Posttraumatic Stress Disorder and Chronic Pain Arising from Motor Vehicle Accidents: Efficacy of Interoceptive Exposure Plus Trauma-Related Exposure Therapy
Bibliographic record
Abstract
Preliminary data are presented on the pattern of treatment response of combining interoceptive exposure (IE) with trauma-related exposure therapy (TRE) in five female patients with posttraumatic stress disorder (PTSD) and comorbid chronic musculoskeletal pain originating from motor vehicle accidents. Treatment consisted of four sessions of IE followed by eight sessions of TRE. Four participants reported a reduction in PTSD symptoms after completing treatment, and three no longer met diagnostic criteria for PTSD. Although both interventions were associated with reductions in PTSD symptoms, TRE was associated with greater reductions in PTSD symptoms than IE and was particularly effective at reducing avoidance. IE was associated with larger reductions in anxiety sensitivity than TRE. Pain symptoms lessened slightly during IE and then worsened following TRE. Anxiety decreased after completing treatment, whereas panic and depressive symptoms responded less so. Three individuals completed a 3-month follow-up assessment. There was no change in their PTSD diagnostic status, and all experienced a slight loss of pre–post gains, particularly involving the return of pain. Clinical and research implications are discussed.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".