Accessibility settings

This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (5068) Mobile Health (mhealth) (5126) mHealth in a Clinical Setting (1125) Design of Processes and Workflows (282) mHealth for Screening (455) Dementia and Cognitive Decline (876) Health Professionals' Training in eHealth, Digital Medicine, Medical Informatics (277)

Published on in Vol 9 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66695, first published .
Elderly woman smiling while using a tablet computer

Digital Assessment of Cognitive Health in Outpatient Primary Care: Usability Study

Digital Assessment of Cognitive Health in Outpatient Primary Care: Usability Study

Authors of this article:

Adam J Doerr1 Author Orcid Image ;   Taylor A Orwig1 Author Orcid Image ;   Matthew McNulty1 Author Orcid Image ;   Stephanie Denise M Sison2 Author Orcid Image ;   David R Paquette3 Author Orcid Image ;   Robert Leung1 Author Orcid Image ;   Huitong Ding4 Author Orcid Image ;   Stephen B Erban5 Author Orcid Image ;   Bruce R Weinstein2 Author Orcid Image ;   Yurima Guilarte-Walker6 Author Orcid Image ;   Adrian H Zai6 Author Orcid Image ;   Allan J Walkey5 Author Orcid Image ;   Apurv Soni1, 5 Author Orcid Image ;   David D McManus1, 5 Author Orcid Image ;   Honghuang Lin1, 5 Author Orcid Image
Article Authors Cited by (8) Tweetations Metrics

Journals

  1. Fiore M, Terracina S, Ferraguti G. Brain Neurotrophins and Plant Polyphenols: A Powerful Connection. Molecules 2025;30(12):2657 View
  2. Jannati A, Thompson K, Toro-Serey C, Gomes-Osman J, Banks R, Higgins C, Showalter J, Bates D, Tobyne S, Pascual-Leone A. Concurrent detection of cognitive impairment and amyloid positivity with a multimodal machine learning-enabled digital cognitive assessment. Alzheimer's Research & Therapy 2025;17(1) View
  3. Weigand A, Tsoy E, Atkins K, Jarrott S, Farias S, Scheffler A, Brailow T, Rankin K, Kramer J, Possin K. Classifying cognitive status with TabCAT Match and UDS executive function tests. Alzheimer's & Dementia 2026;22(3) View
  4. Ye Z, Zai A, Wang B, Bennett A, Guilarte-Walker Y, Wong K, Zai A, Erban S, Lin H. Leveraging routine clinical data for dementia risk prediction using machine learning. Journal of Alzheimer’s Disease 2026;111(4):1516 View
  5. Jannati A, Toro-Serey C, Ciesla M, Chen E, Bates D, Showalter J, Tobyne S, Pascual-Leone A. Initial specialist validation of clinical decision support recommendations from a machine learning-enabled digital cognitive assessment. Frontiers in Neurology 2026;17 View
  6. Jannati A, Toro-Serey C, Ciesla M, Chen E, Showalter J, Bates D, Pascual-Leone A, Tobyne S. Streamlining eligibility assessment for Alzheimer's disease-modifying therapies: Prediction of MMSE scores using the digital clock and recall. Frontiers in Digital Health 2026;8 View
  7. Kurz C, Wüsten N, Tegethoff P, Taute M, Kehrls M, Hufnagel A, de Jonge S, Deckert A, Suchsland M, König A, Feustel E, Heindl P, Mattke S, Perneczky R. Adaptive pathways for multimodal community-based detection of cognitive impairment: the CogScreen I study. Scientific Reports 2026;16(1) View
  8. Mantzourani E, McRae D, Hunter E, Naylor G, Hinks E, Evans A, Cannings-John R. “It’s Worth Its Weight in Gold”: Patient Reported Experience Measures of a National NHS-Funded Community Pharmacy-Based Common Ailments Service. Pharmacy 2026;14(5):112 View