklist can be found in supplementary file.

Searching strategy

Three steps were followed in the search strategy. First, the preliminary search was conducted in the Pubmed database using both MeSH terms and free terms to develop search words. Secondly, two researchers and a medical librarian then devised a search strategy to identify studies reporting on the evidence of the development or validation process of digital health interventions for symptom management for patients with Chronic Kidney Disease. We devised tailored search strategies for each database and tried many times to get an optimal result when it is necessary. Third, we reviewed the references of all the included studies to find potentially eligible supplement literature that may be included. We have searched for grey literature to keep the integrity of searching results. The databases we searched are PubMed, Scopus, Embase, the Cochrane Library, Web of Science, CINAHL (via EBSCO), OpenGrey archive, arXiv, and bioxiv. The searching time limit was from inception to December 2023. The detailed search strategy and results can be found in supplementary file 2. In scoping reviews, it is essential to maximize sensitivity to include as many relevant studies as possible while striving for reasonable precision (Higgins et al., 2019). We choose a highly sensitive searching strategy to reduce the omission of literature and reduce the bias of study selection.

Eligibility criteria

We used P (Population), I (Intervention), C (comparator), and O (Outcome). Studies were included if they met the following criteria- Population: (1) Adult patients with chronic kidney disease (CKD) at any stage from 1 to 5, including those undergoing dialysis or conservative management; (2) Patients facing or awaiting kidney transplants, as they are still considered to be in a state of chronic kidney disease until the transplant process is completed. Intervention: intervention focusing on e-health. E-health is a broad term that includes telemedicine, electronic health records, telehealth, mobile health applications, and other forms of ICT-based health services. We adopted two sources of e-health to help us define the intervention. E-health is defined by the World Health Organization as 鈥渢he transfer of health resources and health care by electronic means鈥� [37]. It encompassed the use of information and communication technologies (ICT) in the health sector, including the delivery of health information, care, and treatment through digital and electronic platforms. The Australian National e-Health strategy further elaborated on this definition by stating that e-Health ensures 鈥渢hat the right health information is provided to the right person at the right place and time in a secure, electronic form to optimize the quality and efficiency of health care delivery鈥� [38]. Outcome: (1) The focus and aim of this study should include at least one aspect of symptom evaluation, symptom burden or symptom management; (2) For experimental studies, the outcome measure should include at least one measure related to symptoms caused by the chronic kidney disease, the progression of disease or the treatment (dialysis, medicine related to Chronic Kidney Disease, etc. al) rather than caused by other external factors such as anxiety caused by COVID-19 epidemic. Others: were full-text, peer-reviewed articles and published in English. Studies were excluded if they were letters, correspondence, dissertations and conference papers.

Study selection

The first screen is based on titles, abstracts and keywords, and the second round screen is based on full texts. Study selection was performed according to the predetermined eligibility criteria following established guidelines for systematic reviews. We choose to follow the guidelines for systematic reviews because the process of selection of systematic reviews is rigorous and repeatable. All search results were initially imported into the reference management software program Endnote X9. After the duplicates were removed, titles and abstracts were read carefully to identify the eligibility of studies. Then full-text documents were scrutinized to further identify the fulfillment of selection criteria. Before the beginning of the screening process, we hold an online meeting to ascertain the criteria of each step of screening (such as 鈥淚n what condition should a study be judged as irrelevant and excluded by reading the title and abstract ?鈥�) to prevent the misunderstanding of the eligibility or subjective understanding. After that, the calibration exercise was conducted on the subset of studies to identify any potential discrepancies or areas of confusion among screeners [39]. One of the researchers chose 50 publications randomly retrieved in the Pubmed database. All reviewers related to the screening process would participate in the exercise to independently evaluate all the literature before the first author of this review compared all their answers and announced the right assessment. At each stage of formal screening, a minimum of two trained reviewers (XT, YZ, AP, YQ) independently read and critically evaluated the eligibility criteria of each study that may be included. Any discrepancies would be discussed to reach a consensus at the pilot and formal screening process stage.

