Self-regulatory efficacy for exercise in cardiac rehabilitation: Review and recommendations for measurement.
Bibliographic record
Abstract
PURPOSE: Self-regulatory efficacy (SRE) is a psychological resource necessary for cardiac rehabilitation (CR) exercise adoption and maintenance. A 2008 review of self-efficacy for CR exercise identified the need for more high-quality research on SRE. The present review had 4 purposes: (a) to review the characteristics of empirical SRE and CR exercise research since 2008; (b) to examine the quality of SRE measurement; (c) to determine whether varying quality of SRE measurement moderated the relationship between SRE, exercise, and CR social cognitions; and (d) to make recommendations for better measurement for future research. METHOD: An initial search of 766 possible studies identified 29 for review. These included individuals engaged in or completing CR where SRE for exercise and relevant outcomes was assessed. Meta-analysis examined whether SRE measurement quality was associated with the magnitude of effects observed and to determine potential moderation by quality. RESULTS: There were 11 unique operationalizations of SRE for exercise. Problematic factors included: non-SRE variables assessed as the construct, using global versus specific measures, and lack of a time frame over which SRE applied. Effect size was related to stronger relationships as level of study and measurement quality increased. CONCLUSION: Since 2008, an increase in studies examining SRE and CR exercise was observed. To advance SRE and CR exercise research, measurement and research quality improvements are recommended that have implications for future mediation and CR intervention assessment. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.033 | 0.068 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.004 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".