Distinguishing Among Symptoms of Posttraumatic Stress Disorder, Complex Posttraumatic Stress Disorder, and Borderline Personality Disorder in a Community Sample of Women
Bibliographic record
Abstract
The diagnosis of complex posttraumatic stress disorder (CPTSD) was included in the ICD-11 in 2018. Debates are still ongoing in the scientific community regarding the conceptual distinction between CPTSD symptoms and those of comorbid PTSD and borderline personality disorder (BPD). The present study aimed to determine whether (a) patterns of symptoms reported by women in a community sample would reveal a CPTSD profile distinct from PTSD and BPD profiles and (b) the resulting profiles could be compared on measures of cumulative childhood trauma exposure, dissociation, and life satisfaction. Women who reported at least one potentially traumatic experience (N = 438) completed questionnaires assessing PTSD, CPTSD, and BPD symptoms. We performed latent profile analyses testing seven models, with the five-profile model emerging as the most appropriate solution. The profiles were characterized as "high PTSD symptoms" (12.0%), "high CPTSD symptoms" (7.6%), "high BPD symptoms" (9.9%), "high CPTSD and BPD symptoms" (3.8%), and "low symptoms" (66.7%). Group comparisons revealed that the profiles characterized by high CPTSD symptoms, high BPD symptoms, and high CPTSD and BPD symptoms tended to include participants with higher levels of cumulative childhood trauma exposure and symptoms of dissociation and lower ratings of life satisfaction compared to the profiles characterized by high PTSD symptoms and low symptoms, ds = 0.55-1.06. These findings support the distinction between ICD-11 CPTSD symptoms and those of PTSD and BPD, promoting an integrative approach to understanding trauma sequelae, diagnosis, and treatment.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".