Repeat participation in annual cross-sectional surveys of drug users and its implications for analysis

Abstract

Abstract Objective We sought to establish the extent of repeat participation in a large annual cross-sectional survey of people who inject drugs and assess its implications for analysis. Results We used “porn star names” (the name of each participant’s first pet followed by the name of the first street in which they lived) to identify repeat participation in three Australian Illicit Drug Reporting System surveys. Over 2013–2015, 2468 porn star names (96.2%) appeared only once, 88 (3.4%) twice, and nine (0.4%) in all 3 years. We measured design effects, based on the between-cluster variability for selected estimates, of 1.01–1.07 for seven key variables. These values indicate that the complex sample is (e.g.) 7% less efficient in estimating prevalence of heroin use (ever) than a simple random sample, and 1% less efficient in estimating number of heroin overdoses (ever). Porn star names are a useful means of tracking research participants longitudinally while maintaining their anonymity. Repeat participation in the Australian Illicit Drug Reporting System is low (less than 5% per annum), meaning point-prevalence and effect estimation without correction for the lack of independence in observations is unlikely to seriously affect population inference.

Keywords

• Repeat participation
• Cross-sectional survey
• Point prevalence estimation
• Design effect estimation
• Population inference