The use of online methods to recruit and follow a hard-to-reach population in the Peer Alternatives for Addiction Study 2021 Cohort.

Abstract

Although studies are increasingly adopting online protocols, few such studies in the addiction field have comprehensively described their data review procedures and successes in detecting low-quality/fraudulent data. The current study describes data collection protocols and outcomes of a large, longitudinal study (the PAL Study 2021) that implemented online design elements to study individuals seeking peer support for an alcohol use disorder. In 2021, the PAL Study collaborated with mutual-help group (MHG) partners and recovery-related organizations to recruit individuals attending a 12-step group, Women for Sobriety (WFS), LifeRing Secular Recovery, and/or SMART Recovery for an alcohol problem in-person and/or online in the prior 30 days. Participation was solicited both online and in-person. Individuals accessed baseline surveys via an open web link; follow-ups occurred at 6 and 12 months. Analyses included calculating the proportion of surveys eliminated in data quality review; comparing MHG subsamples to internal survey (benchmark) data for Alcoholics Anonymous (AA), WFS, LifeRing, and SMART; and examining response rates and attrition. Although 93% of respondents who opened the baseline survey completed it, 87% of baseline surveys were eliminated in data quality review (final N = 531). Nonetheless, cleaned MHG subsamples were generally similar to benchmark samples on gender, age, race/ethnicity, and education. Follow-up rates for the cleaned sample were 88% (6 months) and 85% (12 months). Analyses revealed some differences in attrition by gender, primary MHG, and lifetime drug problems, but there was no evidence of greater attrition among those in earlier/less stable recovery. Study methods appear to have produced a valid, largely representative sample of the hard-to-reach target population that was successfully followed across 12 months. However, given the high survey elimination rate and need for extensive data review, we recommend that researchers avoid open-link designs and include comprehensive data review when incorporating online design elements.