Exploring Gender-based Experiences in a Digitally Delivered Cardiac Rehabilitation Program: Qualitative Insights From the My Heart Coach Program
Bibliographic record
Abstract
BACKGROUND: Cardiac rehabilitation (CR) is a cornerstone of secondary prevention for individuals with cardiovascular disease, yet participation remains suboptimal, particularly among women. Digital CR programs offer flexible alternatives; however, little is known about how gender influences engagement and experience in these settings. METHODS: This qualitative descriptive study explored gendered experiences within the My Heart Coach (MHC) digital CR program. Thirty-two participants (20 women, 12 men), mean age 63.7 years, who had completed the 12-week program were purposively sampled to ensure diversity in education, employment, stress, ethnicity, and geographic region. Semi-structured interviews were conducted between November 2024 and May 2025, audio-recorded and transcribed verbatim. Thematic analysis was used to identify patterns in participant narratives. Data collection and analysis proceeded iteratively until thematic saturation was achieved. RESULTS: Three major themes were identified. Theme one, "From Cardiac Event to Recovery - Characterizing the MHC Cohort," explores participants' gender-based experiences of having a cardiac event. Theme two, "Gender and Accessibility with Digital Program Elements," highlights gender-based differences in engagement with the CR program. Women and men encountered distinct barriers and facilitators, with women prioritizing flexibility and social connection, and men valuing privacy and autonomy. Theme three, "Rebuilding - Gendered Motivations and Identity in Digital Cardiac Rehabilitation," explores other program motivators, facilitators, and changes following completion of the digital program. CONCLUSION: Gender shapes how participants experience and engage in digital CR programs. These findings underscore the need for a gender-responsive design in CR that can enhance participation and support diverse needs in a scalable manner.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.016 | 0.010 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".