Psychological needs and exercise behaviour: a comparison of two psychological needs models
Bibliographic record
Abstract
OBJECTIVE: Psychological need satisfaction, from a self-determination theory (SDT) perspective, has been applied extensively to understand predictors of exercise behaviour. Dweck proposed a psychological needs framework that includes basic needs (optimal predictability, competence, acceptance), compound needs derived from combinations of basic needs (self-esteem/status, trust, control), and a superordinate compound need for self-coherence that includes identity and meaning. The purpose was to examine whether psychological needs operationalized within Dweck's model account for variance in exercise behaviour in ways that the SDT model does not. METHODS AND MEASURES: A community sample of 403 adults completed measures of demographics, psychological needs, and exercise motivation at Time 1, and self-reported moderate-to-vigorous minutes of exercise at both Times 1 and 2 four weeks later. RESULTS: Two structural equation models operationalizing Dweck's needs framework and SDT (basic needs and motivation) were examined in relation to exercise behaviour. In both models, exercise identity and integrated regulation (conceptually similar) were the most salient correlates of prospectively measured exercise behaviour, and both accounted for the relationship between competence and exercise behaviour. CONCLUSION: The results support the importance of identity in the context of exercise behaviour. Future research should investigate factors associated with adopting and maintaining an exercise identity.
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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 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".