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Clinical Manifestations.

Emil Fristed1, Jack Weston1, Melanie J Miller2

  • 1Novoic, London, United Kingdom.

Alzheimer'S & Dementia : the Journal of the Alzheimer'S Association
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

The Storyteller remote cognitive assessment tool effectively differentiates between Mild Cognitive Impairment (MCI) and Cognitively Normal (CN) individuals. Longitudinal tracking of Storyteller scores over six months significantly enhances diagnostic accuracy for MCI.

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Area of Science:

  • Neuroscience
  • Gerontology
  • Cognitive Science

Background:

  • Traditional cognitive testing faces challenges like staff requirements, in-person visits, and variability, leading to underdiagnosis of Mild Cognitive Impairment (MCI).
  • The Storyteller, a self-administered remote story-recall task, offers a low-burden approach for repeat assessments.
  • This study investigated if Storyteller's longitudinal data improves the distinction between MCI and Cognitively Normal (CN) participants.

Purpose of the Study:

  • To evaluate the effectiveness of the Storyteller task in differentiating between MCI and CN participants.
  • To determine if longitudinal measures from Storyteller enhance classification accuracy.
  • To assess the diagnostic utility of remote, self-administered cognitive assessments.

Main Methods:

  • Utilized data from ADNI4 participants diagnosed with CN (n=76) or MCI (n=21).
  • Employed mixed linear regression to analyze the impact of demographics, diagnosis, and time on Storyteller G-match scores.
  • Compared classification performance using logistic regression with 10-fold cross-validation, analyzing baseline scores, 6-month changes, and combined metrics via ROC curve Area Under the Curve (AUC).

Main Results:

  • While demographics like age, sex, and education did not differ significantly between groups, the MCI group exhibited lower baseline and 6-month G-match scores (p<0.001).
  • The mixed model revealed significant effects of sex, education, baseline MCI diagnosis, timepoint, and an MCI*timepoint interaction indicating greater decline in the MCI group.
  • Baseline G-match (AUC=0.754) and 6-month change (AUC=0.712) individually outperformed random classification; combining both yielded an AUC of 0.800, further improving to 0.817 with demographic inclusion.

Conclusions:

  • Storyteller effectively detected a greater cognitive decline in MCI participants compared to CN participants.
  • Incorporating longitudinal Storyteller measures significantly improved the classification accuracy for MCI.
  • Remote, self-administered cognitive assessments like Storyteller provide valuable diagnostic power within a short timeframe (six months).