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Record W4249666756 · doi:10.1016/s0924-9338(10)70335-7

P01-130 - Alexithymia and Suicide Risk among Patients with Obsessive-compulsive Disorder

2010· article· en· W4249666756 on OpenAlexaboutno aff
Domenico De Berardis, Nicola Serroni, C. Ranalli, Daniela Campanella, Francesco Saverio Moschetta, Alessandro Carano, M Caltabiano, Luigi Olivieri, Rosa Maria Salerno, Giovanni Martinotti, Luigi Janiri, Massimo Di Giannantonio

Bibliographic record

VenueEuropean Psychiatry · 2010
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsAlexithymiaToronto Alexithymia ScalePsychologySuicidal ideationClinical psychologyRating scalePsychiatryDepression (economics)IdeationFeelingPoison controlMedicineInjury preventionDevelopmental psychology

Abstract

fetched live from OpenAlex

Objective The aim of our study was to evaluate the relationships between alexithymia and suicidal ideation in a sample of adult outpatients with obsessive-compulsive disorder (OCD). Methods A sample of 90 adult outpatients with DSM-IV diagnosis of OCD were tested with tested with the Yale-Brown Obsessive Compulsive Scale, Toronto Alexithymia Scale (TAS-20), Scale for Suicide Ideation (SSI) and Montgomery-Asberg Depression Rating Scale (MADRS). Results 35 subjects were categorized as alexithymics and showed earlier onset, longer duration of illness and more likelihood to have a chronic course than nonalexithymics; they also scored higher on the MADRS and SSI. Results of a linear regression showed that chronic OCD course together with Difficulty in Identifying Feelings dimension of TAS-20 and higher MADRS scores were significantly associated with higher scores on the SSI. Conclusions Suicidal ideation is frequent among adult outpatients with OCD and is strongly related to the presence of alexithymia and depressive symptoms. Implications are discussed.

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 score0.033
Threshold uncertainty score0.864

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.003
GPT teacher head0.212
Teacher spread0.209 · 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

Citations2
Published2010
Admission routes1
Has abstractyes

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