Social–Emotional Profiles of PTSD, Complex PTSD, and Borderline Personality Disorder Among Racially and Ethnically Diverse Young Adults: A Latent Class Analysis
Bibliographic record
Abstract
The debate around the construct validity of complex posttraumatic stress disorder (CPTSD) has begun to examine whether CPTSD diverges from posttraumatic stress disorder (PTSD) when it co-occurs with the diagnosis of borderline personality disorder (BPD). The present study (a) examined the construct validity of CPTSD through a latent class analysis of a non-treatment-seeking sample of young trauma-exposed adults and (b) characterized each class in terms of trauma characteristics, social emotions (e.g., shame, guilt, blame), and interpersonal functioning. A total of 23 dichotomized survey items were chosen to represent the symptoms of PTSD, CPTSD, and BPD and administered to 197 trauma-exposed participants. Fit statistics compared models with 2-4 latent classes. The four-class model showed the best fit statistics and clinical interpretability. Classes included a "high PTSD+CPTSD+BPD" class, characterized by high-level endorsement of all symptoms for the three diagnoses; a "moderate PTSD+CPTSD+BPD" class, characterized by endorsement of some symptoms across all three diagnoses; a "PTSD" class, characterized by endorsement of the ICD-11 PTSD criteria; and a "healthy" class, characterized by low symptom endorsement overall. Pairwise comparisons showed individuals in the high PTSD+CPTSD+BPD class to have the highest levels of psychological distress, traumatic event history, adverse childhood experiences, and PTSD symptoms. Shame was the only social emotion to significantly differ between the classes, p = .002, η² = .16. The findings diverge from the literature, indicating an overlap of PTSD, CPTSD, and BPD symptoms in a non-treatment-seeking community sample. Further, shame may be a central emotion that differentiates between presentation severities following trauma exposure.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".