Development and Testing of a Just-in-Time Adaptive Smart Phone Intervention to Reduce Drinking Among Homeless Adults (Smart-T)

November 8, 2022 updated by: Scott Walters, PhD, University of North Texas Health Science Center

Development and Testing of a Just-in-Time Adaptive Smart Phone Intervention

Homeless adults are 8 times as likely to be alcohol dependent compared with adults in the general population, yet few studies have examined the precipitants of alcohol use in this vulnerable population. Ecological momentary assessments (EMAs) that involve repeated assessment of thoughts/mood/behaviors (e.g., via smart phone) is currently the most accurate way to assess individuals in real-time in their natural environments. Advances in smartphone technology also allow for the collection of continuous geolocation and other passive sensing data. Thus, researchers can now link environmental risks and protective factors to outcomes, without reliance on subjective reporting alone. Building on prior work, this study will use a three-phase study to develop and test a "just in time" adaptive intervention to reduce alcohol use in homeless men and women. Phase I will use smartphones and passive sensing technologies to monitor geolocation, psychosocial variables (e.g., stress, affect, urge to drink), and alcohol use in a group of 80 homeless adults with an AUD who are receiving shelter-based treatment. Phase I will identify environmental (i.e., geolocation), cognitive, and behavioral antecedents of alcohol use over 4 weeks. Phase II will use this information to create a risk algorithm and tailored treatment messages that anticipate and intervene to prevent drinking. The resulting app will assess imminent risk of alcohol use after each EMA and will deliver relevant treatment messages that match a person's current risk factors. Phase III will test the feasibility, acceptability and preliminary efficacy of the app in a sample of 40 homeless adults with an AUD who receive the EMA plus treatment messages over 4 weeks. Drinking will be determined via self-report, supplemented by a transdermal alcohol sensor (i.e., SCRAM) worn by participants. This project will be the first to combine geolocation and psychosocial variables to identify real-time antecedents of drinking. If effective, this smartphone app could significantly improve treatment engagement, drinking outcomes, and quality of life among homeless adults with alcohol use disorders.

Study Overview

Status

Completed

Detailed Description

An estimated 6.2% of US adults will be homeless at some point in their lifetime. Homeless adults have higher rates of disease, greater risk of interpersonal violence, shorter life expectancies, and disproportionately higher health care utilization and costs compared to housed individuals. A significant contributor to morbidity and mortality among homeless adults is the high prevalence of alcohol use. Approximately 33% of homeless adults have current alcohol dependence, a rate nearly 8 times that of the general population. Although shelter-based treatments are common, compliance is typically poor. Identifying factors that influence alcohol use would significantly improve the ability to develop effective interventions and engage homeless adults in treatment.

Relatively little is known about the environmental, cognitive, and behavioral antecedents of alcohol use in homeless adults. Like other subgroups, alcohol use has most often been examined using traditional lab/clinic based assessment methods that are not well suited to capturing the complicated street-level interactions experienced by most homeless adults. Traditional assessment methodologies may also provide biased and/or inaccurate estimates due to recall biases and errors in memory, particularly in this complicated population. Ecological momentary assessment (EMA), in which handheld devices (e.g., smartphones) are used to capture moment-to-moment experience, is currently the most accurate way to measure phenomena in natural settings. Additionally, recent technological advances have made it possible to collect continuous geolocation data alongside EMA. Researchers can now link environmental risks and protective factors to outcomes, without reliance on subjective reporting alone.

This pilot study will develop and test a "just-in-time" adaptive intervention to reduce alcohol use among homeless adults. Phase I will use smartphones and passive sensing to monitor geolocation, psychosocial variables (e.g., stress, urge to drink), and alcohol use in a group of 80 homeless adults enrolled in shelter-based treatment for an AUD. Phase II will use this information to create a risk algorithm and tailored treatment messages that anticipate and intervene to prevent alcohol use. Phase II will modify an existing app, previously validated for smoking cessation, to create the intervention. Phase III will pilot test the newly developed app for utility, satisfaction, and preliminary effectiveness in a group of 40 homeless adults with an AUD who are enrolled in shelter-based treatment. Alcohol consumption will be validated via a transdermal alcohol sensor (i.e., SCRAM) worn by participants in Phases I and III.

The central hypothesis is that alcohol use is strongly affected by moment-to-moment risk and protective factors. This study will be able to use EMAs to identify and automatically intervene during moments when people are at high risk for drinking. This hypothesis is based on preliminary findings among homeless, justice-involved, and socioeconomically disadvantaged safety-net hospital patients. If effective, this smartphone app could significantly improve treatment engagement, drinking outcomes, and quality of life among homeless adults with AUDs.

