Segmenting Audiences and Tailoring Messages: Using the Extended Parallel Process Model and Cluster Analysis to Improve Health Campaigns

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.