# Using Smartwatches in Stress Management, Mental Health, and Well-Being: A Systematic Review
## 1 Introduction  
Smartwatches have evolved into advanced health monitoring tools, enabling the continuous collection of important biometric data from users. In Ref. [1], modern wearable devices are equipped with various sensors that record vital signs continuously, enhancing self-monitoring and the early detection of health issues. For instance, a smartwatch can continuously monitor a user's heart rate and physical activity levels, track sleep patterns, and, in some advanced models, perform electrocardiograms (ECGs) or measure blood pressure. The purpose of [PERSON] et al. 's study was to showcase how such devices enhance the self-management of health by providing early indicators of potential issues, such as cardiac arrhythmias or excessive stress. Their findings emphasize significant benefits: continuous monitoring via a smartwatch can motivate users toward healthier habits and contribute to the early detection of health anomalies. At the same time, the essential limitations of these technologies are also pointed out. For example, the reliability of measurements may be affected by factors such as skin type or wrist movement, and the limited battery life often hinders uninterrupted data collection. Privacy is another major concern, as the sensitive health data collected requiressecure management and careful interpretation. Overall, the analysis concludes that while a smartwatch is a valuable complement to health monitoring, its effective use depends on trustworthy technologies and responsible user behavior [1]. With these advantages and drawbacks as a backdrop, a critical next question arises: \"How willing are people to adopt smartwatches for health-related purposes, and what factors influence this decision\"? This question was explored by [PERSON] et al. [2], who conducted an empirical study aimed at identifying the determinants of public acceptance and the use of wearable health devices. Their research focused on adults aged 25-40 in India (273 participants), assessing users' perceptions of device intrusiveness and comfort, as well as perceived usefulness and ease of use. Using a structural equation modeling approach (PLS-SEM), [PERSON] et al. examined how these factors relate to users' attitudes toward smartwatches and their intention to use them for personal health monitoring. Their findings revealed a nuanced effect: comfort and perceived intrusiveness do not directly affect the intention to adopt the device. Instead, these factors indirectly shape the perceptions of usefulness and usability. Specifically, when a device is ergonomic and not perceived as intrusive in daily life, users are more likely to find it useful and easy to use--key motivators for adoption according to classic technology acceptance models. Indeed, their analysis confirms that high perceived usefulness and ease of use are associated with positive attitudes and strong usage intentions. They conclude that improvements in the design of smartwatches--making them less intrusive and more comfortable--can enhance their perceived value and thus encourage more people to integrate them into their health monitoring routines. However, as the acceptance of smartwatches grows and they become part of everyday life, a new question emerges as follows: \"How effectively can these devices be used for specific medical purposes, such as stress management\"? This aspect was examined by [PERSON] et al. [3], who conducted a study focused on the ability of smartwatches to detect and predict stress levels using machine learning techniques (Figure 1). The aim of their research was to compare different stress prediction models using both objective indicators (predefined stress-inducing stimuli) and subjective participant self-reports. Figure 1: Sequence of activities for the laboratory-based phase of this study. (**A**) Timeline of the experiment including stress-inducing tasks (e.g., speech, math, cold pressor test), self-report periods, and resting phases. (**B**) Fossil Gen4 Explorist smartwatch instrumented for this study.