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Record W1704209595 · doi:10.3233/jvr-2012-0598

Job tenure and quality of work life of people with psychiatric disabilities working in social enterprises

2012· article· en· W1704209595 on OpenAlexafffund
Nathalie Lanctôt, Marc Corbière, Marie‐José Durand

Bibliographic record

VenueJournal of Vocational Rehabilitation · 2012
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsUniversité de Sherbrooke
FundersUniversité de Sherbrooke
KeywordsSupported employmentPsychologyWork (physics)Social workQuality of life (healthcare)Quality (philosophy)PsychiatryBusinessEconomic growthPsychotherapistEconomics

Abstract

fetched live from OpenAlex

Psychiatric disabilities may impact employment outcomes, particularly job tenure. However, little is known about the role of quality of work life (QWL) on an individual's ability to maintain his/her employment, particularly in the context of social enterprises. This study examines the impact of QWL on maintaining employment for people with psychiatric disabilities working in social enterprises. A prospective study was undertaken with 67 persons with psychiatric disabilities working in social enterprises. Participants were asked to fill out a battery of questionnaires that assessed QWL, self-esteem as a worker, job satisfaction, severity of symptoms, and general quality of life. Directors of human resources were contacted at six-month follow-up in order to obtain information regarding job tenure. Survival analysis was conducted using Kaplan-Meier curve and Cox regression to assess the risk of job termination and identify predictors. Eighty-nine percent (N = 60) of participants maintained their job during the follow-up period. Cox regression showed that individuals who have a higher QWL have a diminished risk of employment termination. This study demonstrated the important role that QWL may have on job tenure for people with psychiatric disabilities working in social enterprises. Interventions aimed at improving QWL should be offered to increase job tenure.

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)0.001
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 score0.014
Threshold uncertainty score0.215

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.040
GPT teacher head0.404
Teacher spread0.364 · 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

Citations26
Published2012
Admission routes2
Has abstractyes

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