Participants.

This scoping review will include studies that focus on older adults (aged 50 years and older) diagnosed with heart failure. Although the conventional threshold for older adulthood is 65 years, the decision to include individuals starting at age 50 is informed by health equity considerations and evidence of accelerated aging in certain marginalized populations [24]. Several groups, including individuals experiencing homelessness [25], those living with HIV [26], Indigenous populations [27], and racialized and socioeconomically disadvantaged communities [28], often experience premature onset of age-related comorbidities, including cardiovascular disease and heart failure. Participants may be community-dwelling or reside in institutional or supportive care environments, provided they are involved in an intervention specifically targeting heart failure management.

Concept.

The core concept of this review is digital health technology, defined as the use of digital platforms or tools that leverage computing and telecommunications to deliver, enhance, or monitor healthcare services [29]. For the purpose of this review, digital health interventions refer to technologies that support the delivery, management, or self-management of heart failure using digital platforms. This includes patient-facing tools that enable communication, monitoring, or data exchange between patients and healthcare providers. Digital health interventions may also include, but are not limited to, mobile health (mHealth) applications, wearable devices, web-based platforms, remote monitoring systems, telemedicine integrated with patient portals, and other digital tools that provide data-driven, interactive, and personalized care for heart failure management [29]. These technologies are typically used to support symptom tracking, medication adherence, self-care education, virtual consultations, or real-time clinical monitoring [30]. Examples include:

• Telemonitoring platforms or mobile applications that allow patients to report symptoms or biometric data (e.g., blood pressure, weight) for clinician review
• Self-management or adherence tools, such as smartphone apps or web-based programs designed to support medication adherence, physical activity, or lifestyle changes
• Remote consultation or communication tools, such as video visits or secure messaging systems

Interventions that are solely provider-facing (e.g., clinical decision support systems without patient interaction) or that do not use a digital interface are excluded.

Context.

The context for this review is limited to high-income countries, as classified by the World Bank [31]. We acknowledge that limiting to HICs does not guarantee uniformity in healthcare infrastructure, digital maturity, broadband access, or technology availability. However, this criterion provides a manageable scope for the review and focuses on settings where digital health interventions are more likely to be implemented, studied, and reported in the literature. Included studies may take place in diverse healthcare environments, such as outpatient clinics, home settings, hospital transitional care, rehabilitation centers, or community-based programs, provided they report on outcomes of digital health interventions for older adults with heart failure. Studies conducted in low- or middle-income countries are excluded to avoid additional heterogeneity introduced by substantially different healthcare systems and digital infrastructure.

In addition to capturing information about intervention design and outcomes, this review will pay particular attention to how equity-related factors are reported, using the PROGRESS-Plus framework to assess whether and how participant characteristics such as place of residence, race/ethnicity, socioeconomic status, education level, gender, or other relevant variables are considered. This approach is central to understanding the breadth of digital health interventions available for older adults with heart failure and the inclusivity and applicability of these interventions across diverse populations.

Types of sources.

Only randomized controlled trials (RCTs) will be included in this scoping review to manage the scope of the literature and allow for the synthesis of interventions that have undergone rigorous evaluation [32]. RCTs also often provide standardized reporting of participant characteristics, making them well-suited for examining how equity-related variables, such as age, sex/gender, race/ethnicity, socioeconomic status, and cognitive status, are represented and considered in digital health interventions [33]. While we acknowledge that observational and qualitative studies may offer insights into user experiences and contextual factors, these study designs are outside the scope of this review, which aims to synthesize evidence on interventions with established efficacy. We will include peer-reviewed publications written in English or that can be translated into English using Google Translate [34]. Studies that report protocols, observational research, quasi-experimental designs, or qualitative-only findings will be excluded. Conference abstracts and theses will also be excluded.

Search strategy.

A three-step search strategy will be utilized in accordance with the JBI methodology for scoping reviews. First, an initial limited search of MEDLINE (via PubMed) and CINAHL (via EBSCOhost) was conducted to identify relevant articles related to digital health interventions in the management of heart failure among older adults. The keywords and index terms used in the titles and abstracts of identified articles were analyzed to inform the development of a comprehensive search strategy. This strategy was iteratively refined and adapted for use across all selected databases.

In the second step, a full electronic search strategy will be implemented across the following databases: MEDLINE (PubMed), CINAHL (EBSCOhost), Embase (Elsevier), and Scopus (Elsevier). The search strategy will include a combination of controlled vocabulary terms (e.g., MeSH, Emtree) and free-text terms related to digital health interventions, heart failure, and older adults. Filters for randomized controlled trials will be applied where appropriate. The final search strategies for each database, including all identified keywords and index terms, will be presented in the final publication. A sample of keywords is presented in Table 1. The strategy will be reviewed by a medical librarian with expertise in systematic searching to ensure completeness and accuracy.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 1. Keywords.

https://doi.org/10.1371/journal.pone.0337990.t001

The third step will involve hand-searching the reference lists of all included studies to identify any additional relevant publications. References from systematic reviews on similar topics will also be screened to identify studies not captured in the database searches. No automated tools will be used to identify additional articles beyond database and reference list screening.

Only peer-reviewed primary studies published between January 1, 2005, and the present will be included. This 20-year time frame reflects the accelerated growth and relevance of digital health technologies in clinical practice, particularly following major mobile, internet-based, and wearable developments. Earlier studies are unlikely to reflect current digital infrastructure, patient usage patterns, or intervention designs and were therefore excluded.

All retrieved records will be uploaded to a reference management software (i.e., Covidence for duplicate removal and screening [35].

