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Record W3118739370 · doi:10.3390/ijerph18020609

Lighting in the Home and Health: A Systematic Review

2021· review· en· W3118739370 on OpenAlexaboutno aff
Oluwapelumi Osibona, Bethlehem Solomon, Daniela Fecht

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicUrban Green Space and Health
Canadian institutionsnot available
FundersMedical Research CouncilWellcome Trust
KeywordsEnvironmental healthMental healthInclusion (mineral)Artificial lightScale (ratio)Quality (philosophy)Human healthGerontologyMedicinePsychologyGeographyCartographyPsychiatry

Abstract

fetched live from OpenAlex

Poor housing is an important determinant of poor health. One key aspect of housing quality is lighting. Light is important for visual performance and safety, and also plays a vital role in regulating human physiological functions. This review aims to synthesise existing evidence on the relationship between lighting in the home and health and recommends areas for future research. Three databases were searched for relevant literature using pre-defined inclusion criteria. Study quality was assessed using the Newcastle Ottawa Scale. Extracted data were qualitatively synthesised according to type of lighting (natural light, artificial light and light at night) and stratified by broad health domains (physical, mental and sleep health). Of the 4043 records retrieved, 28 studies met the inclusion criteria. There was considerable heterogeneity in light exposure metrics used and specific health outcome assessed by the studies. Lighting in the home can negatively affect health but the current evidence base is limited to a small number of studies in different domains of light and health. Further research surrounding specific health outcomes is required to better inform housing quality assessments and lighting practises in the home.

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.015
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.728
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.210
GPT teacher head0.461
Teacher spread0.251 · 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 teacher head, 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

Citations92
Published2021
Admission routes1
Has abstractyes

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