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The goal of this study was to investigate the willingness of Medical Reserve Corps (MRC) volunteers to participate in public health emergency-related activities by assessing their attitudes and beliefs. MRC volunteers responded to an online survey organized around the Extended Parallel Process Model (EPPM). Respondents reported agreement with attitude/belief statements representing perceived threat, perceived efficacy, and personal/organizational preparedness in 4 scenarios: a weather-related disaster, a pandemic influenza emergency, a radiological ("dirty bomb") emergency, and an inhalational anthrax bioterrorism emergency. Logistic regression analyses were used to evaluate predictors of volunteer response willingness. In 2 response contexts (if asked and regardless of severity), self-reported willingness to respond was higher among those with a high perceived self-efficacy than among those with low perceived self-efficacy. Analyses of the association between attitude/belief statements and the EPPM profiles indicated that, under all 4 scenarios and with few exceptions, those with a perceived high threat/high efficacy EPPM profile had statistically higher odds of agreement with the attitude/belief statements than those with a perceived low threat/low efficacy EPPM profile. The radiological emergency consistently received the lowest agreement rates for the attitude/belief statements and response willingness across scenarios. The findings suggest that enrollment with an MRC unit is not automatically predictive of willingness to respond in these types of scenarios. While MRC volunteers' self-reported willingness to respond was found to differ across scenarios and among different attitude and belief statements, the identification of self-efficacy as the primary predictor of willingness to respond regardless of severity and if asked highlights the critical role of efficacy in an organized volunteer response context.

Assessment of Medical Reserve Corps Volunteers' Emergency Response Willingness Using a Threat- and Efficacy-Based Model