Psychometric properties of measures of substance use: a systematic review and meta-analysis of reliability, validity and diagnostic test accuracy - Glenn-Milo Santos; Steffanie A. Strathdee; Nabila El-Bassel; Poonam Patel; Divya Subramanian; Danielle Horyniak; Ryan R. Cook; Charlotte McCullagh; Phillip Marotta; Foram Choksi; Brian Kang; Isabel Allen; et al. (BMC Medical Research Methodology, 2020)
Abstract Background Synthesis of psychometric properties of substance use measures to identify patterns of use and substance use disorders remains limited. To address this gap, we sought to systematically evaluate the psychometric properties of measures to detect substance use and misuse. Methods We conducted a systematic review and meta-analysis of literature on measures of substance classes associated with HIV risk (heroin, methamphetamine, cocaine, ecstasy, alcohol) that were published in English before June 2016 that reported at least one of the following psychometric outcomes of interest: internal consistency (alpha), test-retest/inter-rater reliability (kappa), sensitivity, specificity, positive predictive value, and negative predictive value. We used meta-analytic techniques to generate pooled summary estimates for these outcomes using random effects and hierarchical logistic regression models. Results Findings across 387 paper revealed that overall, 65% of pooled estimates for alpha were in the range of fair-to-excellent; 44% of estimates for kappa were in the range of fair-to-excellent. In addition, 69, 97, 37 and 96% of pooled estimates for sensitivity, specificity, positive predictive value, and negative predictive value, respectively, were in the range of moderate-to-excellent. Conclusion We conclude that many substance use measures had pooled summary estimates that were at the fair/moderate-to-excellent range across different psychometric outcomes. Most scales were conducted in English, within the United States, highlighting the need to test and validate these measures in more diverse settings. Additionally, the majority of studies had high risk of bias, indicating a need for more studies with higher methodological quality.