Abstract
Objective
To examine participant representation, engagement, and equity considerations in randomized controlled trials of digital health interventions for older adults living with heart failure, using the PROGRESS-Plus framework to assess reporting across key social determinants of health.
Methods
We conducted a scoping review following Joanna Briggs Institute methodology. Randomized controlled trials evaluating digital health interventions for older adults with heart failure were identified through systematic database searches. Data were extracted on participant characteristics, intervention features, engagement outcomes, and reporting across PROGRESS-Plus domains, including place of residence, race/ethnicity, occupation, gender/sex, religion, education, socioeconomic status, social capital, age, disability, sexual orientation, and health literacy.
Results
Fourteen studies (n = 5,959 participants) were included. Interventions commonly involved remote monitoring, telehealth, wearable devices, and web-based platforms. While overall engagement among enrolled older adults was generally high, reporting of equity-relevant characteristics was inconsistent. Race/ethnicity and education were variably reported, while socioeconomic status and rurality were often minimally described. Cognitive impairment was frequently an exclusion criterion, and digital literacy was rarely assessed using standardized measures. Sexual orientation and health literacy were not reported in any study. These gaps limit understanding of how digital health interventions reach and benefit socially and clinically diverse older adults.
Conclusions
Digital health interventions for older adults with heart failure demonstrate promising engagement but are characterized by limited and inconsistent reporting of equity-related factors. Greater attention to inclusive recruitment, standardized reporting across PROGRESS-Plus domains, and equity-informed intervention design is needed to ensure that digital innovations support diverse older adults living with heart failure.
Keywords
Introduction
Heart failure is one of the most prevalent chronic conditions among older adults and represents a major public health challenge due to its high rates of morbidity, frequent hospitalizations, and associated healthcare costs. 1 Effective management of heart failure requires ongoing monitoring, timely intervention, and active patient engagement in self-management behaviors, including adherence to complex medication regimens, daily symptom tracking, dietary and lifestyle modifications, and frequent communication with healthcare providers.2,3 Traditional models of care often rely on episodic in-person visits and reactive management, which may be insufficient to address the dynamic and complex needs of older adults living with heart failure.4,5 These limitations are further compounded by structural barriers, such as geographic distance from care centers, transportation challenges, and limitations in healthcare workforce availability, highlighting the need for innovative approaches to care delivery. 4
Digital health interventions, encompassing mobile health applications, wearable sensors, remote monitoring platforms, telehealth services, and interactive web-based programs, have emerged as promising strategies to address these challenges.6–8 By providing continuous, real-time feedback, personalized guidance, and remote connectivity with healthcare providers, digital health technologies can facilitate more proactive, patient-centered management of heart failure. 7 For instance, remote monitoring systems can detect early signs of decompensation, mobile applications can support medication adherence and symptom tracking, and telehealth platforms can facilitate timely provider interventions. 9 Beyond individual-level benefits, these digital health interventions also offer potential system-level advantages, including reduced hospital readmissions, improved care delivery efficiency, and enhanced capacity for longitudinal data collection to inform population health strategies and predictive analytics.10–12
Despite the promise of digital health interventions, their adoption and effectiveness are influenced by both participant characteristics and intervention design.13,14 Older adults are a heterogeneous population with considerable variation in age, cognitive function, digital literacy, socioeconomic status, sex and gender, racial or ethnic identity, and geographic location. 15 These factors can affect access to technology, comfort and proficiency in using digital tools, engagement with interventions, and ultimately, health outcomes. 16 Existing literature suggests that many digital health interventions fail to adequately consider these differences, which may contribute to the underrepresentation of certain subgroups, reduced usability, and inequities in intervention impact. 17 For example, older adults with limited digital literacy or cognitive impairment may struggle to navigate complex interfaces, while those in rural or low-resource settings may lack reliable access to internet-enabled devices. 18 Similarly, interventions that do not account for culturally relevant content or language preferences may be less engaging for racially or ethnically diverse populations. 19
In addition to participant characteristics, intervention design features, including technology type, delivery mode, frequency of interaction, level of personalization, and integration with routine clinical care, play a critical role in shaping engagement and effectiveness.20,21 Some interventions rely on passive monitoring (non-invasive), 22 whereas others require active participant input, which can differentially affect adherence. 23 Interventions delivered through multiple modalities, such as combining mobile applications with telehealth coaching or wearable sensors, may improve engagement by providing redundancy and flexibility. 24 Frequency of use and the intensity of feedback also influence whether older adults can sustain participation over time, highlighting the importance of user-centered design principles and iterative co-design processes in developing effective digital health solutions. 25
Given these considerations, there is a critical need to systematically examine how older adults are represented in research on digital health interventions for heart failure and to explore how intervention characteristics influence participation and engagement. While some reviews have examined the efficacy of digital health interventions for heart failure broadly, few have focused on the inclusion of diverse subgroups or explicitly addressed equity, accessibility, and usability concerns. Mapping this literature can illuminate gaps in representation, identify barriers to participation, and inform the design of interventions that are both effective and inclusive.
