Combining seeking safety with sertraline for PTSD and alcohol use disorders: A randomized controlled trial.
Bibliographic record
Abstract
OBJECTIVE: The current study marks the first randomized controlled trial to test the benefit of combining Seeking Safety (SS), a present-focused cognitive-behavioral therapy for co-occurring posttraumatic stress disorder (PTSD) and alcohol use disorder (AUD), with sertraline, a front-line medication for PTSD shown to also impact drinking outcomes. METHOD: Sixty-nine participants (81% female; 59% African American) with primarily childhood sexual (46%) and physical (39%) trauma exposure, and drug dependence in addition to AUD were randomized to receive a partial-dose (12 sessions) of SS with either sertraline (n = 32; M = 7 sessions) or placebo (n = 37; M = 6 sessions). Assessments conducted at baseline, end-of-treatment, 6- and 12-months posttreatment measured PTSD and AUD symptom severity. RESULTS: Both groups demonstrated significant improvement in PTSD symptoms. The SS plus sertraline group exhibited a significantly greater reduction in PTSD symptoms than the SS plus placebo group at end-of-treatment (M difference = -16.15, p = .04, d = 0.83), which was sustained at 6- and 12-month follow-up (M difference = -13.81, p = .04, d = 0.71, and M difference = -12.72, p = .05, d = 0.65, respectively). Both SS groups improved significantly on AUD severity at all posttreatment time points with no significant differences between SS plus sertraline and SS plus placebo. CONCLUSION: Results support the combining of a cognitive-behavioral therapy and sertraline for PTSD/AUD. Clinically significant reductions in both PTSD and AUD severity were achieved and sustained through 12-months follow-up, Moreover, greater mean improvement in PTSD symptoms was observed across all follow-up assessments in the SS plus sertraline group. (PsycINFO Database Record
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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 | 0.012 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".