Presented at the 2012 AAPM Annual Meeting « Back

Red Flag Personalities: Mood Lability and Oppositional Characteristics Predict Potential Opioid Misuse

Geralyn Datz, PhD, datzgeralyn@gmail.com¹, Melissa A. Bonnell, MS², Toni Merkey, MA², B. Todd Sitzman, MD³, (1) Forrest General Pain Management Program, Hattiesburg, Mississippi, (2) University of Southern Mississippi, Hattiesburg, Mississippi, (3) Advanced Pain Therapy, Hattiesburg, Mississippi

While commonly prescribed for pain, opioids are a leading cause of ER visits (1), drug treatment admissions (2), and the second leading cause of unintentional death in the US (3). Identifying patient characteristics that lead to abuse and misuse is of primary importance. Scant research exists about personality traits that are strongly associated with aberrant drug behaviors. Data from 172 patients consecutively admitted chronic pain outpatients was analyzed. Personality data obtained from the Million Behavioral Medicine Diagnostic (MBMD). Separate hierarchical regression analyses were used. Analysis adjusted for age, gender, duration of pain and pain sites. Model (1) included demographic variables, duration of pain and pain sites (F(6,147) = 2.36, p < .05). Model 1 explained 8% of variance in SOAPP-R scores. Results indicated that Pain Sites significantly predicted SOAPP-R score (p < .01). Model (2) added Depression as a psychiatric indicator. Model (2) explained 29% of variance in SOAPP-R score (F(7,146) = 8.51, p < .001). Number of Pain Sites (p < .01) and Depression (p < .001) were found to significantly predict SOAPP-R score. Model (3) added Emotional Lability and Oppositional traits. Model 3 explained 41% of variance in SOAPP-R score (F(9,144) = 10.98, p < .001), with Emotional Lability (p < .01) and Oppositional traits (p < .01) significantly predicting SOAPP-R score. Psychiatric indicators significantly predicted SOAPP-R scores, suggesting mood and personality factors increase risk of opioid misuse. In risk mitigation it is vital to consider individual differences that contribute to medication misuse. References: 1)Substance abuse treatment admissions by primary substance of abuse, according to sex, age group, race, and ethnicity, 2008: treatment episode data set (TEDS). Drug and Alcohol Services Information System. Substance Abuse and Mental Health Services Adminis 2)Trends in emergency department visits involving nonmedical use of narcotic pain relievers. The DAWN report, SAMHSA. http://store.samhsa.gov/product/DAWN10-0618. Accessed September 5, 2011. 3)Unintentional drug poisoning in the United States [July 2010]. National Center for Injury Prevention and Control. Centers for Disease Control and Prevention. http://www.cdc.gov/HomeandRecreationalSafety/pdf/poison-issue-brief.pdf. Accessed September 5, 20

Funding: None