This project will:

  1. Use EMA to identify environmental (i.e., geolocation), cognitive, and behavioral antecedents of alcohol use among 80 homeless adults with an AUD who are receiving shelter-based treatment.
  2. Informed by Aim 1 findings, develop a "just-in-time" adaptive intervention to reduce alcohol use, including an alcohol use risk algorithm and corresponding theory-based treatment messages.
  3. Examine feasibility, acceptability, and preliminary effectiveness of a just-in-time adaptive smartphone app among 40 homeless adults with an AUD who are receiving shelter-based treatment.

Study Type

Interventional

Enrollment (Actual)

119

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

    • Texas
      • Dallas, Texas, United States, 75201
        • Bridge Homeless Recovery Center

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Description

Inclusion Criteria:

  • Score ≥ 8 on the AUDIT
  • Report consuming ≥ 1 drink of alcohol in the past week
  • Receiving treatment at Metrocare;
  • Willing and able to complete the baseline and follow-up visits;
  • Score ≥ 4 on the REALM-SF, indicating > 6th grade English literacy level
  • Score ≥ 24 on the Mini-Mental State Exam

Exclusion Criteria:

  • Circulation problems, neuropathy, deep vein thrombosis, leg ulcers, tendonitis, diabetes, pregnancy, history of swelling or nickel or other metal allergies that would prohibit wearing the SCRAM ankle bracelet.
  • Self-reported discomfort wearing an alcohol sensing bracelet for 4 weeks.
  • Previously participated in Phase I (for Phase III recruitment).

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: Non-Randomized
  • Interventional Model: Sequential Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Placebo Comparator: EMA only
Phase I will use smartphones and passive sensing to monitor geolocation, psychosocial variables (e.g., stress, urge to drink), and alcohol use in a group of 80 homeless adults with an AUD who are receiving shelter-based treatment.
This study will develop and test a "just-in-time" adaptive intervention to reduce alcohol use among homeless adults. Phase I will use smartphones and passive sensing to monitor geolocation, psychosocial variables (e.g., stress, urge to drink), and alcohol use in a group of 80 homeless adults with an AUD who are enrolled in shelter-based treatment. Phase II will use this information to create a risk algorithm and tailored treatment messages that anticipate and intervene to prevent alcohol use.
Active Comparator: EMA + App/Treatment Messages
Phase III will pilot test the newly developed app for utility, satisfaction, and preliminary effectiveness in a group of 40 homeless adults with an AUD who are receiving shelter-based treatment. The investigators will compare Phase III participants (i.e., received Metrocare, EMAs, and tailored treatment messages) to Phase I participants (i.e., received Metrocare and EMAs only) to examine the preliminary effectiveness of the app.
This study will develop and test a "just-in-time" adaptive intervention to reduce alcohol use among homeless adults. Phase I will use smartphones and passive sensing to monitor geolocation, psychosocial variables (e.g., stress, urge to drink), and alcohol use in a group of 80 homeless adults with an AUD who are enrolled in shelter-based treatment. Phase II will use this information to create a risk algorithm and tailored treatment messages that anticipate and intervene to prevent alcohol use.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Satisfaction With App Treatment Messages
Time Frame: 4 weeks
Satisfaction with app on self-reported questions at follow-up (1-5 scale where 1 = Not at all; and 5 = Extremely)
4 weeks

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Number of Drinking Days
Time Frame: 4 weeks
Number of drinking days (number of days with any self-reported drinking out of 28 days)
4 weeks
Number of Heavy Drinking Days
Time Frame: 4 weeks
Number of drinking days (number of days with self-reported >4 drinks for men; >3 drinks for women out of 28 days)
4 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Collaborators

Investigators

  • Principal Investigator: Scott Walters, PhD, University of North Texas Health Science Center

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

February 14, 2019

Primary Completion (Actual)

July 30, 2021

Study Completion (Actual)

May 31, 2022

Study Registration Dates

First Submitted

November 13, 2018

First Submitted That Met QC Criteria

November 15, 2018

First Posted (Actual)

November 20, 2018

Study Record Updates

Last Update Posted (Actual)

November 18, 2022

Last Update Submitted That Met QC Criteria

November 8, 2022

Last Verified

November 1, 2022

More Information

Terms related to this study

Other Study ID Numbers

  • 1R34AA024584-01A1 (U.S. NIH Grant/Contract)

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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