five

Descriptive statistics.

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NIAID Data Ecosystem2026-05-02 收录
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https://figshare.com/articles/dataset/Descriptive_statistics_/25747311
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Introduction Mothers faced an increased risk of adverse mental health outcomes during the COVID-19 pandemic compared to other populations. However, there is little data on the factors that placed mothers at increased risk of distress. Aims The present study explored a range of individual, familial, and environmental factors associated with psychological distress in mothers during the COVID-19 pandemic. Method This repeated cross-sectional study was composed of a convenience sample of mothers who completed an online survey that included a demographic questionnaire, an emotion regulation questionnaire, and the Depression, Anxiety, and Stress scale. The survey was administered during the second and third lockdowns in Israel in 2020–2021. Results The study included 575 mothers (M age = 39). The findings of a hierarchical regression indicated that individual-level factors, composed of age and emotion regulation tendencies predicted psychological distress. The family-level factors of household income and number of children in the family also predicted distress. In terms of environmental-level factors, COVID-19-related media consumption and school status (open or closed) were also significant predictors of psychological distress. Importantly, the results showed that the most important predictors of psychological distress in mothers during the COVID-19 outbreak were school closures, household income, and the use of adaptive and maladaptive emotion regulation strategies. Conclusions The findings highlight the intersection of individual, familial, and environmental factors in mothers’ mental health during crises.
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2024-05-03
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