Mental health literacy predicts depression in older adults in China: an interpretable machine learning model
The interpretable predictive model facilitates a more precise estimation of the risk of depression in older individuals by health care professionals, providing better prevention plans and treatment targets. Additionally, this transparent framework enhances the clarity of the model, making it easier to understand the reliability of the predictions for mental health concerns.
Authors
- Ainong Zhou
- Li He (ORCID: https://orcid.org/0000-0002-2213-2499)
- Ningning Mao (ORCID: https://orcid.org/0000-0003-4942-6072)
- Yueran Wang (ORCID: https://orcid.org/0000-0002-1420-4480)
- Zhuo Rachel Han (ORCID: https://orcid.org/0000-0001-5686-0366)
- Zhanjun Zhang
- Xiangwei Dai
Institutions
- McGovern Institute for Brain Research (US)
- Beijing Normal University (CN)
- Chinese Institute for Brain Research (CN)
- China Academy of Chinese Medical Sciences (CN)
Publication Details
- Journal
- The Journals of Gerontology Series B
- Published
- 2025-11-27
- DOI
- https://doi.org/10.1093/geronb/gbaf158
- Primary Topic
- Mental Health via Writing
- Type
- article
- Field-Weighted Citation Impact
- 0.00