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Record W2019522751 · doi:10.1080/02678370802564272

The mediating role of work-to-family conflict in the relationship between shiftwork and depression

2008· article· en· W2019522751 on OpenAlexaffabout
Victor Y. Haines, Alain Marchand, Vincent Rousseau, Andrée Demers

Bibliographic record

VenueWork & Stress · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMediationSpousePsychologyMental healthDepression (economics)Work–family conflictStructural equation modelingDevelopmental psychologyPsychiatryWork (physics)

Abstract

fetched live from OpenAlex

With significant segments of the working population involved in shiftwork, there is the possibility of serious health outcomes. There are two possible pathways to ill health. In the biological pathway the body's circadian rhythms are affected, leading to physiological disturbances and the inability to cope. By contrast, the aim of this study is to elucidate a social pathway by which shiftwork may lead to mental ill health. It examines the mediating influence of work-to-family conflict in the association between shiftwork and depression. Gender differences are also investigated. The sample included 2,931 Canadian respondents with a spouse and at least one child living at home. Close to 28% of respondents were involved in some form of shiftwork. Structural equation modelling supported partial mediation through work-to-family conflict. Further analyses found that mediation was supported in sub-samples of male and female respondents. The results, however, suggest that the experience of shiftwork is quite similar for men and women as no significant differences were found between mediating models. Overall, the findings support the social explanation of the effect of shiftwork on mental health, but they do not rule out other social or biological pathways.

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)0.001
metaresearch head score (Gemma)0.004
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 score0.069
Threshold uncertainty score0.137

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.060
GPT teacher head0.311
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 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

Citations74
Published2008
Admission routes2
Has abstractyes

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