MétaCan
Menu
Back to cohort
Record W1506133744 · doi:10.1300/j004v24n01_02

Factors Influencing Occupational Competence in Schizophrenia

2008· article· en· W1506133744 on OpenAlexaff
Claudine Goulet, Jacqueline Rousseau, Pierre Fortier, Jean‐Pierre Mottard

Bibliographic record

VenueOccupational Therapy in Mental Health · 2008
Typearticle
Languageen
FieldPsychology
TopicBehavioral and Psychological Studies
Canadian institutionsInstitut Universitaire de Gériatrie de MontréalHôpital du Sacré-Cœur de MontréalHôpital du Saint-SacrementUniversité de Montréal
Fundersnot available
KeywordsCompetence (human resources)PsychologyPerceptionPsychological interventionSocial skillsOccupational therapyExploratory researchClinical psychologyPsychotherapistSocial psychologyPsychiatry

Abstract

fetched live from OpenAlex

Abstract Objective: To explore and compare the perception of productive activities (studies, work) held by young adults with schizophrenia and their therapists. Method: An exploratory qualitative study was carried out using the Model of Competence (Rousseau, 2003). Nine client-therapist dyads were recruited. Data collected were transcribed, coded, and processed with QSR.N'VIVO (2002). Results: Therapists and clients agree about the personal characteristics (e.g., motivation, coping) and activities (e.g., prior work or study experiences) that have positive (e.g., social skills) or negative influence (e.g., symptoms of schizophrenia) on competence in productive activities. Their perceptions differ about the environmental characteristics that influence competence: some elements are mentioned only by clients (e.g., work environment) or therapists (e.g., using community resources). Conclusion: The framework offered by a specialized clinic can promote exchanges and the congruence of perceptions between therapists and clients. Interventions focusing on the environment should be further developed in relation to productive activities.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.381
GPT teacher head0.437
Teacher spread0.057 · 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

Citations3
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueOccupational Therapy in Mental HealthSame topicBehavioral and Psychological StudiesFrench-language works237,207