Selected article for: "binary logistic regression and gender age"

Author: Wang, Yu; Zhu, Li-Yun; Ma, Yu-Fen; Bo, Hai-Xin; Deng, Hai-Bo; Cao, Jing; Wang, Ying; Wang, Xiao-Jie; Xu, Yuan; Lu, Qiao-Dan; Wang, Hui; Wu, Xin-Juan
Title: Association of insomnia disorder with sociodemographic factors and poor mental health in COVID-19 inpatients in China
  • Cord-id: zfz1rczx
  • Document date: 2020_6_12
  • ID: zfz1rczx
    Snippet: PURPOSE: To examine insomnia disorder and its association with sociodemographic factors and poor mental health in 2019 novel coronavirus (COVID-19) inpatients in Wuhan, China. DESIGN: and Methods: A total of 484 COVID-19 inpatients in Wuhan Tongji Hospital were selected and interviewed with standardized assessment tools. Insomnia disorder was measured by the Chinese version of the Insomnia Severity Index (ISI-7), a total score of 8 or more was accepted as the threshold for diagnosing insomnia di
    Document: PURPOSE: To examine insomnia disorder and its association with sociodemographic factors and poor mental health in 2019 novel coronavirus (COVID-19) inpatients in Wuhan, China. DESIGN: and Methods: A total of 484 COVID-19 inpatients in Wuhan Tongji Hospital were selected and interviewed with standardized assessment tools. Insomnia disorder was measured by the Chinese version of the Insomnia Severity Index (ISI-7), a total score of 8 or more was accepted as the threshold for diagnosing insomnia disorder. RESULTS: The prevalence of insomnia disorder in the whole sample was 42.8%. Binary logistic regression analysis revealed that female gender, younger age, and higher fatigue and anxiety severity were more likely to experience insomnia disorder. CONCLUSION: Given the high rate of insomnia disorder status among COVID-19 inpatients in Wuhan, China, and its negative effects, follow-up assessments and appropriate psychological interventions for insomnia disorder are needed in this population.

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