Machine-learning approaches to identify determining factors of happiness during the COVID-19 pandemic: retrospective cohort study

To investigate determining factors of happiness during the COVID-19 pandemic. Observational study. Large online surveys in Japan before and during the COVID-19 pandemic. A random sample of 25 482 individuals who are representatives of the Japanese population. Self-reported happiness measured using a...

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Bibliographic Details
Published in:BMJ open 2022-12, Vol.12 (12), p.e054862
Main Authors: Osawa, Itsuki, Goto, Tadahiro, Tabuchi, Takahiro, Koga, Hayami K, Tsugawa, Yusuke
Format: Article
Language:English
Subjects:
COVID-19 - epidemiology
Female
Happiness
Humans
Machine Learning
Pandemics
Public Health
Retrospective Studies
SARS-CoV-2
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Summary:To investigate determining factors of happiness during the COVID-19 pandemic. Observational study. Large online surveys in Japan before and during the COVID-19 pandemic. A random sample of 25 482 individuals who are representatives of the Japanese population. Self-reported happiness measured using a 10-point Likert scale, where higher scores indicated higher levels of happiness. We defined participants with ≥8 on the scale as having high levels of happiness. Among the 25 482 respondents, the median score of self-reported happiness was 7 (IQR 6-8), with 11 418 (45%) reporting high levels of happiness during the pandemic. The multivariable logistic regression model showed that meaning in life, having a spouse, trust in neighbours and female gender were positively associated with happiness (eg, adjusted OR (aOR) for meaning in life 4.17; 95% CI 3.92 to 4.43; p
ISSN:2044-6055
2044-6055
DOI:10.1136/bmjopen-2021-054862