Identifying Trajectories and Predictors of Response to Psychotherapy for Post-Traumatic Stress Disorder in Adults: A Systematic Review of Literature
Bibliographic record
Abstract
OBJECTIVE: There exists considerable individual variability in the development and progression of pathological stress reactions after experiencing trauma, as well as in individuals' response to psychological interventions. Yet until recently, such individual differences had not been considered when evaluating the efficacy of therapeutic interventions for post-traumatic stress disorder (PTSD). This systematic review aims to examine the emerging literature on this subject and, specifically, to identify trajectories and predictors of psychotherapeutic response in adults with PTSD. METHOD: Four databases were searched using specific keywords without date or language restrictions. For each study, independent reviewers systematically evaluated whether it met eligibility criteria and assessed risk of bias. For included studies, reviewers completed data extraction using standard formats. Those examining how subgroups of adults respond to therapy for clinical PTSD using trajectory modeling were deemed eligible. Demographic, PTSD, clinical, and trauma-related factors associated to particular trajectories were also examined. RESULTS: Of the 1,727 papers identified, 11 were included in this analysis. Of these studies, six focused on military-related traumas and five on civilian ones. Although studies found between two and five trajectories, most supported a three-trajectory model of response categorized as responders, nonresponders, and subclinical participants. Over 22 predictors of treatment trajectories were examined. Comorbid depression, anxiety, and alcohol abuse were the strongest predictors of poor therapeutic response. Age, combat exposure, social support, and hyperarousal were moderate predictors. CONCLUSION: This review provides valuable insight into the treatment of PTSD, as it supports the heterogeneous trajectories of psychotherapeutic responses and provides avenues for the development of interventions that consider individual-level factors in treatment response.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".