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Record W4405917695 · doi:10.1080/0164212x.2024.2448121

Effectiveness of Occupational Therapy Mental Health Interventions in a Return-to-Work Context: A Scoping Review

2024· review· en· W4405917695 on OpenAlexaff
Bao-Zhu Stephanie Long, Kishana Balakrishnar, Michael A. Drobenko, Kam Dolatyar, Batoul Awada, Kaila Jodoin, Alicia McDougall, Behdin Nowrouzi‐Kia

Bibliographic record

VenueOccupational Therapy in Mental Health · 2024
Typereview
Languageen
FieldHealth Professions
TopicWorkplace Health and Well-being
Canadian institutionsCentre for Addiction and Mental HealthUniversity Health NetworkLaurentian UniversityUniversity of Toronto
Fundersnot available
KeywordsOccupational therapyPsychological interventionMental healthContext (archaeology)Work (physics)PsychologyPsychotherapistMedicineApplied psychologyPsychiatryEngineering

Abstract

fetched live from OpenAlex

Literature on the effectiveness of occupational therapy mental health interventions in return-to-work (RTW) is limited, presenting challenges in implementing appropriate strategies. This scoping review aims to synthesize empirical evidence on the effectiveness of mental health interventions on RTW. The search strategy across databases, including Medline, Embase, CINAHL, Web of Science, APA PsycINFO, and Cochrane Library, yielded over 1430 articles, of which seven met the eligibility criteria. Three main intervention types were identified from the review: work performance/function intervention, vocational rehabilitation, and nature-based rehabilitation. This study will help select effective interventions for RTW and expand on the existing knowledge base.

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)0.011
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.012
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.048
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0080.007
Bibliometrics0.0120.011
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0060.001

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 head0.199
GPT teacher head0.569
Teacher spread0.371 · 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 designSystematic review
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

Citations3
Published2024
Admission routes1
Has abstractyes

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