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White BK, Martin A, White J. Gamification and older adults: opportunities for gamification to support health promotion initiatives for older adults in the context of COVID-19. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2023; 35:100528. [PMID: 35815240 PMCID: PMC9257427 DOI: 10.1016/j.lanwpc.2022.100528] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The COVID-19 pandemic has increased reliance on digital service delivery, including the delivery of health promotion initiatives. Health promotion interventions need to carefully consider user engagement. Gamification is a strategy used to engage and motivate people, and evidence shows overall cautious positive results in the use of gamification for older people across a range of health areas although more evidence is needed. Gamification has been used as a strategy in COVID-19 related initiatives and there is potential to build on the evidence to further develop gamification initiatives for those living in the Western Pacific region to impact positively on healthy behaviours and health outcomes.
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Affiliation(s)
- Becky K. White
- Reach Health Promotion Innovations, Perth, Western Australia
- Curtin University, Perth, Western Australia
| | - Annegret Martin
- Reach Health Promotion Innovations, Perth, Western Australia
| | - James White
- Reach Health Promotion Innovations, Perth, Western Australia
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Cardona JS, Lopez JA, Vela FLG, Moreira F. Meaningful learning: motivations of older adults in serious games. UNIVERSAL ACCESS IN THE INFORMATION SOCIETY 2023:1-16. [PMID: 37361677 PMCID: PMC10012313 DOI: 10.1007/s10209-023-00987-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 03/02/2023] [Indexed: 06/28/2023]
Abstract
Social sustainability is the generation of significant behaviors through balanced levels of education, learning and awareness so that the population has a good standard of living, achieves self-improvement and supports society. This can be achieved with various strategies, one of which is learning through games, which has gained popularity in recent years due to positive results. This is effectively achieved through serious gaming, which is growing steadily, mostly in education and healthcare. This type of strategy has been typically used in young populations with a transparent interaction with technological processes that facilitate its application. However, one cannot neglect other populations such as the elderly, who may experience a technology gap and may not perceive this type of initiative in the best light. The purpose of this article is to identify the different motivations that can encourage older adults to use serious games to encourage learning processes through technology. For this purpose, different previous research on gaming experiences with older adults has been identified, from which it was possible to categorize a series of factors that motivate this population. Subsequently, we represented these factors by means of a model of motivation for the elderly and, to be able to use it, we have defined a set of heuristics based on this model. Finally, we used the heuristics by means of a questionnaire to evaluate the design of serious gaming for older adults, obtaining positive results for the use of these elements to guide the design and construction of serious games for learning in older adults.
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Affiliation(s)
- Johnny Salazar Cardona
- Departamento de Lenguajes y Sistemas Informáticos, ETSI Informática, Universidad de Granada, 18071 Granada, Spain
| | - Jeferson Arango Lopez
- Departamento de Sistemas e Informática, Facultad de Ingenierías, Universidad de Caldas, Calle 65 # 26-10, Edificio del Parque, Manizales, Caldas, Colombia
| | | | - Fernando Moreira
- REMIT, IJP, Universidade Portucalense, Rua Dr. António Bernardino Almeida, 541-619, 4200-072 Porto, Portugal
- IEETA, Universidade de Aveiro, Aveiro, Portugal
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Wang G, Zhu B, Fan Y, Wu M, Wang X, Zhang H, Yao L, Sun Y, Su B, Ma Z. Design and evaluation of an exergame system to assist knee disorders patients' rehabilitation based on gesture interaction. Health Inf Sci Syst 2022; 10:20. [PMID: 36032777 PMCID: PMC9411482 DOI: 10.1007/s13755-022-00189-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 08/05/2022] [Indexed: 10/15/2022] Open
Abstract
We designed a knee rehabilitation exercise game (Exergame) for home-based rehabilitation of patients with knee disorders. The system includes three functional components: knee exercise plan formulation, exergame, and exercise feedback. The 3D Human Pose Estimation based on images is used as the gesture interaction to capture the patient's primary joint motion data. We recruited 20 knee osteoarthritis (KOA) to evaluate the system's feasibility and user experience. The physician's group formulated the patient's exercise plans. The average accuracy of motion recognition is 95.2%, indicating that the system can effectively guide rehabilitation training for KOA patients. The results of the UEQ-S questionnaire, namely the practical quality value (1.63 ± 0.85), hedonic quality value (1.75 ± 0.86), and the total value (1.69 ± 0.86) of 20 patients, indicate that the system provides an excellent user experience, which improves the willingness and compliance of the patients for the active exercise. The above evidence confirms that the proposed approach is suitable for Knee disorders rehabilitation exercise and has promising application prospects. Supplementary Information The online version contains supplementary material available at 10.1007/s13755-022-00189-5.
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Affiliation(s)
- Guangjun Wang
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, 230026 China
- The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246013 China
| | - Bangguo Zhu
- The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246013 China
| | - Yi Fan
- The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246013 China
| | - Ming Wu
- The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001 China
| | - Xueshu Wang
- The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246013 China
| | - Hanyuan Zhang
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, 230026 China
- Department of Sports Medicine and Arthroscopic Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei, 230022 China
| | - Liangliang Yao
- The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246013 China
| | - Yining Sun
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, 230026 China
| | - Benyue Su
- The University Key Laboratory of Intelligent Perception and Computing of Anhui Province, Anqing Normal University, Anqing, 246013 China
| | - Zuchang Ma
- Anhui Province Key Laboratory of Medical Physics and Technology, Institute of Intelligent Machines, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, 230031 China
- Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, 230026 China
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