Relationships between personality, an extended theory of planned behaviour model and exercise behaviour
Bibliographic record
Abstract
OBJECTIVES: The purpose of this study was to investigate the theory of planned behaviour's (TPB) mediating hypothesis between the five-factor model of personality and exercise behaviour using an extended TPB model including concepts of affective and instrumental attitude, injunctive and descriptive norm, controllability, and selfefficacy. It was hypothesized that extraversion's activity facet would have a significant direct effect on exercise behaviour while controlling for the TPB, based on the presupposition that activity may represent a disposition that predicts exercise beyond planned behaviour. DESIGN: To test the replicability of these findings, we examined this research question with undergraduate students prospectively and cancer survivors, using a cross-sectional design. RESULTS: Using structural equation modelling, the results indicated that activity had a significant effect (p <.05) on exercise behaviour (study 1 =.20; study 2 =.31) while controlling for the TPB. CONCLUSIONS: This study suggests the importance of extraversion's activity facet on exercise behaviour, even when controlling for a TPB model with additional socialcognitive concepts and disparate population samples.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".