Adolescent use of social media and associations with sleep patterns across 18 European and North American countries
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
OBJECTIVE: Over the past decade, concurrent with increasing social media use (SMU), there has been a shift toward poorer sleep among adolescents in many countries. The purpose of this study was to examine the cross-national associations between adolescent SMU and sleep patterns, by comparing 4 different categories of SMU (nonactive, active, intense, and problematic use). DESIGN, SETTING, AND PARTICIPANTS: Data were from 86,542 adolescents in 18 European and North American countries that participated in the 2017/18 Health Behaviour in School-aged study. MEASUREMENTS: Mixed-effects linear regression models were used to examine cross-national associations between 4 SMU categories and adolescent sleep duration, bedtime and social jetlag derived from self-reported data. RESULTS: For all countries combined, nonactive SMU was associated with longer sleep, earlier bedtimes, and less social jetlag, compared to active SMU, although the differences were minor. By comparison, intense and problematic SMU were associated with less sleep and later bedtimes on both school and nonschool days, and greater social jetlag, compared to active SMU. While findings were relatively consistent between countries, some differences were observed, suggesting that the national and cultural context may be important in interpreting results. CONCLUSIONS: These findings suggest that both intense and problematic SMU are associated with poorer sleep patterns in adolescents across most countries. Further research is needed to identify effective policies, programs, and messaging to promote the healthy use of social media and prevent potential negative impacts on adolescent sleep.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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