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The Relationship Between Client Characteristics and Wraparound Services in Substance Use Disorder Treatment Centers
Maria Paino1, Lydia Aletraris2, Paul Roman2
1Department of Sociology, Anthropology, Social Work and Criminal Justice, Oakland University, Rochester, Michigan.
Substance use disorder (SUD) treatment centers offer few wraparound services, despite recommendations. Client characteristics influence service availability, but most centers do not provide comprehensive care.
Area of Science:
- Addiction Medicine
- Public Health
- Health Services Research
Background:
- The National Institute on Drug Abuse (NIDA) recommends comprehensive treatment for substance use disorder (SUD), including wraparound services addressing medical, mental health, and social needs.
- Wraparound services are crucial for a holistic approach to SUD treatment, aiming to improve patient outcomes by addressing co-occurring conditions and social determinants of health.
Purpose of the Study:
- To assess the relationship between client characteristics and the availability of wraparound services in SUD treatment centers.
- To understand how patient demographics and referral sources correlate with the provision of ancillary support services.
Main Methods:
- Utilized two nationally representative samples of SUD treatment centers.
- Employed negative binomial and logistic regression analyses to examine associations between client demographics and service offerings.
Main Results:
- Treatment centers offered, on average, less than half of the NIDA-recommended wraparound services.
- The proportion of adolescent clients correlated positively with educational services; female clients correlated positively with childcare services.
- Clients referred from the criminal justice system showed a negative association with the availability of multiple wraparound services.
Conclusions:
- SUD treatment centers demonstrate some responsiveness to client needs but generally fail to provide most recommended wraparound services.
- Client characteristics significantly predict service availability, highlighting potential disparities in comprehensive care for diverse patient populations.
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