https://orcid.org/0000-0001-6843-8568
Figures
Abstract
A method of overcoming barriers associated with implementing lifestyle interventions in CKD may be through the use of eHealth technologies. The aim of this review was to provide an up-to-date overview of the literature on this topic. Four bibliographical databases, two trial registers, and one database for conference proceedings were searched from inception to August 2023. Studies were eligible if they reported a lifestyle intervention using eHealth technologies. A narrative synthesis of the findings from the included studies structured around the type of eHealth intervention was presented. Where a sufficient number of studies overlapped in terms of the type of intervention and outcome measure these were brought together in a direction of effect plot. There were 54 included articles, of which 23 were randomised controlled trials (RCTs). The main component of the intervention for the included studies was mobile applications (n = 23), with the majority being in the dialysis population (n = 22). The majority of eHealth interventions were reported to be feasible and acceptable to participants. However, there was limited evidence that they were efficacious in improving clinical outcomes with the exception of blood pressure, intradialytic weight gain, potassium, and sodium. Although eHealth interventions appear acceptable and feasible to participants, there is insufficient evidence to make recommendations for specific interventions to be implemented into clinical care. Properly powered RCTs which not only demonstrate efficacy, but also address barriers to implementation are needed to enhance widespread adoption.
Citation: Curtis F, Burton JO, Butt A, Dhaliwal HK, Graham-Brown MM, Lightfoot CJ, et al. (2024) Lifestyle interventions delivered by eHealth in chronic kidney disease: A scoping review. PLoS ONE 19(1): e0297107. https://doi.org/10.1371/journal.pone.0297107
Editor: Henry H.L. Wu, Kolling Institute of Medical Research, The University of Sydney, AUSTRALIA
Received: September 11, 2023; Accepted: December 22, 2023; Published: January 24, 2024
Copyright: © 2024 Curtis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: All relevant data are within the manuscript and its Supporting Information files.
Funding: The author(s) received no specific funding for this work.
Competing interests: The authors have declared that no competing interests exist
Introduction
For individuals living with chronic kidney disease (CKD), having a healthy lifestyle (e.g. being physically active, consuming a healthy diet, and not smoking) can slow disease progression and reduce both cardiovascular risk and all-cause mortality [1–3]. For these reasons adopting a healthy lifestyle is recommended by clinical practice guidelines for this population [4–6]. These recommendations are supported by recent randomised controlled trial (RCT) data showing that a 36-month lifestyle intervention doubled the number of individuals with CKD who were able to meet physical activity guidelines [7]. Despite this evidence, there are no interventions to promote a healthy lifestyle embedded as part of normal clinical care for individuals living with CKD. Some of the challenges to implementing lifestyle interventions in clinical practice include their resource-intensive nature (and subsequent funding limitations) [7], issues around effectiveness, accessibility, feasibility with translating research findings into real world settings [8], and the lack of cost-effective analyses [9]. Furthermore, CKD is more common in older age, and is associated with multiple long-term conditions [10], and low levels of health literacy [11], which further complicates the implementation process. Further research is still needed with particular focus on how to translate lifestyle interventions of proven efficacy into clinical practice in a sustainable way.
One innovative method of delivering healthy lifestyle interventions that may overcome the identified barriers to implementation [8] is through technology-based electronic health (eHealth) interventions defined as “health services and information delivered or enhanced through the internet and related technologies” [12]. Lifestyle interventions containing a number of components may be more suited to delivery through eHealth particularly for those individuals with early stages CKD where promoting behaviour change may have a positive impact on disease progression and outcome [3]. A Cochrane review from 2019 [13] reported that eHealth interventions aiming to promote behaviour change in CKD may improve the management of dietary sodium intake and fluid management. The overall findings were limited due to the heterogeneity and low quality of available evidence. However, participants did report high levels of satisfaction due to the eHealth interventions being informative, of low burden, and easy to use [13]. There is a growing interest in the use eHealth and digital technologies for the delivery of healthcare in CKD, particularly following the rise of digital healthcare utilisation during COVID-19, and thus an up-to-date scope of the evidence in this population is required [14, 15].
The research aims of this review were to:
- Identify the mode of eHealth interventions that have been employed to deliver lifestyle interventions in the CKD population within the existing literature.
- Provide a summary overview of the effect of these interventions on a range of outcomes as reported in the primary studies.
