Moderators of the intention-behaviour and perceived behavioural control-behaviour relationships for leisure-time physical activity
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Intention is a key determinant of action. However, there is a gap between intention and behavioural performance that remains to be explained. Therefore, the aim of this study was to identify moderators of the intention-behaviour and perceived behavioural control (PBC)- behaviour relationships for leisure-time physical activity. METHOD: This was tested in reference to Ajzen's Theory of Planned Behaviour. A sample of 300 volunteers, 192 women and 108 men, aged 18 to 55, participated in the study. At baseline, the participants completed a self-administrated psychosocial questionnaire assessing Ajzen's theory variables (i.e., intention and perceived behavioural control). The behavioural measure was obtained by mail three months later. RESULTS: Multiple hierarchical regression analyses indicated that age and annual income moderated the intention-behaviour and PBC-behaviour relationships. However, in the final model predicting behaviour (R2 = .46), only the interaction term of PBC by annual income (beta = .24, p = 0.0003) significantly contributed to the prediction of behaviour along with intention (beta = .49, p = 0.0009) and past behaviour (beta = .44, p < 0.0001). CONCLUSION: Physical activity promotion programs would benefit not only from focusing on increasing the intention of low intenders, but also from targeting factors that moderate the perceived behavioural control-behaviour relationships.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it