Literature DB >> 33582522

The relationship between circadian typology and lifetime experiences of hypomanic symptoms.

Kounseok Lee1, Hye-Kyung Lee2, Sunhae Kim1, Seok Hyeon Kim3.   

Abstract

Circadian rhythms have been known to be associated with bipolar disorders. There are many cases in which hypomanic symptoms are not recognized as indicators of an illness. This study aimed to determine the correlation between the experience of lifetime hypomanic symptoms and circadian typology of university students. A total of 8,562 university students participated in the study. The participants completed the Composite Scale of Morningness (CSM) for circadian typology and Mood Disorder Questionnaire (MDQ). Chi-square test and analysis of variance were performed, and the post-hoc result was computed using the FDR adjusted p-values. Overall, the MDQ score was higher in the evening-type group. There was no significant difference between the intermediate-type group and morning-type group for male students. In the evening-type group, the positive response rate was significantly higher for 10 out of 13 items in the MDQ. The evening-type group was more likely to experience hypomanic symptoms. This study showed that circadian and seasonal characteristics related to circadian typology are associated with lifetime hypomanic symptoms. Hence, further investigation is needed to determine the eveningness trait, as it could be a trait marker of bipolar spectrum disorder.
Copyright © 2021 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Bipolar spectrum disorder; Circadian typology; Hypomania

Year:  2021        PMID: 33582522     DOI: 10.1016/j.psychres.2021.113788

Source DB:  PubMed          Journal:  Psychiatry Res        ISSN: 0165-1781            Impact factor:   3.222


  2 in total

1.  Can the MMPI Predict Adult ADHD? An Approach Using Machine Learning Methods.

Authors:  Sunhae Kim; Hye-Kyung Lee; Kounseok Lee
Journal:  Diagnostics (Basel)       Date:  2021-05-28

2.  Which PHQ-9 Items Can Effectively Screen for Suicide? Machine Learning Approaches.

Authors:  Sunhae Kim; Hye-Kyung Lee; Kounseok Lee
Journal:  Int J Environ Res Public Health       Date:  2021-03-24       Impact factor: 3.390

  2 in total

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