Materials and methods
A scoping review was chosen as there has been a growth in eHealth interventions since the COVID-19 pandemic, therefore we wished to provide an overview from the existing literature on the mode and effect of delivery of these technologies in the lifestyle context within the CKD population. We followed the preferred reporting items for systematic reviews and meta-analyses extension for scoping reviews (PRISMA-ScR) checklist [16] (S1 Checklist) and the Arksey & O’Malley [17] framework for conducting this review. This review was prospectively registered on Figshare: https://figshare.com/articles/preprint/EHealth_and_Lifestyle_Review_Protocol_v1_1_16122022/21842958. With the last protocol update on the 16th of December 2022.
Inclusion criteria
Studies were eligible if they reported a lifestyle intervention using eHealth technologies. eHealth technologies include: mobile applications, computer and tablet based applications, personal digital assistants, web-based/internet applications, virtual reality tools and other eHealth technologies as defined by the CONSORT eHealth Group [18].
More specifically, the inclusion criteria were:
- Participants: Individuals (including paediatric) with all stages of CKD (including those with end-stage kidney disease (ESKD) receiving kidney replacement therapy). We included those individuals with an episode of acute kidney injury (AKI).
- Concept: The review considered studies that include any combined lifestyle intervention (e.g. physical activity or exercise, dietary (including modifying sodium and protein intake), weight loss and reducing alcohol intake) or lifestyle component delivered alone (e.g. physical activity only) via eHealth in the CKD.
- Setting: Lifestyle eHealth interventions could be delivered in a number of settings including primary care, clinics, haemodialysis units or rehabilitation services.
- Types of study: This scoping review considered the following study design (but not limited to): interventional studies (randomised and non-randomised controlled trials, quasi-randomised studies), observational studies (e.g. cohort and cross-sectional studies), qualitative studies, and process evaluations relating to eHealth interventions. Published protocols of studies and conference abstracts were included. Studies that included individuals with CKD and caregivers or family members were excluded.
Search strategy
The following bibliographical databases and trial registers were searched for completed and ongoing studies: MEDLINE, EMBASE, CINAHL, Cochrane Central Register of Controlled Trials (CENTRAL); trials only, ClinicalTrials.gov, and the World Health Organisation International Clinical Trials Registry Platform. Conference Proceedings Citation Index (Web of Science™ Core Collection) were searched for unpublished data. All databases were searched from inception to 2nd August 2023, with no limits on language set. Database searches were supplemented with a Google Scholar search with the first 200 titles screened for inclusion [19]. An example of a full search strategy for MEDLINE is presented in S1 File.
Study selection and data charting
Search results were compiled using the web-based screening and data extraction tool Covidence (Veritas Health Innovation Ltd., Melbourne, Australia). Duplicate records were removed and a two-part study selection process was used: (first part) title and abstracts were screened independently by two reviewers against the inclusion criteria, and (second part) full-text articles not excluded based on title or abstracts were retrieved and assessed by two reviewers. If there was a disagreement then this was resolved through the inclusion of a third reviewer.
Data extraction and synthesis
We developed, tested, and refined a structured data collection form based on the Cochrane Data Extraction Template for interventions but with modifications for non-interventional studies. One reviewer undertook data extraction for each study, with a second reviewer (DSM) cross checking all extracted data. For each included study, characteristics including study design, CKD population, sample size, lifestyle component, type of eHealth intervention, and main outcomes were extracted and presented in table format. As were the eHealth intervention description, type of comparison, length of follow-up and main findings.
We created a narrative synthesis of the findings from included studies structured around the type of eHealth intervention reported (e.g. mobile applications, short message service (SMS), videoconferencing/online videos, virtual reality exercise (VREx), and web-based platforms)). Data were presented as text, tables, and where a sufficient number of studies overlapped in terms of type of eHealth intervention, and outcome measure, then we brought these together visually in a direction of effect plot [20, 21]. For the direction of effect plots the direction and magnitude of (clinically meaningful) change along with the statistical significance from within each study were considered to indicate either a positive health effect, negative health effect, or no effect [20].
Quality assessment
Whilst quality assessment of the included studies is not an essential component of a scoping review, we chose to include it because we felt that it would add value, potentially providing the basis for recommendations for future research with regard to the design, conduct and reporting. We quality assessed full-text articles of studies (n = 37) with the exception of conference abstracts, developmental studies and process evaluations. The National Institutes of Health (NIH) Quality Assessment Tool for Controlled Intervention Studies was used to assess the quality of each included study (available from https://www.nhlbi.nih.gov/health-topics/study-quality-assessment-tools). Please see S1 Table for the criteria used to assess the quality of the included studies. Two reviewers evaluated the quality of the included studies independently. Overall quality rating was rated as poor (0–4 as “yes”), fair (5–10 as “yes”), or good (11–14 as “yes”) for the controlled intervention studies (RCTs), and the non-RCTs) [22]. If there was a “fatal flaw” defined as high dropout rates (question 7), high differential dropout rates (question 8), no intention to treat analysis (question 14) then it was downgraded a category (regardless of overall score). The overall rating for the cohort and cross-sectional was scored in the same way as the controlled intervention studies (with no “fatal flaw” questions). The uncontrolled before-after studies were rated as poor (0–4 as “yes”), fair (5–8 as “yes”), or good (9–12 as “yes”), a “fatal flaw” was defined as not sufficiently large sample size (question 5), or >20% loss to follow-up (question 9).