Research cycle classification

In our study, we have utilized the Medical Research Council framework to guide the development, evaluation, and implementation of digital health interventions for Chronic Kidney Disease (CKD) symptom management. This structured approach ensures that our research comprehensively covers the lifecycle of the interventions from conceptual development through to practical application. The MRC framework is structured into four distinct phases, each serving a specific objective:

Development Phase: This phase focuses on identifying the evidence base for the intervention, developing its components, and understanding the theoretical underpinnings of how the intervention is expected to produce change.

Feasibility/Piloting Phase: The primary objective here is to test the procedures, estimate recruitment and retention, and assess whether the intervention is feasible for further testing in a more extensive study.

Evaluation Phase: This phase aims to rigorously assess the effectiveness and cost-effectiveness of the intervention in practice, typically through well-designed controlled trials.

Implementation Phase: The focus in this final phase is on monitoring the broader implementation of the intervention in real-world settings and evaluating its sustainability and scalability over time.

Data extraction

Before the beginning of the extraction, the coordinator (LS) who did not participate in the screening and extraction process conducted the extractor masking to reduce bias in the extraction process. All included papers were transformed to reproducible form and their study-specific details such as the author, study type, affiliations, and journal names were replaced with generic terms (such as author A, affiliations A, journal B) to prevent bias. We used a pre-designed data extraction table to extract the characteristics and content of the evidence, including the first author, publication or update year, type of evidence, the main theme of the evidence, and related evidence of this topic. At least two trained researchers (XT, YQ, YZ) participated in the data extraction process. The extracted evidence was compared with each other and any discrepancies related to the content of the extraction were discussed in interpretation to reach a consensus on the correct extraction.

Data synthesis and coding framework

Narrative synthesis was conducted from multiple studies to get a descriptive summary and interpret the collective evidence fully [40, 41]. Two researchers (XT, and YQ) independently synthesized the evidence and compared the results with each other. Any discrepancies were discussed and resolved by the third researcher (AP).

Data synthesis in this scoping review was conducted using a narrative approach, which facilitated a comprehensive summary of the findings across the included studies. This approach was chosen to accommodate the diverse methodologies and outcomes present in the studies under review, allowing for a descriptive synthesis that aligns with the exploratory nature of a scoping review.

To structure our data synthesis, we employed a coding framework that was developed based on the MRC guidance for developing and evaluating complex interventions [31, 42]. This framework was instrumental in categorizing the data according to key components of complex intervention development, including:

• (1) Intervention Development: Codes were assigned to segments of texts describing intervention design, stakeholder engagement, and initial feasibility testing. This included descriptions of multidisciplinary inputs and iterations based on pilot feedback. Details regarding the technological platforms used (e.g., mobile apps, web-based platforms, wearables) and their functionalities (e.g., symptom tracking, educational content) are meticulously catalogued.

• (2) Feasibility and Pilot Testing: We document the initial testing of interventions to assess their practical implementation, refine prototypes, and determine the feasibility of broader deployment. Adjustments made following pilot testing, based on feedback from end-users and stakeholders, are detailed to track iterative improvements.

• (3) Evaluation of Interventions: This involves extracting data on how interventions are evaluated for their effectiveness in managing CKD symptoms, using both qualitative and quantitative research methods. We noted specific outcomes measured, such as patient engagement, symptom relief, and health-related quality of life improvements. We coded data relevant to the evaluation phase, capturing information on trial designs, outcome measures used, and results of studies evaluating the effectiveness of interventions.

• (4) Implementation: We evaluated how and what factors may cause digital health interventions for CKD to be adopted and sustained in various healthcare settings. Data from included studies was extracted and organized into a tabulated form, noting study design, intervention details, and outcomes. Thematic Analysis was used to code in this review [43]. Themes were derived from the coded data, identifying common patterns and insights related to the development and efficacy of digital health interventions for CKD.

