| Popis: |
For the second study, a web-based survey was developed and distributed to all members of four major health education organizations. A total of 1,925 HEs’ completed the survey and 1,607 responses were utilized in the final analysis. This study indicated that participants had deficient knowledge and unfavorable attitudes toward the CDCproposed genomic competencies. In the third study, a theoretical model was developed to predict HEs’ likelihood to incorporate genomic competencies into their practice. Using techniques from Structural Equation Modeling (SEM), the model was tested with the same data of the second study. Findings supported the proposed theoretical model. While genomic knowledge, attitudes, and self-efficacy were significantly associated with HEs’ likelihood to incorporate genomic competencies into their practice, attitudes was the strongest predictor of likelihood. In summary, these studies indicated that participating HEs had deficient genomic knowledge, unfavorable attitudes toward a set of CDC-proposed genomic competencies, and low likelihood to adopt genomic competencies into health promotion. Relevant training should be developed and advocated. As the SEM analysis results indicated the survey findings supported the proposed theoretical model, which can be utilized to steer future training for HEs. statistics, 2) unadjusted inferential statistics, 3) stratified analysis, and 4) multivariable models. My investigation produced results in accord with generally accepted notions in addition to significant findings that interestingly counter current preconceptions. Intraspecies contact was more common than inter-species, with indirect contact occurring more frequently than direct. Direct contact between species occurred extremely rarely. The most important factors that influenced the rate of contact for both species were water, winter, and cultivated fields. Information regarding probability of infectious agent survival and transfer will be used in the future to advance current epidemiological models, including geographicautomata (Ward et al. 2007: In Press) and cellular automata models (Doran and Laffan 2005) to better understand and manage integrated domestic cattle and free-ranging wildlife populations. Such modeling provides essential and necessary knowledge for developing prevention, detection, response, and recovery strategies – employed in advance, during, and after a disease outbreak, respectively. |
