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Video Games and Gamification for Assessing Mild Cognitive Impairment: Scoping Review.

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  • 1e-Media Research Lab, Faculty of Engineering Technology, KU Leuven, Leuven, Belgium.

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Summary

Gamified interactive systems (GISs) show promise for assessing mild cognitive impairment (MCI) in older adults, with performance comparable to traditional tools. However, further research is needed to improve validation methods and ensure accuracy in cognitive decline assessment.

Keywords:
AIartificial intelligencecognitive function assessmentdigital biomarkersgamificationmild cognitive impairmentvideo games

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Area of Science:

  • Gerontology
  • Neuroscience
  • Human-Computer Interaction

Background:

  • Early assessment of mild cognitive impairment (MCI) is vital for timely interventions in older adults.
  • Gamified interactive systems (GISs) are emerging as a novel approach for cognitive decline assessment.
  • Optimizing GIS design and integration for accurate MCI assessment remains an active research area.

Purpose of the Study:

  • To comprehensively review gamified interactive systems (GISs) designed for mild cognitive impairment (MCI) assessment.
  • To analyze game types, interaction paradigms, and targeted cognitive functions of existing GISs.
  • To evaluate the validation quality and diagnostic performance of GISs for MCI detection.

Main Methods:

  • A scoping search was conducted across IEEE Xplore, ACM Digital Library, and Scopus databases.
  • Identified GISs were categorized by game type (genre, interaction paradigm) and cognitive functions assessed.
  • Validation quality, sample size, and diagnostic performance (sensitivity, specificity, AUC) were critically examined.

Main Results:

  • The review included 81 articles detailing 49 GISs, with casual and simulation games being predominant.
  • Only 12% of systems comprehensively assessed cognitive functions compared to MoCA standards.
  • While 29% had validation studies showing comparable performance to traditional tools, many suffered from small sample sizes and methodological limitations.

Conclusions:

  • Current GISs demonstrate potential for MCI assessment, with diagnostic performance rivaling established screening instruments.
  • Significant improvements in validation rigor, including larger sample sizes and prospective designs, are necessary.
  • Future research should focus on prospective validation and methodological standardization for reliable GIS application in MCI assessment.