The relationship between treatment accessibility and preference amongst out-of-treatment individuals who engage in non-medical prescription opioid use

Abstract

Background Relatively little is known regarding the perception of medication-assisted treatments (MATs) and other treatment options amongst individuals that engage in non-medical prescription opioid use. This study surveyed out-of-treatment individuals that misuse opioids to better understand how perceived access to treatment shapes treatment preference. Methods Participants (n=357) were out-of-treatment adults registered as workers on the Amazon Mechanical Turk platform who reported current non-medical prescription opioid use. Participants were surveyed regarding demographics, insurance status, attitudes toward opioid use disorder (OUD) treatments, and self-reported symptoms of OUD. Results Participants who were male, did not have health insurance, and knew that counseling-type services were locally available were most likely to first attempt counseling/detox treatments (χ2(6) = 30.19, p<.001). Participants who met criteria for severe OUD, used heroin in the last 30 days, knew their insurance covered MAT, and knew of locally available MAT providers were most likely to first attempt MAT (χ2(4) = 26.85, p<.001). Participants with insurance and who knew of locally available physicians were most likely to attempt physician visits without the expressed purpose of MAT (χ2(3) = 24.75, p<.001). Conclusion Out-of-treatment opioid users were particularly interested in counseling-based services and medical care that could be attained from a primary-care physician. Results suggest that insurance coverage and perceived access to OUD treatment modalities influences where out-of-treatment opioid users might first seek treatment; understanding the factors that shape treatment preference is critical in designing early interventions to effectively reach this population.

Emerging Evidence for Cannabis' Role in Opioid Use Disorder

“… 72 In this review, we focus on the most widely used OUD therapies, their shortcomings, and the bottlenecks to accessing them. 11 …”

“…9 , 78 , 79 There are only 1590 methadone distributers in the United States, which are highly regulated clinics that are concentrated in urban areas, creating geographical disparities in OUD treatment. 10 , 11 , 79 In addition to geographical barriers, these clinics frequently have stringent and stigmatizing compliance requirements, such as daily visits and frequent urine screenings for illicit drugs. 11 , 80 Although these barriers to treatment could potentially be addressed through concerted efforts to expand access, 40% of patients still relapse within 1 year of initiating methadone therapy.…”

“…10 , 11 , 79 In addition to geographical barriers, these clinics frequently have stringent and stigmatizing compliance requirements, such as daily visits and frequent urine screenings for illicit drugs. 11 , 80 Although these barriers to treatment could potentially be addressed through concerted efforts to expand access, 40% of patients still relapse within 1 year of initiating methadone therapy. 67 …”

Feasibility, acceptability, and validity of crowdsourcing for collecting longitudinal alcohol use data

“…More recently, researchers in addiction science have also begun to utilize mTurk. These studies have spanned a diverse range of theoretical perspectives and methods including, but not limited to, behavioral economics (e.g., Bickel, Jarmolowicz, Mueller, Koffarnus, & Gatchalian, 2012;Johnson, Herrmann, & Johnson, 2015;Kaplan et al, 2017;Morris et al, 2017;Peters, Rosenberry, Schauer, O'Grady, & Johnson, 2017), tobacco control policy (e.g., Lazard et al, 2017;Pearson et al, 2016;Shi, Wang, Emery, Sheerin, & Romer, 2017), behavioral addictions (e.g., Bock et al, 2016;Gearhardt, Corbin, & Brownell, 2016), public opinion related to addiction-related policy (e.g., Huhn, Tompkins, & Dunn, 2017;Rudski, 2016;Wen, Higgins, Xie, & Epstein, 2016), and measure development (e.g., Dunn, Barrett, Herrmann et al, 2016;Dunn, Barrett, Yepez-Laubach et al, 2016;Lac & Berger, 2013). Existing evidence supports the reliability and validity of common substance use scales when used on mTurk (e.g., the Alcohol Use Disorder Identification Test [AUDIT]; Kim & Hodgins, 2017).…”

Recovery Goals and Long-term Treatment Preference in Persons Who Engage in Nonmedical Opioid Use

“…Individuals engaging in non-medical opioid use who meet criteria for OUD may choose not to engage in OMT, instead preferring supervised withdrawal only, or counseling and/or 12step based mutual support groups for ongoing care. Our group recently reported that 46.2% of individuals engaging in non-medical opioid use had a negative view of OMT and/or naltrexone (Huhn, Tompkins, and Dunn, 2017). Individual motivation for treatment and conceptualization of recovery likely affects where and for how long patients may choose to engage in treatment.…”