Result

Search result

We retrieved a total of 38,154 articles from the database. After removing duplicates, there were 18,006 remaining articles. Following a review of titles and abstracts, 17,926 irrelevant articles were excluded, leaving 4 articles without full text available and 76 articles requiring full-text review. After excluding articles that did not meet the inclusion criteria, 28 articles remained. The reference lists of these 28 articles were reviewed, resulting in the addition of 3 more references. Ultimately, we included 31 articles. Of the 31 included articles, 7 described the development process of interventions, 27 were validation of interventions, and 3 both described the development of interventions and reported on experimental results. The process of literature retrieval, screening, and evaluation is summarized in Fig.听1. Reference excluded for eligibility check (with reasons) could be found in the supplemental file.

Fig. 1

Flow chart for the literature screening

Characteristics of development studies

From Table听1, most interventions involved patient participation and expert guidance in their development process. Some also worked with specific patient communities to incorporate their values and needs. 6 studies [44,45,46,47,48,49] involved patients in the stakeholder input and evaluation process. 3 studies [44, 45, 48] included input from caregivers and family members. 4 studies [44, 46, 47, 50] involved multidisciplinary experts like clinicians, health providers, and policymakers to provide guidance.

Table 1 Characteristics of the development process

Most chronic kidney disease interventions underwent iterative cycles of refinement based on input from various stakeholders. 7 studies [44,45,46,47, 49, 50] refined the interventions based on feedback from stakeholders like patients, experts, nurses etc. This included modifications to content, features, graphics, and colours and correcting errors. 3 studies [44, 50] adapted the delivery methods of the interventions based on access needs and preferences. This included changing an in-person program to a teleconference and building an e-health tool. 1 study [45] highlights the importance of involving end-users in refining health interventions to enhance effectiveness and acceptance.

Only 5 studies use the program theory to devise or develop the intervention [44,45,46,47, 50]. Only 4 studies鈥� development processes are evidence-based [44, 47, 50, 51].

Characteristics of validation studies

Of the 27 validation studies, as indicated in Tables听2 and 9 studies are from the USA [45, 48, 50, 52,53,54,55,56,57]. 7 studies are from Iran [58,59,60,61,62,63,64]. 1 study each is from South Korea [65], Japan [51], the Netherlands [66], Poland [67], UK [68], Ireland [62] and United Arab Emirates [69]. Two studies are from the and China [70, 71]. 3 studies are from Australia [72,73,74].

Table 2 Characteristic of included studies of the validation process

Considering the purpose of the study, 13 studies are feasibility, acceptability or utility studies [45, 50,51,52,53, 55,56,57, 62, 66, 68, 72,73,74]. 14 studies are efficacy studies [48, 54, 58,59,60,61, 63,64,65, 67, 69,70,71].

22 studies focused specifically on hemodialysis patients [51,52,53, 55,56,57,58,59,60,61,62,63,64,65,66,67,68,69, 71,72,73,74], 2 studies focused on chronic kidney disease [45, 48], 2 on kidney transplant candidates [50, 54], and 1 on peritoneal dialysis [70].

The intervention could be categorized into 9 categories: (1) Telephone-based interventions (telenursing/telenursing): 8 studies [50, 54, 58, 61, 66, 68,69,70]. (2) Mobile health (mHealth) applications/interventions: 6 studies [51, 59, 60, 63, 64, 71]. (3) Virtual reality based interventions: 3 studies [52, 65, 67]. (4) Patient-reported outcome measures (PROMs/EPROMs): 3 studies [53, 72, 74]. (5) Text-message-based: 3 studies [45, 48, 73]. (6) website-based: 2 studies [55, 56]. (7) online internet-based platform: 1 study [57]. (8) wearable monitor study [62].

The study designs could be categorized into 6 categories: (1) randomized controlled trials: 11 studies [48, 50, 52, 54, 61, 63, 64, 67, 68, 70, 72], (2) quasi-experimental studies: 2 studies [58, 69]. (3) Observational studies: 3 studies [62, 66, 71]. (4) Pretest-posttest studies: 5 studies [45, 55, 56, 59, 60, 65]; (5) Mixed methods studies: 3 studies [45, 53, 57]; (6) qualitative studies: 3 studies [51, 73, 74].

