Research trends in computerized cognitive training contents with text network
Computerized Cognitive Training (CCT) contents used to improve patients’ cognitive ability with Mild Cognitive Impairment (MCI) can provide customized training through individual data collection and analysis. However, studies on transfer effect of improving other untrained cognitive domains while pe...
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Veröffentlicht in: | Journal of intelligent & fuzzy systems 2021-01, Vol.41 (4), p.4983-4993 |
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Sprache: | eng |
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Zusammenfassung: | Computerized Cognitive Training (CCT) contents used to improve patients’ cognitive ability with Mild Cognitive Impairment (MCI) can provide customized training through individual data collection and analysis. However, studies on transfer effect of improving other untrained cognitive domains while performing the contents are insufficient. The present paper intended to collect literature published by PubMed, EMBASE, Cochrane Library, and Web of Science until December 2019 and analyze the trends of CCT and the transfer effect in each training area. Studies on CCT (82/891) have been increasing each year, and universities (60/82) in the United States (17/82) have published the most. In the literature that reported clinical effect (18/82), the cognitive domain mostly studied was memory (14/18), and the N-Back (3/14) method accounted for most of the training contents. Moreover, the contents that showed the highest degree, closeness, and betweenness centrality (BC) indices were the memory area, and video accounted for the highest among the intervention methods. In particular, the closeness centrality (CC) index of the memory and attention contents showed similar results. It can be interpreted that the possibility of the transfer effect occurring from memory and attention areas is the highest since the semantic distance (i.e. the similarity of the training process) between the attention contents and memory contents was the closest. The effectiveness of the actual transfer effect between the memory and attention should be verified. |
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ISSN: | 1064-1246 1875-8967 |
DOI: | 10.3233/JIFS-189985 |