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Record W3032553571 · doi:10.1017/dmp.2020.61

Mental Disorders in Firefighters Following Large-Scale Disaster

2020· review· en· W3032553571 on OpenAlexaff
Shannon L. Wagner, Nicole White, Christine Randall, Cheryl Regehr, Marc White, Lynn E. Alden, Nicholas Buys, Mary G. Carey, Wayne Corneil, Trina Fyfe, Lynda R. Matthews, Alex Fraess‐Phillips, Elyssa Krutop

Bibliographic record

VenueDisaster Medicine and Public Health Preparedness · 2020
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of OttawaUniversity of British ColumbiaResponse Biomedical (Canada)University of TorontoUniversity of Northern British Columbia
Fundersnot available
KeywordsMental healthAnxietyOccupational safety and healthPopulationClinical psychologyDepression (economics)MedicinePoison controlSuicide preventionScale (ratio)Injury preventionFirefightingPsychologyHuman factors and ergonomicsPsychiatryEnvironmental health

Abstract

fetched live from OpenAlex

Firefighting service is known to involve high rates of exposure to potentially traumatic situations, and research on mental health in firefighting populations is of critical importance in understanding the impact of occupational exposure. To date, the literature concerning prevalence of trauma-related mental disorders such as posttraumatic stress disorder (PTSD) has not distinguished between symptomology associated routine duty-related exposure and exposure to large-scale disaster. The present systematic review synthesizes a heterogeneous cross-national literature on large-scale disaster exposure in firefighters and provides support for the hypothesis that the prevalence of PTSD, major depressive disorder, and anxiety disorders are elevated in firefighters compared with rates observed in the general population. In addition, we conducted narrative synthesis concerning several commonly assessed predictive factors for disorder and found that sociodemographic factors appear to bear a weak relationship to mental disorder, while incident-related factors, such as severity and duration of disaster exposure, bear a stronger and more consistent relationship to the development of PTSD and depression in cross-national samples. Future work should expand on these preliminary findings to better understand the impact of disaster exposure in firefighting personnel.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), 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 score0.862
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.170
GPT teacher head0.476
Teacher spread0.306 · 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

Citations37
Published2020
Admission routes1
Has abstractyes

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