The outcome measure could be divided into 6 categories: (1) Feasibility and acceptability outcomes: recruitment and retention rate [45, 52, 53, 55, 69, 72], completion time and rate [51, 53, 72], usability result [51, 56, 72], adherence rate [45, 52, 55, 69], barriers and enablers to uptake the system [74], and participants鈥� subjective rating [52, 55, 74]. (2) Clinical outcomes: physical fitness and body composition [65], dialysis weight [51, 62, 63], the occurrence of complications [70], and body mass index [48]. (3) Patient-reported outcome: quality of life [48, 50, 51, 54, 55, 57, 68, 70, 72], symptom burden [53, 58, 70, 72], specific symptom burden such as fatigue [54, 57, 65, 66], mood-related symptom [50, 52, 54, 57, 60, 61, 66,67,68], hyper/hypovolaemia symptoms [62], patient activation [48], medical adherence [48], sleep quality [50], social support [52, 66], self efficiency [59]. (4) Laboratory parameters: blood chemistry such as creatinine, potassium, and haemoglobin [48, 64, 70, 71]. (5) Dietary outcomes: Energy and protein intakes [69], adherence to fluid and dietary recommendations [55]. (6) other outcomes: cost-effectiveness [68], and health service utilization [70].

The limitations of the included studies mainly consist of limitations in study design, intervention measures, and implementation. See Table听3. In terms of study design limitations, 10 studies reported a small sample size, 5 studies reported a short follow-up period, 6 studies reported a lack of control groups, 1 study reported a high dropout rate and 13 studies reported insufficient sample representativeness. Regarding limitations in intervention measures, 1 study reported that the intervention was too general, lacking specificity and targeting, while 5 studies reported potential insufficiencies in the dosage (intervention intensity) and duration of the intervention. In terms of implementation, 4 studies reported low recruitment rates.

Table 3 Limitation of included studies

Barriers to implementation

We identified four types of barriers in the implementation process from published studies. The first type is participant and intervention-related barriers. Four studies indicated that participants lacked interest or motivation for digital interventions [45, 65, 68, 73]. Some research has found that intervention-related factors could also affect the implementation process; interventions that are too uniform, boring, or complex can burden participants, thereby affecting the implementation of the intervention [48, 52, 55, 60, 65, 72, 73]. Patients鈥� educational levels may also influence the implementation, as four studies showed that digital interventions are particularly sensitive to patients鈥� digital health literacy, with low levels of digital health literacy possibly hindering implementation [55, 57, 64, 68]. Participants鈥� physical conditions are also a significant factor; reasons such as aging, cognitive decline, decreased vision, or physical disabilities may impact the implementation of interventions [45, 50, 53, 65, 67, 68]. Five studies noted that the heterogeneity of the intervention population and environment might affect the generalizability and implementation of the intervention measures [48, 52, 57, 67, 70]. The second barrier comes from technical and resource factors, starting with the digital divide. Since digital interventions rely on the internet and digital devices, some studies found that participants might have difficulty accessing the internet or not own smart devices for interventions [50, 55, 57, 67, 71]. The complexity of digital interventions requires substantial resources, and some studies found that implementing digital health interventions could be challenging due to the need to develop specialized software or backend support from experts [55, 69, 73, 74]. Additionally, two studies mentioned privacy issues as a significant concern [50, 57]. The third factor is barriers related to professionals or organizational and systemic issues. First, there is skepticism and resistance from healthcare personnel towards digital interventions, with some not believing that such interventions can bring tangible benefits to patients [65, 72, 74]. Secondly, the shortage of healthcare personnel makes it difficult to handle the additional workload required for digital interventions [72]. Moreover, the intervention measures themselves might disrupt the healthcare personnel鈥檚 workflow, increasing their workload and burden for data collection or follow-up [53, 61, 62, 73]. The fourth barrier is economic, legal, and cultural barriers. Some studies found the costs associated with the intervention group to be too high [68], and some found conflicts between the intervention measures and local laws [72]. Culture is also a crucial factor, with research indicating that interventions might be difficult to implement if they do not consider the local cultural context [48, 70].

