Who gets included? A scoping review protocol of digital health interventions for older adults with heart failure through an equity lens
Bibliographic record
Abstract
INTRODUCTION: Heart failure is a common and progressive condition that significantly impacts older adults, leading to increased morbidity, reduced quality of life, and healthcare utilization. As its prevalence continues to rise, there is a need for effective management strategies tailored to this population. Digital health interventions (DHIs) have emerged as promising tools for managing chronic conditions like heart failure, potentially improving accessibility and personalizing care. However, there is limited understanding of the inclusivity and effectiveness of these interventions across diverse subgroups of older adults, particularly those differentiated by age, cognitive status, socioeconomic status, sex/gender, and race/ethnicity. METHODS: This protocol outlines a scoping review to assess the extent of literature on DHIs for managing heart failure among older adults, focusing on the representation of diverse subgroups and the characteristics of the interventions. Specifically, the review will explore which populations are included in current DHIs, how they are represented, and how intervention characteristics influence participation and outcomes. This scoping review will follow the Joanna Briggs Institute methodology for scoping reviews, using the PROGRESS-Plus framework to assess equity-related factors such as socioeconomic status, race/ethnicity, geographic location, and cognitive status. The review will focus on randomized controlled trials published between January 1, 2005, and the present, in high-income countries. CONCLUSIONS: The forthcoming scoping review will provide a comprehensive mapping of the existing literature on digital health interventions for heart failure management in older adults, focusing on the inclusivity of diverse subgroups. By identifying gaps in the representation of key demographic factors such as age, cognitive status, socioeconomic status, sex/gender, and race/ethnicity, the review will highlight areas for future research and inform the development of more equitable, effective digital health solutions for heart failure. The findings will be valuable for healthcare practitioners, policymakers, and researchers seeking to improve the accessibility and impact of DHIs in managing heart failure among older populations.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.151 | 0.185 |
| Meta-epidemiology (narrow) | 0.005 | 0.006 |
| Meta-epidemiology (broad) | 0.017 | 0.017 |
| Bibliometrics | 0.026 | 0.020 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.010 | 0.014 |
| Open science | 0.007 | 0.012 |
| Research integrity | 0.012 | 0.009 |
| Insufficient payload (model declined to judge) | 0.078 | 0.014 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".