Associations between bedtime media use and sleep outcomes in an adult population-based cohort
Bibliographic record
Abstract
Abstract Background We aimed to extend existing research on associations between bedtime media use and sleep in adults by taking relevant covariates into account and testing hypothesised mediating and moderating pathways. Methods Frequency of bedtime media use and sleep outcomes were examined by questionnaire in 4188 adults (59% women, aged 19-94 years) from the Specchio cohort in Geneva, Switzerland. We tested: 1) associations between bedtime media use and sleep (bedtimes, sleep latency, sleep duration, sleep quality, insomnia symptoms, and daytime sleepiness), adjusting for prior sleep, mental health, and health behaviours (physical activity, binge drinking, smoking, total leisure screen time), 2) whether bedtime media use mediates associations between individual susceptibility factors (age, chronotype, and mental health) and sleep, and 3) whether individual susceptibility factors moderate associations between bedtime media use and sleep. Results Often using a screen in the 30 minutes before going to sleep at night was associated with a late bedtime (≥midnight; OR [95% CI]=1.90 [1.44, 2.51], p < 0.001), short sleep duration (<7 hours; 1.21 [1.01, 1.46], p < 0.05), and excessive daytime sleepiness (Epworth score >9; 1.47 [1.25, 1.74], p < 0.001) after adjustment for all covariates. Bedtime media use partly mediated the association between younger age and an evening chronotype and these sleep outcomes. Mental health moderated the association between bedtime media use and sleep quality/insomnia, such that the former was associated with poorer sleep quality/insomnia among individuals with better mental health, but not among those with poorer mental health. Conclusions Frequent bedtime media use was associated with various sleep outcomes, independently of relevant covariates. Limiting the use of screens at bedtime is important to promote sleep among adults. Individuals with poorer mental health likely require additional support to improve their sleep quality. Key messages • Frequent bedtime media use is associated with a late bedtime, short sleep duration, and more daytime sleepiness in adults, and these associations hold after adjustment for relevant covariates. • Frequent bedtime media use mediates the association between individual susceptibility factors and sleep outcomes. Mental health moderates the association between bedtime media use and sleep quality.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".