COVID-19禍における勤労者の心理社会的負担―テキストマイニングを用いた探索的検討―

抄録

This study used text mining and examined workers’ psychosocial burdens caused by the COVID-19 pandemic. Employees in the Fukushima Branch of the Japanese Trade Union Confederation (RENGO Fukushima) and related workplaces responded to a web-based questionnaire survey. The survey inquired about psychosocial burdens caused by COVID-19, and the participants responded using a free-text format. We analyzed the responses of 215 respondents. Logistic regression analysis indicated a stronger association between female workers and severe psychological distress than male workers. In addition, correspondence analysis showed that workers with severe psychological distress used more words related to “income” and more first-personal pronouns such as “I” or “we.” In contrast, women with college-age children used more words related to “online college courses,” “burdens,” and “anxiety.” These results suggest that female workers with children experience significant stresses associated with their children, and workers with severe psychological distress experience psychosocial burdens related to their income.