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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".