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Record W4307423261 · doi:10.3390/ijerph192113993

Organizational Factors and Their Impact on Mental Health in Public Safety Organizations

2022· review· en· W4307423261 on OpenAlexafffund
Megan Edgelow, Emma Scholefield, Matthew Q. McPherson, Kathleen Legassick, Jessica Novecosky

Bibliographic record

VenueInternational Journal of Environmental Research and Public Health · 2022
Typereview
Languageen
FieldHealth Professions
TopicOccupational Health and Safety Research
Canadian institutionsQueen's University
FundersQueen's University
KeywordsMental healthPsychologyPopulationOrganizational cultureOccupational safety and healthSupervisorOrganizational commitmentNursingMedicinePublic relationsSocial psychologyEnvironmental healthPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

Public safety personnel (PSP), including correctional officers, firefighters, paramedics, and police officers, have higher rates of mental health conditions than other types of workers. This scoping review maps the impact of organizational factors on PSP mental health, reviewing applicable English language primary studies from 2000–2021. JBI methodology for scoping reviews was followed. After screening, 97 primary studies remained for analysis. Police officers (n = 48) were the most frequent population studied. Correctional officers (n = 27) and paramedics (n = 27) were the second most frequently identified population, followed by career firefighters (n = 20). Lack of supervisor support was the most frequently cited negative organizational factor (n = 23), followed by negative workplace culture (n = 21), and lack of co-worker support (n = 14). Co-worker support (n = 10) was the most frequently identified positive organizational factor, followed by supervisor support (n = 8) and positive workplace culture (n = 5). This scoping review is the first to map organizational factors and their impact on PSP mental health across public safety organizations. The results of this review can inform discussions related to organizational factors, and their relationship to operational and personal factors, to assist in considering which factors are the most impactful on mental health, and which are most amenable to change.

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)0.009
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.004
Insufficient payload (model declined to judge)0.0060.000

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 head0.204
GPT teacher head0.525
Teacher spread0.321 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations39
Published2022
Admission routes2
Has abstractyes

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