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Record W7071309756

A structural model for predicting alexithymia based on early maladaptive schemas with the mediation of emotional self-disclosure

2023· article· en· W7071309756 on OpenAlexaboutno aff

Bibliographic record

VenueDOAJ (DOAJ: Directory of Open Access Journals) · 2023
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaMediationPopulationToronto Alexithymia ScaleStructural equation modelingScale (ratio)
DOInot available

Abstract

fetched live from OpenAlex

Background: alexithymia means the inability to cognitively process information and regulate emotions, which is characterized by the clinical inability to identify emotions experienced by oneself or others. alexithymia is one of the factors affecting the incompatibility and interaction of couples, which has a negative effect on their interaction and compatibility, but there is a research gap in the field of predicting these schemas in the target society, so in this research, alexithymia is discussed based on Early maladaptive schemas in married people. Aims: The purpose of this research was to present a structural model for predicting alexithymia based on Early maladaptive schemas with the mediation of emotional self-disclosure. Methods: The method of descriptive research is correlation type using structural equations. The research population was all married women referred to counseling and assistance clinics in Robat Karim city for consensual divorce in the year 2019, and 200 people were selected by the available sampling method. In order to collect data, the Toronto Persian scale of alexithymia (Beshart, 2007), Early maladaptive schemas scale, short form of Yang (2003), and emotional self-disclosure scale (Snell, 2001) were used. In order to analyze the data, descriptive statistical methods and structural equations were used. Results: The results showed that emotional self-disclosure is mediating in the relationship between alexithymia and Early maladaptive schemas (p>0.05) and between alexithymia and Early maladaptive schemas. Considering emotional self-disclosure as a mediating factor, there is an indirect relationship. Conclusion: The results of this research showed that there is a direct and meaningful relationship between Early maladaptive schemas and alexithymia, so that among the variables of Early maladaptive schemas, the variables of emotional deprivation, defectiveness/shame, dependency/Incompetence, Self-sacrifice and Entitlement/Grandiosity predict alexithymia and among the variables of emotional processing, the variable of weakened and suppressed emotions predicts alexithymia and generally, alexithymia in couples can be He predicted based on the mentioned variables. Therefore, these factors should be considered in prevention and treatment programs.

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)0.003
metaresearch head score (Gemma)0.008
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 score0.011
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.003
Bibliometrics0.0020.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.160
GPT teacher head0.481
Teacher spread0.321 · 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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