ABSTRACT
BACKGROUND: The COVID-19 pandemic has profoundly transformed substance use disorder (SUD) treatment in the United States, with many web-based treatment services being used for this purpose. However, little is known about the long-term treatment effectiveness of SUD interventions delivered through digital technologies compared with in-person treatment, and even less is known about how patients, clinicians, and clinical characteristics may predict treatment outcomes. OBJECTIVE: This study aims to analyze baseline differences in patient demographics and clinical characteristics across traditional and telehealth settings in a sample of participants (N=3642) who received intensive outpatient program (IOP) substance use treatment from January 2020 to March 2021. METHODS: The virtual IOP (VIOP) study is a prospective longitudinal cohort design that follows adult (aged ≥18 years) patients who were discharged from IOP care for alcohol and substance use-related treatment at a large national SUD treatment provider between January 2020 and March 2021. Data were collected at baseline and up to 1 year after discharge from both in-person and VIOP services through phone- and web-based surveys to assess recent substance use and general functioning across several domains. RESULTS: Initial baseline descriptive data were collected on patient demographics and clinical inventories. No differences in IOP setting were detected by race (χ22=0.1; P=.96), ethnicity (χ22=0.8; P=.66), employment status (χ22=2.5; P=.29), education level (χ24=7.9; P=.10), or whether participants presented with multiple SUDs (χ28=11.4; P=.18). Significant differences emerged for biological sex (χ22=8.5; P=.05), age (χ26=26.8; P<.001), marital status (χ24=20.5; P<.001), length of stay (F2,3639=148.67; P<.001), and discharge against staff advice (χ22=10.6; P<.01). More differences emerged by developmental stage, with emerging adults more likely to be women (χ23=40.5; P<.001), non-White (χ23=15.8; P<.001), have multiple SUDs (χ23=453.6; P<.001), have longer lengths of stay (F3,3638=13.51; P<.001), and more likely to be discharged against staff advice (χ23=13.3; P<.01). CONCLUSIONS: The findings aim to deepen our understanding of SUD treatment efficacy across traditional and telehealth settings and its associated correlates and predictors of patient-centered outcomes. The results of this study will inform the effective development of data-driven benchmarks and protocols for routine outcome data practices in treatment settings.