Results
Fig 1 provides a flow diagram of article identification and inclusion. There was one study in Korean [23], which contributed only limited information [24] (S2 Table). Seven trial registrations were excluded from the narrative synthesis as they did not contain enough information (S2 Table). Two articles [25, 26] reported the same study but in different journals, and a further trial was published as two reports in the same journal [27, 28]. This left 54 individual articles (52 separate studies). (Fig 1).
Characteristics of included reports
Of the 54 articles, there were 23 RCTs (one reported as a conference abstract). Intervention duration ranged from 4 to 52 weeks, and included 1,682 randomised participants. There was 15 non-randomised studies (one study was reported twice [25, 26]) (this included eight uncontrolled before-after studies, four non-RCTs, two cohort studies and one cross-sectional study), four process evaluations (plus a further evaluation [28] of an included RCT [27]) and two developmental studies [29, 30] (Table 1). Lastly, there were eight protocol publications of RCTs in progress [31–38] (S3 Table). The eHealth component for 22 of these primarily involved mobile applications, seven involved web-based platforms, six involved SMS messages, six included videoconferencing or online videos, five included VREx, three included wearables, one was web-based messaging, and the remaining two involved a personal digital assistant (PDA), and tablet-based application (Tables 2 and S3). There were 22 studies/evaluations in the dialysis population, 18 in the CKD stages 1–5 population and a further nine in transplant recipients (including one in the paediatric population). In addition, there were two in the CKD and ESKD population, and one in individuals with either CKD or ESKD (dialysis and transplant) (Tables 1 and S3). There were no studies in the AKI population. Twenty-two studies/evaluations involved lifestyle (including dietary and physical activity) interventions, with a further 15 including physical activity and dietary interventions respectively (Tables 1, 2 and S3).
Quality rating for the included RCTs
Quality rating summaries are provided in Figs 2–4. Four of the included RCTs & non-RCTs were rated as “good” quality with the remaining rated as either “fair” or “poor” (Fig 2). All the uncontrolled before-after studies, cohort and cross-sectional studies were rated as either “fair” or “poor” (Figs 3 and 4).
Overall quality rating was rated as poor (0–4 as “yes”), fair (5–10 as “yes”), as good (11–14 as “yes”). A “fatal flaw” defined as “no” for questions 7, 8, or 14 resulted in the study being downgraded a category (regardless of overall score).
Overall rating was rated as poor (0–4 as “yes”), fair (5–8 as “yes”), as good (9–12 as “yes”). A “fatal flaw” was defined as “no” for either questions 5 or 9.
Overall quality rating was rated as poor (0–4 as “yes”), fair (5–10 as “yes”), as good (11–14 as “yes”).
Mobile applications
There were eight RCTs [43, 47, 49, 51–54, 56], nine non-randomised study designs [25, 26, 40–42, 44, 45, 48, 50, 55] and two process evaluations [39, 46] of dietary or lifestyle interventions primarily delivered by mobile applications on a range of outcomes (Table 1). There were six reports of feasibility/usability [26, 42, 44, 48, 49, 52], five for self-efficacy [40, 43, 47, 49, 56] and acceptability [42, 44, 49, 52, 56], and four for health related quality of life (HRQoL) [42, 43, 47, 48], with positive effects generally reported for these outcomes (Table 3). Similarly, there were three reports on knowledge [25, 40, 53], two for self-management [43, 48] and one for disease knowledge [55] with positive effects reported on these outcomes (Table 3). Seven reported serum phosphorus [25, 42, 47, 48, 52–54], one serum phosphate [40], two urine phosphorus [50, 51], and another dietary phosphorus intake [56] (Table 1). With most reporting no change (Table 4). Five reported serum albumin [26, 40, 47, 52, 53], with another reporting urine albumin [50], there was no effect on this outcome (Table 4). There were five reports of serum potassium [26, 42, 47, 48, 54], one for dietary potassium intake [56], and one for urine potassium [50] with the majority reporting a positive effect (Table 4). For sodium there were either no change or positive effects reported [26, 50, 51, 56] (Table 4). Majority of reports were of no change for body mass [26, 43, 50, 51], circulating lipids [43, 51, 54], and energy and protein intake [25, 50, 53, 56]. With positive effects reported for blood pressure [49–51] and no change or positive effects reported for intradialytic weight gain [42, 48, 54, 56]. (Table 4). There were two reports for serum calcium [48, 53] and parathyroid hormone [48, 53], with reports of positive effects on serum calcium [53]. A retrospective cohort analysis showed an improvement in their composite outcome of decline in eGFR and incidence of ESKD following the use of a lifestyle application [45]. See Table 2 for the findings from the mobile application process evaluations [39, 46].
