Project Title
The Effects of Drug of Choice on Substance Use Recovery
Faculty Mentor(s) Name(s)
Dr. Lee Gillis
Abstract
In North America, the epidemic of substance misuse is impacting the overall health of the population (Lipari & Van Horn, 2017). More than 20 million people have been diagnosed with substance use disorder (SUD) in 2019 alone (SUD; Substance Abuse and Mental Health Services Administration [SAMHSA], 2020). To support those battling substance misuse, the use of individualized substance use treatment programs is becoming more prevalent (Pierce et. al., 2009). However, the impact drug of choice (DOC) has on SUD treatment programs is often overlooked due to the lack of research in the field (Cease, 2019). Recent research suggests that there may be a difference in treatment-seeking and treatment-engaging behaviors when examining the relationship between DOC and approach/avoidance tendencies (Johnson et. al., 2020). Stahler et. al. explored how a client’s DOC impacts their treatment to better define recovery amongst clients (2020). The study found that opioid users responded better to residential therapy opposed to outpatient. However, other forms of therapy need to be explored. Additionally, those who used marijuana as their DOC were least likely to benefit from residential treatment. Chapman et al. explored the relationship between self-reported drug use prior to intake and treatment effectiveness (2018). Clients with higher reported prior drug use experienced higher levels of symptom distress and lower awareness. However, they found that treatment was equally effective for clients regardless of reported prior drug use. Exploring the impact DOC has on individuals could prove to be useful in SUD recovery treatment. This research examined the relationship between DOC and treatment completion by using quantitative and qualitative data from a deidentified database. This data was provided by Enviros Shunda Creek, a 90-day Outdoor Behavioral Healthcare (OBH) program that treats young adult males ages 18-24 with SUD. In this study, correlational analysis is used to explore a link between the clients’ DOC and their progress or repetition of treatment. At Shunda, a client is considered to have completed the program at the 90-day mark, or when the client and treatment staff decides, he is equipped to go home. Some clients choose to repeat the program after leaving it once before, and a correlational analysis was also used to distinguish a link between DOC and repeated treatment at Shunda. This research has the potential that it can help indicate that users may need different types of treatment depending on their DOC, which can facilitate the treatment process and get people the specialized help they need. Our research used The Personal Experience Inventory (PEI) and the 2. The PEI has multiple subscales that explore the frequency, duration, and age of onset for use of twelve categories of drugs (Winters and Henly, 1989). One subscale called the Personal Involvement with Chemicals Scales (PICS) examines drug use prior to receiving SUD treatment. While another subscale called the Substance Use Frequency Scale (SUFS) is a self-report measure that explores the severity of a client’s drug use specifically within the last 90 days. The FAI measures a client's outcome 6 months post-treatment. In this research we assess the impact DOC has on a client’s pathway to recovery in this sample. From a de-identified alumni dataset, relationships were found between the client’s reported drug of choice and their attitudes towards their recovery post treatment. Reported DOC was coded numerically using two codes of drug classification, the first according to the American drug schedule (DEA, 2018) and the second according to the frequency of drug use within the given sample. Drugs were coded on a scale of 1 to 9, with 1 representing drugs with a higher potential for abuse from the American schedule coding (ex. 1=alcohol, 2 = marijuana) and 1 representing drugs with the highest frequency of use amongst the sample (ex. 1= alcohol, 2= multiple drugs reported). Potential for abuse on the American coding and frequency of use on the frequency coding decreases as the number for the indicated DOC increases. Positive correlations were found between DOC and FAI questions on both scales, indicating that alumni from the Shunda program whose DOC had a higher potential for abuse reported a more difficult experience adjusting to everyday life post-treatment than those whose DOC had a lower potential for abuse. References Cease, J. E. (2019). Court-mandated substance use treatment: Implications for treatment adherence based on drug of choice (Doctoral dissertation). Chapman, J., Groark, S., Beale, M. M., Mandas, P., Argo, K., Gillis, H. L. L., & Russell, K. (2018). The relationship between self-reported prior drug use and treatment effectiveness in substance use disorder during outdoor behavioral healthcare treatment for young adult males. Journal of Therapeutic Schools and Programs, 10(1), 93-106. DEA. (2018, July 10). Drug Scheduling. https://www.dea.gov/drug-information/drug-scheduling Johnson, K., Rigg, K. K., & Eyles, C. H. (2020). Receiving addiction treatment in the US: Do patient demographics, drug of choice, or substance use disorder severity matter?. International Journal of Drug Policy, 75, 102583. Lipari, R. N., & Van Horn, S. L. (2017). Trends in substance use disorders among adults aged 18 or older. Peirce, J. M., King, V. L., & Brooner, R. K. (2009). From individual therapy to individualized treatment. In L. M. Cohen, F. L. Collins, Jr., A. M. Young, D. E. McChargue, T. R. Leffingwell, & K. L. Cook (Eds.), Pharmacology and treatment of substance abuse: Evidence- and outcome-based perspectives (pp. 153–178). Routledge/Taylor & Francis Group. Substance Abuse and Mental Health Services Administration. (2020). Key substance use and mental health indicators in the United States: Results from the 2019 National Survey on Drug Use and Health (HHS Publication No. PEP20-07-01-001, NSDUH Series H-55). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/ Stahler, G. J., Mennis, J., & DuCette, J. P. (2016). Residential and outpatient treatment completion for substance use disorders in the US: Moderation analysis by demographics and drug of choice. Addictive Behaviors, 58, 129-135. Winters, K. C., Henly, G. A., & CUQ, C. U. Q. (1989). Personal experience inventory (PEI) a measure of substance abuse in adolescents.
