Using past behaviour and spontaneous implementation intentions to enhance the utility of the theory of planned behaviour in predicting exercise
Bibliographic record
Abstract
OBJECTIVES: This study examined the utility of the theory of planned behaviour (TPB), past behaviour, and spontaneous implementation intentions in predicting exercise behaviour. The psychological correlates of spontaneous implementation intentions and the moderating effects of intention, perceived behavioural control, past behaviour, and implementation intentions at various time points were also examined. DESIGN: Data collection occurred over three phases with a 2- and 3-week interval. The attrition rate was 35.97% leaving a total of 162 participants (63 males, 99 females). In the first wave, participants completed measures of TPB, spontaneous implementation intentions, and past behaviour. Behaviour was assessed in the second and third waves, and a follow-up measure of spontaneous implementation intentions was completed in Phase 3. RESULTS: Several regression analyses were conducted. Attitude towards exercise and perceived behavioural control made a significant contribution to the prediction of intention. Intention made a significant contribution to the prediction of implementation intentions. Spontaneous implementation intentions reduced the effect of intention and past behaviour for behaviour at 2 weeks and when indexed over a 5-week period. When behaviour was measured for a 3-week period (following an initial 2-week period), the variance that intention and past behaviour accounted for in exercise behaviour decreased, and spontaneous implementation intentions were no longer a significant predictor of behaviour. Spontaneous implementation intentions were found to interact with past behaviour, such that implementation intentions predicted exercise behaviour only among participants who did not exercise frequently in the past. CONCLUSIONS: Implications and future research directions are discussed.
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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 | 0.007 | 0.027 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".