Body image and health-related behaviors among fitspirit participants
Bibliographic record
Abstract
BACKGROUND: Body image variables such as body size perception (BSP) and body size dissatisfaction (BSD) can influence health-related behaviors. However, few studies have investigated these body image variables in adolescent girls participating in a physical activity intervention. Therefore, the study objectives were to examine the 1) associations between health-related behaviors (physical activity, screen-time, eating habits and sleep duration) and BSP and BSD among girls participating in FitSpirit, a physical activity intervention for girls; and 2) influence of weight control practices on the association between health-related behaviors and BSP and BSD. METHODS: This cross-sectional study assessed a sample of 545 adolescent girls (mean age: 15.0±1.5 years) from 240 schools. Body mass index, health-related behaviors, perceived actual body size and desired body size variables were self-reported and collected via an online questionnaire at the end of the FitSpirit intervention. A negative BSP score [perceived actual body size - calculated BMI z-score] indicates an underestimation of body size. A positive BSD score [perceived actual body size - desired body size] indicates a desire to reduce body size. A multiple linear regression analysis examined the effects of age, zBMI and health behaviors on BSP and BSD. A second multiple linear regression analysis examined the independent associations between BSP and BSD by weight control practice. The linear relationships between BSP and BSD were evaluated with Pearson's correlations. RESULTS: Underestimation and dissatisfaction of body size are more prevalent in participants living with overweight/obesity. Screen-time and sleep duration were independently associated with BSP score (Beta=0.02; P<0.05 and Beta=-0.07; P<0.05, respectively), whereas only screen-time was associated with the BSD score (Beta=0.07; P<0.001). Physical activity was independently associated with the BSP score only in participants trying to control (maintain) their weight (Beta=-0.18; P<0.05). CONCLUSIONS: Body size overestimation and dissatisfaction are associated with health-related behaviors, specifically with more screen-time and less optimal sleeping habits. Physical activity level does not appear to be associated with body image in girls engaged in a physical activity intervention and who want to lose or gain weight. Health promotion interventions could include screen-time and sleep components as they may influence body image.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".