Healthier Lifestyle for Girls Who Accumulate More Years in the FitSpirit School-Based Intervention
Bibliographic record
Abstract
The main aim was to verify in a group of adolescent girls undergoing a school-based intervention if the number of years of participation in the intervention is related to healthy lifestyle habits, body weight status, and perceived health. Cross-sectional analysis of the FitSpirit data was performed. Body mass index, lifestyle variables, and perceived health were collected through an online questionnaire. Chi-square test, Fisher’s test, and ANOVA were performed. Mean age of the 272 girls was 14.7 ± 1.5 years. Higher percentage of girls with 3 or more years of participation met the recommendations for physical activity (PA) and sleep duration (P < .05). Girls who participated ≥3 years showed higher levels of moderate-to-vigorous PA than girls with 1 and 2 years of participation (P < .01). No differences were found between the number of years of participation and body mass index, screen time, fruit/vegetable consumption, or perceived health. A healthier body weight status and following recommendations for healthier habits (PA, screen time, sleep, fruit/vegetable consumption) were related to better perceived health (P < .05). Girls with more years in FitSpirit had healthier lifestyle habits (PA and sleep) compared to those with fewer years. A healthier body weight status and meeting healthy lifestyle recommendations were related to better perceived health.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".