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Record W2353034744

The role of personality traits in cognitive function of depression with cognitive impairments

2014· article· en· W2353034744 on OpenAlexaboutno aff
Dai Yuanyua

Bibliographic record

VenueJournal of International Psychiatry · 2014
Typearticle
Languageen
FieldPsychology
TopicCognitive Abilities and Testing
Canadian institutionsnot available
Fundersnot available
KeywordsPsychologyPsychoticismWechsler Adult Intelligence ScaleNeuroticismExtraversion and introversionHamdCognitionEysenck Personality QuestionnaireWisconsin Card Sorting TestClinical psychologyPersonalityDepression (economics)PsychiatryBig Five personality traitsDevelopmental psychologyRating scaleNeuropsychology
DOInot available

Abstract

fetched live from OpenAlex

Objective The study investigated on the association of personality traits and cognitive function in depression with cognitive impairments,and whether personality factors moderated the relationship between depression and cognitive function. Methods All participants underwent the examination of Hamilton Depression Scale( HAMD),Montreal Cognitive Assessment( MoCA),and then were divided into two groups: the depression group with cognitive impairments and the healthy control group. They all completed the Eysenck Personality Questionnaire( EPQ) and a series of cognitive assessments,such as the Wisconsin Card Sorting Test( WCST) and parts of scales of Wechsler Adult Intelligence Scale( WAIS) and Wechsler Memory Scale( WMS). Results The scores of Psychoticism( P) and Neuroticism( N) in depression group were more than those in control group,but there were no significant differences in the score of Extraversion( E). The HAMD、personality traits and the interaction of them could have effects on cognitive function in depression disorders. Conclusion The personality factors is not only influenced the cognitive function of depression with cognitive impairments directly but also modified the interaction of depression and cognitive function. Interventions aimed at decreasing one's P、N and increasing one's E could potentially attenuate some of the cognitive impairments that are associated with depression.

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)0.000
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 score0.060
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.303
Teacher spread0.290 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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