＜编辑精选＞使用文本挖掘开发在线讲座可减少COVID-19非震中地区卫生工作者的焦虑

摘要(中文译文)

2019冠状病毒病（COVID-19）与焦虑、失眠、抑郁等多种精神障碍间接相关，而诊治COVID-19患者的医护人员尤其容易出现严重焦虑。然而，迄今为止，非疫情中心地区医护人员的焦虑状况以及知识支持的效果均尚未得到研究。研究对象为丰田地区医疗中心的458名工作人员，他们完成了一份关于COVID-19知识和焦虑的初步问卷。基于对问卷回答的文本挖掘，向参与者提供了一场在线讲座。通过讲座前后对焦虑和知识信心的评分以及定量文本挖掘，分析讲座的效果。讲座前和讲座后的应答率分别为45.6%和62.9%。关于焦虑和知识的开放式回答通过共现网络被分为七个聚类。讲座前，分别有28.2%、27.2%和20.3%的参与者对“感染预防与本院的应对措施”“感染及其对我自身、家人和邻居的影响”以及“COVID-19的一般知识”感兴趣并感到焦虑。讲座后，COVID-19焦虑的李克特量表评分显著下降，知识信心显著提高。这些变化通过关于焦虑、生活方式改变和知识的开放式回答分析得到证实。积极变化与讲座所聚焦的主题密切相关，尤其是感染预防。非疫情中心地区医护人员的COVID-19焦虑可以通过问卷调查和基于文本挖掘的在线讲座得到有效缓解。

Abstract

COVID-19 is indirectly associated with various mental disorders such as anxiety, insomnia, and depression, and healthcare professionals who treat COVID-19 patients are particularly prone to severe anxiety. However, neither the anxiety of healthcare workers in non-epicenter areas nor the effects of knowledge support have been examined thus far. Participants were 458 staff working at the Toyota Regional Medical Center who completed a preliminary questionnaire of their knowledge and anxiety regarding COVID-19. Based on text mining of the questionnaire responses, participants were offered an online lecture. The effect of the lecture was analyzed using a pre- and post-lecture rating of anxiety and knowledge confidence, and quantitative text mining. The response rates were 45.6% pre- and 62.9% post-lecture. Open-ended responses regarding anxiety and knowledge were classified into seven clusters using a co-occurrence network. Before the lecture, 28.2%, 27.2%, and 20.3% of participants were interested in and anxious about "infection prevention and our hospital's response," "infection and impact on myself, family, and neighbors," and "general knowledge of COVID-19," respectively. As a result of the lecture, Likert-scale ratings for anxiety of COVID-19 decreased significantly and knowledge confidence increased significantly. These changes were confirmed by analyses of open-ended responses about anxiety, lifestyle changes, and knowledge. Positive changes were strongly linked to the topics focused on in the lecture, especially infection prevention. The anxieties about COVID-19 of healthcare workers in non-epicenter areas can be effectively reduced through questionnaire surveys and online lectures using text mining.

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