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Updated: Sep 1, 2025
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Usability Evaluation of Augmented Reality: A Neuro-Information-Systems Study
Published on: November 30, 2022
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The impact of users' cognitive function on evaluator perceptions of usability.
Ana Isabel Martins1, Anabela G Silva2, Joana Pais3
1Center for Health Technology and Services Research-CINTESIS@RISE, University of Aveiro, Aveiro, Portugal. anaisabelmartins@ua.pt.
Scientific Reports
|August 12, 2022
Summary
User cognitive function significantly impacts how evaluators perceive the usability of digital tools like Brain on Track. Other factors such as age and education also play a role, highlighting the need for comprehensive usability assessments.
Area of Science:
- Human-Computer Interaction
- Cognitive Science
- Usability Engineering
Background:
- Usability is crucial for digital health solutions.
- Understanding factors influencing usability assessments is essential.
- Cognitive function is a potential determinant of perceived usability.
Purpose of the Study:
- To investigate the relationship between users' cognitive function and evaluator-reported usability.
- To identify user characteristics associated with usability assessments of the 'Brain on Track' digital solution.
Main Methods:
- A cross-sectional study with a community sample of 238 participants.
- Data collection included cognitive function, demographics, sleep, and memory complaints.
- Usability was evaluated using the 'Brain on Track' digital solution.
- Linear regression analyses explored associations between usability and user characteristics.
Main Results:
- Cognitive function, age, education, and subjective memory complaints were significantly associated with usability.
- In multivariable analysis, these factors explained 39.1% of the variance in reported usability (adjusted R²=0.391).
- Cognitive function alone accounted for 28.8% of the variance (adjusted R²=0.288).
Conclusions:
- User cognitive function is a significant factor influencing evaluator-reported usability.
- Usability evaluations should consider a range of user characteristics and individual needs.
- These findings have implications for the design and assessment of digital health technologies.
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