This oral presentation will highlight findings from a descriptive study investigating what biopsychosocial characteristics best predict outcomes for adults receiving treatment for opioid use in a rural state. Addressing gaps in research, policy, and practice, this study accounts for individual, interpersonal, and societal factors – biopsychosocial characteristics – that might influence outcomes Treatment Duration (days) and self-reported Change in Use. Though the problems associated with opioid use are widely recognized in scope and severity, addressing them remains an intractable challenge at both the practice and policy levels, particularly in rural areas. Individuals in rural areas typically face inequities of service access and provision that complicate treatment. Understanding factors influencing outcomes for adults receiving treatment for opioid use disorder – which includes both childless adults and adults responsible for dependent children – can help shape policy and practice responses supporting rural opioid-affected families.
Based on review of relevant theoretical and empirical literature, initial hypotheses were that primary substance of use, gender, and rurality would be significant predictors of outcomes. Data analysis supported the primary substance and rurality hypotheses. Gender is not a significant predictor of outcomes in this study. In addition, the variables living with others, opioid replacement therapy, and responsibility for dependent child(ren) emerged as significant predictors in at least some models.
The dataset is a de-identified secondary sample drawn from the 2017 State of Maine Treatment Episode Dataset. “Treatment” means non-crisis, non-intensive adult (18+) outpatient interventions meant to support detoxification from opioids, moving the individual toward physical and psychological recovery from opioid use disorder. The analysis population is 2746 unique cases of individuals ages 18+ who met inclusion and exclusion criteria. Descriptive statistics generated demographic characteristics. Inferential stepwise multiple regression, multinomial logistic regression, between-group ANOVA or Kruskal-Wallis non-parametric equivalent, and/or Pearson r correlations or Spearman rho non-parametric equivalent provide insight into biopsychosocial factors predicting treatment outcomes.
More than three-quarters of the analysis population indicated opioids as one of three substances of use when entering treatment (n=2153,78%). Yet findings showed 61% of the analysis population (n=1669/2746), and 28% of those indicating an opioid as primary substance (n=382/1335) did not receive opioid replacement therapy as part of treatment. Rurality and responsibility for dependent child(ren) predict negative treatment outcomes, while living with others at discharge and receiving opioid replacement therapy predict enhanced outcomes. Primary substance of use outcomes are mixed: opioids predicted longer durations of treatment and greater likelihood of reduced use; alcohol predicted shorter treatment duration and greater likelihood of unchanged use.
Findings suggest approaches increasing opportunities for human connection may achieve greater success, particularly in rural areas. Fewer professionals practice in rural areas, limiting access to treatment. Social work can contribute by harnessing the potential of telehealth, advocating for equitable internet access and insurance coverage, and collaborating across professional training programs to create statewide joint-training ventures extending opportunities for preparing providers able to address systemic injustices and treatment inequities related to rurality.