Testing Attitudes, Social Desirability and Behavioral Regulations as Moderators of Implicit-Explicit Exercise Cognition Discrepancies in Iranian Students
Bibliographic record
Abstract
Abstract Background: Although there is interest among regarding implicit-explicit exercise cognition discrepancies, there is mixed evidence regarding what moderates the relationship between implicitly and explicitly measured constructs. This study examined this issue with evaluations of exercise relative to health or appearance in a sample of Iranian adolescents. Methods: Participants were 471 students enrolled in grades 9 to 12 from Kurdistan, Iran, of whom 269 (54.9%) were female. The possible moderators included behavioral regulations, explicit attitudes, and social desirability. All students completed questionnaire measures of physical activity behavior, attitudes, social desieality and behavioral regulation. They also completed two Go/No Go Association tasks to measure implicit evaluations of exercise relative to health and apperarance. Results. Attitude was a significant moderator of discrepancies between implicit evaluations of exercise with health and health motives. Interjected regulation moderated implicit-explicit appearance discrepancies in the health models. Participants with low social desirability and negative implicit appearance scores had the highest appearance motivation. Conclusions: Investigating implicit-explicit discrepancies provides insight into the development of interventions targeting exercise behavior among Iranian adolescents.
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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 | 0.003 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".