{
  "abstract": "Introduction Despite the continued burden of opioid overdose in communities in the USA, effective treatments for opioid use disorder (OUD), such as medication for opioid use disorder (MOUD), remain underused. Motivational interviewing techniques and linkage to MOUD via digital health are innovative practices developed to overcome persistent barriers to accessing MOUD treatment. These practices are merged in a comprehensive digital health platform, RecoveryPad (developed by the Center for Progressive Recovery). Our study, ‘Using System Dynamics Modeling to Foster Real-time Connections to Care’ (NIH Award #: 1R61DA057675-01), is a pilot to assess the feasibility and behaviour change potential of RecoveryPad for our target audience of people experiencing OUD.Methods and analysis This study will recruit 40 participants in Connecticut and New York through online platforms, such as social media and digital advertising, and direct access via quick-response (QR) codes distributed by local community partners. Eligibility assessment and enrolment will be conducted virtually. Individuals reporting symptoms indicating moderate to severe OUD who are at least 18 years of age are eligible for the study, excluding those who are currently receiving MOUD, pregnant or incarcerated. Enrolled participants will interact with an automated chatbot, live recovery coaches and, if desired, be referred to a telehealth MOUD provider via the RecoveryPad platform. Participants will have access to the platform for 30 days and will be asked to complete brief surveys to assess MOUD engagement and secondary outcomes at 30 and 90 days. Additionally, system dynamics (SD) models will be developed at the individual level to simulate participant interactions with RecoveryPad, and at the community level to improve understanding of the systems affecting OUD and MOUD access.Ethics and dissemination This project received approval from the Yale University Human Investigation Committee in 2024 (HIC # 2000034414). All participants will complete an electronic consent form with detailed study information and release of information to obtain data related to MOUD appointment attendance. Findings and conclusions from this pilot will be disseminated via peer-reviewed publication, advisory board meetings and meetings with community partners.Trial registration number NCT05832879.",
  "authors": [
    {
      "affiliations": [
        "Center for Systems and Community Design, CUNY Graduate School of Public Health & Health Policy, New York, New York, USA"
      ],
      "name": "Turner Canty"
    },
    {
      "affiliations": [
        "Center for Systems and Community Design, CUNY Graduate School of Public Health & Health Policy, New York, New York, USA",
        "Health Policy and Management, CUNY Graduate School of Public Health & Health Policy, New York, New York, USA"
      ],
      "name": "Nasim S Sabounchi"
    },
    {
      "affiliations": [
        "Department of Epidemiology of Microbial Diseases, Yale University School of Public Health, New Haven, Connecticut, USA"
      ],
      "name": "Robert Heimer"
    },
    {
      "affiliations": [
        "School of Health Professions, Long Island University, Brookville, New York, USA",
        "Center for Progressive Recovery, New Haven, Connecticut, USA"
      ],
      "name": "Michael Pantalon"
    },
    {
      "affiliations": [
        "Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA"
      ],
      "name": "Caitlin Ryus"
    },
    {
      "affiliations": [
        "Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA"
      ],
      "name": "Laurel Buchanan"
    },
    {
      "affiliations": [
        "Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA"
      ],
      "name": "Mikas Grewal"
    },
    {
      "affiliations": [
        "Center for Systems and Community Design, CUNY Graduate School of Public Health & Health Policy, New York, New York, USA"
      ],
      "name": "Justine Maffei"
    },
    {
      "affiliations": [
        "Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA",
        "Department of Chronic Disease Epidemiology, Yale University School of Public Health, New Haven, CT, USA"
      ],
      "name": "Gail D’Onofrio"
    },
    {
      "affiliations": [
        "Department of Emergency Medicine, Yale University School of Medicine, New Haven, Connecticut, USA",
        "Department of Anesthesiology, Yale University School of Medicine, New Haven, CT, USA"
      ],
      "name": "Rebekah Heckmann"
    }
  ],
  "title": "Increasing timely access to evidence-based treatment for opioid use disorder using novel digital health and system dynamics modelling approaches: a study protocol",
  "uid": "ccd6aed6-2654-5522-96dc-f3b810118ecf"
}