谷歌浏览器插件
订阅小程序
在清言上使用

Factors linked to participant attrition in a longitudinal occupational health surveillance program (vol 65, pg 431, 2022)

AMERICAN JOURNAL OF INDUSTRIAL MEDICINE(2022)

引用 0|浏览14
暂无评分
摘要
Background For occupational medical screening programs focused on long-term health surveillance, participant attrition is a significant barrier to success. We investigate demographic, medical history, and clinical data from National Supplemental Screening Program (NSSP) examinees for association with likelihood of return for a second exam (rescreening). Methods A total of 15,733 individuals completed at least one NSSP exam before December 31, 2016; of those, 4832 also completed a second exam on or before December 31, 2019. Stepwise logistic regression models were used to identify variables associated with whether a participant was rescreened in the NSSP. Results Individuals were less likely to return for rescreening if they had a history of any cancer; cardiovascular problems; diabetes or kidney disease; or if they used insulin. Age at time of first exam and job site category significantly influenced likelihood of return. Workers categorized as "guests" were more likely to return. Participants were less likely to return if they had an abnormal urinalysis, abnormal pulmonary function, pneumoconiosis, aortic atherosclerosis, or hearing loss at their initial exam. Participants who received a chest X-ray at their initial screening were more likely to return. Conclusions The presence of health problems is strongly linked to screening program attrition. Participants who are older at the time of their initial screening exam are less likely to return. The discovery of several strong demographic, medical, and job associations reveals the importance for medical screening programs to understand and address factors that influence participant retention and, consequently, the effectiveness of long-term health surveillance activities.
更多
查看译文
关键词
attrition, exposures, former worker, occupational health, screening
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