Gender diversity and daily steps: Findings from the Adolescent Brain Cognitive Development Study
Bibliographic record
Abstract
PURPOSE: To examine the association between multiple dimensions of gender diversity and physical activity (daily steps) in a diverse national sample of early adolescents in the United States. METHODS: =12.0 years). Linear regression models were used to estimate the associations of gender diversity across multiple measures (transgender identity, felt gender, gender expression, gender non-contentedness) with daily step count measured by wrist-worn Fitbit devices. RESULTS: In this sample of early adolescents, 49.7 % were assigned female at birth, 39.4 % were from racial/ethnic minority groups, and 1 % to 16.9 % identified as gender diverse, depending on the measure used. Transgender identity was associated with 1394 (95 % confidence interval 284-2504) fewer steps per day compared to cisgender identity after adjusting for all covariates. Greater gender diversity, as measured by felt gender and gender non-contentedness, was also associated with lower daily steps. CONCLUSIONS: Transgender and gender-diverse adolescents engage in less physical activity than their cisgender peers. This research has important implications for public health and policies focused on supporting physical activity among transgender and gender-diverse early 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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".