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Record W4382680907 · doi:10.1111/joop.12457

Healthy for some but not for all: The moderating role of BMI on perceived health climate–insomnia relationship

2023· article· en· W4382680907 on OpenAlexaff
Seulki Jang, Ho Kwan Cheung, Michael R. Ford

Bibliographic record

VenueJournal of Occupational and Organizational Psychology · 2023
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of Calgary
FundersNational Institute for Occupational Safety and Health
KeywordsMediationPsychologyInsomniaBody mass indexHealth promotionSocial psychologyClinical psychologyDevelopmental psychologyPublic healthPsychiatryMedicinePolitical science

Abstract

fetched live from OpenAlex

Abstract This study examines the mediated relationship between perceived health climate and insomnia via exhaustion, and whether the mediation effect is weaker for individuals with higher body mass index (BMI). Results from multi‐wave field data revealed that perceived health climate negatively predicted insomnia through reduced exhaustion. Moreover, the mediation effect was weaker among people with higher BMI (obese individuals) than people with lower BMI (non‐obese individuals). This study expands our understanding of the workplace health climate and its unintended consequences for obese individuals. Also, it encourages practitioners to develop health climate promotion programmes that intend to reduce employee exhaustion first prior to specific behavioural changes and takes into account individual differences.

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)0.002
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.103
GPT teacher head0.470
Teacher spread0.368 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2023
Admission routes1
Has abstractyes

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