Early Identification of Cognitive Impairment in Community Environments Through Modeling Subtle Inconsistencies in Questionnaire Responses: Machine Learning Model Development and Validation
We developed a novel prediction tool that integrates psychometric methods with data science to facilitate "passive or backend" cognitive impairment assessments in community settings, aiming to promote early cognitive impairment detection. This tool simplifies the cognitive impairment assessment process, making it more adaptable and reducing burdens. Our approach also presents a new perspective for using questionnaire data: leveraging, rather than dismissing, low-quality data.
Authors
- Doerte U. Junghaenel (ORCID: https://orcid.org/0000-0002-7733-571X)
- Jenny Harris (ORCID: https://orcid.org/0000-0001-8933-117X)
- Haomiao Jin (ORCID: https://orcid.org/0000-0001-8908-1959)
- Bart Orriens (ORCID: https://orcid.org/0000-0002-1304-7735)
- Elizabeth M. Zelinski (ORCID: https://orcid.org/0000-0003-3994-399X)
- Arthur A. Stone (ORCID: https://orcid.org/0000-0001-7490-1758)
- Hongxin Gao (ORCID: https://orcid.org/0000-0002-6030-1118)
- Arie Kapteyn (ORCID: https://orcid.org/0000-0002-1855-5528)
- Erik Meijer (ORCID: https://orcid.org/0000-0001-7959-4670)
- Pey-Jiuan Lee (ORCID: https://orcid.org/0000-0001-6163-2325)
- Danny Maupin (ORCID: https://orcid.org/0000-0002-0510-6627)
- Raymond Hernandez (ORCID: https://orcid.org/0000-0002-6761-9276)
- Stefan Schneider (ORCID: https://orcid.org/0000-0002-4562-0524)
Institutions
- University of Southern California (US)
- University of Surrey (GB)
Publication Details
- Journal
- JMIR Formative Research
- Published
- 2024-09-23
- DOI
- https://doi.org/10.2196/54335
- Citations
- 1
- Primary Topic
- Dementia and Cognitive Impairment Research
- Type
- article
- Field-Weighted Citation Impact
- 0.39