Closing the intention‐behaviour gap in physical activity: The moderating effect of individual differences in the valuation of physical effort
Bibliographic record
Abstract
OBJECTIVE: Intention is a proximal antecedent of physical activity, but it often falls short of driving actual engagement in physical activity. Recently, it was suggested that the valuation of physical effort may explain the intention-behaviour gap. However, this hypothesis has not been formally tested. We aimed to examine whether individual differences in approach and avoidance tendencies towards physical effort moderate the strength of the association between intention and behaviour. METHODS: Four hundred and one English-speaking Canadian participants completed two online surveys separated by 1 week. Intention strength and individual differences in the tendencies to approach and avoid physical effort were first assessed, and moderate-to-vigorous physical activity was self-reported 7 days later. The moderating effect of approach and avoidance tendencies towards physical effort on the association between intention and physical activity was tested using linear regression models. RESULTS: Individual differences in approach tendencies (β = .11, p = .007), avoidance tendencies (β = -.11, p = .005) and in relative approach (vs avoidance) tendencies towards physical effort (β = .11, p = .005) moderated the association between the intention and moderate-to-vigorous physical activity. As expected, the association between intention and physical activity was stronger as approach tendencies towards physical effort increased, but weaker as avoidance tendencies increased. However, this moderating effect was only significant for vigorous physical activity, not for moderate physical activity. CONCLUSION: This study suggests that individual differences in the valuation of physical effort represent a relevant moderator of the intention-behaviour gap in physical activity, especially the most vigorous ones.
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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 | 0.004 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".