Faculty Opinions recommendation of A qualitative systematic review of influences on attendance at cardiac rehabilitation programs after referral.
Bibliographic record
Abstract
BACKGROUND: Cardiac rehabilitation and secondary prevention programs can prevent heart disease in high-risk populations. However, up to half of all patients referred to these programs do not subsequently participate. Although age, sex, and social factors are common predictors of attendance, to increase attendance rates after referral, the complex range of factors and processes influencing attendance needs to be better understood.METHODS: A systematic review using qualitative meta-synthesis was conducted. Ten databases were systematically searched using 100+ search terms until October 31, 2011. To be included, studies had to contain a qualitative research component and population-specific primary data pertaining to program attendance after referral for adults older than 18 years and be published as full articles in or after 1995.RESULTS: Ninety studies were included (2010 patients, 120 caregivers, 312 professionals). Personal and contextual barriers and facilitators were intricately linked and consistently influenced patients' decisions to attend. The main personal factors affecting attendance after referral included patients' knowledge of services, patient identity, perceptions of heart disease, and financial or occupational constraints. These were consistently derived from social as opposed to clinical sources. Contextual factors also influenced patient attendance, including family and, less commonly, health professionals. Regardless of the perceived severity of heart disease, patients could view risk as inherently uncontrollable and any attempts to manage risk as futile.CONCLUSIONS: Decisions to attend programs are influenced more by social factors than by health professional advice or clinical information. Interventions to increase patient attendance should involve patients and their families and harness social mechanisms.Copyright © 2012 Mosby, Inc. All rights reserved. PMID: 23194483 Funding information This work was supported by: Canadian Institutes of Health Research, Canada Grant ID: G118160769
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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 | 0.134 | 0.383 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.007 | 0.009 |
| Bibliometrics | 0.018 | 0.022 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.008 | 0.010 |
| Research integrity | 0.013 | 0.005 |
| Insufficient payload (model declined to judge) | 0.199 | 0.035 |
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".