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The relationship of dissociative experience, alexithymia, and non-suicidal self-harming behavior

2020· article· en· W3138300423 on OpenAlexaboutno aff
Vimal Chandra Bhagat, Gaukaran Janghel, Rajesh Kumar Ajagallay

Bibliographic record

VenueInternational Journal of Psychiatry Research · 2020
Typearticle
Languageen
FieldPsychology
TopicSuicide and Self-Harm Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaDissociative Experiences ScaleDissociativeClinical psychologyToronto Alexithymia ScalePsychiatryPsychologyAnxietyDissociative disordersBorderline personality disorderMedicineCognition

Abstract

fetched live from OpenAlex

Introduction: Nonsuicidal self-injury (NSSI) is the deliberate injury to body tissue without any suicidal intent, which is culturally or socially unacceptable. It includes a range of behavior such as cutting or scratching of the skin, self-battery, and self-poisoning. Objective: The objective of the study is to find out relationships between NSSI, specific psychological traits (such as alexithymia and dissociation), and sociodemographic factors. Materials and Methods: The study was conducted at the Department of Psychiatry, LAMGMC and associated hospital Raigarh Chhattisgarh and involved patients reported in the department of psychiatry both as outpatient and inpatient, with a history of self-harming behavior (between 18 and 60 years of age) (N = 500). The study was done by the use of Inventory of Statements about Self-Injury (ISAS), Dissociative Experience Scale (DES), and Toronto Alexithymia Scale (TAS). Results: The majority of the subjects with NSSI are adult, female, and unemployed. NSSI is associated with dissociative symptoms, alexithymia, anxiety, depression, substance abuse, tension-type headache, and type B personality. Conclusion: Dissociative symptoms and alexithymia are highly correlated with NSSI.

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)0.001
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 score0.019
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.001
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 head0.111
GPT teacher head0.448
Teacher spread0.337 · 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

Citations1
Published2020
Admission routes1
Has abstractyes

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