AIDS and Behavior 2017;21(2):534-546. [doi: 10.1007/s10461-016-1628-y]
Yue Pan, PhD (Univerity of Miami Miller School of Medicine, FNA Node), Hongmei Liu (Univerity of Miami Miller School of Medicine, FNA Node), Lisa R. Metsch, PhD (Columbia University, FNA Node), Daniel J. Feaster, PhD (Univerity of Miami Miller School of Medicine, FNA Node).
HIV testing is the foundation for consolidated HIV treatment and prevention. This study aimed to discover the most relevant variables for predicting HIV testing uptake among substance users in substance use disorder treatment programs by applying random forest (RF), a robust multivariate statistical learning method. It also provides a descriptive introduction to this method for those who are unfamiliar with it. This secondary analysis used data from the NIDA Clinical Trials Network HIV testing and counseling study (CTN-0032). A total of 1281 HIV-negative or status unknown participants from 12 U.S. community-based substance use disorder treatment programs were included and were randomized into three HIV testing and counseling groups. The a priori primary outcomes was self-reported receipt of HIV test results. Classification accuracy of RF was compared to logistic regression, a standard statistical approach for binary outcomes. Variable importance measures for the RF model were used to select the most relevant variables. RF based models produced much higher classification accuracy than those based on logistic regression. Treatment group is the most important predictor among all covariates, with a variable importance index of 12.9%. RF variable importance revealed that several types of condomless sex behaviors, condom use self-efficacy and attitudes towards condom use, and level of depression are the most important predictors of receipt of HIV testing results. There is a non-linear negative relationship between count of condomless sex acts and the receipt of HIV testing.
Conclusions: RF seems promising in discovering important factors related to HIV testing uptake among large numbers of predictors and should be encouraged in future HIV prevention and treatment research and intervention program evaluations. (Article (Peer-Reviewed), PDF, English, 2017)
Keywords: CTN platform/ancillary study | HIV/AIDS | HIV rapid testing | Statistical models | AIDS and Behavior (journal)
Document No: 1240, PMID: 27933461, PMCID: PMC5583728 (available 2/1/2018).
Submitted by CTN Dissemination Librarians, 12/14/2016.