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Mobile applications for cognitive training: Content analysis and quality review

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...

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Autores principales: Bang, Myeonghwan, Jang, Chan Woong, Kim, Hyoung Seop, Park, Jung Hyun, Cho, Han Eol
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258500/
https://www.ncbi.nlm.nih.gov/pubmed/37312799
http://dx.doi.org/10.1016/j.invent.2023.100632
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author Bang, Myeonghwan
Jang, Chan Woong
Kim, Hyoung Seop
Park, Jung Hyun
Cho, Han Eol
author_facet Bang, Myeonghwan
Jang, Chan Woong
Kim, Hyoung Seop
Park, Jung Hyun
Cho, Han Eol
author_sort Bang, Myeonghwan
collection PubMed
description 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.
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spelling pubmed-102585002023-06-13 Mobile applications for cognitive training: Content analysis and quality review Bang, Myeonghwan Jang, Chan Woong Kim, Hyoung Seop Park, Jung Hyun Cho, Han Eol Internet Interv Full length Article 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. Elsevier 2023-05-26 /pmc/articles/PMC10258500/ /pubmed/37312799 http://dx.doi.org/10.1016/j.invent.2023.100632 Text en © 2023 The Authors https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Full length Article
Bang, Myeonghwan
Jang, Chan Woong
Kim, Hyoung Seop
Park, Jung Hyun
Cho, Han Eol
Mobile applications for cognitive training: Content analysis and quality review
title Mobile applications for cognitive training: Content analysis and quality review
title_full Mobile applications for cognitive training: Content analysis and quality review
title_fullStr Mobile applications for cognitive training: Content analysis and quality review
title_full_unstemmed Mobile applications for cognitive training: Content analysis and quality review
title_short Mobile applications for cognitive training: Content analysis and quality review
title_sort mobile applications for cognitive training: content analysis and quality review
topic Full length Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10258500/
https://www.ncbi.nlm.nih.gov/pubmed/37312799
http://dx.doi.org/10.1016/j.invent.2023.100632
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