MétaCan
Menu
Back to cohort
Record W1782400754 · doi:10.7870/cjcmh-2006-0013

The Impact of Psychosocial and Physical Work Experience on Mental Health: A Nested Case Control Study

2006· article· en· W1782400754 on OpenAlexaffvenueabout
Aleck Ostry, Stefania Maggi, James Tansey, James R. Dunn, Ruth Hershler, Lisa Chen, Clyde Hertzman

Bibliographic record

VenueCanadian Journal of Community Mental Health · 2006
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsUniversity of TorontoUniversity of British ColumbiaThompson Rivers UniversityUniversity of Victoria
Fundersnot available
KeywordsOddsPsychosocialMental healthConfoundingOdds ratioNeuroticismLongitudinal studyMedicineCohort studyCohortGerontologyPsychologyDemographyEnvironmental healthPsychiatryLogistic regressionPersonalitySocial psychology

Abstract

fetched live from OpenAlex

This investigation is a nested case control study based on a large cohort of sawmill workers employed in 14 sawmills in British Columbia (BC) in Western Canada. The purpose of the study was to assess the association between objectively measured physical and psychosocial work conditions and objectively measured mental health outcomes using a longitudinal study design. The investigation ensured that all cases and controls were free of mental health disease for a 5-year period prior to commencement of the study. The study found that Sikh sawmill workers had elevated odds for all the mental health outcomes investigated, and that workers with low duration of employment had elevated odds for adjustment reaction and acute reaction to stress. After controlling for sociodemographic and nonphysical/nonpsychosocial work condition confounders, high psychological demand was associated with elevated odds for neurotic disorder.

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)0.002
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 score0.193
Threshold uncertainty score0.384

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.444
Teacher spread0.400 · 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

Citations9
Published2006
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Community Mental HealthSame topicWorkplace Health and Well-beingFrench-language works237,207