Effects of the COVID-19 pandemic on sleep health among Middle Eastern and North African (MENA) populations: a systematic review of the literature
Bibliographic record
Abstract
OBJECTIVES: This study sought to conduct a systematic review of the literature on the impact of the COVID-19 pandemic on sleep health among Middle Eastern and North African (MENA) populations, understudied geographic regions including with regards to sleep health. SETTING: A systematic literature search of studies published from inception to 27 March 2022 was conducted on multiple databases using developed keywords. PARTICIPANTS: Studies were included if they (1) investigated one or more aspects/dimensions of sleep health as an outcome (eg, sleep duration, sleep quality, sleep problems); (2) measured the impact of a COVID-19 pandemic-related domain (eg, impact of quarantine, work from home, lifestyle changes); (3) focused on at least one MENA region population; (4) were peer-reviewed; (5) included ≥100 participants; (6) were written in English and (7) had full-text article publicly available. PRIMARY AND SECONDARY OUTCOMES MEASURED: Primary outcomes were sleep duration, sleep quality and sleep problems. RESULTS: In line with Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, 164 studies were included for data extraction. The Newcastle-Ottawa scale for cross-sectional studies was used to assess the quality of the studies. Overall, the COVID-19 pandemic significantly impacted sleep duration, sleep quality and presence and severity of sleep disorders in MENA populations, including adults, children, students, healthcare workers and people with chronic illnesses. The directionality and strength of associations, as well as the determinants of sleep health, varied by subpopulations. CONCLUSIONS: Longitudinal studies are needed to understand the longer-term impact of the COVID-19 pandemic on the sleep health of MENA populations. Sleep health interventions and policy measures should be tailored to the need of each subpopulation. PROSPERO REGISTRATION NUMBER: CRD42022321128.
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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 | 0.018 | 0.069 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.008 | 0.010 |
| Bibliometrics | 0.015 | 0.012 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| 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".