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Record W2157513962 · doi:10.1176/appi.ajp.159.4.660

Comparative Study of Trauma-Related Phenomena in Subjects With Pseudoseizures and Subjects With Epilepsy

2002· article· en· W2157513962 on OpenAlexaff
William Fleisher, Douglas Staley, Patricia Krawetz, Neelon Pillay, John L. Arnett, John Maher

Bibliographic record

VenueAmerican Journal of Psychiatry · 2002
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsPsychologyEpilepsyPittsburgh Sleep Quality IndexDissociativePsychiatryClinical psychologyElectroencephalographySleep qualityInsomnia

Abstract

fetched live from OpenAlex

OBJECTIVE: The purpose of this study was to examine potential differences in measures of trauma-related phenomena between subjects with pseudoseizures and subjects with intractable epilepsy. METHOD: Thirty-one adult subjects with pseudoseizures and 32 subjects with intractable epilepsy (confirmed by video-EEG) were recruited from the epilepsy unit of a tertiary care hospital. Each participant completed the Impact of Event Scale, the Davidson Trauma Scale, the Mississippi Scale for Combat-Related Posttraumatic Stress Disorder (PTSD), the Dissociative Experience Scale, and the Pittsburgh Sleep Quality Index, as well as demographic, seizure history, and family functioning measures. RESULTS: Subjects with pseudoseizures had significantly higher mean scores on the Davidson Trauma Scale, Mississippi Scale for Combat-Related PTSD, Impact of Event Scale, and Pittsburgh Sleep Quality Index than subjects with epilepsy. In addition, a significantly higher percentage of subjects with pseudoseizures had scores above the clinical cutoff level of 30 on the Dissociative Experience Scale. CONCLUSIONS: Subjects with pseudoseizures exhibited trauma-related profiles that differed significantly from those of epileptic comparison subjects and closely resembled those of individuals with a history of traumatic experiences. Interventions aimed at trauma-related issues may be beneficial for patients with pseudoseizures.

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 score0.104
Threshold uncertainty score0.549

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.260
Teacher spread0.248 · 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

Citations72
Published2002
Admission routes1
Has abstractyes

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