The opioid epidemic has spurred urgent and widespread legal, medical, and behavioral approaches to promote effective opioid prescribing. Between 21-29% of chronic pain patients misuse prescription (Rx) opioids (Vowles et al., 2015). Responsible opioid prescribing depends on accurate and early identification of misuse as well as comprehensive understanding of predictors of pain treatment seeking and successful pain management (Dowell, Haegerich, & Chou, 2016). One promising and practical pain management solution is remote self-monitoring, a state-of-the-art assessment tool shown to be superior to retrospective assessment (e.g., Heron & Smyth, 2010). Unfortunately, low rates of adherence have impeded the use of remote self- monitoring among chronic pain patients (e.g., Jamison et al., 2016), even when non-monetary rewards were included (Jamison et al., 2017). One robust strategy for improving adherence is contingency management (CM). While CM has been widely used in research, translation to clinical practice has been limited, due to practical barriers (e.g., costs) and counselor concerns. This Stage 1 behavioral therapies development grant (Rounsaville et al., 2001) seeks to pilot test a novel, fully automated CM app (DynamiCare Rewards) for promoting daily self-monitoring of pain symptom severity and related variables (e.g., sleep, mood), as well as quantity and frequency of Rx opioid, alcohol, and Rx benzodiazepine use in a sample of chronic pain patients currently prescribed opioids. We plan to customize the DynamiCare Rewards app for chronic pain in primary care in the first 3 months of the study. In the following 18 months, a pilot RCT (N=80) will be conducted comparing participants receiving CM for completing daily self-monitoring surveys (CM group) and those receiving only electronic daily reminders to complete the survey (control group) over a 30-day period. Primary outcome measures include number of daily surveys completed and longest period of sustained adherence to survey completion. We hypothesize that those in the CM group will complete more daily self-monitoring surveys and have a longer sustained period of daily survey completion compared to controls. Secondarily, we will examine feasibility; acceptability; and accuracy of Rx opioid, alcohol, and Rx benzodiazepine use reporting. This dissertation proposal will provide benchmark data on the efficacy and feasibility of CM to promote self- monitoring of pain severity, related factors, and Rx opioid use. More comprehensive information about pain experience and Rx opioid use has the potential to help clinicians provide better care and make better opioid prescribing decisions. Additionally, findings will inform future research on early identification, prevention, and intervention for Opioid Use Disorders.

Public Health Relevance

Responsible opioid prescribing depends on effective identification of prescription (Rx) opioid misuse as well as an understanding of clinically-relevant variables (e.g., pain). Remote self-monitoring is a promising, practical, and readily available method for tracking these variables; however, low rates of adherence have impeded the use of remote self-monitoring among chronic pain patients, limiting the potential beneficial effects. The present study will examine the efficacy and feasibility of contingency management (CM; as delivered by an innovative CM app) for improving self-monitoring of clinically- relevant variables among chronic pain patients, which will inform future research on effective pain management and early identification of Opioid Use Disorders.

Agency
National Institute of Health (NIH)
Institute
National Institute on Drug Abuse (NIDA)
Type
Dissertation Award (R36)
Project #
3R36DA046671-01S1
Application #
9926478
Study Section
Special Emphasis Panel (ZRG1)
Program Officer
Thomas, David A
Project Start
2018-09-30
Project End
2020-08-31
Budget Start
2018-09-30
Budget End
2019-08-31
Support Year
1
Fiscal Year
2019
Total Cost
Indirect Cost
Name
Virginia Commonwealth University
Department
Psychology
Type
Schools of Arts and Sciences
DUNS #
105300446
City
Richmond
State
VA
Country
United States
Zip Code
23298