Short-messaging service (SMS)
Three trials [27, 58, 60] reported that the SMS intervention was feasible and acceptable, with one [27] reporting a positive effect on HRQoL (Table 5). There was no effect found for diet quality [27, 60], and mixed effects for adherence to renal dietary recommendations [57, 60] (Table 5). Two [57, 60] out of three [27, 57, 60] trials reported a positive effect on serum phosphate (Table 6). Overall the effect of the intervention on blood pressure [27, 60], body mass [27, 61], serum albumin [57, 60], serum bicarbonate [27, 60] and serum potassium [27, 57, 60] was unclear (Table 6). Two trials [57, 60] reported an improvement in medication including adherence [57], and decreases in phosphate binders [60], whilst another no difference in anti-hypertensives [27] (Table 6).
Videoconferencing/online videos
Two studies employed video technologies to deliver health coaching [62] or supervised exercise [78], they were found to be feasible and acceptable [62], and they improved some outcomes such as HRQoL [62] and six-minute walking distance [78]. Process evaluations have also shown that video technologies are implementable [63, 64] (Table 1).
Virtual reality exercise
Three RCTs [66, 67, 69] and two non-RCTs [65, 68] investigated the effect of VREx on a range of outcomes (Table 1). Two trials reported gait speed [66, 67], with one reporting no effect compared to usual care [66], and another reporting increases in both virtual reality and standard intradialytic training groups [67]. The aforementioned trial [67] also reported similar findings for the STS-10 and STS-60 with improvement following VREx, although not compared to a standard intradialytic exercise group. There were positive effects reported for physical activity [66, 68], but there appeared no effect for depressive symptoms [66, 67].
Web-based platforms
There were two RCTs [70, 72], and one un-controlled before-after study [71] which investigated the effect of web-based platform, where participants completed sessions aimed at delivering either lifestyle [70, 71] or dietary [72] content. The dietary trial [72] involved a 3-month web-based self-management programme dedicated to sodium restriction, they found that urinary sodium excretion decreased (compared to baseline) following a 9-month follow-up [72]. The lifestyle interventions investigated the effect of web-based education platform for 8 [71] and 12-weeks [70], the trials independently reported positive effects on body mass and physical function [70], and were understandable and acceptable to participants [71]. These findings around the acceptability of these interventions are congruent with the findings of two developmental and qualitative studies [29, 30].
Other eHealth interventions
An RCT [73] investigated the effect of a wearable on physical activity levels, they reported that the intervention was feasible, although steps per day decreased in the intervention group, the minutes of moderate to vigorous physical activity increased. There appeared to be no effect on HRQoL and mental health measures during the study [73]. A similar study [75] found a wearable activity tracker was feasible and acceptable in encouraging physical activity in older transplant recipients. A study that employed a web-based tablet application to deliver and record a 12-week physical activity programme was found to be feasible [77]. Two RCTs aimed at assessing dietary interventions delivered by telegram messages [74], and through a PDA [76], were shown to improve HRQoL [74], and be acceptable and feasible to participants [76].
Discussion
This is the first review that has aimed to scope the available literature to understand the type of eHealth interventions that have been employed to deliver lifestyle interventions in the CKD population. The majority were mobile applications which included both dietary and physical activity components. There was also a number of interventions that used SMS messages, videoconferencing, virtual reality and web-based platforms to deliver lifestyle interventions. There was considerable heterogeneity with regards to the study outcomes reported. These eHealth interventions appeared acceptable and feasible to participants with some tentative evidence that mobile applications may have an effect on blood pressure, intradialytic weight gain, potassium and sodium, although these effects were not observed in all included reports and are therefore far from definitive. Moreover, the aim of the current review was to scope the literature rather than prove efficacy. We assessed the quality of the included RCTs, allocation concealment, blinding (of participants, providers and outcome assessment), the reporting of adherence, and the avoidance of other interventions were noted as common concerns across studies and should be addressed in the design and conduct of future studies. This resulted in many of the included studies in the current review being rated as poor quality.
