Use Patterns of Smartphone Apps and Wearable Devices Supporting Physical Activity and Exercise: Large-Scale Cross-Sectional Survey

Abstract

Background 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. Objective This study aims to investigate the use patterns of apps and wearables supporting physical activity and exercise in a Japanese-speaking community sample. Methods 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. Results 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. Conclusions 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.

Functional and Symbolic Aspects of App Use for Improving Physical Activity: A Six-month Prospective Analysis

“…First, we included in the analyses any PA apps that participants were using, as we wanted to maintain the generalizability of the results across different PA apps. Most participants identi ed iOS Healthcare and Google Fitness (see Oba et al [29] for details), whereas others used different apps, such as those with a speci c focus on tness, training, or disease management (e.g., for hypertension and diabetes). Future research should investigate the differences in app-use aspects based on the types of apps and their implemented functions.…”

“…We analyzed a dataset of how people use commercial apps to support PA and exercise, some of which have been published elsewhere [29,30]. The data contained questionnaire responses from 20,573 Japanese-speaking adults who were online panels registered in a sample pool database (see Oba et al [29] for more details on the sampling procedure). The inclusion criteria were being aged > 18, having a good command of Japanese, and having residency in Japan.…”

“…The questions included (a) the names of the apps in use, (b) how long they had been using the app that was used most frequently (less than a week to more than a year), and (c) how frequently they were using the app (less than once per month to multiple times per day). The complete description of the questionnaire is available in Oba et al [29]. At the 6-month follow-up, participants reported on their current app use (vs. non-use) again, selecting one from the three response options (using an app, used but not using it anymore, or have never used it).…”

What Functions of Smartphone Apps and Wearable Devices Promote Physical Activity? Six-Month Prospective Study on Japanese-Speaking Adults (Preprint)

“…Participants were recruited from the sample of respondents who completed the first (hereafter, baseline) survey, the results of which have been published elsewhere [33,34]. The baseline survey was conducted in 2023, where N=20,573 online respondents (residents in Japan who had been registered in a database of potential participants for online surveys) completed the questionnaires concerning general health and health-related behaviors, including PA levels and use of mHealth apps.…”

“…The questions covered the duration and frequency of app use (how long and frequently they had used/were using the apps) as well as the functions and features of the apps in use. Participants were presented with a list of 41 app functions (e.g., sensor information, goal setting, and energy analysis) [33], and they indicated any applicable functions they were using [20,29]. However, as most of the listed functions were rarely used [33], we exclusively focused on the most frequently used functions for the current analyses: sensor information (e.g., step count and heart rate), goal setting and goal progress (e.g., steps achieved), energy analysis (e.g., estimated daily energy expenditure), weight recording, journaling (e.g., diary or notes that are manually entered), GPS/map, sleep information, reward points, and blood-pressure recording.…”