Assessing Information Management for Breast Cancer Prevention & Information Management to Younger Women.
详细信息
- 作者：Heminger ; Christina L.
- 学历：Dr.P.H.
- 年：2014
- 毕业院校：The George Washington University
- Department：Public Health and Health Services
- ISBN：9781303817786
- CBH：3615703
- Country：USA
- 语种：English
- FileSize：4686226
- Pages：256
文摘
Patient-driven information management is vital for positive health outcomes and informed decision making. Younger women (＜50 years old) with family history may be at risk for breast cancer,yet while they are often encouraged to pursue risk reduction options,are left to their own devices to gather information,weigh cancer risk reduction options,and ultimately make an informed decision for a complex and uncertain issue. This dissertation tested an integrated theoretical model,combining constructs from the Risk Perception Attitude Framework and the Theory of Motivated Information Management,to assess how and why women move from risk perception to the ultimate decision to seek or avoid information. The integrated model succeeded in predicting information management: the omnibus model fit the data (R2 of 0.547)； similarly,the multi-group family history model was predictive of information management (no family history R2 ＝0.561； some/moderate family history R2 ＝ 0.573； significant family history R2 ＝ 0.701) and demonstrated that women with varying risk levels go through the information management process differently - namely,as family history "level" increases,so does risk perception. Overall,the dissertation data highlight the need for tailored communication for women with differing family histories in order to promote information seeking and informed decision making for breast cancer risk reduction. Specifically,the integrated model provides formative research for a tailored risk perception tool that can provide comparison-based risk assessments to help women categorize their risk level,particularly when current clinical guidelines either recommend or discourage risk reduction behaviors based on these categorizations.