The Effects of Drug of Choice on Substance Use Recovery
In North America, the epidemic of substance misuse is impacting the overall health of the population (Lipari & Van Horn, 2017). More than 20 million people have been diagnosed with substance use disorder (SUD) in 2019 alone (SUD; Substance Abuse and Mental Health Services Administration [SAMHSA], 2020). To support those battling substance misuse, the use of individualized substance use treatment programs is becoming more prevalent (Pierce et. al., 2009). However, the impact drug of choice (DOC) has on SUD treatment programs is often overlooked due to the lack of research in the field (Cease, 2019). Recent research suggests that there may be a difference in treatment-seeking and treatment-engaging behaviors when examining the relationship between DOC and approach/avoidance tendencies (Johnson et. al., 2020). Stahler et. al. explored how a client’s DOC impacts their treatment to better define recovery amongst clients (2020). The study found that opioid users responded better to residential therapy opposed to outpatient. However, other forms of therapy need to be explored. Additionally, those who used marijuana as their DOC were least likely to benefit from residential treatment. Chapman et al. explored the relationship between self-reported drug use prior to intake and treatment effectiveness (2018). Clients with higher reported prior drug use experienced higher levels of symptom distress and lower awareness. However, they found that treatment was equally effective for clients regardless of reported prior drug use. Exploring the impact DOC has on individuals could prove to be useful in SUD recovery treatment. This research examined the relationship between DOC and treatment completion by using quantitative and qualitative data from a deidentified database. This data was provided by Enviros Shunda Creek, a 90-day Outdoor Behavioral Healthcare (OBH) program that treats young adult males ages 18-24 with SUD. In this study, correlational analysis is used to explore a link between the clients’ DOC and their progress or repetition of treatment. At Shunda, a client is considered to have completed the program at the 90-day mark, or when the client and treatment staff decides, he is equipped to go home. Some clients choose to repeat the program after leaving it once before, and a correlational analysis was also used to distinguish a link between DOC and repeated treatment at Shunda. This research has the potential that it can help indicate that users may need different types of treatment depending on their DOC, which can facilitate the treatment process and get people the specialized help they need. Our research used The Personal Experience Inventory (PEI) and the 2. The PEI has multiple subscales that explore the frequency, duration, and age of onset for use of twelve categories of drugs (Winters and Henly, 1989). One subscale called the Personal Involvement with Chemicals Scales (PICS) examines drug use prior to receiving SUD treatment. While another subscale called the Substance Use Frequency Scale (SUFS) is a self-report measure that explores the severity of a client’s drug use specifically within the last 90 days. The FAI measures a client's outcome 6 months post-treatment. In this research we assess the impact DOC has on a client’s pathway to recovery in this sample. From a de-identified alumni dataset, relationships were found between the client’s reported drug of choice and their attitudes towards their recovery post treatment. Reported DOC was coded numerically using two codes of drug classification, the first according to the American drug schedule (DEA, 2018) and the second according to the frequency of drug use within the given sample. Drugs were coded on a scale of 1 to 9, with 1 representing drugs with a higher potential for abuse from the American schedule coding (ex. 1=alcohol, 2 = marijuana) and 1 representing drugs with the highest frequency of use amongst the sample (ex. 1= alcohol, 2= multiple drugs reported). Potential for abuse on the American coding and frequency of use on the frequency coding decreases as the number for the indicated DOC increases. Positive correlations were found between DOC and FAI questions on both scales, indicating that alumni from the Shunda program whose DOC had a higher potential for abuse reported a more difficult experience adjusting to everyday life post-treatment than those whose DOC had a lower potential for abuse. References Cease, J. E. (2019). Court-mandated substance use treatment: Implications for treatment adherence based on drug of choice (Doctoral dissertation). Chapman, J., Groark, S., Beale, M. M., Mandas, P., Argo, K., Gillis, H. L. L., & Russell, K. (2018). The relationship between self-reported prior drug use and treatment effectiveness in substance use disorder during outdoor behavioral healthcare treatment for young adult males. Journal of Therapeutic Schools and Programs, 10(1), 93-106. DEA. (2018, July 10). Drug Scheduling. https://www.dea.gov/drug-information/drug-scheduling Johnson, K., Rigg, K. K., & Eyles, C. H. (2020). Receiving addiction treatment in the US: Do patient demographics, drug of choice, or substance use disorder severity matter?. International Journal of Drug Policy, 75, 102583. Lipari, R. N., & Van Horn, S. L. (2017). Trends in substance use disorders among adults aged 18 or older. Peirce, J. M., King, V. L., & Brooner, R. K. (2009). From individual therapy to individualized treatment. In L. M. Cohen, F. L. Collins, Jr., A. M. Young, D. E. McChargue, T. R. Leffingwell, & K. L. Cook (Eds.), Pharmacology and treatment of substance abuse: Evidence- and outcome-based perspectives (pp. 153–178). Routledge/Taylor & Francis Group. Substance Abuse and Mental Health Services Administration. (2020). Key substance use and mental health indicators in the United States: Results from the 2019 National Survey on Drug Use and Health (HHS Publication No. PEP20-07-01-001, NSDUH Series H-55). Rockville, MD: Center for Behavioral Health Statistics and Quality, Substance Abuse and Mental Health Services Administration. https://www.samhsa.gov/data/ Stahler, G. J., Mennis, J., & DuCette, J. P. (2016). Residential and outpatient treatment completion for substance use disorders in the US: Moderation analysis by demographics and drug of choice. Addictive Behaviors, 58, 129-135. Winters, K. C., Henly, G. A., & CUQ, C. U. Q. (1989). Personal experience inventory (PEI) a measure of substance abuse in adolescents.