Exploring the link between smartphone use and sleep quality: A systematic review
Bibliographic record
Abstract
Abstract Purpose The purpose of this systematic review was to investigate how smartphone use affected sleep quality. The review aimed to clarify the nature of this relationship and its implications for overall well‐being and health. Methodology Following the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses (PRISMA) 2009 guidelines, literature published between 2014 and 2024 was reviewed across multiple databases, including PubMed, ScienceDirect, and Google Scholar. Studies were selected based on their focus on smartphone use and its effects on sleep quality. The quality of the studies was assessed using the modified Newcastle–Ottawa Scale. Findings After screening 1760 records, 25 studies met PRISMA guidelines and were included in the review. The review consistently indicated a significant negative relationship between excessive smartphone use and sleep quality with younger populations and females being more susceptible. Standardized tools such as the Pittsburgh Sleep Quality Index reinforced these findings. However, limitations include reliance on self‐reported data and the predominance of cross‐sectional studies, which hinder establishing causality. Conclusion and Policy Implications Smartphone use harms sleep quality. Interventions should raise awareness of blue‐light filters, digital detox, and evening device use limits. Educational campaigns for parents, educators, and healthcare providers can promote healthier smartphone habits, especially for adolescents and young adults.
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How this classification was reachedexpand
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 | 0.021 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".