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Record W4225743498 · doi:10.2152/jmi.69.80

Relationship between quality of life and clinical factors in inpatients with schizophrenia

2022· article· en· W4225743498 on OpenAlexaboutno aff
Yoshimune Ishii, Masahito Tomotake, Shinichi Chiba, Rie Tsutsumi, Masatomo Aono, Koushirou Taguchi

Bibliographic record

VenueThe Journal of Medical Investigation · 2022
Typearticle
Languageen
FieldMedicine
TopicSchizophrenia research and treatment
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)Quality of life (healthcare)Depression (economics)Rating scaleExtrapyramidal symptomsPsychiatryBrief Psychiatric Rating ScaleStepwise regressionMedicineDepressive symptomsPsychologyPositive and Negative Syndrome ScaleClinical psychologyCognitionPsychosisInternal medicineAntipsychotic

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to clarify the relationship between quality of life (QOL) and clinical factors in inpatients with schizophrenia. METHODS: Subjects were 50 hospitalized patients with schizophrenia. Their mean age was 56.48 (Standard Deviation=11.93) years. Japanese version of the schizophrenia Quality of Life Scale (JSQLS) and Subjective Well-being under Neuroleptic drug Treatment Short form, Japanese version (SWNS-J) were used to assess subjective QOL, and Mini Mental State Examination-Japanese was used to evaluate cognitive function. Japanese version of the Calgary Depression Scale for Schizophrenia (JCDSS), Brief Psychiatric Rating Scale, and Drug-Induced Extrapyramidal Symptoms Scale were used to assess depression severity, psychotic symptoms, and drug-induced extrapyramidal symptoms, respectively. Stepwise regression analyses were conducted to find factors influencing JSQLS and SWNS-J. RESULTS: JCDSS was a predictor of two scales of JSQLS, and JCDSS also predicted SWNS-J Total and it's two subscales. However, other clinical factors were not related to JSQLS and SWNS-J. CONCLUSION: The results indicate that treating depressive symptoms may lead to improvement of subjective QOL in inpatients with schizophrenia. J. Med. Invest. 69 : 80-85, February, 2022.

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)0.005
metaresearch head score (Gemma)0.006
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 score0.008
Threshold uncertainty score0.675

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.006
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 integrity0.0000.001
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 head0.174
GPT teacher head0.405
Teacher spread0.231 · 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

Citations11
Published2022
Admission routes1
Has abstractyes

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