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<编辑推荐>使用文本挖掘开发在线讲座可降低 COVID-19 非震中地区卫生工作者的焦虑。

<Editors' Choice> Developing online lectures using text mining reduces health workers' anxiety in non-epicenter areas of COVID-19.

机构信息

Department of General Medicine, Toyota Regional Medical Center, Toyota, Japan.

Department of General Medicine, Nagoya University Hospital, Nagoya, Japan.

出版信息

Nagoya J Med Sci. 2022 Feb;84(1):42-59. doi: 10.18999/nagjms.84.1.42.

DOI:10.18999/nagjms.84.1.42
PMID:35392011
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8971037/
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.

摘要

COVID-19 与各种精神障碍间接相关,如焦虑、失眠和抑郁,治疗 COVID-19 患者的医护人员尤其容易出现严重焦虑。然而,到目前为止,还没有研究非疫区医护人员的焦虑状况以及知识支持的效果。参与者是在丰田地区医疗中心工作的 458 名工作人员,他们完成了一份关于 COVID-19 的知识和焦虑初步问卷。基于问卷回答的文本挖掘,向参与者提供了在线讲座。使用焦虑和知识信心的讲座前后评分以及定量文本挖掘分析了讲座的效果。讲座前的应答率为 45.6%,讲座后的应答率为 62.9%。使用共现网络将关于焦虑和知识的开放式回答分为七个簇。在讲座之前,分别有 28.2%、27.2%和 20.3%的参与者对“感染预防和我们医院的应对措施”、“感染及其对我自己、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,对 COVID-19 的焦虑的李克特量表评分显著降低,知识信心显著增加。通过对焦虑、生活方式改变和知识的开放式回答的分析证实了这些变化。积极的变化与讲座中关注的主题密切相关,特别是感染预防。通过问卷调查和使用文本挖掘的在线讲座,可以有效减轻非疫区医护人员对 COVID-19 的焦虑。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/6f1ca0bf5340/2186-3326-84-0042-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/002072d32657/2186-3326-84-0042-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/dd90d786b366/2186-3326-84-0042-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/b4765af47e4e/2186-3326-84-0042-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/6f1ca0bf5340/2186-3326-84-0042-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/002072d32657/2186-3326-84-0042-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/dd90d786b366/2186-3326-84-0042-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/b4765af47e4e/2186-3326-84-0042-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0424/8971037/6f1ca0bf5340/2186-3326-84-0042-g004.jpg

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