Predicting Substance Use among Military Veterans with a Positive MST Screen: A Machine Learning Approach

Information

  • Research Project
  • 10458304
  • ApplicationId
    10458304
  • Core Project Number
    F31DA051167
  • Full Project Number
    3F31DA051167-01A1S1
  • Serial Number
    051167
  • FOA Number
    PA-20-272
  • Sub Project Id
  • Project Start Date
    5/24/2021 - 3 years ago
  • Project End Date
    5/23/2023 - a year ago
  • Program Officer Name
    KURAMOTO-CRAWFORD, SATOKO JANET
  • Budget Start Date
    5/24/2021 - 3 years ago
  • Budget End Date
    5/23/2022 - 2 years ago
  • Fiscal Year
    2021
  • Support Year
    01
  • Suffix
    A1S1
  • Award Notice Date
    8/18/2021 - 3 years ago

Predicting Substance Use among Military Veterans with a Positive MST Screen: A Machine Learning Approach

Project Summary/Abstract Military sexual trauma (MST) is a serious and pervasive problem among military populations, affecting approximately 16% of military personnel and veterans [1]. Substance use disproportionately affects individuals with a history of MST. Individuals with (vs. without) a history of MST are twice as likely to misuse substances [2-4]. Substance use among military samples has been linked to higher rates of negative consequences across several domains (e.g., health, occupational, legal [5, 6]), including death (e.g., overdose [7], traffic accidents [8], suicide [7, 8]). Further, while understudied among individuals with a history of MST in particular, negative substance use outcomes have been shown to be more severe among trauma-exposed populations, including more severe clinical presentations and poorer treatment prognosis [9, 10]. These findings emphasize the importance of clarifying the association between MST and substance use among military populations. Despite the clinical relevance and public health significance of substance use among military populations, research in this area has relied almost exclusively on cross-sectional designs. Moreover, the vast majority of studies in this area have utilized traditional statistical methods, which are limited in scope and capabilities. These limitations have important clinical implications, as they restrict our ability to specify the exact nature and directionality of the relationship between MST and substance use, thereby affecting how findings are translated into prevention and intervention efforts. The proposed research aims to fill these critical gaps by utilizing the Army STARRS pre/post-deployment study, a large, prospective military dataset to: (1) explicate the directional relation between MST and substance use using a longitudinal dataset, and (2) employ machine learning methods to develop an algorithm to optimize detection of substance use in military personnel with a history of MST. These findings will assist in elucidating the etiology of substance use among this high-risk group, as well as provide a prediction model for clinical use to better target at-risk individuals in this population. This research project will take place within the Department of Psychology at the University of Rhode Island; an institution with a strong history and commitment to health behavior research and methodology. The applicant will have access to sponsors and consultants with expertise in MST, substance use, advanced methodology, and statistical analysis that will facilitate her career objectives to develop increased knowledge and proficiency in (a) sexual trauma (e.g., MST) and substance use in military veterans; (b) grant/manuscript development; (c) statistical and methodological capabilities (i.e., machine learning); and (d) big data. The proposed project uses a timely and innovative approach to advance science on the relation between MST and substance use in military personnel. Addressing substance use in this population is necessary to improve the health of our nation's veterans, and aligns with the mission of the National Institute on Drug Abuse.

IC Name
NATIONAL INSTITUTE ON DRUG ABUSE
  • Activity
    F31
  • Administering IC
    DA
  • Application Type
    3
  • Direct Cost Amount
    2500
  • Indirect Cost Amount
  • Total Cost
    2500
  • Sub Project Total Cost
  • ARRA Funded
    False
  • CFDA Code
    279
  • Ed Inst. Type
    SCH ALLIED HEALTH PROFESSIONS
  • Funding ICs
    NIDA:2500\
  • Funding Mechanism
    TRAINING, INDIVIDUAL
  • Study Section
  • Study Section Name
  • Organization Name
    UNIVERSITY OF RHODE ISLAND
  • Organization Department
    PSYCHOLOGY
  • Organization DUNS
    144017188
  • Organization City
    KINGSTON
  • Organization State
    RI
  • Organization Country
    UNITED STATES
  • Organization Zip Code
    028810811
  • Organization District
    UNITED STATES