The Associations Between Self-Perceived Actual and Ideal Body Sizes and Physical Activity Among Early Adolescents
Bibliographic record
Abstract
PURPOSE: This study examined the association between self-perceived actual and ideal body sizes and objectively assessed moderate-to-vigorous physical activity (MVPA) among adolescents, controlling for puberty, fat mass index, and sex. A secondary objective was to explore the association between objectively assessed fat mass index and MVPA. METHODS: Participants were 438 early adolescents (Mage = 11.61, SD = 0.92). Participants selected body sizes that represented their self-perceived actual and ideal bodies. Participants then wore an accelerometer for 1 week to assess MVPA. Polynomial regression analysis with response surface methods was used to explore MVPA in relation to the discrepancy and agreement (ie, no discrepancy) between self-perceived actual and ideal body sizes. RESULTS: When self-perceived actual and ideal body sizes were in agreement and represented smaller and larger bodies, MVPA was low. Participants with similar self-perceived actual and ideal bodies in the middle of the body-size spectrum demonstrated the highest levels of MVPA. The direction and degree of the discrepancy between self-perceived actual and ideal bodies were not significantly associated with MVPA. Fat mass index was significantly and negatively associated with MVPA. CONCLUSIONS: These findings may inform physical activity promotion programs and provide methodological contributions to the study of how body image and MVPA are related.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".