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

Early assessment of mild cognitive impairment (MCI) in older adults is crucial, as it enables timely interventions and decision-making. In recent years, researchers have been exploring the potential of gamified interactive systems (GISs) to assess pathological cognitive decline. However, effective methods for integrating these systems and designing GISs that are both engaging and accurate in assessing cognitive decline are still under investigation.

We aimed to comprehensively investigate GISs used to assess MCI. Specifically, we reviewed the existing systems to understand the different game types (including genres and interaction paradigms) used for assessment. In addition, we examined the cognitive functions targeted. Finally, we investigated the evidence for the performance of assessing MCI through GISs by looking at the quality of validation for these systems in assessing MCI and the diagnostic performance reported.

We conducted a scoping search in IEEE Xplore, ACM Digital Library, and Scopus databases to identify interactive gamified systems developed for assessing MCI. Game types were categorized according to genres and interaction paradigms. The cognitive functions targeted by the systems were compared with those assessed in the Montreal Cognitive Assessment (MoCA). Finally, we examined the quality of validation against the reference standard (ground truth), relevance of controls, and sample size. Where provided, the diagnostic performance on sensitivity, specificity, and area under the curve was reported.

A total of 81 articles covering 49 GISs were included in this review. The primary game types used for MCI assessment were classified as casual games (30/49, 61%), simulation games (17/49, 35%), full-body movement games (4/49, 8%), and dedicated interactive games (3/49, 6%). Of the 49 systems, 6 (12%) assessed cognitive functions comprehensively, compared to those functions assessed via the MoCA. Of the 49 systems, 14 (29%) had validation studies, with sensitivities ranging from 70.7% to 100% and specificities ranging from 56.5% to 100%. The reported diagnostic performances of GISs were comparable to those of common screening instruments, such as Mini-Mental State Examination and MoCA, with some systems reporting near-perfect performance (area under the curve>0.98). However, these findings often stemmed from small samples and retrospective designs. Moreover, some of these systems' model training and validation exhibited substantial deficiencies.

This review provides a comprehensive summary of GISs for assessing MCI, exploring the cognitive functions assessed by these systems and evaluating their diagnostic performance. The results indicate that current GISs hold promise for the assessment of MCI, with several systems demonstrating diagnostic performance comparable to established screening tools. Nevertheless, despite some systems reporting impressive performance, there is a need for improvement in validation, particularly concerning sample size and methodological rigor. Future work should prioritize prospective validation and present greater methodological consistency.