Accepted for/Published in: JMIR Human Factors
Date Submitted: May 4, 2023
Open Peer Review Period: May 4, 2023 - May 18, 2023
Date Accepted: Oct 5, 2023
(closed for review but you can still tweet)
Virtual and In-Person Intensive Outpatient Treatment for Substance Use Disorders: Association Between Clinician-Level Factors and Patient Outcomes
ABSTRACT
Background:
Utilization of virtual treatment services increased dramatically during the COVID-19 pandemic. Unfortunately, large-scale research on virtual treatment for substance use disorder (SUD), including factors that may influence outcomes, has not advanced with the rapidly changing landscape.
Objective:
This study aims to evaluate the link between clinician-level factors and patient outcomes in populations receiving virtual and in-person intensive outpatient services.
Methods:
Data came from patients (n=1410) treated in virtual (VIOP) and in-person intensive outpatient programming (IOP), who discharged between January 2020 and March 2021 from a national treatment organization. Patient data were nested by treatment provider (n=58) examining associations with no-shows and discharge with staff approval. Empathy, comfort with technology, perceived stress, resistance to change, and demographic covariates were examined at the clinician level.
Results:
VIOP (β=-5.71, p = 0.032) and the personal distress subscale measure (β=-6.31, p = 0.003) were negatively associated with the percentage of no-shows. VIOP was positively associated with discharges with staff approval (OR= 2.38, 95% CI=1.50, 3.76). Clinician scores on perspective taking (β=-9.22, p = 0.02), personal distress (β=-9.44, p = 0.017) and male clinician gender (β=-6.43, p = 0.041) were negatively associated with in-person no-shows. Patient load was positively associated with discharge with staff approval (OR= 1.04, 95% CI=1.02, 1.06).
Conclusions:
Overall, patients in VIOP had fewer no-shows and a higher rate of successful discharge. Few clinician-level characteristics were significantly associated with patient outcomes. Further research is necessary to understand the relationships between factors such as clinician gender, patient load, personal distress, and patient retention.
Citation
Request queued. Please wait while the file is being generated. It may take some time.
Copyright
© The authors. All rights reserved. This is a privileged document currently under peer-review/community review (or an accepted/rejected manuscript). Authors have provided JMIR Publications with an exclusive license to publish this preprint on it's website for review and ahead-of-print citation purposes only. While the final peer-reviewed paper may be licensed under a cc-by license on publication, at this stage authors and publisher expressively prohibit redistribution of this draft paper other than for review purposes.