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The main objectives of our study were to explore reasons for seasonal influenza vaccine acceptance and declination in employees of a large integrated healthcare system and to identify underlying constructs that influence acceptance versus declination. Secondary objectives were to determine whether vaccine acceptance varied by hospital location and to identify facility-level measures that explained variability.
A national health promotion survey of employees was conducted that included items on vaccination in the 2009-2010 influenza season. The survey was administered with two other institutional surveys in a stratified fashion: approximately 40% of participating employees were randomly assigned to complete the health promotion survey.
National single-payer healthcare system with 152 hospitals.
Employees of the healthcare system in 2010 who responded to the survey.
Factor analysis was used to identify underlying constructs that influenced vaccine acceptance versus declination. Mean factor scores were examined in relation to demographic characteristics and occupation. Multilevel logistic regression models were used to determine whether vaccine acceptance varied by location and to identify facility-level measures that explained variability.
Four factors were identified related to vaccine declination and were labeled as (1) “don't care,” (2) “don't want,” (3) “don't believe,” and (4) “don't know.” Significant differences in mean factor scores existed by demographic characteristics and occupation. Vaccine acceptance varied by location, and vaccination rates in the previous year were an important facility-level predictor.
Results should guide interventions that tailor messages on the basis of particular reasons for declination. Occupation-specific and culturally appropriate messaging should be considered. Continued efforts will be taken to better understand how workplace context influences vaccine acceptance.
Attracting students to engineering is a challenge. In addition, ABET requires that engineering graduates be able to work on multi-disciplinary teams and apply mathematics and science when solving engineering problems. One manner of integrating teamwork and engineering contexts in a first-year foundation engineering course is through the use of Model-Eliciting Activities (MEAs) - realistic, client-driven problems based on the models and modeling theoretical framework. A Model-Eliciting Activity (MEA) is a real-world client-driven problem. The solution of an MEA requires the use of one or more mathematical or engineering concepts that are unspecified by the problem - students must make new sense of their existing knowledge and understandings to formulate a generalizable mathematical model that can be used by the client to solve the given and similar problems. An MEA creates an environment in which skills beyond mathematical abilities are valued because the focus is not on the use of prescribed equations and algorithms but on the use of a broader spectrum of skills required for effective engineering problem-solving. Carefully constructed MEAs can begin to prepare students to communicate and work effectively in teams; to adopt and adapt conceptual tools; to construct, describe, and explain complex systems; and to cope with complex systems. MEAs provide a learning environment that is tailored to a more diverse population than typical engineering course experiences as they allow students with different backgrounds and values to emerge as talented, and that adapting these types of activities to engineering courses has the potential to go beyond “filling the gaps” to “opening doors” to women and underrepresented populations in engineering. Further, MEAs provide evidence of student development in regards to ABET standards. Through NSF-funded grants, multiple MEAs have been developed and implemented with a MSE-flavored nanotechnology theme. This paper and presentation will focus on the content, implementation, and student results of these MEAs.
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