Overweight and obesity, as one of the leading risks for death and disability globally in 2019 (1), have become a major public health problem in China and around the world. The recent China national data showed that nearly 50% of adults were overweight or obese and the trend is still going upward (2).

Many studies have shown that taking enough physical activity is an effective way for weight loss and other health benefits (3–5). In addition, literature has also shown that supervised exercise by offering encouragement and motivation resulted in a higher adherence and more health benefits than unsupervised exercise for people with obesity (6), diabetes (7), and intermittent claudication (8). However, most of the studies about supervised exercise were on-site in clinic settings with face-to-face instructions, which makes it costly, resource-intensive, and difficult to implement at other venues. Therefore, in community settings, the prescription of exercise therapy is usually as simple as “go home and walk.”

Mobile health (mHealth) is defined by the WHO as medical or public health practices supported by mobile devices, such as mobile phones, wearable devices, and other personal wireless devices (9). Physical activity can be monitored by using wearable trackers, such as pedometers, accelerometers, and heart-rate trackers (10). For the efficacy of wearable devices on obesity, two systematic reviews suggested may be a better option than a standard weight loss program (11, 12). However, as commercialized physical activity trackers are getting more and more popular for self-management, one scholar who said “wearable devices as facilitators, not drivers of health behaviors”(13), believed that wearable devices alone have limited effects on behaviors engagement like exercise. This may be true because Jakicic et al. found wearable trackers may not offer an advantage over standard behavioral weight loss approaches (14). Therefore, the combination of supervised exercise with self-directed exercise may be a promising strategy for weight management.

In fact, data generated by wearable devices can be used not only for customers to self-manageme but also for professionals to supervise exercise remotely. However, many studies on wearable devices with professional supervision and feedback had minimal or standard care as control (15), which made it impossible to estimate the effects of wearable devices-based remote supervision while wearable devices-based self-directed exercise was involved in the intervention group at the same time.

As supervision can be realized by expanding the using of data from wearable devices, introducing remote supervision into the mHealth-based weight control program might be a useful strategy to enhance the effects of weight control. However, the specific effects of remotely supervised exercise on weight control have not been fully documented. This study is therefore aimed to investigate the clinical effects of heartbeat tracker-mediated remotely supervised exercise on overweight and obesity.

The supervised exercise which was usually conducted on-site has been proven to be effective compared with nonsupervised exercise on weight loss, glycemic control, claudication, or improved body composition (6–8, 18). But this type of face-to-face supervision is costly and resource-intensive (12), which limits its application to overweight and obese individuals, who usually live in communities. On the contrary, remote supervision can be realized through wearable devices and modern communication technologies with more flexibility and resource-saving. Therefore, the effects of remote supervision on the exercise of overweight and obesity need to be evaluated before scaling up for weight control. Despite many studies provided online professional support based on behavior change theories, such as goal setting, education, reminder, and instruction, etc., and showed positive effects on weight loss (19), those online supports were given either without monitoring (20) or based only on a diary to report performances (21) which lacks in time-sensitivity. Some mHealth studies which showed short-term efficacy in weight loss were conducted with minimal or standard care (11, 12). In fact, studies which had directly compared the mHealth-based remote supervision to mHealth-based self-directed exercise are scarce (10). Therefore, the effects of remotely supervised exercise were far away of being well documented.

We at the baseline gave both groups a personalized exercise prescription for each of the participants and required them to wear heartbeat trackers which can feedback them to follow exercise prescriptions. In addition, researchers supervised exercise in the intervention group by checking performances daily, giving participants instructions, reminders, and encouragements accordingly. Our study showed that nearly 50% of participants lost in 12 weeks of follow-up in both groups, which was similar to the study of Lindner et al. (22). This study further confirmed that adhering to exercise is a big challenge in both groups, and even supervision had limited impacts on adherence. Participants who dropped out in our study may be not ready to do enough exercise for weight loss according to the stages of change theory (SCT) which was proposed by Prochaska (23). For those who completed the trial, the curve of exercise performance by the time was similar to the peak at the second week in both groups, which may indicate the effects of supervision are highly dependent on self-motivated exercise as was shown in the control group, i.e., if someone was self-motivated to do exercise, remote supervision will make them do it in a better way.

Usually, physical activity trackers were sold for people to do self-directed and nonsupervised exercise with or without peer competition or peer support. But Mitesh S. Patel believed that this type of exercise engagement may be easy for the already motivated and quantified-self audience but is likely to be difficult for a large group of people with difficult-to-manage chronic health conditions (13). Supervised exercise, no matter whether on-site or remote, will give people an awareness of being under observation which has a positive influence on behavior (24). Furthermore, supervision can also provide personalized feedback and skills which were believed critical for behavior-changing (25, 26). Therefore, supervised mHealth exercise may exert more profound effects on sustaining prescribed exercise than nonsupervised mHealth exercise.

Even so, our findings suggested that remote supervision could not motivate more people to complete trials but was only useful to those who had already been motivated to engage in regular exercise for at least 3 months. As maintaining long-term exercise is critical for weight control, whether the remotely supervised exercise can keep more people who survive 3 months trial engaging in exercise over 3 months than the wearable device-based self-directed exercise is warranted.

To our best knowledge, this study is the first time to compare the effects of mHealth-based remotely supervised exercise with mHealth-based self-directed exercise among overweight and obesity. This study provided solid evidence with proper control and enough sample size to assess the effects of mHealth-based remotely supervised exercise. But still, there were some limitations in this study. First, this study is a nonrandomized trial which may introduce bias in selection, but the baseline characteristics were comparable between the two groups which indicated selection bias is not obvious. Second, two arms of the trial were tested in tandem, therefore influences of season and implementation seem unavoidable. Third, the intervention duration was only 12 weeks, and the long-term effects of remote supervision are still uncertain. Last, as different supervision regimes and population characteristics may lead to different responses to exercise intervention (11), our results based on middle-aged volunteers with heartbeat tracking may not be generalized to other supervision regimes, wearable devices, and populations.

Physical activity tracker-based remotely supervised exercise can be introduced into a health and exercise program to enhance the effects of wearable devices-based self-directed exercise for overweight and obesity. But further studies are warranted to test the ability of wearable tracker-based supervision to maintain long-term exercise engagement.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and this study is a prospective, non-randomized controlled study approved by Ethics Committee of Chongqing Medical University (s2018-065-01). The patients/participants provided their written informed consent to participate in this study.

All authors listed have made a substantial, direct, and intellectual contribution to the work and approved it for publication.

This research was funded by the following: Chongqing Medical Scientific Research Project (Joint project of Chongqing Health Commission and Science and Technology Bureau) (NO: 2021MSXM057); Humanities and Social Sciences Research Project of Chongqing Municipal Education Commission (NO: 22SKGH065). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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