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Record W4312127312 · doi:10.3390/bs12120505

Mental Health Outcomes among Electricians and Plumbers in Ontario, Canada: Analysis of Burnout and Work-Related Factors

2022· article· en· W4312127312 on OpenAlexaffabout
Ali Bani‐Fatemi, Marcos Sanches, Aaron Howe, Joyce Lo, Sharan Jaswal, Vijay Kumar Chattu, Behdin Nowrouzi‐Kia

Bibliographic record

VenueBehavioral Sciences · 2022
Typearticle
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsUniversity of TorontoCentre for Addiction and Mental Health
Fundersnot available
KeywordsBurnoutMental healthDemographicsPsychologyPopulationWork (physics)Occupational safety and healthGerontologySample (material)MedicineEnvironmental healthClinical psychologyDemographyPsychiatry

Abstract

fetched live from OpenAlex

(i) Background: Working in the electrical and plumbing sectors is physically demanding, and the incidence of physical injury and work disability is high. This study aimed to assess the mental health and well-being of skilled trades workers working in the electrical and plumbing sectors; (ii) Methods: Forty participants completed an online survey assessing burnout, work-related factors, and mental health issues. Data were analyzed to determine the association between demographics, the availability, and importance of work-related factors, and burnout using a two-sample Mann-Whitney U test; (iii) Results: Our findings showed that among the work-related factors, workplace safety, family commitments, income and benefits, and full-time employment opportunities might be crucial factors to keep study participants working at their current position. Financial support for external training, which was found to be the most important factor in preventing colleague-related burnout, was available to the satisfaction of approximately 50% of the participants; (iv) Conclusion: Work-related factors such as workplace safety and the availability and support for external training may be protective against all types of burnout among this population. Future studies may consider a larger sample size with a more diverse group of participants and perform an intersectional analysis to incorporate minority identities in the analyses.

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 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)0.001
metaresearch head score (Gemma)0.000
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 score0.003
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.082
GPT teacher head0.437
Teacher spread0.355 · 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 teacher head, not a consensus.

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

Citations5
Published2022
Admission routes2
Has abstractyes

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