Associations of Contemporary Screen Time Modalities With Early Adolescent Nutrition
Bibliographic record
Abstract
OBJECTIVE: To determine the associations between screen time across several contemporary screen modalities (eg, television, video games, text, video chat, social media) and adherence to the Mediterranean-DASH (dietary approaches to stop hypertension) intervention for neurodegenerative delay (MIND) diet in early adolescents. METHODS: We analyzed data from the Adolescent Brain Cognitive Development study of 9 to 12-year-old adolescents in the United States. Multiple linear regression analyses examined the relationship between self-reported screen time measures at baseline (year 0) and the 1-year follow-up (year 1) and caregiver-reported nutrition assessments at year 1, providing a prospective and cross-sectional analysis. Cross-sectional marginal predicted probabilities were calculated. RESULTS: In a sample of 8267 adolescents (49.0% female, 56.9% white), mean age 10 years, total screen time increased from 3.80 h/d at year 0 to 4.61 h/d at year 1. Change in total screen time from year 0 and year 1 was associated with lower nutrition scores at year 1. PROSPECTIVE: Screen time spent on television, video games, and videos at year 0 was associated with lower nutrition scores at year 1. Cross-sectional: Screen time spent on television, video games, videos, texting, and social media at year 1 was associated with lower MIND diet scores at year 1. CONCLUSIONS: Both traditional (television) and several contemporary modalities of screen time are associated, prospectively and cross-sectionally, with lower overall diet quality, measured by the MIND diet nutrition score, in early adolescents. Future studies should further explore the effect of rising digital platforms and media on overall adolescent nutrition.
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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 | 0.000 | 0.002 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".