Methodology
This scoping review was carried out following the Joanna Briggs Institute (JBI) guidelines for scoping reviews, which provide a structured approach to mapping the breadth and nature of existing evidence. 26 The review was framed using the PROGRESS-Plus framework, which prioritizes examining interventions with attention to equity by considering factors that shape differences in health outcomes and opportunities among diverse populations. 27 PROGRESS-Plus is a widely used tool for examining social determinants of health across research studies. The domains include place of residence (e.g., urban, rural, or geographic location of participants), race/ethnicity (self-identified or reported population groupings), occupation (employment status or type of work), gender/sex (reported gender identity or biological sex), religion (religious affiliation where reported), education (highest level of formal education attained), socioeconomic status (income level, financial indicators, or area-level deprivation measures), social capital (social relationships, caregiver support, or community connectedness), age (age distribution or age-related subgroup reporting), disability (including cognitive or functional impairment), and the additional “Plus” factors of sexual orientation and health literacy.
The protocol was registered on the Open Science Framework (osf.io/2a7hz) and was published (Citation Blinded for Review). We report our methods and findings according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Scoping Review (PRISMA-ScR) checklist (see Appendix A).
Ethical approval was not required for this scoping review, as it did not involve human participants or the collection of primary data. At the host institution, research ethics board approval was also unnecessary for the involvement of patient and family partners, since they were considered members of the research team rather than study participants. Formal consent was not obtained, as their participation was implied through their application to serve as partners.
Review objective and questions
The primary objective of the review was to map the literature on digital health interventions designed for failure management in older adults and to evaluate how the representation of diverse subgroups was described. The review also sought to describe the characteristics of these interventions and examine whether specific features influenced participation among older adults. The main review question focused on identifying the participants represented in digital health interventions for older adults with heart failure. Secondary questions explored how subgroups of older adults, differentiated by age, cognitive function, socioeconomic position, sex or gender, racial or ethnic identity, and geographic location, were included, and what characteristics of the interventions, such as technology type, delivery mode, and frequency of use affected engagement.
Eligibility criteria
Studies were eligible for inclusion if they involved adults aged 50 years and older diagnosed with heart failure. Although 65 years is typically used to define older adulthood, a lower threshold of 50 was applied to account for health equity considerations and evidence of accelerated aging in marginalized populations (e.g., HIV, Indigenous populations, and members of racially or socioeconomically disadvantaged groups) (Citation Blinded for Review). 28 Eligible participants could reside in the community or in institutional or supportive care settings, provided the study specifically targeted heart failure management.
The review focused on interventions that utilized digital health technologies, defined as platforms or tools that employ computing and telecommunications to deliver, enhance, or monitor healthcare services. Eligible interventions included mobile health applications, wearable devices, online platforms, remote monitoring systems, telemedicine integrated with patient portals, and other digital solutions designed to provide interactive and personalized care for heart failure management. Interventions are typically aimed at supporting symptom monitoring, medication adherence, self-care education, virtual consultations, or real-time clinical monitoring.
