{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,30]],"date-time":"2026-06-30T17:58:38Z","timestamp":1782842318451,"version":"3.54.5"},"reference-count":62,"publisher":"JMIR Publications Inc.","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["JMIR Serious Games"],"abstract":"Abstract<\/jats:title>\n \n Background<\/jats:title>\n Complications due to dysphagia are increasingly prevalent among older adults; however, the tediousness and complexity of conventional tongue rehabilitation treatments affect their willingness to rehabilitate. It is unclear whether integrating gameplay into a tongue training app is a feasible approach to rehabilitation.<\/jats:p>\n <\/jats:sec>\n \n Objective<\/jats:title>\n Tongue training has been proven helpful for dysphagia treatment. Following the development of a tongue training app, a feasibility trial aimed to identify physiological and psychological factors that affect user and flow experience and explored whether training specialized muscles could produce a flow experience for optimal immersion. We aimed to provide a useful tool for medical rehabilitation so that older adults could retain tongue muscle flexibility.<\/jats:p>\n <\/jats:sec>\n \n Methods<\/jats:title>\n After consulting professional nurses, we developed a mobile gaming app for middle-aged and older adults to train their tongue muscles. This pilot study used an image recognition system to detect the tongue movements of 32 healthy middle-aged and older adults (7 males, 21.9%; 25 females, 78.1%) during 3 game training tasks, each requiring different reaction speeds. Their physiological and psychological signals, as well as the results of the Flow State Scale 2 (FSS2) questionnaire, were used for correlation analysis regarding relevant flow experiences to establish and evaluate the feasibility of our method.<\/jats:p>\n <\/jats:sec>\n \n Results<\/jats:title>\n \n Through exploratory factor analyses, a 2-factor (operation and immersion) structure was confirmed to have an adequate model fit (\n \u03c7\u00b2<\/jats:italic>\n 36<\/jats:sub>\n =448.478;\n P<\/jats:italic>\n <.001; Kaiser-Meyer-Olkin=0.757) and internal consistency reliability (Cronbach \u03b1=0.802). The slow, medium, and fast levels all significantly affected the FSS2 score for operation (\n P=<\/jats:italic>\n .001), the National Aeronautics and Space Administration Task Load Index (\n P<\/jats:italic>\n <.001), and flow distance (\n P<\/jats:italic>\n <.001). K-means clustering revealed that participants could be further categorized into 3 groups. Through the analysis of changes in the participants\u2019 physiological and psychological signals for each given task, Pearson correlation indicated that changes were primarily related to flow distance. For the 12 indicators measured in this study, the low, medium, and high operation groups showed significance in 58% (7\/12), 50% (6\/12), and 25% (3\/12) of the indicators, respectively. Similarly, the low, medium, and high immersion groups had changes in 50% (6\/12), 33% (4\/12), and 17% (2\/12) of indicators, respectively.\n <\/jats:p>\n <\/jats:sec>\n \n Conclusions<\/jats:title>\n Our research supports the further development of a gaming app to aid older adults with tongue muscle training and measure flow using physiological and psychological signals to enhance training accuracy and feasibility. Next, we aim to conduct a randomized pilot trial, improve app functions, offer alternative rehabilitation options, and encourage long-term participation. Future goals include enhancing long-term efficacy, diversifying training modes, and adding a multiuser interactive option for an added challenge.<\/jats:p>\n <\/jats:sec>","DOI":"10.2196\/53045","type":"journal-article","created":{"date-parts":[[2025,1,10]],"date-time":"2025-01-10T05:36:41Z","timestamp":1736487401000},"page":"e53045-e53045","source":"Crossref","is-referenced-by-count":2,"title":["Tongue Muscle Training App for Middle-Aged and Older Adults Incorporating Flow-Based Gameplay: Design and Feasibility Pilot 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