MétaCan
Menu
Back to cohort
Record W4386151313 · doi:10.1097/jom.0000000000002950

Managers’ Influence on the Prevention of Common Mental Disorders in the Workplace

2023· article· en· W4386151313 on OpenAlexaff
Jenny Hultqvist, P Zhang, Carin Staland‐Nyman, Monica Bertilsson

Bibliographic record

VenueJournal of Occupational and Environmental Medicine · 2023
Typearticle
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsInstitute of Particle Physics
Fundersnot available
KeywordsPsychologyCross-sectional studyLogistic regressionWork (physics)Confidence intervalOdds ratioApplied psychologyMedicineEngineering

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the association among managers' attitudes toward subordinates with common mental disorders (CMDs), self-confidence in supporting these subordinates, and managerial preventive actions (MPAs). METHODS: A cross-sectional study was conducted among Swedish managers (n = 2988) and two types of MPAs: reviewing assignments and work situation (MPA-review), and talking about CMD at the workplace (MPA-talk). Binary logistic regression models were applied and adjusted for individual and organizational covariates. RESULTS: Managers with negative attitudes toward subordinates with CMD were less likely to have done both MPAs. Managers with higher self-confidence in supporting these subordinates were more likely to have done both MPAs compared with managers with lower self-confidence. CONCLUSIONS: Managerial negative attitudes toward CMD and self-confidence in supporting subordinates with CMD have a role in MPAs and should be addressed in manager training programs to encourage preventive actions.

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)0.015
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 score0.004
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.015
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.033
GPT teacher head0.379
Teacher spread0.346 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Occupational and Environmental MedicineSame topicWorkplace Health and Well-beingFrench-language works237,207