Associations between sexual orientation and early adolescent screen use: findings from the Adolescent Brain Cognitive Development (ABCD) Study
Bibliographic record
Abstract
PURPOSE: To assess the association between sexual orientation and screen use (screen time and problematic screen use) in a demographically diverse national sample of early adolescents in the United States. METHODS: We analyzed cross-sectional data from year 2 of the Adolescent Brain Cognitive Development Study (N = 10,339, 2018-2020, ages 10-14 years). Multiple linear regression analyses estimated the association between sexual orientation and recreational screen time, as well as problematic use of video games, social media, and mobile phones. RESULTS: In a sample of 10,339 adolescents (48.7% female, 46.0% racial/ethnic minority), sexual minority (compared to heterosexual) identification was associated with 3.72 (95% CI 2.96-4.47) more hours of daily recreational screen time, specifically more time on television, YouTube videos, video games, texting, social media, video chat, and browsing the internet. Possible sexual minority identification (responding "maybe" to the sexual minority question) was associated with 1.58 (95% CI 0.92-2.24) more hours of screen time compared to heterosexual identification. Sexual minority and possible sexual minority identification were associated with higher problematic social media, video games, and mobile phone use. CONCLUSIONS: Sexual minority adolescents spend a disproportionate amount of time engaging in screen-based activities, which can lead to problematic screen use.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".