Discussion

In this scoping review, we comprehensively explored the development and validation of digital health interventions to manage symptoms in patients with Chronic Kidney Disease (CKD). Our findings delineated a multifaceted landscape where these interventions have a significant impact on various aspects of patient care.

Firstly, patient engagement has emerged as a critical outcome. Digital interventions, by their inherent accessibility and user-friendliness, have facilitated better engagement of patients in their care. This aligns with findings from [75], which demonstrated an increase in self-management behaviours among CKD patients. The interactive nature of these applications, including features like symptom tracking and feedback mechanisms, has empowered patients to take an active role in managing their condition. Secondly, the quality of life for CKD patients has been another focal point. Our review found that well-designed digital interventions could potentially alleviate some of the burdens associated with CKD symptom management. This is particularly relevant considering the chronic nature of CKD, where long-term quality of life is a significant concern. However, the conclusion needs to be provided by systematic review and meta-analysis considering more randomization-controlled trials conducted in the future. Studies like [61, 65, 66] have shown that effective symptom management through digital means can lead to improved mental and physical well-being. Lastly, symptom reduction itself is a direct and measurable outcome of these digital interventions. By providing personalized and timely management options, these tools have shown promise in reducing the severity of CKD-related symptoms. This not only improves patient comfort but also potentially delays disease progression, as suggested by [48, 50, 74]. These findings highlight the transformative potential of digital health interventions in CKD care. By improving patient engagement, enhancing the quality of life, and effectively managing symptoms, these tools offer a new paradigm in the management of chronic diseases like CKD.

The practical implications of our findings in the realm of digital health interventions for CKD are manifold and significant. For healthcare providers, the integration of these digital tools into routine care emerges as a crucial strategy. This involves not just the adoption of technology but also a shift in the care paradigm to include digital monitoring and patient-reported outcomes as part of standard practice. Considering patient preferences and technological literacy is vital to ensure adherence and effectiveness, as diverse patient populations may have varying levels of comfort and access to technology.

This scoping review, using a deductive method based on the Medical Research Council鈥檚 complex intervention framework to categorize the previous studies concerning symptom management. By applying this framework, we have identified some gaps that need to be narrowed in the future. Considering the MRC framework consists of several core components and 4 main phases, we will discuss this in these dimensions.

In the core components, several areas have been identified with gaps that require improvement in the future. Stakeholder engagement is essential for prioritizing the research question. We are delighted to find all development studies have included the stakeholders. However, we want to point out that patients and audiences of the intervention target should be the key stakeholders [31]. Although these studies included reported stakeholder engagement, they did not report the reasons why they chose these stakeholders. In future studies, careful consideration of the appropriateness and method of identification is needed to be clearly reported. Secondly, the programme theory was omitted in some previous studies. Programme theory could describe in what condition could an intervention lead to its effects. It is a key method to understand the underlying mechanism of an intervention. Medical Research Council advised that the programme theory should be developed at the beginning of the research project and refined in successive phases [31]. Programme theory, if chosen appropriately, could reduce the key uncertainties in the complex intervention, such as the context which influences the implementation of e-health, or why the component combined together could generate the effect on the outcome of patients. Future studies should choose or develop appropriate programme theory to guide the development, trial and implementation of a complex intervention to reduce any uncertainties in the research project. The intervention refinement is also very significant in the whole complex intervention cycle. The intervention refinement could improve the feasibility and acceptability of an intervention. As proposed by the original MRC framework, the refinement of an intervention could be on the basis of data analysis or programme theory. However, the modification should be in acceptable boundaries and should state what reason could support the researcher do this. In our scoping review, 85.7% (7/8) studies mention the refinement process based on diverse sources such as advice from the expert [45, 46], target population [44,45,46], stakeholders [44], result of content validation index [49], or feedback / empirical data collected [47]. However, most studies did not clearly state whether it is within the reasonable scope of modification. In future studies, more details of the adaption process such as the basis, the modification process, and the rationale for modification should be considered in the initial stage of the study and reported in detail in the article. Economic evaluation should be considered as advised by the MRC framework [31]. In the scoping review, we only identify one study report the economic outcomes. Hudosn et al. assess the cost of each arm of the intervention, but due to the small sample size, the difference in the cost is not significant [68]. In the future, early engagement of economic expertise may help identify the cost and the benefits to make the decision for the policy maker.

