A mediation analysis of the influence of sleep on the relationship between smartphone screen time and youth mental health
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
Research using subjective measures suggests that young people spend large amounts of their leisure time using digital media, which may affect their mental health. Of particular concern is that smartphone screen-time may replace health-promoting activities such as sleep and thereby contribute to mental health problems. Considering that previous studies primarily relied on subjective reports of screen-time and its effects on youth mental health, the objective of the current research was to examine whether screen-time objectively measured via mobile sensing was associated with internalizing (e.g., anxiety, depression) and externalizing (e.g., impulsivity, aggression) symptoms and whether this association was mediated by reduced sleep duration. 407 Canadian youths aged 15–25 completed questionnaires about their mental health symptoms and used a mobile sensing app to measure screen-time and sleep for at least 14 days. The association between screen-time and mental health symptoms and the mediation of sleep duration were tested by fitting structural equation models. Results suggested that objectively measured smartphone screen-time was indirectly associated with externalizing symptoms through reduced sleep duration, but showed no significant association with internalizing symptoms. These findings complement previous research that used subjective measures and highlight the need to provide support and resources to youth to promote healthy screen use and healthy sleep habits.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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