Maximizing Retention with High Risk Participants in a Clinical Trial

Abstract

Purpose To describe effective retention strategies in a clinical trial with a high risk, low income, and vulnerable patient population with serious mental illness. Design Follow-up assessments were conducted for a randomized clinical tobacco treatment trial at 3-, 6-, and 12-months post-baseline. Initial follow-up rates of <40% at 3-months led to implementation of proactive retention strategies including obtaining extensive contact information; building relationships with case managers and social workers; contacting jails and prisons; text messaging, e-mailing, and messaging via social networking sites; identifying appointments via electronic medical record; and field outreach to treatment facilities, residences, and parks. Setting Large urban public hospital Subjects Participants were current smokers recruited from 100% smoke-free locked psychiatry units. Measures Assessments covered demographics, substance use, and mental health functioning. Analysis Retention rates were plotted over time in relation to key retention strategies. Chi-square and t-tests were used to examine participant predictors of retention at each follow-up. At the 12-month follow-up, the retention strategies that most frequently led to assessment completion were identified. Results The sample (N=100) was 65% male; age M=39.5 years (SD=11.3); 44% non-Hispanic White; 46% on Medicaid and 34% uninsured; 79% unemployed; and 48% unstably housed. Proactive retention strategies dramatically increased follow-up rates, concluding at 3-months=82.65%, 6-months=89.69%, and 12-months=92.78%. Married and divorced/separated/widowed participants, those with higher income, and participants with alcohol or illicit drug problems had increased retention from 3 to 12-months follow-up. Conclusion Follow-up rates improved as proactive methods to contact participants were implemented. Dedicated research staff, multiple methods, community networking, and outreach within drug treatment settings improved retention.

Predictors of retention in a randomised trial of smoking cessation in low-socioeconomic status Australian smokers

“…This is not entirely consistent with the wider literature, as some studies have identified an association between increased motivation and confidence to quit and retention, [26,57,58] while others have found the opposite association or no association at all. [37] It is noteworthy that a number of the more commonly known sociodemographic characteristics that have been associated with retention in other smoking cessation studies, [15,21,59] were not associated with retention in our study, e.g. sex, marital status, nicotine dependence, and self-reported quit status at 2-month follow-up .…”

Initial Findings from a Feasibility Trial Examining the SafeCare Dad to Kids Program with Marginalized Fathers

“…With non-violent discipline, the outcome slope increases for Dad2K participants and decreases for the comparison group. However, the fact that there were no significant findings for this outcome is not all that surprising given that parents who use little to high physical punishment often report using high non-violence discipline (Kim, et al; 2014; Lee et al, 2011). Further study of this outcome is warranted, especially with programs such as SafeCare that focus on teaching nonviolent behaviorally based discipline approaches.…”

Treating Tobacco Dependence at the Intersection of Diversity, Poverty, and Mental Illness: A Randomized Feasibility and Replication Trial

“…More than 80% of follow-up assessments were completed at all time points, with retention rates increasing over the course of the trial due to greater outreach efforts. 30 Retention was 86% for the intervention group and 94% for the usual care group at the 12-month follow-up, a nonsignificant difference (Figure 1). No measured characteristics predicted 12-month retention.…”

“…29 For the current study, treatment adaptations included use of more ethnically diverse and urban images in the computer program and treatment manual, greater reference to menthol tobacco use, the tobacco industry's marketing of cigarettes to Blacks and lower income smokers, and greater outreach in the field to ensure completion of post-hospitalization treatment sessions. 30 We randomly assigned participants to the treatment or enhanced usual care arm through a computer-generated random assignment program stratified by baseline cigarettes per day (>15) and stage of change, two variables predictive of quitting smoking and addressed by the intervention. 27,31 Research staff was blinded to the randomization schedule.…”