In the four phases, we have identified several gaps that require improvement moving forward. Firstly, the implementation outcomes such as fidelity, satisfaction, and adoption needed to be considered in future studies. According to the process evaluation framework, the implementation process could impact the outcome of the intervention. The high adoption, wide reach, and high fidelity of e-health intervention could improve the value of effect size and effectiveness of a trial. Last but not least, the process evaluation was undermined in most of the studies, only two studies [45, 52] used the process evaluation to appraise or validate their theoretical hypothesis. As the process evaluation has been regarded as an essential part of designing and testing the complex intervention [76], a comprehensive and well-designed process evaluation should be considered and integrated into the study protocol before the research project begins.

To address the identified barriers in implementing digital health interventions, several strategies can be considered. First, participant and intervention-related barriers primarily stem from participants鈥� lack of interest, low digital literacy, and physical limitations, which can affect engagement. To mitigate these issues, digital interventions should be designed with user-friendly interfaces and personalized content to align better with participants鈥� interests and needs [77]. Simplifying intervention content and interfaces may reduce the cognitive and physical burden on users, thereby increasing engagement and adherence. Second, technical and resource barriers鈥攕uch as the digital divide and the complexity of digital tools鈥攑ose significant challenges. Bridging these gaps requires providing necessary digital infrastructure, especially in underserved areas, to ensure equitable access [78]. Additionally, collaborating with IT specialists to develop intuitive software with strong backend support can ease the implementation process and reduce technical difficulties [78]. Third, barriers related to professionals or organizational and systemic issues arise from healthcare providers鈥� skepticism and the additional workload digital interventions may impose. Addressing these issues involves training and educating healthcare staff on the benefits of digital health tools, which can foster acceptance [79, 80]. Integrating digital tools into existing workflows, or adjusting workloads where possible, can also help reduce disruption and make the adoption process smoother. Finally, economic, legal, and cultural barriers can restrict the feasibility and acceptance of digital interventions. Conducting cost-effectiveness analyses can help justify the investment by highlighting potential long-term benefits [81]. Moreover, aligning intervention strategies with local legal frameworks and cultural norms, potentially through community engagement, can improve both compliance and cultural relevance.

This scoping review could, to some extent, reveal the inequality of health resources. We found most of the development and validation studies were conducted in developed countries. However, for patients, particularly in remote or undeveloped countries or regions, these digital interventions can be transformative. They offer a means to overcome geographical and logistical barriers, providing consistent and personalized symptom management support [29, 82,83,84]. Cultivating a nephrologist is time-consuming, many developing countries reported the number of a nephrologists is insufficient [19]. This accessibility is crucial in enhancing the overall quality of care for CKD patients who might otherwise have limited access to specialized healthcare services. Policy-wise, the review underscores the necessity of developing guidelines to standardize digital health interventions. This standardization should aim to ensure the quality and efficacy of these tools, making them reliable components of CKD care. Policies should also address issues such as data security, privacy, and interoperability of digital health systems to facilitate their seamless integration into existing healthcare infrastructures [85]. Furthermore, our findings suggest a need for policy initiatives that support research and development in this field, along with the creation of reimbursement models for digital health interventions. This could encourage innovation while ensuring these tools are accessible and affordable for all CKD patients.

In essence, our review highlights a multi-dimensional approach involving healthcare providers, patients, and policymakers, all of whom play a pivotal role in the successful implementation of digital health interventions for CKD symptom management.