Only studies conducted in high-income countries, as classified by the World Bank, were considered to ensure comparability in healthcare infrastructure, technology access, and intervention feasibility. 29 Eligible studies could be conducted in outpatient clinics, hospitals, rehabilitation centers, community programs, or home-based care settings. Studies from low- or middle-income countries were excluded due to significant differences in healthcare system capacity and digital infrastructure. The review also focused on how equity-related factors were reported, using the PROGRESS-Plus framework to assess whether studies considered characteristics such as place of residence, race or ethnicity, socioeconomic status, education, gender, and other relevant variables. 27
Only randomized controlled trials were included, as these study designs enabled rigorous evaluation of interventions and typically provided standardized reporting of participant characteristics, facilitating the assessment of equity-related variables. Eligible studies were peer-reviewed and published in English or capable of being translated into English using Google Translate. Studies reporting protocols, observational designs, quasi-experimental methods, qualitative-only findings, and conference abstracts were excluded.
Search strategy
A three-stage search strategy was used. 26 First, a preliminary search of MEDLINE (via PubMed) and CINAHL (via EBSCOhost) identified relevant studies, and keywords and index terms from these articles were analyzed to inform the development of a comprehensive search strategy. In the second stage, the full search was executed across MEDLINE, CINAHL, Embase, and Scopus, combining controlled vocabulary terms and free-text keywords related to digital health, heart failure, and older adults (See Appendix B). RCT filters were applied where appropriate. A medical librarian reviewed the search strategy to ensure completeness and accuracy. In the third stage, reference lists of included studies and relevant systematic reviews were screened to identify additional studies. Only peer-reviewed studies published between January 1, 2005, and May 12, 2025, were included, reflecting the rapid growth and clinical adoption of digital health technologies. All retrieved records were managed in Covidence for deduplication and screening. 30
Study selection
Before full screening, a pilot test was conducted to ensure consistent application of the inclusion and exclusion criteria. Two reviewers independently screened 25 randomly selected records, and the process was repeated until inter-rater reliability reached a Cohen’s kappa of 0.70 or higher. Discrepancies were discussed, and the criteria were refined as needed. Following the pilot, two reviewers independently screened all titles and abstracts, with studies deemed potentially eligible or unclear progressing to full-text review. Full texts were also independently reviewed by two reviewers, and disagreements were resolved through discussion or by consulting a third reviewer. Reasons for excluding studies at the full-text stage were documented, and the study selection process was summarized in a PRISMA-ScR flow diagram (Figure 1). Prisma Flow Diagram.
Data extraction
Data were independently extracted by two reviewers using a standardized form in Covidence, adapted from JBI methodology. The extraction tool incorporated PROGRESS-Plus domains to capture equity-relevant information, including participants’ age, sex or gender, race or ethnicity, socioeconomic status, education, digital literacy, language proficiency, comorbidities, cognitive or functional status, and other relevant characteristics. 27
Information about study design, setting, funding sources, recruitment strategies, and intervention features, including technology type, primary functions, delivery mode, duration, healthcare provider involvement, co-design elements, and efficacy, was also collected. Additionally, equity considerations were noted, such as whether the intervention was tailored to specific subgroups or included strategies to enhance digital inclusion, and whether outcomes were reported for different subgroups. Limitations and authors’ recommendations regarding equity were also extracted. The extraction form was piloted on a small subset of studies (n=2). Authors (n=2) were contacted when information was missing or unclear. A formal assessment of study quality or risk of bias was not conducted, as this was outside the scope of the review. As this study was a scoping review, a formal sex- and gender-based analysis was not performed, in accordance with JBI guidance for scoping reviews. 31
Data analysis and presentation
Data were analyzed using both quantitative and qualitative descriptive methods. Quantitative data, including publication year, study setting, sample characteristics, and intervention features, were summarized using frequencies and proportions. Qualitative data were synthesized using deductive coding guided by PROGRESS-Plus domains, including place of residence, race or ethnicity, occupation, gender or sex, religion, education, socioeconomic status, social capital, and additional factors such as age, disability, sexual orientation, and health literacy. 27 The synthesis identified patterns in representation, intervention design, and equity-related reporting, highlighted gaps in the literature, and provided insight into how digital health interventions may either mitigate or exacerbate disparities among older adults with heart failure.
