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Predictors of Adherence to Psychological Treatment for Insomnia and Pain: Analysis from a Randomized Trial

Koffel Erin PhD; Vitiello, Michael V. PhD; McCurry, Susan M. PhD; Rybarczyk, Bruce PhD; Von Korff, Michael ScD
The Clinical Journal of Pain: Post Acceptance: September 14, 2017
doi: 10.1097/AJP.0000000000000546
Original Article: PDF Only

Objectives:

Poor adherence to psychological treatment for insomnia is common and limits treatment gains. Very little is known about predictors of adherence among patients with chronic pain, although adherence is theorized to be more critical and more challenging for these patients. This secondary data analysis examines predictors of drop-out and therapy nonattendance in an osteoarthritis population receiving psychological treatment for insomnia and pain.

Methods:

Data were analyzed from the “Lifestyles” trial, a randomized controlled trial of a 6-week group cognitive behavioral pain coping skills intervention (CBT-P), group cognitive-behavioral therapy for pain and insomnia (CBT-PI), and an education only attention control group (EOC). The current analysis focuses on 122 participants randomized to CBT-PI from 6 primary care clinics. Measures of treatment acceptability, demographics, and symptoms were collected at baseline. Factor analysis was used to clarify the boundaries of these domains, and hierarchical regression was used to examine the incremental predictive power of these patient characteristics on therapy attendance.

Results:

Ratings of treatment acceptability were distinct from demographic and medical variables and baseline symptoms. Treatment acceptability was significantly related to session attendance and drop-out (rs ranging from 0.24 to 0.32) and was also one of the strongest predictors of session attendance (β=0.20; P<0.05).

Discussion:

Perceptions of treatment acceptability early in treatment represent a potentially modifiable target to enhance adherence to psychological treatment for insomnia and pain among patients with chronic pain. This work represents an important step towards understanding how to best maximize sleep treatments for this patient population.

The views expressed in this article are those of the authors and do not reflect the official policy or position of the US Department of Veterans Affairs.

Supported by NIH grant R01-AG031126 (M.V.V., S.M.Mc., and M.V.K.—Multiple Principal Investigators). This material is the result of work supported with resources and the use of facilities at the Minneapolis VA Health Care System, Minneapolis, MN. The authors declare no conflict of interest.

Reprints: Erin Koffel, PhD, One Veterans Drive, Minneapolis, MN 55417 (e-mail: Erin.Koffel@va.gov).

Received September 22, 2016

Received in revised form January 6, 2017

Accepted July 6, 2017

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