Patients' Perceptions of Hybrid and Virtual-Only Care Models During the Cardiac Rehabilitation Patient Journey
Bibliographic record
Abstract
BACKGROUND: The COVID-19 pandemic initially led to discontinuation of the "traditional" center-based cardiac rehabilitation (CR) model. Virtual models emerged as an opportunity to deliver care, with many programs continuing to offer these models. OBJECTIVE: The aim of this study was to explore patients' perceptions of virtual models of either hybrid (combining center-based and virtual) or virtual-only CR since the pandemic. METHODS: Men and women who chose to participate in hybrid or virtual CR models between January 2022 and January 2023 were invited to attend 1 of 8 focus group sessions. Focus groups were conducted online until thematic saturation was reached. Transcripts were analyzed using thematic analysis. RESULTS: Twenty-three patients (48% female; 83% attending hybrid CR) participated in the study. Analysis revealed 12 overarching themes associated with the CR patient journey: pre-CR, namely, (1) importance of endorsement from healthcare providers and (2) need for education/communication while waiting for program initiation; during CR, namely, (3) preference for class composition/structure, (4) need to enhance peer support in the virtual environment, (5) convenience and concerns with virtual sessions, (6) necessity of on-site sessions, (7) safety of the exercise prescription, (8) requirement/obligation for allied health offerings, (9) satisfaction with virtual education, and (10) use of technology to facilitate CR participation; and post-CR, namely, (11) acknowledgment of program completion and (12) need for support/education after program graduation. CONCLUSIONS: Patients require ongoing support from time of referral to beyond CR program completion. Physical, psychosocial, nutritional, and educational supports are needed. Perceptions expressed by patients related to the program model are modifiable, and strategies to address these perceptions should be explored.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".