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Record W1994852592 · doi:10.1186/1471-2458-8-104

Paternal psychosocial work conditions and mental health outcomes: A case-control study

2008· article· en· W1994852592 on OpenAlexaff
Stefania Maggi, Aleck Ostry, James Tansey, James R. Dunn, Ruth Hershler, Lisa Chen, Clyde Hertzman

Bibliographic record

VenueBMC Public Health · 2008
Typearticle
Languageen
FieldSocial Sciences
TopicWork-Family Balance Challenges
Canadian institutionsUniversity of British ColumbiaUniversity of VictoriaUniversity of TorontoCarleton University
Fundersnot available
KeywordsMental healthPsychosocialMedicinePsychopathologyBiostatisticsAnxietyYoung adultPublic healthClinical psychologyPsychiatryMultivariate analysisGerontology

Abstract

fetched live from OpenAlex

BACKGROUND: The role of social and family environments in the development of mental health problems among children and youth has been widely investigated. However, the degree to which parental working conditions may impact on developmental psychopathology has not been thoroughly studied. METHODS: We conducted a case-control study of several mental health outcomes of 19,833 children of sawmill workers and their association with parental work stress, parental socio-demographic characteristics, and paternal mental health. RESULTS: Multivariate analysis conducted with four distinct age groups (children, adolescents, young adults, and adults) revealed that anxiety based and depressive disorders were associated with paternal work stress in all age groups and that work stress was more strongly associated with alcohol and drug related disorders in adulthood than it was in adolescence and young adulthood. CONCLUSION: This study provides support to the tenet that being exposed to paternal work stress during childhood can have long lasting effects on the mental health of individuals.

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)0.003
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.082
GPT teacher head0.385
Teacher spread0.303 · 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

Citations7
Published2008
Admission routes1
Has abstractyes

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