Reciprocal relationships between self‐efficacy, outcome satisfaction, and attendance at an exercise programme
Bibliographic record
Abstract
OBJECTIVES: The objectives of this study were to (i) investigate directional influences of self-efficacy, outcome satisfaction, and attendance during an exercise programme and (ii) examine the predictive capabilities of self-efficacy and outcome satisfaction on participant dropout. METHODS: Adults aged 35-65 years were recruited to a 12-month exercise programme. Self-efficacy was collected at baseline, three, six, nine, and 12 months, and outcome satisfaction at the same time-points except baseline. Cross-lagged panel analyses and logistic regression analyses were conducted to examine the primary and secondary objectives, respectively. RESULTS: Coping and scheduling self-efficacy had stronger reciprocal relationships with outcome satisfaction than task self-efficacy, although the strength of these relationships varied across time. Initially, task self-efficacy predicted programme attendance. Midway through the programme, outcome satisfaction predicted attendance, and by the end of the programme, coping self-efficacy was the strongest predictor of attendance. Self-efficacy and outcome satisfaction did not predict programme dropout. CONCLUSIONS: The results support the reciprocal relationship between outcome satisfaction and scheduling and coping self-efficacy and highlight the importance of sequentially targeting different beliefs and skills to facilitate successful initiation and maintenance of exercise behaviour. Statement of contribution What is already known on this subject? Self-efficacy and outcome satisfaction are related to exercise behaviour. The relationship between self-efficacy and outcome satisfaction are typically considered unidirectional. The longitudinal relationships among self-efficacy, outcome satisfaction, and physical activity participation are unclear. What does this study add? Outcome satisfaction had reciprocal relationships with both coping and scheduling self-efficacy for exercise. The importance of self-efficacy and outcome satisfaction to exercise attendance changes over time. Task self-efficacy was the strongest predictor of initial programme attendance. Midway through the programme, outcome satisfaction and task self-efficacy were the strongest predictors of attendance, and by the end of the programme, coping self-efficacy was the strongest predictor.
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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 | 0.003 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".