Dissociative symptoms as measured by the Cambridge Depersonalization Scale in patients with a bipolar disorder
Bibliographic record
Abstract
Abstract Background The Cambridge Depersonalization Scale (CDS) characterizes the quality, frequency, and duration of dissociative symptoms. While the psychometric properties of the CDS have been evaluated in primary dissociative disorder, this has been insufficiently addressed among other psychiatric patient groups such as patients with a bipolar disorder (BD). Methods Outpatients with variable mood (n = 73) responded to a survey that assessed dissociative symptoms and other characteristics. We used factor analysis and McDonald's omega to evaluate psychometric properties of the CDS, and correlations with other characteristics. Results Previously suggested multifactorial models of the CDS were not supported, but the single-dimensional model fit both dichotomized (p = 0.31, CFI = 0.99, RMSEA = 0.02, ECV 70%) and trichotomized CDS responses (p = 0.06, CFI = 0.96, RMSEA = 0.04, ECV 47%). The CDS showed high internal consistency (ω = 0.96). CDS factor scores correlated with symptom severity on the Quick Inventory for Depressive Symptoms (QIDS-SR-16) (ρ = 0.59), the Social Phobia Inventory (ρ = 0.52), the American Association of Psychiatry Severity measure for Panic Disorders (ρ = 0.46), the Childhood Trauma Questionnaire (ρ = 0.44), and the Trauma Screening Questionnaire (ρ = 0.53). Two abbreviated versions of the CDS, retaining the best 14 or 7 items were proposed. Limitations The sample size remained moderate. Conclusions The CDS is a psychometrically sound, unidimensional measure with clinical impact to detect and characterize dissociative symptoms in BD patients. Establishing the reliability and validity of the abbreviated scales for screening necessitates further study.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".