Health surveillance through social networks

被引:5
作者
An, Weihua [1 ,2 ]
Doan, Long [3 ]
机构
[1] Indiana Univ, Dept Sociol, Bloomington, IN 47405 USA
[2] Indiana Univ, Dept Stat, Bloomington, IN 47405 USA
[3] Indiana Univ, Dept Sociol, Bloomington, IN 47405 USA
基金
美国国家科学基金会;
关键词
Health surveillance; Social networks; Informants; Reporting bias; Peer reports; Smoking; P-ASTERISK MODELS; SMOKING; RELIABILITY; ADOLESCENTS; NONSMOKERS; ALCOHOL; SMOKERS;
D O I
10.1016/j.socnet.2015.02.001
中图分类号
Q98 [人类学];
学科分类号
030303 ;
摘要
We propose a network-based method to monitor health behaviors and point out the general conditions for it to work effectively. The method helps to identify effective informants for monitoring future health behaviors and to triangulate self-reports of sensitive health behaviors. We demonstrate the method by studying the smoking behaviors of over 4000 middle school students in China. Using students' observations of their schoolmates smoking in the past 30 days, we construct smoking detection networks and examine the patterns of smoking detection. We find that smokers, optimistic students, and popular students make better informants than their counterparts. We also find that using three to four (or the 3rd quartile of) positive peer reports can uncover a good number of under-reported smokers while not producing excessive false positives. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:8 / 17
页数:10
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