Optimizing Winter‐Type Seasonality Criteria in East Asian Populations: A Machine Learning Approach Using the Seasonal Pattern Assessment Questionnaire
This study evaluated seasonality in a South Korean early-onset mood disorder cohort using SPAQ and Kasper's criteria. Incorporating atypical vegetative symptoms and reduced social activity improved winter seasonality classification accuracy. The revised criteria may facilitate more precise identification and management of seasonal symptoms in East Asia.
Authors
- Ji Won Yeom (ORCID: https://orcid.org/0000-0003-0038-2101)
- Chul‐Hyun Cho (ORCID: https://orcid.org/0000-0002-1663-9680)
- Heon‐Jeong Lee (ORCID: https://orcid.org/0000-0002-9560-2383)
- Jung‐Been Lee
- Soohyun Park (ORCID: https://orcid.org/0000-0002-5284-7188)
Institutions
- Korea University (KR)
- iNtRON (South Korea) (KR)
- Korea University (JP)
- Sun Moon University (KR)
Publication Details
- Journal
- Brain and Behavior
- Published
- 2025-09-01
- DOI
- https://doi.org/10.1002/brb3.70834
- Citations
- 1
- Primary Topic
- Sleep and related disorders
- Type
- article
- Field-Weighted Citation Impact
- 2.12
Funders
- National Research Foundation
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea