<clinical_study>
  <!-- This xml conforms to an XML Schema at:
    https://clinicaltrials.gov/ct2/html/images/info/public.xsd -->
  <required_header>
    <download_date>ClinicalTrials.gov processed this data on September 20, 2023</download_date>
    <link_text>Link to the current ClinicalTrials.gov record.</link_text>
    <url>https://clinicaltrials.gov/ct2/show/NCT02990377</url>
  </required_header>
  <id_info>
    <org_study_id>R01DA039159</org_study_id>
    <nct_id>NCT02990377</nct_id>
  </id_info>
  <brief_title>Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention</brief_title>
  <official_title>Reducing Non-Medical Opioid Use: An Automatically Adaptive mHealth Intervention</official_title>
  <sponsors>
    <lead_sponsor>
      <agency>University of Michigan</agency>
      <agency_class>Other</agency_class>
    </lead_sponsor>
    <collaborator>
      <agency>National Institute on Drug Abuse (NIDA)</agency>
      <agency_class>NIH</agency_class>
    </collaborator>
  </sponsors>
  <source>University of Michigan</source>
  <oversight_info>
    <has_dmc>Yes</has_dmc>
    <is_fda_regulated_drug>No</is_fda_regulated_drug>
    <is_fda_regulated_device>No</is_fda_regulated_device>
  </oversight_info>
  <brief_summary>
    <textblock>
      In recent years in the U.S., problems associated with opioid prescriptions, including&#xD;
      non-medical use and overdose, increased to historically unprecedented levels and represent a&#xD;
      public health crisis. Emergency departments (EDs) play an important role in opioid&#xD;
      prescribing, particularly to individuals at high risk for adverse opioid-related outcomes.&#xD;
      The purpose of this study is to determine whether a new mobile health (mhealth) intervention&#xD;
      can assist people in the safe use of opioid analgesic (OA) medications after leaving the&#xD;
      emergency department (ED).&#xD;
&#xD;
      The specific aims of this project are to: (1) adapt and enhance an existing motivational&#xD;
      intervention to decrease non-medical opioid use after an ED visit by optimizing intervention&#xD;
      intensity and duration through reinforcement learning (RL); (2) examine the impact of an&#xD;
      RL-supported intervention on non-medical opioid use level during the six months post-ED&#xD;
      visit; and (3) examine the impact of the RL intervention on the opioid-related behaviors and&#xD;
      adverse outcomes of driving after opioid use, overdose risk behaviors, and subsequent&#xD;
      opioid-related ED visits. The secondary aims of this project are to: (SA1) examine whether&#xD;
      baseline level of non-medical opioid use moderates the effects of the intervention; and (SA2)&#xD;
      understand barriers and facilitators of implementation of the intervention based on&#xD;
      qualitative interviews with ED patients.&#xD;
    </textblock>
  </brief_summary>
  <detailed_description>
    <textblock>
      The proposed study will test the efficacy of an interactive voice response (IVR) and&#xD;
      reinforcement learning (RL) supported motivational intervention delivered after an emergency&#xD;
      department (ED) visit to participants with recent non-medical OA use who receive an OA in the&#xD;
      ED or who are prescribed an OA at ED discharge, compared to enhanced usual care (EUC). In the&#xD;
      intervention condition, IVR calls will ask participants to report information about their&#xD;
      health and medications using their touch-tone phone, and based on their responses they may&#xD;
      receive brief or extended motivational messages during the IVR call, or they may be assigned&#xD;
      to receive a 20 minute motivational enhancement session with a study therapist over the&#xD;
      phone. Because the most helpful intensity of intervention is unknown and likely to vary&#xD;
      between patients, the project will use an artificial intelligence strategy called&#xD;
      reinforcement learning (RL). The RL system will continuously &quot;learn&quot; from the success of&#xD;
      prior actions in similar situations with similar patients in order to select the action most&#xD;
      likely to reduce non-medical opioid use for each participant during each call.&#xD;
&#xD;
      The proposed study will screen ~ 5,600 ED patients to enroll 600 ED participants in the&#xD;
      randomized controlled trial (RCT). Participants will be randomized to the intervention&#xD;
      condition (n=300) or to EUC (n=300). All participants will be re-assessed at 1, 3 and 6&#xD;
      months post-ED visit for level of non-medical OA use and related outcomes. The RCT will be&#xD;
      complemented by qualitative interviews to inform later implementation.&#xD;
    </textblock>
  </detailed_description>
  <overall_status>Completed</overall_status>
  <start_date type="Actual">November 6, 2018</start_date>
  <completion_date type="Actual">December 31, 2021</completion_date>
  <primary_completion_date type="Actual">December 31, 2021</primary_completion_date>
  <phase>N/A</phase>
  <study_type>Interventional</study_type>
  <has_expanded_access>No</has_expanded_access>
  <study_design_info>
    <allocation>Randomized</allocation>
    <intervention_model>Parallel Assignment</intervention_model>
    <primary_purpose>Health Services Research</primary_purpose>
    <masking>None (Open Label)</masking>
  </study_design_info>
  <primary_outcome>
    <measure>Level of Non-Medical Opioid Use</measure>
    <time_frame>Change over time (1-, 3-, and 6-months post-ED visit)</time_frame>
    <description>The Current Opioid Misuse Measure (COMM) assesses opioid use that is more than prescribed, for non-pain-related reasons, borrowing medications, obtaining medications from sources other than doctors, etc., on a 5-point Likert scale of &quot;Never&quot; to &quot;Very Often.&quot; The primary outcome will be a measure of severity created by summing the items.</description>
  </primary_outcome>
  <secondary_outcome>
    <measure>Emergency Department (ED) Utilization</measure>
    <time_frame>Change over time (1-, 3-, and 6-months post-ED visit)</time_frame>
    <description>ED use will be assessed with adapted items from the Treatment Service Review. A count of visits will be measured for the six months of follow-up.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Driving after consuming opioids</measure>
    <time_frame>Change over time (1-, 3-, and 6-months post-ED visit)</time_frame>
    <description>The investigators have adapted an item from the National Survey of Drinking and Driving Attitudes and Behaviors to apply to opioids. Frequency is assessed with a 5-point Likert scale and will be examined as a categorical variable for each follow-up assessment.</description>
  </secondary_outcome>
  <secondary_outcome>
    <measure>Overdose Risk Behaviors</measure>
    <time_frame>Change over time (1-, 3-, and 6-months post-ED visit)</time_frame>
    <description>The investigators have developed a measure based on items from the published literature on heroin overdose by adding risk factors specific to opioid analgesics. This measure will be a summary score of all items for each follow-up assessment.</description>
  </secondary_outcome>
  <number_of_arms>2</number_of_arms>
  <enrollment type="Actual">459</enrollment>
  <condition>Non-Medical Opioid Use</condition>
  <arm_group>
    <arm_group_label>RL-supported IVR intervention</arm_group_label>
    <arm_group_type>Experimental</arm_group_type>
    <description>Participants in the intervention group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED plus the RL-supported IVR intervention.</description>
  </arm_group>
  <arm_group>
    <arm_group_label>Enhanced Usual Care</arm_group_label>
    <arm_group_type>No Intervention</arm_group_type>
    <description>Participants in the enhanced usual care group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED.</description>
  </arm_group>
  <intervention>
    <intervention_type>Behavioral</intervention_type>
    <intervention_name>RL-supported IVR intervention</intervention_name>
    <description>Participants in the intervention group receive interactive voice response calls where they are asked to report information about their health and medications using their touch-tone phone. Based on their responses, participants may receive brief or extended motivational messages during the call, or they may be assigned to receive a 20 minute motivational enhancement session with a study therapist over the phone.</description>
    <arm_group_label>RL-supported IVR intervention</arm_group_label>
  </intervention>
  <eligibility>
    <criteria>
      <textblock>
        Inclusion Criteria:&#xD;
&#xD;
          -  Presenting at the study site emergency department (ED) for a pain related complaint&#xD;
&#xD;
          -  Past 3-month non-medical opioid analgesic (OA) use&#xD;
&#xD;
          -  Receiving an OA in the ED, or being given an OA prescription to fill after leaving the&#xD;
             ED&#xD;
&#xD;
        Exclusion Criteria:&#xD;
&#xD;
          -  Unable to perform informed consent&#xD;
&#xD;
          -  Presenting for pain related to acute cancer therapy&#xD;
&#xD;
          -  DSM-V moderate or severe opiate (heroin or OA) use disorders (4+ symptoms), or&#xD;
             experiencing tolerance and withdrawal symptoms&#xD;
&#xD;
          -  Unable to read/understand English&#xD;
&#xD;
          -  Lives 50+ miles from the study site&#xD;
&#xD;
          -  Acute risk for self-harm at the time of recruitment&#xD;
&#xD;
          -  Currently pregnant&#xD;
      </textblock>
    </criteria>
    <gender>All</gender>
    <minimum_age>18 Years</minimum_age>
    <maximum_age>N/A</maximum_age>
    <healthy_volunteers>No</healthy_volunteers>
  </eligibility>
  <overall_official>
    <last_name>Amy S Bohnert, Ph.D.</last_name>
    <role>Principal Investigator</role>
    <affiliation>University of Michigan</affiliation>
  </overall_official>
  <location>
    <facility>
      <name>University of Michigan Medical Center</name>
      <address>
        <city>Ann Arbor</city>
        <state>Michigan</state>
        <zip>48109</zip>
        <country>United States</country>
      </address>
    </facility>
  </location>
  <location_countries>
    <country>United States</country>
  </location_countries>
  <verification_date>January 2022</verification_date>
  <study_first_submitted>December 2, 2016</study_first_submitted>
  <study_first_submitted_qc>December 8, 2016</study_first_submitted_qc>
  <study_first_posted type="Estimate">December 13, 2016</study_first_posted>
  <last_update_submitted>January 27, 2022</last_update_submitted>
  <last_update_submitted_qc>January 27, 2022</last_update_submitted_qc>
  <last_update_posted type="Actual">January 31, 2022</last_update_posted>
  <responsible_party>
    <responsible_party_type>Principal Investigator</responsible_party_type>
    <investigator_affiliation>University of Michigan</investigator_affiliation>
    <investigator_full_name>Amy S.B. Bohnert</investigator_full_name>
    <investigator_title>Associate Professor</investigator_title>
  </responsible_party>
  <keyword>Opioid Analgesics</keyword>
  <keyword>Opioid Safety</keyword>
  <keyword>Emergency Department</keyword>
  <keyword>Motivational Enhancement</keyword>
  <keyword>Interactive Voice Response</keyword>
  <keyword>Reinforcement Learning</keyword>
  <keyword>mHealth</keyword>
  <patient_data>
    <sharing_ipd>No</sharing_ipd>
  </patient_data>
  <provided_document_section>
    <provided_document>
      <document_type>Informed Consent Form</document_type>
      <document_has_protocol>No</document_has_protocol>
      <document_has_icf>Yes</document_has_icf>
      <document_has_sap>No</document_has_sap>
      <document_date>February 1, 2021</document_date>
      <document_url>https://ClinicalTrials.gov/ProvidedDocs/77/NCT02990377/ICF_000.pdf</document_url>
    </provided_document>
  </provided_document_section>
  <!-- Results have not yet been posted for this study                                          -->
</clinical_study>


download date: ClinicalTrials.gov processed this data on September 20, 2023
link text: Link to the current ClinicalTrials.gov record.
url: https://clinicaltrials.gov/ct2/show/NCT02990377
org study id: R01DA039159
nct id: NCT02990377
lead sponsor: 
collaborator: 
has dmc: Yes
is fda regulated drug: No
is fda regulated device: No
In recent years in the U.S., problems associated with opioid prescriptions, including
      non-medical use and overdose, increased to historically unprecedented levels and represent a
      public health crisis. Emergency departments (EDs) play an important role in opioid
      prescribing, particularly to individuals at high risk for adverse opioid-related outcomes.
      The purpose of this study is to determine whether a new mobile health (mhealth) intervention
      can assist people in the safe use of opioid analgesic (OA) medications after leaving the
      emergency department (ED).

      The specific aims of this project are to: (1) adapt and enhance an existing motivational
      intervention to decrease non-medical opioid use after an ED visit by optimizing intervention
      intensity and duration through reinforcement learning (RL); (2) examine the impact of an
      RL-supported intervention on non-medical opioid use level during the six months post-ED
      visit; and (3) examine the impact of the RL intervention on the opioid-related behaviors and
      adverse outcomes of driving after opioid use, overdose risk behaviors, and subsequent
      opioid-related ED visits. The secondary aims of this project are to: (SA1) examine whether
      baseline level of non-medical opioid use moderates the effects of the intervention; and (SA2)
      understand barriers and facilitators of implementation of the intervention based on
      qualitative interviews with ED patients.
The proposed study will test the efficacy of an interactive voice response (IVR) and
      reinforcement learning (RL) supported motivational intervention delivered after an emergency
      department (ED) visit to participants with recent non-medical OA use who receive an OA in the
      ED or who are prescribed an OA at ED discharge, compared to enhanced usual care (EUC). In the
      intervention condition, IVR calls will ask participants to report information about their
      health and medications using their touch-tone phone, and based on their responses they may
      receive brief or extended motivational messages during the IVR call, or they may be assigned
      to receive a 20 minute motivational enhancement session with a study therapist over the
      phone. Because the most helpful intensity of intervention is unknown and likely to vary
      between patients, the project will use an artificial intelligence strategy called
      reinforcement learning (RL). The RL system will continuously "learn" from the success of
      prior actions in similar situations with similar patients in order to select the action most
      likely to reduce non-medical opioid use for each participant during each call.

      The proposed study will screen ~ 5,600 ED patients to enroll 600 ED participants in the
      randomized controlled trial (RCT). Participants will be randomized to the intervention
      condition (n=300) or to EUC (n=300). All participants will be re-assessed at 1, 3 and 6
      months post-ED visit for level of non-medical OA use and related outcomes. The RCT will be
      complemented by qualitative interviews to inform later implementation.
allocation: Randomized
intervention model: Parallel Assignment
primary purpose: Health Services Research
masking: None (Open Label)
measure: Level of Non-Medical Opioid Use
time frame: Change over time (1-, 3-, and 6-months post-ED visit)
description: The Current Opioid Misuse Measure (COMM) assesses opioid use that is more than prescribed, for non-pain-related reasons, borrowing medications, obtaining medications from sources other than doctors, etc., on a 5-point Likert scale of "Never" to "Very Often." The primary outcome will be a measure of severity created by summing the items.
measure: Emergency Department (ED) Utilization
time frame: Change over time (1-, 3-, and 6-months post-ED visit)
description: ED use will be assessed with adapted items from the Treatment Service Review. A count of visits will be measured for the six months of follow-up.
measure: Driving after consuming opioids
time frame: Change over time (1-, 3-, and 6-months post-ED visit)
description: The investigators have adapted an item from the National Survey of Drinking and Driving Attitudes and Behaviors to apply to opioids. Frequency is assessed with a 5-point Likert scale and will be examined as a categorical variable for each follow-up assessment.
measure: Overdose Risk Behaviors
time frame: Change over time (1-, 3-, and 6-months post-ED visit)
description: The investigators have developed a measure based on items from the published literature on heroin overdose by adding risk factors specific to opioid analgesics. This measure will be a summary score of all items for each follow-up assessment.
arm group label: RL-supported IVR intervention
arm group type: Experimental
description: Participants in the intervention group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED plus the RL-supported IVR intervention.
arm group label: Enhanced Usual Care
arm group type: No Intervention
description: Participants in the enhanced usual care group receive brief, non-tailored information related to decreasing opioid analgesic risk via pamphlets given at the ED.
intervention type: Behavioral
intervention name: RL-supported IVR intervention
description: Participants in the intervention group receive interactive voice response calls where they are asked to report information about their health and medications using their touch-tone phone. Based on their responses, participants may receive brief or extended motivational messages during the call, or they may be assigned to receive a 20 minute motivational enhancement session with a study therapist over the phone.
arm group label: RL-supported IVR intervention
criteria: 
gender: All
minimum age: 18 Years
maximum age: N/A
healthy volunteers: No
last name: Amy S Bohnert, Ph.D.
role: Principal Investigator
affiliation: University of Michigan
facility: 
country: United States
responsible party type: Principal Investigator
investigator affiliation: University of Michigan
investigator full name: Amy S.B. Bohnert
investigator title: Associate Professor
sharing ipd: No
provided document: 