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Record W1992658011 · doi:10.1186/1471-2458-8-181

Job strain — Attributable depression in a sample of working Australians: Assessing the contribution to health inequalities

2008· article· en· W1992658011 on OpenAlex
Anthony D. LaMontagne, Tessa Keegel, Deborah Vallance, Aleck Ostry, Rory Wolfe

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueBMC Public Health · 2008
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of Victoria
FundersNational Health and Medical Research CouncilUniversity of British ColumbiaMedical Research CouncilUniversity of TasmaniaUniversity of MelbourneMichael Smith Health Research BC
KeywordsJob strainMedicineOccupational stressDepression (economics)Cronbach's alphaPopulationAttributable riskMental healthDemographyPublic healthEpidemiologyEnvironmental healthPsychiatryClinical psychologyPsychometricsInternal medicineNursing

Abstract

fetched live from OpenAlex

BACKGROUND: The broad aim of this study was to assess the contribution of job strain to mental health inequalities by (a) estimating the proportion of depression attributable to job strain (low control and high demand jobs), (b) assessing variation in attributable risk by occupational skill level, and (c) comparing numbers of job strain-attributable depression cases to numbers of compensated 'mental stress' claims. METHODS: Standard population attributable risk (PAR) methods were used to estimate the proportion of depression attributable to job strain. An adjusted Odds Ratio (OR) of 1.82 for job strain in relation to depression was obtained from a recently published meta-analysis and combined with exposure prevalence data from the Australian state of Victoria. Job strain exposure prevalence was determined from a 2003 population-based telephone survey of working Victorians (n = 1101, 66% response rate) using validated measures of job control (9 items, Cronbach's alpha = 0.80) and psychological demands (3 items, Cronbach's alpha = 0.66). Estimates of absolute numbers of prevalent cases of depression and successful stress-related workers' compensation claims were obtained from publicly available Australian government sources. RESULTS: Overall job strain-population attributable risk (PAR) for depression was 13.2% for males [95% CI 1.1, 28.1] and 17.2% [95% CI 1.5, 34.9] for females. There was a clear gradient of increasing PAR with decreasing occupational skill level. Estimation of job strain-attributable cases (21,437) versus "mental stress" compensation claims (696) suggest that claims statistics underestimate job strain-attributable depression by roughly 30-fold. CONCLUSION: Job strain and associated depression risks represent a substantial, preventable, and inequitably distributed public health problem. The social patterning of job strain-attributable depression parallels the social patterning of mental illness, suggesting that job strain is an important contributor to mental health inequalities. The numbers of compensated 'mental stress' claims compared to job strain-attributable depression cases suggest that there is substantial under-recognition and under-compensation of job strain-attributable depression. Primary, secondary, and tertiary intervention efforts should be substantially expanded, with intervention priorities based on hazard and associated health outcome data as an essential complement to claims statistics.

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.

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)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.116
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0150.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.002
Science and technology studies0.0030.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.230
GPT teacher head0.453
Teacher spread0.223 · 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