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Record W2947309552 · doi:10.1080/15299732.2019.1597806

The Dissociative Subtype of PTSD Interview (DSP-I): Development and Psychometric Properties

2019· article· en· W2947309552 on OpenAlexaff
Marloes B. Eidhof, F. Jackie June ter Heide, Niels van der Aa, Monika Schreckenbach, Ulrike Schmidt, Bethany L. Brand, Ruth A. Lanius, Richard J. Loewenstein, David Spiegel, Eric Vermetten

Bibliographic record

VenueJournal of Trauma & Dissociation · 2019
Typearticle
Languageen
FieldMedicine
TopicPsychosomatic Disorders and Their Treatments
Canadian institutionsWestern University
FundersInternational Society for the Study of Trauma and Dissociation
KeywordsDerealizationDepersonalizationPsychologyDissociativeSomatizationClinical psychologyAnxietyConvergent validityPsychiatryPsychometricsBurnoutInternal consistencyEmotional exhaustion

Abstract

fetched live from OpenAlex

(DSP-I). This clinician-administered instrument assesses the presence and severity of PTSD-DS (i.e., symptoms of depersonalization or derealization) and contains a supplementary checklist that enables assessment and differentiation of other trauma-related dissociative symptoms (i.e., blanking out, emotional numbing, alterations in sensory perception, amnesia, and identity confusion). The psychometric properties were tested in 131 treatment-seeking individuals with PTSD and histories of multiple trauma, 17.6 % of whom met criteria for PTSD-DS in accordance with the DSP-I. The checklist was tested in 275 treatment-seeking individuals. Results showed the DSP-I to have high internal consistency, good convergent validity with PTSD-DS items of the CAPS-5, and good divergent validity with scales of somatization, anxiety and depression. The depersonalization and derealization scales were highly associated. Moreover, the DSP-I accounted for an additional variance in PTSD severity scores of 8% over and above the CAPS-5 and number of traumatic experiences. The dissociative experiences of the checklist were more strongly associated with scales of overall distress, somatization, depression, and anxiety than scales of depersonalization and derealization. In conclusion, the DSP-I appears to be a clinically relevant and psychometrically sound instrument that is valuable for use in clinical and research settings.

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)0.000
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 score0.371
Threshold uncertainty score0.212

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.035
GPT teacher head0.282
Teacher spread0.247 · 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

Citations27
Published2019
Admission routes1
Has abstractyes

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