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Record W3091874241 · doi:10.3233/wor-203283

Feasibility evaluation of a return-to-work program for workers with common mental disorders: Stakeholders’ perspectives

2020· article· en· W3091874241 on OpenAlexaff
Élyse Marois, Marie‐France Coutu, Marie‐José Durand

Bibliographic record

VenueWork · 2020
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsDuration (music)StakeholderWork (physics)Mental healthImpossibilityPerspective (graphical)BusinessPsychologyPublic relationsComputer scienceEngineeringPolitical sciencePsychiatry

Abstract

fetched live from OpenAlex

OBJECTIVE: This study aimed to evaluate the feasibility of a newly developed return-to-work program for workers with common mental disorders from the perspective of stakeholders (insurers, employers, unions, and workers). METHODS: We used a sequential mixed design. First, we conducted a survey to evaluate the levels of stakeholder agreement with the program's feasibility. Second, we conducted a number of independent, homogeneous-group discussions or individual interviews to deepen stakeholders' reflections and allow co-construction of a shared perspective of the program's feasibility. RESULTS: Overall, the stakeholders (insurers (n = 6), employers (n = 7), unions (n = 8), and workers (n = 3)), agreed partly to totally with the feasibility of the specific/intermediate objectives, components/tasks, and duration of the components. They identified obstacles that could hinder program implementation. These obstacles pertained mainly to employers' contexts, e.g., difficulty/impossibility of offering job accommodations. They also proposed facilitators to counteract most of these obstacles. Diverging views were found regarding both the role of union representatives and health professionals in the program, and for the duration of the components. CONCLUSION: Overall, the program was perceived as feasible to implement, provided that the potential factors discussed are taken into account. The next step will be to evaluate its implementation in real practice settings.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.181
Threshold uncertainty score0.404

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.150
GPT teacher head0.386
Teacher spread0.237 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations8
Published2020
Admission routes1
Has abstractyes

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