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The ability and characteristic of self-reflection and insight in schizophrenia and depression patients

2018· article· en· W3031083221 on OpenAlexaboutno aff
Lu Liu, Jian Liu

Bibliographic record

VenueZhonghua xingwei yixue yu naokexue zazhi · 2018
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsSchizophrenia (object-oriented programming)AlexithymiaDepression (economics)PsychologyInternal medicineSelf-reflectionToronto Alexithymia ScalePsychiatryMedicineClinical psychology

Abstract

fetched live from OpenAlex

Objective To investigate the ability of the self-reflection and insight in schizophrenia and depression patients and their characteristics. Methods Self-reflection and insight scale (SRIS) and the toronto alexithymia scale-20(TAS-20)were used to test the self-reflection and insight of 140 schizophrenia patients, 92 depression patients and 131 healthy controls. Results (1)The SRIS score((73.51±12.78), (79.94±11.11)), self-reflection(RE) score ((42.08±10.95), (47.48±9.19)) and insight(IN) score((31.43±4.92), (32.46±5.70)) in schizophrenia and depression patients were significantly lower than those in healthy controls (SRIS score(86.84±12.70), RE score(51.73±9.95), IN score(35.11±5.48)), and the differences were statistically significant(P 0.05). (3) The correlation between TAS-20 score and RE score (r=-0.227, P<0.05) and IN score (r=-0.538, P<0.01) was statistically significant in patients with mental disorder. Conclusion Patients with mental disorder have different levels of self-reflection and insight impairment. Patients with depression suffer from a lower degree of self-reflection than schizophrenia patients. Key words: Self-reflection; Insight; Schizophrenia; Depressive disorder

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 score0.079
Threshold uncertainty score0.583

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 head0.011
GPT teacher head0.287
Teacher spread0.276 · 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

Citations2
Published2018
Admission routes1
Has abstractyes

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