Patient engagement strategy
An integrated knowledge translation approach was applied in this scoping review. 32 The time commitment for the public partner was 2 hours per month, as confirmed and agreed upon in advance. Although patient engagement has not traditionally been part of scoping review methodology, there has been growing recognition of the value of including patient input in literature reviews. 33 Recruitment was facilitated through pre-existing relationships with the research team. Partnership procedures were co-developed in accordance with the CIHR Patient Engagement Framework. 34
High-level meeting minutes captured decisions, so no identifying information about partners’ experiences was collected.
Results
Study characteristics.
Theme 1. Intervention characteristics and engagement
There was variation in the type of intervention and in the degree of involvement of healthcare professionals with participants. The majority of the studies (n=8, 57%) used some form of remote home monitoring.35,38,40–45 Four studies (28.5%) featured the use of an app-based intervention,36,38,40,46 two used the telephone (14%),39,47 one used a web-based platform (7%), 48 and one used a shared electronic health record (7%). 37 Four studies also used biometric monitoring as part of the intervention (28.5%).35,38,43,45 Interventions varied in the intensity and structure of participant–provider interaction. Some programs relied primarily on passive monitoring with automated feedback, while others incorporated scheduled communication, real-time alerts, or active clinical review by healthcare professionals. Overall, the included studies did not consistently report detailed metrics describing interaction frequency, duration, or qualitative aspects of engagement, limiting the ability to compare intervention “dose” across trials.
Nine of the studies (64%)35,38,39,41,42,45,47,48 included interventions that involved regular feedback and interaction between healthcare providers and participants. Some studies with limited engagement from healthcare providers also showed beneficial outcomes, including higher medication optimization rates 46 and high adherence rates. 44 One study found that a majority of participants felt they had improved access to healthcare providers through remote care. 46 We summarize the interventions in Table 1.
Theme 2. Participant demographic representation
Participant characteristics.
Intervention characteristics.
The majority of studies (n=11, 79%)35–42,44–46 did not report participants’ age range. Of the studies that did, the age range was wide, from 33 48 to 92. 47 Despite this diversity in range, the mean age (among studies that reported it) was clustered in the higher range, ranging from 63 to 80.36–45,47,48 Age did not appear to be a contributing factor to adherence or engagement across the sample. Multiple studies noted that, despite participants being older adults, they were capable of using the technology associated with the interventions35,40,45,48 and even reported high satisfaction with it.40,45,48
Only five studies (36%) reported participants’ socioeconomic indicators.35,38,39,43,47 Two studies38,39 reported on the employment status. The two studies used broad categories as “employees, freelancers, pensioners, homemakers, and others”.38,39
Four (28.5%) studies included information on the marital status of participants.35,38,39,43 Furthermore, in those studies, 46-66% of participants were married and/or living with a partner. Boyne et al. (2012) noted that participants in their study who cohabited with a partner derived greater benefits from the telemonitoring intervention. 43
Educational attainment was another socioeconomic indicator covered by four of the studies (28.5%).35,38,39,43 One study conducted in the United States explicitly noted that its findings on educational achievement were lower than the national average. 35 This did not appear to have an impact on adherence or engagement with the intervention. 35 Where reported, participants’ education ranged from less than high school to university or graduate degrees, with most samples skewed toward individuals with secondary or post-secondary education.35,38,39 In studies that reported both intervention and control groups, distributions were generally similar between groups. 43
The majority of studies (n=9, 64%) in this review did not report the racial or ethnic identity of their participants.36,38,42–48 In the studies that did report it,2,4,11,12,14 there were differences in the identities present, as well as the level of detail reported. Thirteen studies reported a majority of White participants and one reported a majority of African Americans. 39
Theme 3. Equity-relevant exclusion and underreported domains
Several equity-relevant domains were poorly reported across studies. Sexual orientation and health literacy were not reported in any included study, and disability status was rarely measured. Cognitive impairment was frequently used as an exclusion criterion. Over half of the studies (n=9, 64%) included in this review did not report participants’ cognitive status. The three studies that included cognitive status35,39,40 used different criteria, including the Callahan Cognitive Scale, the Mini-Mental State Examination (MMSE), and the St. Louis University Mental Status Score (SLUMS). Additionally, participants with cognitive impairment were excluded from the sample. One study, which examined medication adherence using an electronic pillbox, explained that the exclusion was due to the fact that those with severe cognitive impairment would not reasonably be expected to manage their medication. 40
Language requirements were rarely reported across the included studies. Of the 14 studies, 4 (29%) explicitly described participants’ language: two required participants to be English-speaking only,39,40 one required English as the primary language, 35 and one included only Swedish-speaking patients. 44 The remaining 10 studies (71%) did not report any information on participants’ language. Only five (36%) of the fourteen included studies provided details on the geographic location of the periods. Of those studies, three involved participants exclusively in urban areas and one had a high proportion of urban participants, ranging from 72.1% to 75.8% across groups. 4 One study focused on participants from rural settings. 12 None of the 14 included studies reported participants’ sexual orientation or health literacy. This represents a significant gap in understanding how these factors may influence engagement, access, and outcomes in virtual rehabilitation interventions for older adults.
