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Record W2065107437 · doi:10.1080/15299732.2013.834860

Empirical Testing of Criteria for Dissociative Schizophrenia

2013· article· en· W2065107437 on OpenAlexafffund
Marie-Christine Laferrière-Simard, Tania Lecomte, Lola Ahoundova

Bibliographic record

VenueJournal of Trauma & Dissociation · 2013
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsHôpital Louis-H LafontaineUniversité de Montréal
FundersCanadian Institutes of Health Research
KeywordsDissociativeDissociative disordersPsychologyDissociative Experiences ScaleSchizophrenia (object-oriented programming)Clinical psychologyPsychiatryPositive and Negative Syndrome ScaleDissociative identity disorderDSM-5ComorbidityPsychosisSchizotypy

Abstract

fetched live from OpenAlex

This study examined the validity of dissociative schizophrenia diagnostic criteria. In the first phase, 50 participants with a psychotic disorder were administered the Dissociative Experiences Scale and the Childhood Trauma Questionnaire to identify those with dissociative characteristics. In the second phase, we selected those who had a score of 15 or above on the Dissociative Experiences Scale. Fifteen of these participants were evaluated thoroughly with the Structured Clinical Interview for DSM-IV Axis I, Structured Clinical Interview for DSM-IV Axis II, and Structured Clinical Interview for DSM-IV Dissociative Disorders to determine whether they met the criteria for dissociative schizophrenia and to generate a clinical description. Our results indicated that 24% of the individuals we tested met these criteria. We propose making mandatory 1 of the 3 dissociative symptoms of the criteria to eliminate people with only nonspecific symptoms (e.g., extensive comorbidity). According to this modified criterion, 14% of our sample would receive a diagnosis of dissociative schizophrenia. However, a more comprehensive look at the clinical picture begs the question of whether dissociative schizophrenia is truly present in every person meeting the criteria. We discuss the relevance of creating a new schizophrenia subtype and offer recommendations for clinicians.

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)0.001
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 score0.127
Threshold uncertainty score0.303

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
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 head0.058
GPT teacher head0.367
Teacher spread0.309 · 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

Citations16
Published2013
Admission routes2
Has abstractyes

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