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Factors of Anxiety-Affective Symptoms Persistence in Depressions of Various Origins

2023· article· en· W4323041078 on OpenAlexaboutno aff
Kalinin Vv, M A Syrtsev, A.A. Zemlyanaya, Е. А. Федоренко, L V Sokolova

Bibliographic record

VenuePsikhiatriya · 2023
Typearticle
Languageen
FieldPsychology
TopicPersonality Disorders and Psychopathology
Canadian institutionsnot available
Fundersnot available
KeywordsNeuroticismPsychopathologyClinical psychologyPersistence (discontinuity)Schizophrenia (object-oriented programming)PsychologyAnxietyAlexithymiaPositive and Negative Syndrome ScalePsychiatryPersonalityPsychosis

Abstract

fetched live from OpenAlex

The aim of study: the current study has been caried out in order to find the anxiety-affective symptomatology persistence duration (AASPD) under standard antidepressants therapy and its neurobiological and premorbid personality predictors in different diagnostic groups. Patients and methods: 191 patients were included into study. Among them 57 patients with organic anxiety affective disorder (OAAD), 41 with endogenous depression (ED), 14 with anxiety neurotic disorder (AND) and 93 with schizophrenia. The Munich personality test and Toronto alexithymia scale were used for assessment of premorbid personality, while SCL-90 and MMSE — for the assessment of psychopathology structure. For the assessment of handedness Annett scale has been used. The product moment correlation analysis was performed for the assessment of relationships between premorbid personality, MMSE and Annett scale score and psychopathology persistence. Results: the symptomatology persistence was maximal in OAAD (21.37 ± 8.33) and smallest in ED (16.27 ± 4.38). Neuroticism correlated positively with AASPD in ED ( r = 0.481; р = 0.001). Duration of disorder correlated positively with AASPD ( r = 0,286; p = 0.031), while MMSE correlated negatively ( r = –0.267; p = 0.045) in OAAD. In AND the negative correlation between MMSE and AASPD ( r = –0.585; p = 0.028) and between Annett score and AASPD ( r = –0.617; p = 0.032). No stochastically significant correlations were revealed in schizophrenia. Conclusion: the data obtained are important both for further study of the pathogenesis of these disorders and for the prediction and prevention of affective disorders in clinical practice.

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 score0.014
Threshold uncertainty score0.588

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.039
GPT teacher head0.328
Teacher spread0.289 · 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
Published2023
Admission routes1
Has abstractyes

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