Muscle-building behaviors from adolescence to emerging adulthood: A prospective cohort study
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This study aimed to identify patterns of change in muscle-building behaviors from adolescence to emerging adulthood and determine what adolescent factors predict new-onset muscle-building behavior in emerging adulthood. Prospective cohort data from a diverse sample of 1,535 participants followed from adolescence (baseline, Mage = 14.4 ± 2.0 years) to emerging adulthood (follow-up, Mage = 22.1 ± 2.0 years) from the population-based EAT 2010–2018 (Eating and Activity over Time) study were analyzed. Changes in muscle-building behavior were identified (starting, stopping, persistent use, or never use). Log-binomial regression models examined adolescent predictors of starting (i.e., new-onset) muscle-building behaviors in emerging adulthood. Prevalence of any use in adolescence (EAT 2010) and/or emerging adulthood (EAT 2018) was 55.1% (males) and 33.0% (females) for protein powder/shakes, 6.7% (males) and 5.4% (females) for steroids, and 19.4% (males) and 6.5% (females) for other muscle-building substances (e.g., creatine, amino acids). In particular, 22.6% (males) and 13.7% (females) started protein powder/shakes, 2.2% (males) and 1.0% (females) started steroid use, and 9.0% (males) and 2.0% (females) started other muscle-building substances during emerging adulthood. Adolescent protein powder/shake consumption was associated with starting steroids/other muscle-building substances use in emerging adulthood in males (adjusted risk ratio [ARR] 2.09, 95% confidence interval [CI] 1.29–3.39) and females (ARR 4.81, 95% CI 2.01–11.48). Adolescent use of protein powders/shakes may lead to a two- to five-fold higher risk of new use of steroids and other muscle-building products in emerging adulthood. Clinicians, parents, and coaches should assess for use of muscle-building behaviors in adolescents and emerging adults and discourage use of harmful products.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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 it