Sensitivity and specificity of the Posttraumatic Stress Disorder Checklist for <i>DSM‐5</i> in a Canadian psychiatric outpatient sample
Bibliographic record
Abstract
The Posttraumatic Stress Disorder (PTSD) Checklist for DSM-5 (PCL-5) is a widely used, self-report measure that is employed to assess PTSD symptom severity and determine the presence of probable PTSD in various trauma-exposed populations. The PCL-5 is often administered in clinical settings as a screening tool for PTSD, with a suggested cutoff score of 33 indicating a probable PTSD diagnosis. Recent research indicates that a higher cutoff may be required in psychiatric samples. In the present study, we aimed to determine the sensitivity and specificity of the PCL-5 in a Canadian outpatient psychiatric sample and establish an optimal cutoff score for detecting probable PTSD in this sample. Participants were 673 individuals who reported a history of trauma exposure and were assessed using a semistructured interview and self-report measures. Individuals diagnosed with PTSD (N = 193) reported a mean PCL-5 score of 56.57, whereas individuals without PTSD (N = 480) reported a mean score of 33.56. A score of 45 was determined to be the optimal cutoff score in this sample, balancing sensitivity and specificity while detecting a probable diagnosis of PTSD. Consistent with findings in other psychiatric samples, these findings indicate that in an outpatient psychiatric sample with a history of exposure to a variety of trauma types, a higher cutoff score is required to determine probable PTSD. In addition, given the estimated rate of false positives even with a higher cutoff, follow-up diagnostic assessments are recommended.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".