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Record W3159490220 · doi:10.1186/s13643-021-01677-7

Proactive psychological programs designed to mitigate posttraumatic stress injuries among at-risk workers: a systematic review and meta-analysis

2021· review· en· W3159490220 on OpenAlexafffundabout
Paula M. Di Nota, Anees Bahji, Dianne Groll, R. Nicholas Carleton, Gregory S. Andérson

Bibliographic record

VenueSystematic Reviews · 2021
Typereview
Languageen
FieldPsychology
TopicPosttraumatic Stress Disorder Research
Canadian institutionsUniversity of ReginaThompson Rivers UniversityQueen's UniversityUniversity of CalgaryUniversity of Toronto
FundersWorkSafeBC
KeywordsMedicinePsychoeducationAbsenteeismAnxietyOccupational safety and healthMental healthPublic healthClinical psychologyPsychiatryNursingPsychological interventionPsychology

Abstract

fetched live from OpenAlex

BACKGROUND: Public safety personnel and frontline healthcare professionals are at increased risk of exposure to potentially psychologically traumatic events (PPTE) and developing posttraumatic stress injuries (PTSI, e.g., depression, anxiety) by the nature of their work. PTSI are also linked to increased absenteeism, suicidality, and performance decrements, which compromise occupational and public health and safety in trauma-exposed workers. Evidence is lacking regarding the effectiveness of "prevention" programs designed to mitigate PTSI proactively. The purpose of this review is to measure the effectiveness of proactive PTSI mitigation programs among occupational groups exposed to PPTE on measures of PTSI symptoms, absenteeism, and psychological wellness. METHODS: Five electronic databases were searched per PRISMA guidelines for English or French peer-reviewed studies from 2008 to 2019 evaluating PTSI and psychological wellness in adults exposed to occupational PPTE. The risk of bias was assessed using the Newcastle-Ottawa Scale. RESULTS: We identified 42 studies evaluating 3182 public safety and frontline healthcare professionals, PPTE-exposed educational staff, and miners. Significant overlap was found across program themes that included mindfulness, psychoeducation, resilience promotion, and stress management strategies. Post-program effect sizes were small (SMD < 0.5) to moderate (SMD < 0.8) for reductions in PTSI symptoms and for promoting measures of well-being as indicated by a meta-analysis on 36 studies. There was no evidence for significant reductions in substance use, absenteeism, or biomarkers of distress except for heart rate. Subgroup analyses indicated that multimodal programs effectively improved general psychological health, while resilience programs improved measures of depression, burnout, coping, and resilience. Effect sizes for resilience, depression, and general psychological health improvements were greatest immediately or 1-month post-training, while improvements in PTSD symptoms and coping were larger at longer follow-up. Studies were of moderate quality and risk of bias. CONCLUSIONS: The current results showcase modest evidence for time-limited reductions in PTSI following participation in holistic programs that promote resilience, stress, and emotion regulation among at-risk workers. Implications for organizational implementation of proactive PTSI mitigation programs and areas of future research are discussed. SYSTEMATIC REVIEW REGISTRATION: PROSPERO (CRD42019133534).

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)0.009
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.045

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.025
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0160.022
Bibliometrics0.0070.007
Science and technology studies0.0010.001
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0040.000

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 head0.307
GPT teacher head0.484
Teacher spread0.177 · 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 designMeta-analysis
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

Citations77
Published2021
Admission routes3
Has abstractyes

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