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Record W3162977180 · doi:10.1080/0164212x.2021.1923430

Environmental Scan of Return to Work Programs for Trauma-Related Mental Health Conditions

2021· article· en· W3162977180 on OpenAlexaffabout
Megan Edgelow, Megan A. Lewis, Melanie Toope, Heidi Cramm

Bibliographic record

VenueOccupational Therapy in Mental Health · 2021
Typearticle
Languageen
FieldPsychology
TopicPsychiatric care and mental health services
Canadian institutionsProvidence Health CareQueen's University
Fundersnot available
KeywordsMental healthPopulationSWOT analysisWork (physics)MedicinePsychologyEnvironmental healthPsychiatryBusinessEngineeringMarketing

Abstract

fetched live from OpenAlex

Exposure to psychological trauma can cause disruptions in employment; however, program-level return to work (RTW) best practices for clients with trauma-related mental health conditions are limited. We completed an environmental scan to identify RTW programs for this population. English-language webpages from Australia, Canada, New Zealand, the UK, and the USA were included in the scan. Resources were reviewed and informed a SWOT (strength, weakness, opportunity, and threat) analysis. The environmental scan found 35 programs that provide RTW services for this population. Further research, including studies that focus on the efficacy of RTW programs for this population, is required.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.654
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
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 head0.050
GPT teacher head0.409
Teacher spread0.359 · 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

Citations13
Published2021
Admission routes2
Has abstractyes

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