Date of Award
Doctor of Philosophy in Psychology
This study examined how adjusting the degree of school involvement and types of recruitment channel relate to research recruitment effectiveness in both rural and urban high-school populations. Presently, there is a lack of consensus in the literature on the most useful media based channel or cost-effective strategy for sampling adolescents in school-based research. This study represents the second of a two-phased exploratory trial to determine effectiveness and cost-efficiency of examined methods to recruit adolescents to participate in online research. Varying combinations of social media channels (QR codes, Facebook ads) and degrees of school involvement (none, passive, active) were implemented at six different high schools, and a systematic tracking method was implemented to maintain involvement fidelity in each of the six schools. The results revealed that the combination of using QR Codes with active level of school involvement recruited the highest sample response percentage, but generated the highest cost per recruited participant; whereas QR Codes combined with no school involvement recruited the second lowest recruitment percentage but generated the second lowest recruitment cost per participant. Furthermore, in both rural and urban communities, there appeared to be a strong pattern of decreased cost-effectiveness of using social media for recruitment as the amount of school involvement increased. This is the first known study to examine QR Codes and Facebook combined with varying amounts of school involvement; as well as the first known study that seeks to understand how adjusting the amount of school involvement relates to recruitment effectiveness and cost-efficiency in this context. The findings are interpreted from a variety of theoretical and conceptual frameworks, including implementation feasibility, method sustainability, and cost-effectiveness.
Gu, Lucy Ling, "Varying Social Media and Involvement to Determine Recruitment Effectiveness in Adolescent Populations" (2018). Open Access Dissertations. Paper 733.
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