Smart Wearable Technology for Health Tracking: What Are the Factors that Affect Their Use?

Wearable devices are essential tools for personalized healthcare. Their usage is steadily expanding due to increasing capabilities and levels of accuracy. They are used by consumers for numerous reasons, ranging from measuring physical activity, tracking health status or just competing with friends based on activity data. Different user groups have different motivations such as losing weight, sleep tracking, fertility tracking or gait monitoring. In recent years, capabilities of smart wearable devices increased continuously, enabling vast data collection. Such data can be used by health professionals to support medical diagnosis and treatment and also by consumers to assist self-motivation to adopt and track healthier daily life practices [1]. However, there are very few researches conducted on the factors affecting consumer adoption in this area. This research aims to find the determinants of technology acceptance of wearable device usage for tracking health information. Most of the existing studies in this area use the technology acceptance model (TAM), which focuses on technology acceptance from an organizational perspective. The Extended Unified Theory of Acceptance and Use of Technology (UTAUT2) model, which is tailored for consumers, is under-appreciated in acceptance studies examining mobile health and wearable devices. This study applies UTAUT2 model to explain the factors affecting consumers’ intention to use wearable mobile devices to track health information. In addition to the original UTAUT2 model, a model based on UTAUT2 with additional generic constructs (privacy concern, side-benefit expectancy and mere exposure effect) and domain-specific constructs (perceived health status and future health expectancy) is applied and tested.


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Appointment planning and scheduling (APS) plays a crucial role in patient service quality as well as utilization of valuable resources in healthcare. In this study, we considered the integrated problem of appointment planning and scheduling in an outpatient procedure center (OPC) over a planning horizon of multiple periods. We formulated the problem as a two-stage stochastic mixed-integer linear program (SMILP) with uncertainty in surgery durations. The first-stage problem consists of period assignment of s...
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With the rapid emergence of mobile technologies in recent years, mobile health (m-health) has become fundamental to healthcare. Persuasion strategies and behavior change support features are widely used in m-health applications to increase the effectiveness of these applications on users. However, in the literature, there is a lack of research to analyze the current situation of m-health applications particularly from the perspective of behavior change approaches. In this study, the workout applications in ...
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Citation Formats
T. Pancar and S. Özkan Yıldırım, Smart Wearable Technology for Health Tracking: What Are the Factors that Affect Their Use? 2021.