Understanding adaptive tasks in cardiac rehabilitation among patients with acute myocardial infarction: a qualitative study
Bibliographic record
Abstract
BACKGROUND: While Cardiac Rehabilitation (CR) programs have shown effectiveness in improving cardiac outcomes, there is limited understanding of how patients perceive and adapt to these interventions. Furthermore, alternative modes of delivering CR that have received positive evaluations from participants remain underexplored, yet they have the potential to enhance CR uptake. OBJECTIVES: To explore the patient experience in CR programmes following Acute Myocardial Infarction (AMI) and describe their adaptive processing. PATIENTS AND METHODS: This qualitative study was conducted at a nationally certified centre in China between July 2021 and September 2022, encompassing three stages: in-hospital, centre-based, and home-based CR programs. Purposive sampling was used to select eligible AMI patients for in-depth semi-structured interviews. The interview outline and analytical framework were aligned with the key concepts derived from the middle-range theory of adaptation to chronic illness and the normalization process theory. The findings were reported following the Consolidated Criteria for Reporting Qualitative Research checklist. RESULTS: Forty AMI patients were recruited. Four main themes describing the process of AMI patients normalizing CR intervention were identified, including (1) experiencing CR service driving by role's responsibilities, (2) engaging in collaborative relationship based on interpersonal trust, (3) exploring a personalized rehabilitation plan by complex integration, and (4) expecting a promised outcome to shape decision-making. CONCLUSION: Integrated care interventions for AMI patients could benefit from a collaborative co-designed approach to ensure that CR interventions are normalized and fit into patients' daily lives. Organizational-level CR services should align with the rehabilitation needs and expectations of patients.
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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 | 0.010 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".