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

Alcohol Use Disorder Clinical Trial

— Smart-T  

Official title:

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

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT03746808
• Other study ID #: 1R34AA024584-01A1
• Status: Completed
• Phase: N/A
• Start date: February 14, 2019
• Est. completion date: May 31, 2022

Study information

• Verified date: November 2022
• Source: University of North Texas Health Science Center
• Contact: n/a
• Is FDA regulated: No
• Study type: Interventional

Clinical Trial Summary

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.

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.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 119
• Est. completion date: May 31, 2022
• Est. primary completion date: July 30, 2021
• Accepts healthy volunteers: Accepts Healthy Volunteers
• Gender: All
• Age group: N/A and older

Eligibility

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).

Related Conditions & MeSH terms

• Alcohol Use Disorder
• Alcoholism
• Homelessness
• Treatment

Intervention

Behavioral:
• EMA + App/Treatment Messages
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.

Locations

Country	Name	City	State
United States	Bridge Homeless Recovery Center	Dallas	Texas

Sponsors (2)

Lead Sponsor	Collaborator
University of North Texas Health Science Center	University of Oklahoma

Country where clinical trial is conducted

United States, 

References & Publications (4)

Businelle MS, Walters ST, Mun EY, Kirchner TR, Hébert ET, Li X. Reducing Drinking Among People Experiencing Homelessness: Protocol for the Development and Testing of a Just-in-Time Adaptive Intervention. JMIR Res Protoc. 2020 Apr 16;9(4):e15610. doi: 10.2 — View Citation

Mun EY, Li X, Businelle MS, Hébert ET, Tan Z, Barnett NP, Walters ST. Ecological Momentary Assessment of Alcohol Consumption and Its Concordance with Transdermal Alcohol Detection and Timeline Follow-Back Self-report Among Adults Experiencing Homelessness — View Citation

Walters ST, Businelle MS, Suchting R, Li X, Hébert ET, Mun EY. Using machine learning to identify predictors of imminent drinking and create tailored messages for at-risk drinkers experiencing homelessness. J Subst Abuse Treat. 2021 Aug;127:108417. doi: 1 — View Citation

Walters ST, Mun EY, Tan Z, Luningham JM, Hébert ET, Oliver JA, Businelle MS. Development and preliminary effectiveness of a smartphone-based, just-in-time adaptive intervention for adults with alcohol misuse who are experiencing homelessness. Alcohol Clin — View Citation

Outcome

Type	Measure	Description	Time frame	Safety issue
Primary	Satisfaction With App Treatment Messages	Satisfaction with app on self-reported questions at follow-up (1-5 scale where 1 = Not at all; and 5 = Extremely)	4 weeks
Secondary	Number of Drinking Days	Number of drinking days (number of days with any self-reported drinking out of 28 days)	4 weeks
Secondary	Number of Heavy Drinking Days	Number of drinking days (number of days with self-reported >4 drinks for men; >3 drinks for women out of 28 days)	4 weeks