Gamifying Risk Identification for Alcohol Use Behaviors Across Countries and Cultures (2022-2023)

Background

Alcohol use is the seventh global risk factor for premature mortality and life-long disability. Predisposition towards harmful alcohol use is a result of a complex web of biopsychosocial factors, such as genetics and neural circuits, while social isolation, unemployment and socioenvironmental factors all contribute to increased alcohol consumption and risks of alcohol-related disorders. 

Current assessments of alcohol use disorders rely on self-reports of consumption and harm, which poses difficulties for transcultural and translingual interpretation in global health settings. With the growing burden of alcohol-related disorders in low- and middle-income countries, it is crucial to develop valid and reliable tools that allow systematic and comprehensive study of factors that can enhance our understanding of alcohol use and improve patient diagnosis, prognosis and treatment. 

Project Description

This project team will further the work of the 2021-2022 team on the Alcohol Use Behavioral Phenotyping Test (AUBPT). The purpose of this tool is to understand differences among drinking behaviors based on constructs like reward valuation, relative reward efficacy and proportionate reinforcement due to alcohol. The team will focus on expanding the implementation of the AUBPT app in global settings. 

The National Institute of Mental Health’s Research Domain Criteria (RDoC) framework is in its nascent stages for experimental validation and implementation. AUBPT includes gamified versions of RDoC-based behavioral paradigms that can evaluate the biopsychosocial constructs belonging to positive valence, negative valence and cognitive domains of RDoC. 

This project team will test AUBPT’s ability to predict the risk for alcohol use disorders. The team will also create simulated artificial intelligence agents that will model individual patients’ performance on AUBPT and thereby identify their alcohol use phenotypes. Team members will further develop and validate AUBPT adaptations in Portuguese and Hindi (or other relevant Indian languages) by working with researchers at the University of Sao Paulo, Brazil, and the Association for Socially Applicable Research, India.

Team members will follow a multiphase data collection including clinical and general population samples in the U.S. and Tanzania as well as pilot samples in Brazil and India. Team members will then use iterative feedback from research and clinical staff at the collaborating sites to adapt the AUBPT’s cultural and textual context to Portuguese and Hindi translations. The Unity platform will be used to deploy AUBPT as an open-source free app for desktop and laptop computers as well as hand-held devices.

Anticipated Outputs

Open-source computer application for AUBPT in English, Swahili, Portuguese and Hindi; open-source artificial intelligence models for optimization; research papers; data for grant proposal; presentations at international neuroscience and global health conferences

Student Opportunities

Ideally, this project team will be comprised of 2 graduate students and 12 undergraduate students. All student members should have a strong interest in global mental health, possess an aptitude for quantitative and qualitative research methods and be willing to work with global collaborators. 

Graduate students will have a background in global health, public policy, interdisciplinary data science, computer science, cognitive science or biostatistics. Undergraduate team members will be divided into three subteams according to their interests and backgrounds.

The Implementation subteam will include students majoring in global health; the Data Science subteam will include students with prior web development experience in open-source languages (Python, R, Java, etc.) and interest in data analysis and computational modeling. For the Content subteam, students with a major or minor in biology, neuroscience, cognitive science or psychology will be preferred. Premed students will also contribute to and benefit from several aspects of the project.

Students will gain hands-on research skills, including study design and planning, working with international collaborators, conducting literature synthesis, collecting quantitative and qualitative data, using statistical techniques, contributing to research papers and presenting at conferences. Undergraduate students will gain first-hand experience working in translational research while graduate students will lead the subteams, draft research papers as first/second authors and work independently on advanced data analyses.

Students will work with local collaborators to collect data and interact with global organizations in Tanzania, Brazil and India for cultural adaptation and validation of AUBPT.

Siddhesh Zadey will serve as project manager.

See the related Data+ project for Summer 2022; there is a separate application process for students who are interested in this optional component.

Timing

Fall 2022 – Summer 2023

  • Fall 2022: Collect data in the U.S.; conduct simulation experiments for creating individualized models for collected data
  • Spring 2023: Work with global collaborators to translate AUBPT contents to Portuguese and Hindi; draft manuscripts; analyze data collected from Tanzania; incorporate model-based adaptations into the app
  • Summer 2023 (optional): Conduct content validation of Hindi and Portuguese adaptations of AUBPT; coordinate pilot data collection in India; analyze pilot data from other collaborating sites

Crediting

Academic credit available for fall and spring semesters; summer funding available

See related Data+ summer project, Gamifying Risk Identification for Alcohol Use Behaviors (2022), and earlier related team, Alcohol Use Behaviors Across Countries and Cultures (2021-2022).

 

Image: Drinks in Paraty, by Chaval Brasil, licensed under CC BY-NC-ND 2.0

Bar in Brazil.

Team Leaders

  • Catherine Staton, School of Medicine-Surgery
  • Joao Vissoci, School of Medicine-Surgery: Emergency Medicine
  • Siddhesh Zadey, School of Medicine-Surgery

/undergraduate Team Members

  • Phineas Brauer, Psychology (BS)
  • Michael Dieu, Public Policy Studies (AB), Global Health (AB2)
  • Anthony Hinton, Neuroscience (BS)
  • Sanjana Jha, Robertson Scholarship - UNC
  • Brendan Kelleher
  • Rushil Knagaram
  • Dev Shah
  • Isabella Swigart, Statistical Science (BS), Computer Science (BS2)
  • Christina (Yishan) Yu

/zcommunity Team Members

  • Kilimanjaro Christian Medical Centre, Tanzania
  • Association for Socially Applicable Research (ASAR)
  • Leonardo Oliveira, University of Sao Paulo, Maringa Campus, Brazil