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Substance use disorders involve a pattern of using drugs more extensively than intended and continuing use despite harmful consequences. This includes legal substances like alcohol and nicotine, as well as illegal drugs. These disorders often involve both physical and psychological dependence, reflecting compulsive use of substances that significantly alter thoughts, feelings, and behaviors, contributing to a major public health issue.
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Improving treatment completion for young adults with substance use disorder: Machine learning-based prediction

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  • 1School of Social Work, Indiana University, Indianapolis, IN, USA.

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Substance use disorder (SUD) treatment completion for young adults depends on multiple interacting factors. Rural location and criminal justice involvement, especially with opioid use disorders, were linked to lower completion rates in publicly funded programs.

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Area of Science:

  • Addiction Medicine
  • Public Health
  • Social Psychology

Background:

  • Substance use disorder (SUD) treatment completion is influenced by numerous factors, yet the interplay of psychosocial and system-level elements remains underexplored, particularly within publicly funded services.
  • Understanding these intersections is crucial for improving treatment outcomes for vulnerable populations.

Purpose of the Study:

  • To investigate the combined effects of psychosocial and system-related factors on SUD treatment completion among young adults in publicly funded outpatient settings.
  • To identify specific interaction patterns that predict treatment success or failure.

Main Methods:

  • Analysis of psycho-social assessment data from 2909 young adults in publicly funded outpatient SUD treatment in 2021.
  • Utilized the Chi-square Automatic Interaction Detection (CHAID) method to explore complex interactions influencing treatment completion.

Main Results:

  • Treatment completion rates varied significantly based on improvement in total actionable items (TAI).
  • Young adults with high TAI improvement in rural areas showed lower completion rates than urban counterparts.
  • Middle-level TAI improvement intersected with criminal justice involvement; those with justice involvement and opioid use disorders had lower completion rates than those with non-opioid SUD.

Conclusions:

  • SUD treatment completion is multifactorial, requiring consideration of TAI improvement, family strengths, demographics, and social determinants.
  • Targeted interventions addressing rural disparities and justice system involvement are needed for young adults with SUD.
  • Monitoring individual progress via TAI improvement is vital for predicting and supporting treatment completion.