Health Information Technology Commons^™

The Feasibility And Utility Of Harnessing Digital Health To Understand Clinical Trajectories In Medication Treatment For Opioid Use Disorder: D-Tect Study Design And Methodological Considerations, Lisa A. Marsch, Ching-Hua Chen, Sara R. Adams, Asma Asyyed, Monique B. Does, Saeed Hassanpour, Emily Hichborn, Melanie Jackson-Morris, Nicholas C. Jacobson, Heather K. Jones, David Kotz, Chantal A. Lambert-Harris, Zhiguo Li, Bethany Mcleman, Varun Mishra, Catherine Stanger, Geetha Subramaniam, Weiyi Wu, Cynthia I. Campbell

Dartmouth Scholarship

Introduction: Across the U.S., the prevalence of opioid use disorder (OUD) and the rates of opioid overdoses have risen precipitously in recent years. Several effective medications for OUD (MOUD) exist and have been shown to be life-saving. A large volume of research has identified a confluence of factors that predict attrition and continued substance use during substance use disorder treatment. However, much of this literature has examined a small set of potential moderators or mediators of outcomes in MOUD treatment and may lead to over-simplified accounts of treatment non-adherence. Digital health methodologies offer great promise for capturing intensive, longitudinal ecologically-valid …

When Do Drivers Interact With In-Vehicle Well-Being Interventions? An Exploratory Analysis Of A Longitudinal Study On Public Roads, Kevin Koch, Varun Mishra, Shu Liu, Thomas Berger, Elgar Fleisch, David Kotz, Felix Wortmann

Dartmouth Scholarship

Recent developments of novel in-vehicle interventions show the potential to transform the otherwise routine and mundane task of commuting into opportunities to improve the drivers' health and well-being. Prior research has explored the effectiveness of various in-vehicle interventions and has identified moments in which drivers could be interruptible to interventions. All the previous studies, however, were conducted in either simulated or constrained real-world driving scenarios on a pre-determined route. In this paper, we take a step forward and evaluate when drivers interact with in-vehicle interventions in unconstrained free-living conditions.

To this end, we conducted a two-month longitudinal study with 10 …

Implementing An Mhealth System For Substance Use Disorders In Primary Care: A Mixed Methods Study Of Clinicians’ Initial Expectations And First Year Experiences, Marie-Louise Mares, David H. Gustafson, Joseph E. Glass, Andrew Quanbeck, Helene Mcdowell, Fiona Mctavish, Amy Atwood, Lisa Marsch

Dartmouth Scholarship

Millions of Americans need but don’t receive treatment for substance use, and evidence suggests that addiction-focused interventions on smart phones could support their recovery. There is little research on implementation of addiction-related interventions in primary care, particularly in Federally Qualified Health Centers (FQHCs) that provide primary care to underserved populations. We used mixed methods to examine three FQHCs’ implementation of Seva, a smart-phone app that offers patients online support/discussion, health-tracking, and tools for coping with cravings, and offers clinicians information about patients’ health tracking and relapses. We examined (a) clinicians' initial perspectives about implementing Seva, and (b) the first year …

Integrating Addiction Treatment Into Primary Care Using Mobile Health Technology: Protocol For An Implementation Research Study, Andrew R. Quanbeck, David H. Gustafson, Lisa A. Marsch, Fiona Mctavish

Dartmouth Scholarship

Healthcare reform in the United States is encouraging Federally Qualified Health Centers and other primary-care practices to integrate treatment for addiction and other behavioral health conditions into their practices. The potential of mobile health technologies to manage addiction and comorbidities such as HIV in these settings is substantial but largely untested. This paper describes a protocol to evaluate the implementation of an E-Health integrated communication technology delivered via mobile phones, called Seva, into primary-care settings. Seva is an evidence-based system of addiction treatment and recovery support for patients and real-time caseload monitoring for clinicians.