Liao Pei-Hung, Huang Yu-Jie, Ho Chen-Shie, Chu William
School of Nursing, National Taipei University of Nursing and Health Sciences, Taipei, Taiwan.
Department of Nursing, Cheng Hsin General Hospital, Taipei, Taiwan.
BMC Nurs. 2023 Oct 9;22(1):369. doi: 10.1186/s12912-023-01545-w.
Aging leads to changes in the body system, such as sarcopenia. This can result in several health issues, particularly physical and mobility dysfunction. Asian people typically have little awareness of sarcopenia. Thus, this study incorporated nursing instruction into the mobile application design to allow users to easily learn about sarcopenia.
This study evaluated a model for predicting high-risk populations for sarcopenia in home settings. We further developed a sarcopenia nursing guidance mobile application and assessed the effectiveness of this application in influencing sarcopenia-related knowledge and self-care awareness among participants.
Using a one-group pretest-posttest design, data were collected from 120 participants at a teaching hospital in northern Taiwan. This study used an artificial intelligence algorithm to evaluate a model for predicting high-risk populations for sarcopenia. We developed and assessed the sarcopenia nursing guidance mobile application using a questionnaire based on the Mobile Application Rating Scale.
The application developed in this study enhanced participants' sarcopenia-related knowledge and awareness regarding self-care. After the three-month intervention, the knowledge and awareness was effectively increase, total score was from 4.15 ± 2.35 to 6.65 ± 0.85 and were significant for all questionnaire items (p values < 0.05). On average, 96.1% of the participants were satisfied with the mobile app. The artificial intelligence algorithm positively evaluated the home-use model for predicting high-risk sarcopenia groups.
The mobile application of the sarcopenia nursing guidance for public use in home settings may help alleviate sarcopenia symptoms and reduce complications by enhancing individuals' self-care awareness and ability.
NCT05363033, registered on 02/05/2022.
衰老会导致身体系统发生变化，如肌肉减少症。这可能会引发多种健康问题，尤其是身体和行动功能障碍。亚洲人通常对肌肉减少症了解甚少。因此，本研究将护理指导融入移动应用程序设计中，以便用户轻松了解肌肉减少症。
本研究评估了一种在家中预测肌肉减少症高危人群的模型。我们进一步开发了一款肌肉减少症护理指导移动应用程序，并评估了该应用程序在影响参与者对肌肉减少症相关知识和自我护理意识方面的效果。
采用单组前后测设计，从台湾北部一家教学医院的120名参与者中收集数据。本研究使用人工智能算法评估一种预测肌肉减少症高危人群的模型。我们基于移动应用程序评分量表开发并使用问卷评估了肌肉减少症护理指导移动应用程序。
本研究开发的应用程序增强了参与者对肌肉减少症相关知识和自我护理的意识。经过三个月的干预，知识和意识得到有效提高，总分从4.15±2.35提高到6.65±0.85，所有问卷项目均具有显著性（p值<0.05）。平均而言，96.1%的参与者对该移动应用程序满意。人工智能算法对预测肌肉减少症高危人群的家庭使用模型给予了积极评价。
用于家庭环境中公众使用肌肉减少症护理指导移动应用程序，可能通过增强个人的自我护理意识和能力来帮助缓解肌肉减少症症状并减少并发症。
NCT05363033，于2022年5月2日注册。
