Mobile applications for cognitive training: Content analysis and quality review

Myeonghwan Bang; Chan Woong Jang; Hyoung Seop Kim; Jung Hyun Park; Han Eol Cho

doi:10.1016/j.invent.2023.100632

Mobile applications for cognitive training: Content analysis and quality review

Internet Interv. 2023 May 26:33:100632. doi: 10.1016/j.invent.2023.100632. eCollection 2023 Sep.

Authors

Myeonghwan Bang^{1

2}, Chan Woong Jang³, Hyoung Seop Kim¹, Jung Hyun Park^{2

3

4}, Han Eol Cho³

Affiliations

¹ Department of Physical Medicine and Rehabilitation, National Health Insurance Service Ilsan Hospital, Goyang, Republic of Korea.
² Department of Integrative Medicine, Yonsei University Graduate School, Seoul, Republic of Korea.
³ Department of Rehabilitation Medicine, Gangnam Severance Hospital, Rehabilitation Institute of Neuromuscular Disease, Yonsei University College of Medicine, Seoul, Republic of Korea.
⁴ Department of Medical Device Engineering and Management, Yonsei University Graduate School, Seoul, Korea.

Abstract

Background: As the number of individuals suffering from cognitive diseases continues to rise, dealing with the diminished cognitive function that comes with age has become a serious public health concern. While the use of mobile applications (apps) as digital treatments for cognitive training shows promise, the analysis of their content and quality remains unclear.

Objective: The aim of this study was to systematically search and assess cognitive training apps using the multidimensional mobile app rating scale (MARS) to rate objective quality and identify critical points.

Methods: A search was conducted on the Google Play Store and Apple App Store in February 2022 using the terms "cognitive training" and "cognitive rehabilitation." The cognitive domains provided by each app were analyzed, and the frequency and percentage according to the apps were obtained. The MARS, a mHealth app quality rating tool including multidimensional measures, was used to analyze the quality of the apps. The relationship between the MARS score, the number of reviews, and 5-star ratings were examined.

Results: Of the 53 apps, 52 (98 %) included memory function, 48 (91 %) included attention function, 24 (45 %) included executive function, and 19 (36 %) included visuospatial function. The mean (SD) scores of MARS, 5-star ratings, and reviews of 53 apps were 3.09 (0.61), 4.33 (0.30), and 62,415.43 (121,578.77). From the between-section comparison, engagement (mean 2.97, SD 0.68) obtained lower scores than functionality (mean 3.18, SD 0.62), aesthetics (mean 3.13, SD 0.72), and information (mean 3.11, SD 0.54). The mean quality score and reviews showed a statistically significant association (r = 0.447 and P = .001*). As the number of domains increased, the mean quality score showed a statistically significant increasing trend (P = .002*).

Conclusions: Most apps provided training for the memory and attention domains, but few apps included executive function or visuospatial domains. The quality of the apps improved significantly when more domains were provided, and was positively associated with the number of reviews received. These results could be useful for the future development of mobile apps for cognitive training.

Keywords: Cognition; Mobile apps; Quality; Rehabilitation; Training; mHealth.