Of the 14 included studies, 7 (50%) provided some information about participants’ digital literacy or access, though details were often minimal or implicit.36,38,39,48 To capture participants’ digital literacy, we extracted descriptions of participants’ ability to access or use technology (e.g., device ownership like a phone, 35 training, 43 or inclusion criteria related to digital skills38,39). When reported, we noted whether participants were required to have digital skills at baseline, received training or support, 43 or demonstrated mixed ability. In one study, participants demonstrated mixed levels of digital health access, with several requiring technical support to engage with the intervention. 36
Reporting of participants’ disability status was very limited. Of the 14 studies, only 1 (7%) provided data, reporting that approximately 47-49% of participants in intervention and control groups had a disability. 39
Theme 4. Clinical and comorbidity characteristics
Comorbidity burden was commonly reported using standardized indices, with participants generally presenting with multiple chronic conditions. 11 of 14 studies (79%) provided data on participants’ comorbid conditions. Comorbidities were commonly reported, though with varying detail across studies. The most frequently reported conditions among participants included hypertension,35,38,42,44,46,48 diabetes mellitus,35,44,46,48 COPD/asthma/lung disease,35,44,46,48 atrial fibrillation,37,42,44 chronic kidney disease, cardiovascular disease, and stroke.42,46 Other reported comorbidities included dyslipidemia, 46 hypothyroidism, 38 obstructive sleep apnea, 38 arthritis/rheumatic disease, 35 and cancer. 35 Several studies reported overall comorbidity burden using the Charlson Comorbidity Index or median number of conditions per participant, 39 with mean indices ranging from 3.2 to 3.4 and a median of ≥5 comorbid conditions per person. 41 Reporting often included separate percentages for intervention and control groups.
Recommendations from included studies for equity
Equity considerations.
Discussion
This scoping review examined how older adults are represented in research on digital health interventions for heart failure and how participant characteristics and intervention design influence engagement. We conducted a systematic search of four databases following the Joanna Briggs Institute methodology and used the PROGRESS-Plus framework to assess equity-related reporting across 14 randomized controlled trials. We focused on identifying who was included in these studies and how factors such as age, cognitive function, socioeconomic status, sex or gender, racial or ethnic identity, and geographic location were considered. Most studies underreported or inconsistently described these characteristics, particularly cognitive status, race or ethnicity, and socioeconomic background, which limited assessment of equity and generalizability. Despite this, older adults demonstrated good engagement and satisfaction with technology across interventions. However, the evidence base remains skewed toward urban, White, and male participants, underscoring the need for more inclusive research designs and standardized equity reporting in digital health trials for heart failure.
