Volume 35, Issue 4 pp. 330-338
RESEARCH ARTICLE

In rape trauma PTSD, patient characteristics indicate which trauma-focused treatment they are most likely to complete

John R. Keefe MA

Corresponding Author

John R. Keefe MA

Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA

Correspondence

John R. Keefe, Department of Psychology, University of Pennsylvania, 425 S. University Avenue, Philadelphia, PA 19146.

Email: [email protected]

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Shannon Wiltsey Stirman PhD

Shannon Wiltsey Stirman PhD

Psychiatry and Behavioral Sciences, Palo Alto Veterans Affairs Health System, Palo Alto, CA, USA

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Zachary D. Cohen MA

Zachary D. Cohen MA

University of Pennsylvania, Philadelphia, PA, USA

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Robert J. DeRubeis PhD

Robert J. DeRubeis PhD

Department of Psychology, University of Pennsylvania, Philadelphia, PA, USA

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Brian N. Smith PhD

Brian N. Smith PhD

National Center for PTSD, VA Boston Healthcare System, Boston, MA, USA

Department of Psychiatry, Boston University School of Medicine, Boston, MA, USA

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Patricia A. Resick PhD

Patricia A. Resick PhD

Duke University, Durham, NC, USA

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First published: 28 February 2018
Citations: 52

Clinical Trial Registration: NCT00239772

Funding information: Grant sponsor: National Institute of Mental Health; Grant number: NIH-1 R01-MH51509; Grant sponsor: MQ: Transforming mental health; Grant number: MQ14PM_27.

Abstract

Background

Dropout rates for effective therapies for posttraumatic stress disorder (PTSD) can be high, especially in practice settings. Although clinicians have intuitions regarding what treatment patients may complete, there are few systematic data to drive those judgments.

Methods

A multivariable model of dropout risk was constructed with randomized clinical trial data (n = 160) comparing prolonged exposure (PE) and cognitive processing therapy (CPT) for rape-induced PTSD. A two-step bootstrapped variable selection algorithm was applied to identify moderators of dropout as a function of treatment condition. Employing identified moderators in a model, fivefold cross-validation yielded estimates of dropout probability for each patient in each condition. Dropout rates between patients who did and did not receive their model-indicated treatment were compared.

Results

Despite equivalent dropout rates across treatments, patients assigned to their model-indicated treatment were significantly less likely to drop out relative to patients who did not (relative risk = 0.49 [95% CI: 0.29–0.82]). Moderators included in the model were: childhood physical abuse, current relationship conflict, anger, and being a racial minority, all of which were associated with higher likelihood of dropout in PE than CPT.

Conclusions

Individual differences among patients affect the likelihood they will complete a particular treatment, and clinicians can consider these moderators in treatment planning. In the future, treatment selection models could be used to increase the percentage of patients who will receive a full course of treatment, but replication and extension of such models, and consideration of how best to integrate them into routine practice, are needed.

CONFLICT OF INTEREST

Patricia A. Resick is the developer of one of the two treatments examined in this manuscript (cognitive processing therapy) and an author of both the original therapy manual “Cognitive Processing Therapy for Rape Victims: A Treatment Manual” and the more recent “Cognitive Processing Therapy for PTSD: A Comprehensive Manual.”

The full text of this article hosted at iucr.org is unavailable due to technical difficulties.