Use of digital screens by adolescents and association on sleep quality: a systematic review
Bibliographic record
Abstract
This study aimed to analyze the influence of digital screen use on adolescents' quality of sleep. This systematic review was recorded on PROSPERO (CRD42020203403) and conducted according to PRISMA guidelines. Studies covering adolescents from 10 to 19 years were included without language or publication restrictions which answered the following guiding question: "Does the use of digital screen influence adolescents' quality sleep?". Article search included the following databases: (MEDLINE/PubMed), LILACS, SciELO, Scopus, EMBASE, Web of Science, IBECS, Cochrane Library, ClinicalTrials.gov, and Open Gray. The following descriptors were used: "Sleep Quality", "Screen Time", and "Adolescent". The Newcastle-Ottawa Scale (NOS) assessed the methodological quality of the cohort studies, and a modified NOS was used to assess the cross-sectional ones. In total, 2,268 articles were retrieved, of which 2,059 were selected for title and abstract reading, after duplicates were deleted. After this stage, 47 articles were selected for full reading, resulting in the 23 articles which compose this review. Excessive use of digital screens was associated with worse and shorter sleep, showing, as its main consequences, night awakenings, long sleep latency, and daytime sleepiness. The use of mobile phones before bedtime was associated with poor quality of sleep among adolescents. Our evaluation of the methodological quality of the chosen studies found seven to be poor and 16, moderate.
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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 | 0.011 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.007 |
| Bibliometrics | 0.010 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".