Similarly to this review (and another recent review in the diabetes population [79]), the previous Cochrane review assessing the effect of eHealth interventions in the CKD population reported the majority of included studies were mobile or tablet applications alongside electronic monitoring and were acceptable to participants [13]. They reported that eHealth interventions may improve the management of dietary sodium intake and fluid management [13] which aligns with our findings. In agreement with our review, they found poor methodological quality of the included studies which limited the translation of the findings [13]. Another systematic review investigated the effect of nutritional mobile applications on a range of outcomes in the CKD population [80]. They reported that mobile applications have the potential to help improve adherence to dietary restrictions pertaining to sodium, potassium, phosphorus, protein, calories and fluid within CKD [80], in like manner to our review. However, they only included two RCTs in the review [80], the present review included eight RCTs [43, 47, 49, 51–54, 56] assessing dietary or lifestyle mobile applications reporting outcomes such phosphorus, potassium and sodium, and found some improvement in these outcomes. Assessing the effect of dietary mobile applications on circulating clinical markers such as those aforementioned may be an area for an updated systematic review (and meta-analysis).
The majority of the included e-Health interventions in our review were in the ESKD (dialysis and transplant recipient) population. There should be further investigation of these interventions in early stages CKD, as the modifications of lifestyle factors is one of the cornerstones of disease management, and may positively impact disease progression and outcomes. Lifestyle interventions being delivered by e-Health may also have to be tailored for these different CKD populations, for example dietary protein recommendations vary dependent on CKD stage [4]. Physical activity and/or exercise components may also be required to be adapted based on CKD stage to ensure that there are options for all individuals to become active.
Given the association between increased physical activity levels and mortality in the CKD population [81], there were only five studies which examined this outcome [41, 62, 66, 68, 73]. The previous review from 2019 did not include any studies reporting physical activity as an outcome [13]. Given that the CKD population is largely sedentary and changing behaviour is a major barrier to individuals becoming more active, future trials should endeavour to test new digital technology and eHealth interventions aimed at increasing activity levels. The present review included a number of studies of VREx. For many of the reported outcomes VREx was effective, although not superior to standard (intradialytic) exercise programmes. Standard exercise programmes may not be the most appropriate option to engage all individuals with CKD in physical activity, and therefore there may be some individuals who would benefit from VREx, although further testing is required.
The preponderance of studies demonstrated that such technologies are feasible and acceptable to participants. Future work should aim to test the efficacy of these interventions on relevant outcomes in appropriately designed and powered RCTs. The co-development and design of these interventions should occur alongside participants and key-stakeholders [15]. Moreover, these trials should include implementation work or pragmatic and adaptive designs that take into account feasibility, as the widespread uptake of eHealth interventions is currently limited [15]. That said, there were two included protocol publications [35, 36] for appropriately powered RCTs investigating the effect and engagement of web-based self-management platforms, they were co-designed with relevant stakeholders so that they can be embedded as part of usual clinical care should they prove efficacious. There was no cost-effectiveness analysis included in the current review, although eHealth interventions may have the potential to reduce cost in the long-term they will undoubtedly require upfront investment. Resultantly cost-analysis alongside efficacy work will be crucial and may increase the chances of widespread adoption.
Many of the eHealth interventions did not include participant information regarding the socioeconomic background and health literacy levels, these individuals have the worse health outcomes and are the least likely to access and benefit from eHealth interventions. Future eHealth research should investigate ways to engage these individuals. There was heterogeneity in the intervention components of the included studies and a large number of outcomes reported in the included studies which limited our narrative synthesis. Future research should report the core (minimum) outcomes as outlined by the SONG collaboration [82]. Lack of, and poor reporting of allocation concealment, blinding and adherence was a common theme in the included quality assessment. Some of the deficiencies in reporting could be addressed by following the CONSORT statement [83].
Conclusion
The use of eHealth interventions will only grow and there is likely be a move towards new technologies (such as artificial intelligence and virtual reality). However, currently there is insufficient evidence to make recommendations for specific lifestyle eHealth interventions to be implemented into clinical care in the CKD populations. Properly powered RCTs which not only demonstrate efficacy, but also address barriers to implementation are needed to enhance widespread adoption.
Supporting information
S1 Table. Criteria used to assess the quality of the included studies.
https://doi.org/10.1371/journal.pone.0297107.s003
(DOCX)
S2 Table. Relevant study and trial registrations excluded from synthesis.
https://doi.org/10.1371/journal.pone.0297107.s004
(DOCX)
Acknowledgments
We thank Selina T. Lock (University of Leicester Library) for her advice with the database searching.
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