Post-9/11 Veterans' Heart Disease Knowledge, Self-Perceived Risk, and Prevention Beliefs and Behaviors

HEALTH PSYCHOLOGY(2021)

引用 2|浏览11
暂无评分
摘要
Objective: Veterans, including the growing number of women veterans, have a greater risk of heart disease than nonveterans, and the incidence of heart disease is increasing among the most recent veterans who participated in post-9/11 military conflicts. Investigating heart disease-related knowledge, self-perceived risk, and prevention beliefs and behavior among these veterans, and identifying potential differences in knowledge, risk, beliefs and behavior between men and women, may guide prevention strategies. Method: Cross-sectional data from a nationwide survey of 1,141 (53% women) post-9/11 veterans were used to examine heart disease awareness and information-seeking, perceived risk and importance of heart disease risk factors, beliefs about traditional (e.g., weight, blood pressure) and nontraditional (e.g., stress, sleep) factors, and engagement in prevention behaviors. Differences between men and women were also tested, using t-tests, chi-square, and Fisher's exact tests. Results: Only one-third reported they felt very informed or sought information about heart disease, or that their providers had discussed heart disease with them. Although veterans generally believe that addressing traditional and nontraditional factors can reduce their risk of heart disease, far fewer endorsed the value of mental health treatment in prevention. Overall, women were slightly more knowledgeable about heart disease risk, and of behaviors that can lower this risk, but for both men and women, this knowledge did not translate to engaging in equivalent prevention behaviors. Conclusions: Post-9/11 veterans, and potentially their providers, may each benefit from improved education regarding their risk of heart disease. Veterans may also require better, more personalized approaches to prevention.
更多
查看译文
关键词
cardiovascular disease, health knowledge, prevention, sex differences, veterans
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要