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Record W4387150558 · doi:10.1016/s2468-2667(23)00182-2

The need to promote sleep health in public health agendas across the globe

2023· review· en· W4387150558 on OpenAlexafffund
Diane C Lim, Arezu Najafi, Lamia Afifi, Claudio L. Bassetti, Daniel J. Buysse, Fang Han, Birgit Högl, Yohannes Adama Melaku, Charles M. Morin, Allan I Pack, Dalva Poyares, Virend K. Somers, Peter R. Eastwood, Phyllis C. Zee, Chandra L. Jackson

Bibliographic record

VenueThe Lancet Public Health · 2023
Typereview
Languageen
FieldPsychology
TopicSleep and related disorders
Canadian institutionsUniversité Laval
FundersNational Institute of Environmental Health SciencesNational Heart, Lung, and Blood InstituteNational Health and Medical Research CouncilMedical Research CouncilNational Institute on Minority Health and Health DisparitiesCenters for Disease Control and PreventionNational Institutes of HealthNational Natural Science Foundation of ChinaNational Institute on AgingJack Brockhoff FoundationEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentWorld Health OrganizationCanadian Institutes of Health ResearchU.S. Department of Veterans Affairs
KeywordsGlobePublic healthGlobal healthEconomic growthMental healthSocial determinants of healthSleep (system call)Developing countryPublic relationsHealth policyPolitical scienceEnvironmental healthMedicinePsychiatryNursingEconomics

Abstract

fetched live from OpenAlex

Healthy sleep is essential for physical and mental health, and social wellbeing; however, across the globe, and particularly in developing countries, national public health agendas rarely consider sleep health. Sleep should be promoted as an essential pillar of health, equivalent to nutrition and physical activity. To improve sleep health across the globe, a focus on education and awareness, research, and targeted public health policies are needed. We recommend developing sleep health educational programmes and awareness campaigns; increasing, standardising, and centralising data on sleep quantity and quality in every country across the globe; and developing and implementing sleep health policies across sectors of society. Efforts are needed to ensure equity and inclusivity for all people, particularly those who are most socially and economically vulnerable, and historically excluded.

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 imitation

Not 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.

metaresearch head score (Codex)0.008
metaresearch head score (Gemma)0.012
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.010
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0030.003
Science and technology studies0.0010.003
Scholarly communication0.0050.007
Open science0.0020.004
Research integrity0.0060.008
Insufficient payload (model declined to judge)0.0100.003

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.

Opus teacher head0.237
GPT teacher head0.470
Teacher spread0.233 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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".

Quick stats

Citations331
Published2023
Admission routes2
Has abstractyes

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