SBIR-STTR Award

The goal of this SBIR project is to develop a method for creating algorithmically generated control groups. These will be composed of synthetic cases that have two characteristics: (1) pretest similarity to whatever prevention treatment group may present itself and (2) patterns of change over time that closely mimic the normal course of alcohol and drug use development. The field of alcohol and drug prevention is one that has significantly matured and has rich data resources that can be employed to this end. Notably, numerous school and community efficacy studies have employed control groups in randomized control trials. Additional etiological and epidemiological studies have collected similar data. Given the large amount of data available for analysis, it is now possible to model the onset of alcohol and drug use among adolescents. We propose to gather data from previous studies and develop statistical models that can be used to predict the onset of alcohol and drug use. An algorithm will be developed that will create integrative control cases to match to a treatment group's demographics and pretest mediating variable scores and then estimate future drug use. Several benefits of this method are anticipated. Alcohol and drug prevention researchers and practitioners will be able to use this approach to test the effectiveness of disseminated interventions and to quickly evaluate the potential of new and alternative prevention interventions. Specifically, this method will provide a means to evaluate the effectiveness of alcohol and drug prevention programs that are disseminated when randomization cannot occur. This method will also make evaluating new and adapted programs easier by reducing the challenges of recruitment, subject retention, and onsite data collection and pretest non-equivalence that often occur when l classrooms, schools and communities are assigned to condition.

Public Health Relevance Statement:


Public Health Relevance:
This project will address evaluating interventions that address alcohol and drug use and abuse. Methods will be developed to allow researchers and practitioners to evaluate programs that are being publicly disseminated to assess their effectiveness. Researchers will also be able to use this method to quickly evaluate newly developed or adapted prevention programs.

NIH Spending Category:
Alcoholism, Alcohol Use and Health; Clinical Research; Clinical Trials and Supportive Activities; Comparative Effectiveness Research; Prevention; Substance Abuse; Substance Abuse Prevention

Project Terms:
Address; Adolescent; Affect; Alcohol consumption; alcohol prevention; Alcohols; Algorithms; Archives; Area; Big Data; Biomedical Computing; Businesses; case control; Characteristics; Communities; Control Groups; cost; course development; Data; Data Collection; data integration; Data Science; Data Set; Databases; demographics; Development; Drug Prevention Program; Drug usage; Effectiveness; Effectiveness of Interventions; Elements; Epidemiologic Studies; Funding Opportunities; Future; Goals; Informatics; Intervention; Knowledge; Measures; Mediating; Methodology; Methods; Modeling; models and simulation; Participant; Pattern; Pharmaceutical Preparations; Phase; Prevention; Prevention approach; Prevention program; Prevention Research; Preventive Intervention; programs; psychosocial; public health relevance; Randomized; Randomized Controlled Trials; Research; Research Personnel; Research Project Grants; research study; Resources; response; Schools; Small Business Innovation Research Grant; Statistical Models; Technology; Testing; therapy development; Time; treatment group

The goal of this Phase II SBIR project is to develop a method for creating algorithmically generated control groups – virtual controls. These will be composed of synthetic cases that have two characteristics: (1) pretest similarity to whatever prevention treatment group may present itself and (2) patterns of change over time that closely mimic the normal course of alcohol and drug use development. The field of alcohol and drug prevention is one that has significantly matured and has rich data resources that can be employed to this end. Notably, numerous school and community efficacy studies have employed control groups in randomized control trials. Additional etiological and epidemiological studies have collected similar data. Given the large amount of data available for analysis, it is now possible to model the onset of alcohol and drug use among adolescents. We propose to gather data from previous studies and develop statistical models that can be used to predict the onset of alcohol and drug use. An algorithm will be developed that will create integrative control cases to match to a treatment group’s demographics and pretest mediating variable scores and then estimate future drug use. Several benefits of this method are anticipated. Alcohol and drug prevention researchers and practitioners will be able to use this approach to test the effectiveness of disseminated interventions and to quickly evaluate the potential of new and alternative prevention interventions. Specifically, this method will provide a means to evaluate the effectiveness of alcohol and drug prevention programs that are disseminated when randomization cannot occur. This method will also make evaluating new and adapted programs easier by reducing the challenges of recruitment, subject retention, and onsite data collection and pretest non-equivalence that often occur when l classrooms, schools and communities are assigned to condition. In this project, we will (1) gather data from previous longitudinal drug and alcohol research projects focused on adolescents; (2) harmonize these data to match a predefined coding scheme and include them in an integrated referential database; (3) refine and validate statistical models developed during Phase I to ensure algorithms used to generate virtual control cases are valid and replicable; (4) prepare a web-based system that will allow virtual control group technology to be maximally automated; and (5) conduct de novo field trials of disseminated interventions to demonstrate the viability of the system for providing meaningful comparisons.

Public Health Relevance Statement:
NARRATIVE Adolescent drug use, including the consumption of alcohol, cigarettes and marijuana remain significant health and social problems. Programs designed to prevent substance use need to be evaluated to assure they are effective. This research will develop a tool that program providers and those charged with administrative oversight can use to evaluate program effectiveness.

Project Terms:
Adolescent; adolescent drug use; Adopted; Affect; Alcohol consumption; alcohol prevention; alcohol research; Alcohols; Algorithms; Archives; Area; case control; Characteristics; Charge; Cigarette; cigarette smoking; Code; Communities; Control Groups; control trial; cost; course development; Data; Data Collection; data resource; Data Set; Databases; demographics; design; Development; Drug Prevention Program; Drug usage; Effectiveness; Effectiveness of Interventions; efficacy study; Elements; Ensure; epidemiology study; Etiology; Funding; Future; Goals; Health; Intervention; Knowledge; Marijuana; marijuana use; Measures; Mediating; Methods; Modeling; Online Systems; Outcome; Participant; Pattern; Pharmaceutical Preparations; Phase; Prevention; Prevention Research; Preventive Intervention; Process; Program Effectiveness; programs; Provider; psychosocial; Randomized; recruit; Research; Research Personnel; Research Project Grants; research study; Scheme; Schools; Services; Small Business Innovation Research Grant; Social Problems; Statistical Models; substance use prevention; System; Technology; Testing; Time; tool; treatment group; virtual; Work