Self-determined motivation predicts independent, home-based exercise following cardiac rehabilitation.
Bibliographic record
Abstract
OBJECTIVE: To investigate self-determined motivation as a predictor of exercise behavior 3 and 6 weeks following completion of cardiac rehabilitation (CR) as well as the relationship between psychological need satisfaction and self-determined motivation to exercise. PARTICIPANTS AND DESIGN: CR outpatients (n = 68; M(age) = 64.90 +/- 8.86 years). The design was correlational (cross-sectional and prospective), with psychological need satisfaction predicting self-determined motivation at the completion of CR and self-determined motivation predicting exercise behavior at 3- and 6-week follow-ups. RESULTS: Psychological need satisfaction for competence predicted self-determined motivation to exercise (beta = .32, p < .05, pr(2) = .08). Self-determined motivation at the end of CR was correlated with exercise behavior at 3-week follow-up (r(68) = .22, p < .05) and predicted exercise at 6 weeks (R(2) (adjusted) = .11; beta = .35, p < .01). CONCLUSION: CR participants who report higher levels of psychological need satisfaction regarding exercise report greater self-determined motivation. Greater self-determined motivation to exercise, in turn, relates to higher levels of subsequent independent exercise behavior. Nurturing psychological needs and self-determined motivation during CR may assist participants in maintaining exercise following CR.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 | 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 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".