SMART-r: Substance Monitoring and Active Relapse Tracking Repository

Обзор

Background: About 1.5 million adults in the US enter alcohol or substance use treatment programs each year. Unfortunately, more than half of patients do not finish their program. For those who start treatment, about 70% return to substance use within weeks or months after starting treatment. To discover why patients drop out of treatment and return to substance use - and what can be done about it - researchers need to learn more about people who use drugs and alcohol. Objective: To create a data repository by gathering survey and smartphone data from adults who use drugs and alcohol in order to conduct future research. Eligibility: Adults who have used drugs or alcohol in the past and have a Android smartphone. The researchers will recruit targeted demographics at different times throughout the duration of the study period. Design: Data will be collected for up to 6 months. All research activities will be online. Participants will download a smartphone app called TTRU-Curtis AWARE and keep it active on their phone. The app will run in the background and collect participant data, including: screen unlocks, duration of time the screen is on; apps used; words typed (except passwords); duration and time of phone calls; estimated location (exact location is not collected); and movement, such as how many steps are taken in a day. All personally identifying information is automatically removed before the data is stored (including phone numbers, names, or locations described in messages). Each day, participants will receive a text with a link to a survey. They will answer questions about their mood, behavior, and substance use from the day before. This survey should take less than 5 minutes to complete. Every 30 days, participants will complete a longer survey. They will answer questions about their personal relationships, risky behaviors, mood, substance use, and feelings. They can skip any questions they do not feel comfortable answering. These surveys should take about 30 minutes to complete. Participants may opt to allow researchers to access their social media posts.

Подробное описание

Description:

This project aims to establish a comprehensive data repository for conducting secondary research, including the analysis of digital phenotype data from individuals who have historically used drugs, including alcohol. Our hypothesis is that digital phenotyping can reveal unique behavioral patterns and risk factors associated with substance use. By collecting data such as smartphone app usage, social media interactions, language data, phone sensor measurements, historical conversational AI data, and wearable device metrics, the TTRU research lab will be able to conduct secondary analyses and uncover insights that could inform prevention and intervention strategies with individuals who use substances.

Objectives

Primary Objective:

The primary objective is to establish the NIDA-IRP Technology and Translational Research Unit (TTRU) Substance Monitoring and Active Relapse Tracking Repository (SMART-r) for collection, storage, and analysis of the human data from individuals who use substances. The secure, high-quality resource of digital, sensor, social media, conversational AI data, self-report, and clinical data (Repository Materials) will be created. Core variables of interest include sensor data, language, and relevant self-report measures. The intention to collect digital phenotyping data is to aid in the efficiency and efficacy of secondary research investigating health outcomes for individuals who use substances by creating a repository of de-identified data.

Первичные конечные точки

• SMARTr data repository [Срок оценки: 20 years]

Критерии участия

• INCLUSION CRITERIA:

In order to be eligible to participate in the repository, an individual must meet all of the following criteria:

• Must understand and be willing to complete an online informed consent process.
• Be an adult aged 18 or older.
• Self-report alcohol or other drug use within the past 30 days.
• Have a smartphone as their primary mobile phone.

--For the AWARE app data monitoring procedure, there may be times during this study period where, due to technical or OS limitations, the app is only available to users of certain devices (e.g., Android, iOS). If there is such a limitation, this information will be evaluated during screening. For example, if the AWARE app is not available for iOS, then the screening form may exclude iPhone users for that time period where the limitation exists, if the only procedures offered are daily diary surveys and AWARE data monitoring.

• Be willing to adhere to the procedures, such as downloading the AWARE app onto their smartphone and keeping it active throughout the data collection period, completing baseline questionnaires, daily diary EMAs, open-ended survey questions with the TTR Chatbot, uploading historical conversational AI data, and/or follow-up surveys.
• Understand and write in English.

--This exclusion criterion is included because future research on the data collected will include linguistic analysis. all linguistic analyses, we remove rare words (e.g., words must be said by at least 95% of participants)95. Additionally, there are cultural differences across languages and, thus, interpreting language results across more than one language becomes difficult.96 As a result, we must keep analysis limited to a single language (English), since words in other languages will not meet that criteria.

• Live in the United States.

Критерии исключения

An individual who meets any of the following criteria will be excluded from participation in this repository:

1\. Any impairment severe enough to preclude informed consent or valid self-report.

Критерии приведены из реестра в оригинале (на английском). Окончательную оценку соответствия проводит исследовательский центр.

Здоровые добровольцы: Нет

Дизайн исследования

Модель наблюдения

Другое

Центры проведения

США · 1 центр

• National Institute on Drug Abuse — Baltimore

Публикации

• Sinha R. New findings on biological factors predicting addiction relapse vulnerability. Curr Psychiatry Rep. 2011 Oct;13(5):398-405. doi: 10.1007/s11920-011-0224-0. PMID 21792580
• Bauer LO. Predicting relapse to alcohol and drug abuse via quantitative electroencephalography. Neuropsychopharmacology. 2001 Sep;25(3):332-40. doi: 10.1016/S0893-133X(01)00236-6. PMID 11522462
• Claus RE, Kindleberger LR. Engaging substance abusers after centralized assessment: predictors of treatment entry and dropout. J Psychoactive Drugs. 2002 Jan-Mar;34(1):25-31. doi: 10.1080/02791072.2002.10399933. PMID 12003110
• Darke S, Campbell G, Popple G. Retention, early dropout and treatment completion among therapeutic community admissions. Drug Alcohol Rev. 2012 Jan;31(1):64-71. doi: 10.1111/j.1465-3362.2011.00298.x. Epub 2011 Mar 22. PMID 21426420
• Evans E, Li L, Hser YI. Client and program factors associated with dropout from court mandated drug treatment. Eval Program Plann. 2009 Aug;32(3):204-12. doi: 10.1016/j.evalprogplan.2008.12.003. Epub 2008 Dec 11. PMID 19150133
• Lejuez CW, Zvolensky MJ, Daughters SB, Bornovalova MA, Paulson A, Tull MT, Ettinger K, Otto MW. Anxiety sensitivity: a unique predictor of dropout among inner-city heroin and crack/cocaine users in residential substance use treatment. Behav Res Ther. 2008 Jul;46(7):811-8. doi: 10.1016/j.brat.2008.03.010. Epub 2008 Mar 28. PMID 18466878
• Lopez-Goni JJ, Fernandez-Montalvo J, Arteaga A. Addiction treatment dropout: exploring patients' characteristics. Am J Addict. 2012 Jan-Feb;21(1):78-85. doi: 10.1111/j.1521-0391.2011.00188.x. Epub 2011 Dec 1. PMID 22211350
• Odenwald M, Semrau P. Dropout among patients in qualified alcohol detoxification treatment: the effect of treatment motivation is moderated by Trauma Load. Subst Abuse Treat Prev Policy. 2013 Mar 21;8:14. doi: 10.1186/1747-597X-8-14. PMID 23514277

Идентификаторы

NCT: NCT06676059 · 10002094 · 002094-DA

Первоисточники (государственные реестры)

• ClinicalTrials.gov (NIH, США)

Открыть это исследование на ClinicalTrials.gov ↗