International Research Institute of Disaster Science (IRIDeS), Tohoku University, Sendai 980-8572, Japan.
Department of Architecture and Building Science, School of Engineering, Tohoku University, Sendai 980-8579, Japan.
Int J Environ Res Public Health. 2022 Sep 25;19(19):12146. doi: 10.3390/ijerph191912146.
This study aims to examine people's perception of well-being during the COVID-19 pandemic in Japan and quantitatively clarify key factors towards realizing evidence-based policymaking. In March 2022, 400 participants responded to a survey conducted through Rakuten Insight. The authors applied an ordinal logistic regression (OLR), followed by principal component analysis (PCA), to create a new compound indicator (CI) to represent people's perception of well-being during the pandemic in addition to ordinary least squares (OLS) regression with a forward-backward stepwise selection method, where the dependent variable is the principal component score of the first principal component (PC1), while the independent variables are the same as the abovementioned OLR. Consequently, while analyzing OLR, some independent variables showed statistical significance, while the CI provided an option to grasp people's perception of well-being. Furthermore, family structure was statistically significant in all cases of OLR and OLS. Moreover, in terms of the standardized coefficients (beta) of OLS, the family structure had the greatest impact on the CI. Based on the study results, the authors advocate that the Japanese government should pay more attention to single-person households affected by the COVID-19 pandemic.
本研究旨在探讨日本民众在 COVID-19 大流行期间的幸福感认知,并通过定量方法明确实现循证决策的关键因素。2022 年 3 月,通过 Rakuten Insight 对 400 名参与者进行了调查。作者采用有序逻辑回归(OLR),随后进行主成分分析(PCA),创建了一个新的综合指标(CI),以代表大流行期间人们对幸福感的认知,同时采用向前-向后逐步选择法进行普通最小二乘法(OLS)回归,其中因变量为主成分得分第一主成分(PC1),而自变量与上述 OLR 相同。因此,在分析 OLR 时,一些自变量具有统计学意义,而 CI 则提供了一种把握人们幸福感认知的选择。此外,在 OLR 和 OLS 的所有情况下,家庭结构均具有统计学意义。而且,就 OLS 的标准化系数(beta)而言,家庭结构对 CI 的影响最大。基于研究结果,作者主张日本政府应更加关注受 COVID-19 大流行影响的单身家庭。