This review found that age did not appear to limit adherence or engagement, which challenges assumptions that older adults are less able or willing to adopt digital health interventions. This finding has been echoed in previous research, which also found that older adults are willing to adopt digital health interventions, particularly when they perceive them as useful, easy to use, and beneficial for their health. 49
Overall, our findings demonstrate persistent underrepresentation and inconsistent reporting of cognitive status, socioeconomic background, racial/ethnic identity, geographic location, digital literacy, and language across trials of digital health interventions for older adults with heart failure. Participants with cognitive impairment were frequently excluded from randomized trials, despite the high prevalence of cognitive decline in this population. For example, while only a few studies reported on cognitive status, those studies measured cognitive impairment to exclude individuals from randomized controlled trials, despite the high prevalence of cognitive decline among those living with heart failure. 50 Similarly, individuals from lower socioeconomic backgrounds, racial and ethnic minority groups, rural or remote regions, and those with limited education, digital literacy, or non-English language proficiency were rarely represented. These gaps have important implications for the generalizability and real-world applicability of digital health interventions, particularly in the context of heart failure self-management, which requires sustained monitoring, medication adherence, and timely symptom recognition. Language and literacy barriers may further limit comprehension of automated alerts, instructional content, and health data displays when interventions are developed primarily in English or at higher literacy levels. This omission has important implications for heart failure care, as patients with lower educational attainment or limited digital skills may struggle to navigate app-based platforms or interpret complex health data, leading to lower engagement and adherence. 51 Without intentional design adaptations, digital health technologies risk widening existing inequities by privileging populations with greater technological familiarity and resource access. Future digital heart failure programs should prioritize user-centered development, including multilingual and plain-language interfaces, caregiver-inclusive features, and iterative testing with diverse older adults. These recommendations are consistent with national and international calls for inclusive digital innovation articulated Canada’s Pan-Canadian Health Data Strategy 52 and the WHO’s Global Strategy on Digital Health (2020–2025), 53 both of which emphasize equitable access, accessibility, and population-level benefit in digital health implementation. These policies explicitly call for digital health solutions adaptable to varying levels of literacy, language, and access, recognizing that, without intentional inclusion, technology can exacerbate rather than reduce disparities in care.
The systematic exclusion of participants with cognitive impairment in several trials is particularly concerning in the context of heart failure care. Cognitive decline is highly prevalent among older adults living with heart failure and is associated with challenges in symptom recognition, medication adherence, and complex self-management behaviors. Excluding individuals with cognitive impairment may therefore limit the external validity of trial findings and restrict understanding of how digital health interventions perform in populations who may benefit most from supportive monitoring technologies. This pattern reflects a broader tendency in digital health research to prioritize participants perceived as technologically capable rather than those with greatest clinical vulnerability. Similarly, socioeconomic variables such as education level and marital status were reported inconsistently and often treated as descriptive characteristics rather than analytic factors linked to intervention accessibility or outcomes. Limited reporting of socioeconomic indicators constrains assessment of structural barriers that influence digital health adoption, including resource availability, caregiving support, and technology familiarity. From a health equity perspective, these gaps hinder evaluation of whether digital interventions align with goals of inclusive care for older adults with heart failure, where social and economic context plays a critical role in intervention feasibility and benefit distribution. Future trials should actively recruit participants who have been historically underrepresented, including individuals with cognitive impairment, lower socioeconomic status, racial and ethnic minorities, rural residents, and those with limited digital literacy or non-English language proficiency. Standardized reporting of these characteristics is necessary to assess generalizability, identify disparities in engagement or outcomes, and ensure interventions are accessible and effective across diverse populations. Without tailoring interventions to accommodate varying literacy and language needs, digital health tools risk widening existing disparities in outcomes, leaving those most vulnerable to hospitalization and a poor prognosis least able to benefit from available innovations. Digital heart failure programs integrating digital health tools should prioritize user testing with diverse older adults, offer multilingual and plain-language interfaces, and include training or caregiver support to bridge digital literacy gaps.
Our review found that some interventions still produced beneficial outcomes despite minimal direct engagement with healthcare providers, while others with regular provider interaction had mixed results. This suggests that the design and features of the digital intervention itself, such as modality, frequency, and personalization, may have a stronger influence on engagement and effectiveness than the degree of provider involvement. The implications of this finding are that well-designed digital interventions for heart failure can reduce reliance on intensive provider contact without compromising patient engagement or outcomes, potentially helping address workforce constraints and improving the scalability of care. For example, research on remote monitoring and app-based interventions has shown that features such as automated feedback, personalized alerts, and interactive symptom tracking can sustain adherence and self-management even when direct provider interaction is limited.54,55 Theoretically, this means health systems could deploy scalable digital programs that maintain patient engagement and optimize outcomes, while freeing provider time for patients who need more intensive support.
