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Mood and Age Predict Cognitive Complaints in Memory Clinic Patients: A Machine-Learning and Linear Modeling Approach.

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Summary
This summary is machine-generated.

Mood and age significantly predict cognitive complaints in memory clinic patients. Gamified and standard cognitive tests did not correlate with these complaints, emphasizing personalized assessment for Alzheimer's disease risk.

Keywords:
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Area of Science:

  • Neuroscience
  • Gerontology
  • Psychiatry

Background:

  • Cognitive complaints are early indicators of Alzheimer's disease (AD), prompting memory clinic visits.
  • The relationship between cognitive complaints, mood, and objective cognition requires further elucidation.
  • Machine learning approaches can identify predictors of cognitive complaints and evaluate novel cognitive testing methods.

Purpose of the Study:

  • To identify key predictors of cognitive complaints in memory clinic attendees.
  • To compare the efficacy of gamified (ACE-X) versus standard neuropsychological testing in detecting subtle cognitive deficits.
  • To explore the interplay between mood, age, and subjective cognitive complaints.

Main Methods:

  • International multi-center study with 98 participants from memory clinics.
  • Utilized Cognitive Failures Questionnaire (CFQ), mood/apathy scales, gamified ACE-X, and standard neuropsychological tests.
  • Employed elastic net regression, Boruta algorithm, and linear mixed-effects modeling to analyze predictors of CFQ scores.

Main Results:

  • Increased mood symptoms and older age were associated with more cognitive complaints.
  • Neither gamified (ACE-X) nor standard cognitive testing scores predicted the severity of cognitive complaints.
  • The predictive model for cognitive complaints explained a substantial proportion of variance (R²=0.48).

Conclusions:

  • Mood and age are primary predictors of cognitive complaints in memory clinic populations.
  • Neither gamified nor standard cognitive assessments directly correlated with subjective cognitive complaints.
  • Highlights the need for systematic mood assessment and personalized cognitive evaluation, with potential for gamified tools in AD screening.