Supplemental Material for Links Between Adolescent Time-Use Sequences and Well-Being
Bibliographic record
Abstract
Studies on time use and adolescent well-being typically focus on total time but rarely examine how an activity is embedded within a sequence of various activities. However, the potential importance of time-use sequences is apparent in pediatric recommendations like avoiding technology before bed. Using 24-hr time-use diaries from a representative birth cohort of 2,198 U.K. adolescents, we examined whether time-use sequences are prospectively associated with subjective well-being and 23 developmental outcomes. Preregistered analyses identified two weekday and four weekend sequences linked to different demographic and well-being correlates. For example, adolescents with high screen time throughout the day and late bedtimes experienced poorer outcomes than those whose late-night screen time followed diverse activities or active leisure. Yet, in exploratory analyses accounting for total time, only a few significant associations remained. This illustrates the advantage of examining total time-use and time-use sequences together to gain a more comprehensive understanding of adolescent well-being.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.477 | 0.042 |
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".