Study/Source of evidence selection.

Before full screening begins, a pilot screening process will be conducted to ensure consistent application of the inclusion and exclusion criteria. The review team will screen a random sample of at least 25 records independently. This pilot will be repeated iteratively until inter-rater agreement reaches a Cohen’s kappa statistic of >0.70, indicating sufficient reliability among screeners [36]. During the pilot phase, discrepancies will be discussed, and the screening criteria may be refined for clarity and consistency. Once this threshold is achieved, the remaining citations will be screened.

Following the pilot, two reviewers will independently perform title and abstract screening. Any citations deemed potentially eligible or unclear will proceed to full-text review. Full-text articles will also be screened independently by two reviewers. Disagreements at any stage will be resolved through discussion or by consulting a third reviewer if consensus cannot be reached.

Reasons for exclusion of full-text articles that do not meet the inclusion criteria will be documented. The study selection process will be summarized in a PRISMA-ScR flow diagram, detailing the number of studies screened, assessed, included, and excluded, along with justifications for exclusions [37].

Data extraction.

Data will be extracted from papers included in the scoping review by two independent reviewers using a data extraction tool on Covidence. Two reviewers will extract data independently using a standardized and piloted data extraction form (See Sample in Supplemental Material 2). The form will be developed based on JBI methodology and adapted to capture equity considerations through the PROGRESS-Plus framework, which includes: Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, as well as additional factors such as age, disability, sexual orientation, and health literacy [22]. Where available, we will also extract and report participants’ working or employment status to examine how engagement with digital health interventions may vary between those who are still employed and those who are retired.

The data extraction form will be piloted on a small sample of included studies (n=~2) to ensure clarity and consistency. Revisions will be made based on team consensus, and inter-rater reliability will be monitored. Discrepancies will be resolved through discussion or by a third reviewer when necessary.

We will extract the following information:

• Study Characteristics: Author(s), year of publication, country, study setting (e.g., rural/urban), funding source, study design, recruitment techniques
• Participant Characteristics: Age (including age ranges and means), sex/gender, racial/ethnic background (if reported), socioeconomic indicators (e.g., income, housing status, employment), education level, digital literacy, language proficiency, comorbidities, and indicators related to other PROGRESS-Plus factors (e.g., cognitive status, geographic isolation, disability)
• Intervention Characteristics:
  1. Type of digital health intervention (excluding phone-only interventions)
  2. Technology/platform used (e.g., apps, remote monitoring devices, web portals, wearables)
  3. Targeted functions (e.g., symptom monitoring, medication adherence, health coaching)
  4. Mode of delivery and duration
  5. Involvement of healthcare providers
  6. Co-design with patients or marginalized communities (if applicable)
  7. Efficacy of the intervention (yes/no; based on statistically significant outcomes if reported)

1. •. Equity Considerations:
   1. ◦. Whether the intervention was designed or adapted for specific subgroups (e.g., rural populations, those with limited digital literacy)
   2. ◦. Strategies to enhance digital inclusion (e.g., technical support, training, accessibility adaptations)
   3. ◦. Explicit reporting of subgroup outcomes or disparities
2. •. Limitations and Implications:
   1. ◦. Authors’ discussion of equity limitations or gaps
   2. ◦. Recommendations for future research with equity implications

Where possible, extracted data will be disaggregated by equity-relevant variables. If data are missing or unclear, we will attempt to contact the study authors for clarification. Extracted data will be stored securely on institutional servers, and, where possible, de-identified extraction tables will be made available in an open-access repository upon publication.

Data analysis and presentation.

Data will be organized and summarized using both quantitative and qualitative descriptive approaches. Quantitative data (e.g., publication year, study setting, sample characteristics, intervention type) will be analyzed using descriptive statistics, such as frequencies and proportions, to provide a numerical overview of the included studies [38]. This synthesis will be guided by deductive coding informed by the PROGRESS-Plus framework, which includes the following equity domains: Place of residence, Race/ethnicity/culture/language, Occupation, Gender/sex, Religion, Education, Socioeconomic status, and Social capital, along with additional factors such as age, disability, sexual orientation, and health literacy [22]. Equity-related data will be synthesized using a structured analytic approach informed by the PROGRESS-Plus framework. We will quantify the frequency of reporting for each equity factor (e.g., age subgroups, sex/gender, race/ethnicity, socioeconomic indicators, cognitive status) and identify missing variables across studies. Where possible, we will cross-tabulate equity factors with intervention characteristics, such as technology type, mode of delivery, accessibility strategies, and co-design elements. We will also conduct a thematic analysis of reporting patterns to assess whether subgroup inclusion is superficial or substantive. This approach ensures that equity considerations are analyzed systematically and meaningfully, beyond descriptive reporting alone. By linking equity variables to intervention characteristics, we aim to identify features such as co-design, training, or accessibility strategies that may enhance inclusion and engagement of underrepresented subgroups in digital health interventions for older adults with heart failure.

The synthesis will highlight patterns in representation, reporting, and outcomes related to equity-relevant subgroups, identify gaps in the literature, and provide insight into how digital health interventions may reinforce or mitigate disparities among older adults with heart failure.

As a scoping review, no formal statistical hypothesis testing will be performed. Extracted data will be summarized using descriptive quantitative measures (e.g., frequencies, proportions) and qualitative narrative synthesis to highlight patterns, gaps, and equity considerations across studies.

All co-authors will contribute to study design, screening, data extraction, synthesis, and manuscript preparation. All authors will participate in interpreting findings and drafting the manuscript.