When comparing our findings with existing literature in the field, a few key areas of convergence and divergence emerge. Our review aligns with studies like [75], which emphasize the effectiveness of digital interventions in enhancing patient self-management in CKD. However, our review goes further, offering a detailed analysis of how these interventions are developed and validated, a perspective less explored in current literature. One notable divergence is in the area of intervention customization and patient adherence. While existing studies, such as those by [86, 87], highlight the potential of digital health interventions in improving clinical outcomes, our review sheds light on the complexities of ensuring consistent patient engagement. This includes challenges in maintaining long-term adherence, which have been less emphasized in previous studies. Another area where our review contributes new insights is in the integration of digital health interventions within the broader healthcare ecosystem for CKD patients. While the literature often focuses on the efficacy of individual digital tools, our review considers how these tools interact with existing healthcare practices and the implications for holistic care. Overall, our review enriches the existing body of literature by providing a more nuanced understanding of the complexities involved in the development and implementation of digital health interventions for CKD, highlighting areas that require further exploration and development.

Our scoping review, while comprehensive, acknowledges several limitations inherent in the current body of research on digital health interventions for CKD symptom management. One primary limitation is the significant variability in intervention types. This diversity, spanning from simple mobile applications to complex telehealth systems, poses challenges in drawing generalized conclusions about efficacy and usability. Another critical limitation is the differences in study methodologies. Many studies in this field employ varied research designs, sample sizes, and outcome measures, making it difficult to conduct direct comparisons or meta-analyses. This inconsistency in research design hinders the ability to develop a cohesive understanding of how digital interventions can be most effectively implemented in CKD care. Furthermore, there is a notable gap in long-term outcome data. Most studies focus on short-term outcomes, leaving questions about the sustainability and long-term effectiveness of these interventions. This lack of long-term data is a significant concern in CKD, a chronic condition where the long-term management of symptoms is crucial. Additionally, patient adherence and engagement over extended periods remain under-explored. While initial engagement with digital health interventions may be high, maintaining this engagement over time, particularly in a chronic disease context, is not well understood. Overall, these limitations highlight the need for more standardized, long-term, and comprehensive research in the field to fully understand and optimize the role of digital health interventions in CKD symptom management. Given the limitations and gaps identified in the current research, several recommendations for future research in digital health interventions for CKD symptom management are warranted:

There鈥檚 a critical need for long-term studies that evaluate the sustained impact of digital interventions on CKD symptom management. Such studies should not only assess immediate clinical outcomes but also explore long-term adherence, patient satisfaction, and quality of life. CKD affects patients differently, influenced by factors such as age, disease stage, and comorbid conditions. Future research should focus on specific subgroups of CKD patients to understand how digital interventions can be tailored to meet diverse needs. Research should also explore how digital interventions can be effectively integrated with traditional care models. This includes examining the roles of healthcare providers in supporting these interventions and understanding how digital tools can complement existing treatments. Investigating new technologies and their adaptation in the context of CKD care is essential. This includes exploring the potential of emerging technologies like artificial intelligence and machine learning in personalizing care and predicting symptom fluctuations. Future research should prioritize patient-centred design, assessing the usability and accessibility of digital interventions from the patient鈥檚 perspective. Understanding patient preferences, challenges, and barriers to technology use will be crucial in designing effective interventions. Studies should also include economic evaluations to assess the cost-effectiveness of digital interventions. This is vital for policymakers and healthcare providers in making informed decisions about the allocation of resources and reimbursement policies. These recommendations aim to address the current limitations and pave the way for more robust, effective, and patient-centric digital health interventions in CKD symptom management.

In conclusion, this scoping review illuminates the intricate landscape of digital health interventions in CKD symptom management, emphasizing their potential to transform patient care. The review not only highlights the current state of these interventions but also sheds light on the complexities involved in their development and validation. The findings underscore the need for more standardized, patient-centred approaches and the integration of these technologies into broader CKD care strategies. Looking forward, the research paves the way for future explorations that can further refine and enhance the effectiveness of digital health interventions in chronic disease management. This work stands as a testament to the evolving nature of healthcare delivery and the critical role of technology in shaping future patient care paradigms.