Long-term outcomes of cognitive–behavioral treatments for posttraumatic stress disorder among female rape survivors.
Bibliographic record
Abstract
OBJECTIVE: We conducted a long-term follow-up (LTFU) assessment of participants from a randomized controlled trial comparing cognitive processing therapy (CPT) with prolonged exposure (PE) for posttraumatic stress disorder (PTSD). Competing hypotheses for positive outcomes (i.e., additional therapy, medication) were examined. METHOD: Intention-to-treat (ITT) participants were assessed 5-10 years after participating in the study (M = 6.15, SD = 1.22). We attempted to locate the 171 original participants, women with PTSD who had experienced at least one rape. Of 144 participants located, 87.5% were reassessed (N = 126), which constituted 73.7% of the original ITT sample. Self-reported PTSD symptoms were the primary outcome. Clinician-rated PTSD symptoms, comorbid diagnoses, and self-reported depression were secondary outcomes. RESULTS: Substantial decreases in symptoms due to treatment (as reported in Resick, Nishith, Weaver, Astin, & Feuer, 2002) were maintained throughout the LTFU period, as evidenced by little change over time from posttreatment through follow-up (effect sizes ranging from pr = .03 to .14). No significant differences emerged during the LTFU between the treatment conditions (Cohen's d = 0.06-0.29). The ITT examination of diagnostics indicated that 22.2% of CPT and 17.5% of PE participants met the diagnosis for PTSD according to the Clinician-Administered PTSD Scale (Blake et al., 1995) at the LTFU. Maintenance of improvements could not be attributed to further therapy or medications. CONCLUSIONS: CPT and PE resulted in lasting changes in PTSD and related symptoms over an extended period of time for female rape victims with extensive histories of trauma.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".