Faculty Publications
Segmenting Audiences And Tailoring Messages: Using The Extended Parallel Process Model And Cluster Analysis To Improve Health Campaigns
Document Type
Article
Keywords
Audience segmentation, Extended parallel process model, Unintended pregnancy
Journal/Book/Conference Title
Social Marketing Quarterly
Volume
18
Issue
2
First Page
98
Last Page
111
Abstract
Half of all pregnancies in young adult women are unintended, but few interventions have been successful in encouraging contraceptive use. The group heterogeneity likely contributes to the lack of success. Segmenting based on theories that provide meaningful information may improve tailoring and targeting of behavioral interventions. Previous research has indicated that threat, efficacy, and fear were important factors in influencing intentions to use contraceptives; therefore, the extended parallel process model (EPPM) was used for this cluster analysis. A telephone survey of randomly selected 18-to 30-year-old women in Iowa was conducted (N = 401). The constructs of EPPM and age were used for conducting a K means cluster analysis with four clusters. The cluster analysis pointed to the importance of fear, perceived susceptibility, and age. All of the clusters had varying degrees of ambivalence about the severity of a pregnancy. Cluster 1 (27.8%) had high susceptibility, with little fear. Cluster 2 (23.8%) had high efficacy and higher fear. The third cluster (34.7%) was not fearful and had low susceptibility. The final cluster (13.8%) was younger than the other groups and had the lowest efficacy. Additional analyses were conducted to explore how the clusters varied on other variables. The clusters help campaign developers prioritize audiences and tailor messages. © The Author(s) 2012.
Department
Department of Psychology
Original Publication Date
6-1-2012
DOI of published version
10.1177/1524500412450490
Recommended Citation
Campo, Shelly; Askelson, Natoshia M.; Carter, Knute D.; and Losch, Mary, "Segmenting Audiences And Tailoring Messages: Using The Extended Parallel Process Model And Cluster Analysis To Improve Health Campaigns" (2012). Faculty Publications. 1777.
https://scholarworks.uni.edu/facpub/1777