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Record W2237310931 · doi:10.4236/ojpsych.2016.61007

Relationship between Cognitive Function and Employment in Japanese Schizophrenia Patients

2016· article· en· W2237310931 on OpenAlexaboutno aff
Tomoya Takeda, Masahito Tomotake, Yoshinori Ueoka, Tsunehiko Tanaka, Takeo Tominaga, Y Kaneda, Tetsuro Ohmori

Bibliographic record

VenueOpen Journal of Psychiatry · 2016
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)CognitionDepression (economics)Positive and Negative Syndrome ScaleVerbal memoryPsychologyLogistic regressionWorking memoryUnemploymentClinical psychologyPsychiatryMedicinePsychosisInternal medicine

Abstract

fetched live from OpenAlex

The purpose of the present study was to examine the relationship between cognitive function and employment in Japanese schizophrenia patients. Subjects were 61 outpatients. Cognitive function was assessed using the Brief Assessment of Cognition in Schizophrenia. Clinical symptoms were also evaluated with the Positive and Negative Syndrome Scale and the Calgary Depression Scale for Schizophrenia. Verbal memory (F(1, 58) = 5.50, p = 0.02) and attention and speed of information processing scores (F(1, 58) = 4.92, p = 0.03) showed significant differences between employment and unemployment groups. Logistic regression analysis showed that employment was significantly predicted by verbal memory (x2 = 16.09, df = 2, p = 0.01) and depression scores (x2 = 16.09, df = 2, p = 0.02). The results suggest that improving verbal memory and depression may lead to employment in Japanese schizophrenia patients.

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 score0.021
Threshold uncertainty score0.253

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)0.0000.000

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 head0.331
Teacher spread0.291 · 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

Citations1
Published2016
Admission routes1
Has abstractyes

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