Community-Based Study Recruitment of American Indian Cigarette Smokers and Electronic Cigarette Users

• DOI: 10.1007/s10900-017-0401-0
• Publication Date: 2017-07-07T08:58:49Z
• Authors: Dana Mowls Carroll; Lacy S. Brame; Lancer D. Stephens; Theodore L. Wagener; Janis E. Campbell; Laura A. Beebe
• Keywords: Adult; Male; Adolescent; Patient Selection; Pilot Projects; Electronic Nicotine Delivery Systems; Middle Aged; 16. Peace & justice; Young Adult; 03 medical and health sciences; 0302 clinical medicine; Research Design; Indians, North American; Humans; Female; Aged

Data on the effectiveness of strategies for the recruitment of American Indians (AIs) into research is needed. This study describes and compares methods for identifying and recruiting AI tobacco users into a pilot study. Community-based strategies were used to recruit smokers (n = 35), e-cigarette users (n = 28), and dual users (n = 32) of AI descent. Recruitment was considered proactive if study staff contacted the individual at a pow wow, health fair, or vape shop and participation on-site or reactive if the individual contacted the study staff and participation occurred later. Screened, eligible, participated and costs and time spent were compared with Chi square tests. To understand AI descent, the relationship between number of AI grandparents and AI blood quantum was examined. Number of participants screened via the proactive strategy was similar to the reactive strategy (n = 84 vs. n = 82; p-value = 0.8766). A significantly greater proportion of individuals screened via the proactive than the reactive strategy were eligible (77 vs. 50%; p-value = 0.0002) and participated (75 vs. 39%; p-value = < 0.0001). Per participant cost and time estimated for the proactive strategy was $89 and 87 min compared to $79 and 56 min for the reactive strategy. Proportion at least half AI blood quantum was 32, 33, and 70% among those with 2, 3, and 4 AI grandparents, respectively (p = 0.0017). Proactive strategies resulted in two-thirds of the sample, but required more resources than reactive strategies. Overall, we found both strategies were feasible and resulted in the ability to reach sample goals. Lastly, number of AI biological grandparents may be a good, non-invasive indicator of AI blood quantum.