Human Informatics and Interaction Research Institute, National Institute of Advanced Industrial Science and Technology, Ibaraki, Japan.
JMIR Mhealth Uhealth. 2023 Nov 22;11:e49148. doi: 10.2196/49148.
Physical inactivity is a global health issue, and mobile health (mHealth) apps are expected to play an important role in promoting physical activity. Empirical studies have demonstrated the efficacy and efficiency of app-based interventions, and an increasing number of apps with more functions and richer content have been released. Regardless of the success of mHealth apps, there are important evidence gaps in the literature; that is, it is largely unknown who uses what app functions and which functions are associated with physical activity.
This study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample.
We recruited 20,573 web-based panelists who completed questionnaires concerning demographics, regular physical activity levels, and use of apps and wearables supporting physical activity. Participants who indicated that they were using a physical activity app or wearable were presented with a list of app functions (eg, sensor information, goal setting, journaling, and reward), among which they selected any functions they used.
Approximately one-quarter (n=4465) of the sample was identified as app users and showed similar demographic characteristics to samples documented in the literature; that is, compared with app nonusers, app users were younger (odds ratio [OR] 0.57, 95% CI 0.50-0.65), were more likely to be men (OR 0.83, 95% CI 0.77-0.90), had higher BMI scores (OR 1.02, 95% CI 1.01-1.03), had higher levels of education (university or above; OR 1.528, 95% CI 1.19-1.99), were more likely to have a child (OR 1.16, 95% CI 1.05-1.28) and job (OR 1.28, 95% CI 1.17-1.40), and had a higher household income (OR 1.40, 95% CI 1.21-1.62). Our results revealed unique associations between demographic variables and specific app functions. For example, sensor information, journaling, and GPS were more frequently used by men than women (ORs <0.84). Another important finding is that people used a median of 2 (IQR 1-4) different functions within an app, and the most common pattern was to use sensor information (ie, self-monitoring) and one other function such as goal setting or reminders.
Regardless of the current trend in app development toward multifunctionality, our findings highlight the importance of app simplicity. A set of two functions (more precisely, self-monitoring and one other function) might be the minimum that can be accepted by most users. In addition, the identified individual differences will help developers and stakeholders pave the way for the personalization of app functions.
身体活动不足是一个全球性的健康问题,移动健康(mHealth)应用程序有望在促进身体活动方面发挥重要作用。实证研究已经证明了基于应用程序的干预措施的有效性和效率,并且越来越多具有更多功能和更丰富内容的应用程序已经发布。无论 mHealth 应用程序的成功如何,文献中都存在重要的证据差距;也就是说,人们在很大程度上不知道谁在使用哪些应用程序功能,以及哪些功能与身体活动有关。
本研究旨在调查在一个讲日语的社区样本中,支持身体活动的应用程序和可穿戴设备的使用模式。
我们招募了 20573 名在线参与者,他们完成了有关人口统计学、定期身体活动水平以及使用支持身体活动的应用程序和可穿戴设备的问卷。表示正在使用身体活动应用程序或可穿戴设备的参与者会看到一份应用程序功能清单(例如传感器信息、目标设定、日记记录和奖励),其中他们选择了他们使用的任何功能。
大约四分之一(n=4465)的样本被确定为应用程序用户,他们具有与文献中记录的样本相似的人口统计学特征;也就是说,与应用程序非用户相比,应用程序用户更年轻(优势比[OR]0.57,95%置信区间[CI]0.50-0.65),更可能是男性(OR 0.83,95%CI 0.77-0.90),BMI 评分更高(OR 1.02,95%CI 1.01-1.03),教育程度更高(大学或以上;OR 1.528,95%CI 1.19-1.99),更有可能有孩子(OR 1.16,95%CI 1.05-1.28)和工作(OR 1.28,95%CI 1.17-1.40),并且家庭收入更高(OR 1.40,95%CI 1.21-1.62)。我们的结果揭示了人口统计学变量与特定应用程序功能之间的独特关联。例如,男性比女性更频繁地使用传感器信息、日记记录和 GPS(ORs<0.84)。另一个重要发现是,人们在一个应用程序中平均使用 2(IQR 1-4)个不同的功能,最常见的模式是使用传感器信息(即自我监测)和其他一个功能,例如目标设定或提醒。
无论当前应用程序开发向多功能性的趋势如何,我们的研究结果都强调了应用程序简单性的重要性。一组两个功能(更准确地说,自我监测和其他一个功能)可能是大多数用户可以接受的最低要求。此外,确定的个体差异将帮助开发人员和利益相关者为应用程序功能的个性化铺平道路。