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Artificial Intelligence-Based System for Detecting Attention Levels in Students

Artificial Intelligence-Based System for Detecting Attention Levels in Students

Published on: December 15, 2023

Validation analysis of the Attention Questionnaire Scale.

Sang Yun Kim¹, Moon Ho Park, Seol-Heui Han

¹Department of Neurology, Seoul National University College of Medicine & Seoul National University Bundang Hospital, Seongnam, Republic of Korea. neuroksy@snu.ac.kr

Journal of Alzheimer'S Disease : JAD

|February 8, 2011

Summary

A new Attention Questionnaire Scale (AQS) effectively screens for early cognitive dysfunction in Alzheimer's disease (AD). The AQS distinguishes between normal cognition, mild cognitive impairment, and early AD stages better than the MMSE.

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Area of Science:

Neurology
Cognitive Science
Geriatrics

Background:

Screening tools for early Alzheimer's disease (AD) cognitive dysfunction are limited.
Early detection is crucial for timely intervention and management of AD.
Existing cognitive tests may not adequately capture subtle, early-stage changes.

Purpose of the Study:

To introduce and validate the Attention Questionnaire Scale (AQS) for early detection of cognitive dysfunction.
To assess the AQS's performance in differentiating various stages of cognitive impairment, including mild cognitive impairment (MCI) and early AD.
To compare the AQS's screening ability against established cognitive assessments like the Mini-Mental Status Examination (MMSE).

Main Methods:

Prospective study involving 268 subjects with diverse cognitive function levels.
Administration of the AQS and comparison with multiple established cognitive and functional scales (MMSE, digit span, etc.).
Statistical analysis including internal consistency (Cronbach's alpha) and receiver operating characteristic (ROC) curve analysis.

Main Results:

The AQS demonstrated excellent internal consistency (Cronbach's α = 0.945).
Significant differences in AQS scores were observed across normal elderly, MCI, early AD, mild AD, and moderate AD groups.
The AQS showed superior ability to distinguish early cognitive dysfunction compared to the MMSE, with an ROC AUC of 0.93.

Conclusions:

The Attention Questionnaire Scale (AQS) is a reliable and effective tool for screening early cognitive dysfunction.
The AQS offers enhanced screening capabilities for identifying individuals with MCI and early-stage AD.
The AQS is a simple, valuable questionnaire for both screening and assessing early cognitive decline.