Psychosocial Factors Influencing Adherence to Cardiac Rehabilitation in Patients After Myocardial Infarction
Bibliographic record
Abstract
BACKGROUND Compliance with medical recommendations and adherence to cardiac rehabilitation remains one of the pressing problems in helping patients who have suffered a myocardial infarction (MI). Additional difficulties include insufficient research in this area and limited tools. One possible solution may be a qualitative method such as a semi-structured McGill Illness Narrative Interview to describe the disease. AIM OF THE STUDY to identify factors influencing adherence to cardiac rehabilitation. MATERIAL AND METHODS The study was conducted at the Federal State Budgetary Institution E.I. Chazov National Medical Research Center of Cardiology from April to August 2023. The sample included 17 people (14 men, 3 women) aged 36 to 62 years, the average age was 51 years. Of these, 7 people were admitted directly by ambulance to the cardiology center at the time of myocardial infarction (3–7 days ago), 10 people underwent treatment for the cardiovascular system in various departments of the cardiology center and had myocardial infarction in the past (from 2 months to 3 years ago). Each respondent was interviewed once, in an individual format, mainly in the cardiac rehabilitation department, in the office of a medical psychologist. RESULTS AND CONCLUSIONS Insufficient awareness of the signs and possibilities of first aid for myocardial infarction was found among the target group. It is advisable to allocate additional consultations to increase awareness of cardiac rehabilitation, strengthen motivation and draw up a plan for independent patient actions. Involvement of people close to the patient in the cardiac rehabilitation process can have a positive impact on achieving the desired changes. CONCLUSION The use of qualitative research methods allowed additional factors that influence poor adherence to cardiac rehabilitation to be identified. The data obtained can be used by cardiologists, medical psychologists, and other members of the medical team to improve the quality of interaction and motivate patients to change.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".