Unplanned Closure of Public Schools in Michigan, 2015-2016: Cross-Sectional Study on Rurality and Digital Data Harvesting
Unplanned Closure of Public Schools in Michigan, 2015-2016: Cross-Sectional Study on Rurality and Digital Data Harvesting
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DOI：
10.1111/josh.12901
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发表时间：
2020-05-07
影响因子：
2.2
通讯作者：
Fung, Isaac C-H
中科院分区：
文献类型：
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作者：
Jackson, Ashley M.;Mullican, Lindsay A.;Fung, Isaac C-H
在预防大流行的背景下，研究人员使用在线系统搜索来跟踪计划外学校关闭(USC)。我们确定Twitter是否提供了补充数据。方法确定了密歇根州公立学校和学区的Twitter账号。与这些账号关联的所有推文都已下载。使用5个关键词识别了与南加州大学相关的推文。结果2003年在3469所密歇根州公立学校中，有自己的活跃Twitter账户或属于拥有活跃Twitter账户的学区。在这2003所学校中，在2015-2016学年，仅通过当前方法为349所学校确定了至少一项南加州大学公告，仅通过Twitter确定了678所学校，通过两种方法确定了562所学校。没有确定414所学校的南加州大学公告。农村学校比城市学校更不可能有活跃的推特覆盖(调整后的相对风险[adjRR]=0.3956，95%可信区间[CI]0.3312-0.4671)，并在推特上宣布USC(adjRR=0.5692，95%CI 0.4645-0.6823)，但更有可能通过当前方法识别USC(adjRR=1.4545，95%CI 1.3545-1.5490)。我们的结果表明，在Twitter上识别USC是对当前方法的补充。
BACKGROUND For pandemic preparedness, researchers used online systematic searches to track unplanned school closures (USCs). We determine if Twitter provides complementary data.METHODS Twitter handles of Michigan public schools and school districts were identified. All tweets associated with these handles were downloaded. USC-related tweets were identified using 5 keywords. Descriptive statistics and multivariable logistic regression were performed in R.RESULTS Among 3469 Michigan public schools, 2003 maintained their own active Twitter accounts or belonged to school districts with active Twitter accounts. Of these 2003 schools, in 2015-2016 school year, at least 1 USC announcement was identified for 349 schools via the current method only, 678 schools via Twitter only, and 562 schools via both methods. No USC announcements were identified for 414 schools. Rural schools were less likely than city schools to have active Twitter coverage (adjusted relative risk [adjRR] = 0.3956, 95% confidence interval [CI] 0.3312-0.4671), and to announce USCs on Twitter (adjRR = 0.5692, 95% CI 0.4645-0.6823), but more likely to have USCs identified by the current method (adjRR = 1.4545, 95% CI 1.3545-1.5490).CONCLUSIONS Each method identified USCs that were missed by the other. Our results suggested that identifying USCs on Twitter is complementary to the current method.