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Record W4285670041 · doi:10.34883/pi.2020.11.1.010

Interrelation of Alexithymia and the structure of Personal semantic self-Assessment of Patients in the state of Partial Mental Maladaptation with Psychosomatic Diseases

2020· article· ru· W4285670041 on OpenAlexaboutno aff
В.Д. Мишиев, В.Ю. Омельянович, М.А. Трещинская, Eugenia Grinevich

Bibliographic record

VenueПсихиатрия психотерапия и клиническая психология · 2020
Typearticle
Languageru
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaMaladaptationPsychologyClinical psychologyToronto Alexithymia ScalePartial correlationMultilevel modelNeuroticismDevelopmental psychologyPersonalityCorrelationPsychiatrySocial psychology

Abstract

fetched live from OpenAlex

В статье изложены результаты исследования, целью которого было выявление и структурирование гендерных особенностей влияния алекситимии на уровень семантической самооценки пациентов в состоянии парциальной психической дезадаптации и страдающих психосоматическими заболеваниями. Для достижения поставленной цели были решены следующие исследовательские задачи: в рамках отдельно рассматриваемых гендерных групп исследованы выраженность алекситимии у пациентов, страдающих психосоматическими заболеваниями, респондентов в состоянии парциальной психической дезадаптации и у практически здоровых; проведено сравнение выраженности алекситимии между исследуемыми группами и гендерами; проведена оценка взаимосвязи выраженности алекситимии с базовыми социально-психологическими и кросс-культуральными характеристиками обследованного контингента; обнаружены взаимосвязи выраженности алекситимии и семантической самооценки представителей исследуемых групп и выявлены гендерные особенности этих взаимосвязей.Исследование проводилось на репрезентативном материале, состоящем из 1400 респондентов, с использованием методики «Личностный (семантический) дифференциал», Торонтской алекситимической шкалы и дальнейшим статистическим анализом полученных результатов с использованием иерархического кластерного анализа, однофакторного дисперсионного анализа Фишера, вычисления коэффициента ранговой корреляции Спирмена и коэффициента частичной регрессии η2. Thearticlepresentstheresultsofthestudyaimedatidentificationandstructuringthegenderfeatures of the influence of alexithymia on the level of semantic self-esteem of patients in the state of partial mental maladaptation with psychosomatic diseases. to achieve this goal, the following research tasks were accomplished: within the framework of separately considered gender groups, there was studied the severity of alexithymia in patients with psychosomatic diseases, the respondents in the state of partial mental maladaptation, and practically healthy ones. there was done the comparison of severity of alexithymia between the studied groups and genders. there was made the evaluation of the relationship between the severity of alexithymia and the basic socio-psychological and cross- cultural characteristics of the studied contingent. there was revealed the relationship between the severity of alexithymia and the semantic self-esteem of the representatives of the studied groups; the gender features of these relationships were revealed.the study was conducted on the representative material, which consisted of 1400 respondents, using the Personal (Semantic) differential approach, the toronto alexithymic scale, and further statistical analysis of the obtained results using hierarchical cluster analysis, Fisher’s one-factor analysis of variance, calculation of the Spearman rank correlation coefficient, and the partial regression η2.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.008
GPT teacher head0.253
Teacher spread0.246 · 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 source (direct Gemma or distilled Codex), 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".

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Citations0
Published2020
Admission routes1
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