On the other hand, some existing self-management interventions have failed to achieve expected outcomes when the technology was overly complex, poorly integrated with daily routines, or insufficiently tailored to users’ health literacy or cognitive capacity. 56 Thus, clinically, the implication is that digital heart failure programs must prioritize careful co-design and usability testing, balancing automation with targeted provider support, to optimize both engagement and health outcomes. It also suggests that health systems should evaluate interventions not just on provider involvement but also on how the digital tool’s features align with patient needs, promoting scalable and effective models of care.
Limitations
This scoping review has several limitations that should be considered when interpreting the findings. First, the review was restricted to studies published in English and conducted in high-income countries. This may have excluded relevant research from low- and middle-income contexts, where digital health interventions face different infrastructural, cultural, and resource challenges. Consequently, the generalizability of findings is limited to settings with comparable healthcare systems and technological capacity. Second, only randomized controlled trials were included. While this decision strengthened the methodological rigor of the included evidence, it excluded qualitative and mixed-method studies that could have provided valuable insights into participant experiences, usability, and contextual barriers to engagement. Third, publication bias may also be present, as studies demonstrating positive or significant findings are more likely to be published than those reporting null or negative results. Similarly, as many included studies were conducted over a decade ago, the technologies used may not reflect current digital health capabilities, potentially underestimating the usability and accessibility of more recent innovations. Finally, as is typical of scoping reviews, this study did not include a formal assessment of methodological quality or risk of bias, nor did it attempt to evaluate intervention efficacy. The purpose was to map and describe the existing evidence base rather than to assess causal relationships. Future systematic reviews could build on these findings by incorporating quality appraisal, subgroup analyses, and meta-analytic approaches to evaluate how intervention design and participant characteristics influence outcomes in digital health for heart failure. In addition, the review was limited to studies published in English and conducted in high-income country contexts, which may introduce selection bias and restrict the generalizability of equity-related findings, particularly for populations in low- and middle-income settings where digital health access and reporting practices may differ.
Conclusion
This scoping review highlights both the potential and the current limitations of digital health interventions for older adults with heart failure. Overall, older adults demonstrated strong engagement and satisfaction with these technologies, challenging assumptions that age is a barrier to adoption. However, the evidence base is limited by underrepresentation of key subgroups, including individuals with cognitive impairment, lower socioeconomic status, racial and ethnic minorities, rural residents, and those with limited digital literacy or non-English language proficiency. Intervention design features, such as modality, frequency, personalization, and usability, appear to have a greater influence on engagement and outcomes than the degree of direct healthcare provider involvement, suggesting that well-designed digital programs can achieve meaningful impacts even with minimal provider contact. These findings underscore the importance of inclusive, user-centered design, multilingual and plain-language interfaces, and supportive strategies such as caregiver involvement or training to bridge digital literacy gaps. Clinically, adopting these principles can improve the scalability, accessibility, and effectiveness of digital heart failure programs, helping to reduce disparities in care and optimize self-management across diverse older adult populations. Future research should prioritize equity-focused recruitment, standardized reporting of participant characteristics, and rigorous evaluation of intervention features to ensure that digital health innovations benefit all older adults living with heart failure.
Supplemental material
Supplemental material - Digital health interventions for older adults with heart failure: A scoping review of participant representation, engagement, and equity considerations
Supplemental material for Digital health interventions for older adults with heart failure: A scoping review of participant representation, engagement, and equity considerations by Kristina M. Kokorelias, Peter M Hoang, Maira Khan, and Maurita T. Harris in Digital Health.
Supplemental material
Supplemental material - Digital health interventions for older adults with heart failure: A scoping review of participant representation, engagement, and equity considerations
Supplemental material for Digital health interventions for older adults with heart failure: A scoping review of participant representation, engagement, and equity considerations by Kristina M. Kokorelias, Peter M Hoang, Maira Khan, and Maurita T. Harris in Digital Health.
Footnotes
Funding
The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by a TRANSFORM HF Collaboration Starter Grant.
Declaration of conflicting interests
The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
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