Factors affecting female college students' intention to use digital technology in wearable devices to stimulate health monitoring.

In this study, we measured female college students' mental health and physical activities to identify factors that affect their intention to use wearable health-monitoring devices. Specifically, the study derived correlations between female students' health-related quality of life (HRQoL) including, physical activity, stress level, attitudes toward eating, and self-esteem. Using this information, we ascertained the relationship between female college students' use of wearable devices and physical activity and examined the requirements for smartphone applications for healthcare. We collected data from 308 female college students in the Republic of Korea over four months starting in July 2021 using an anonymous online survey. We then analyzed the data using descriptive statistics and linear regression. The results showed that the factors that caused stress in female college students during the past six months were fatigue, COVID-19, grades, worries about getting a full-time job, menstruation, and being overweight. This paper found a negative correlation between stress and self-esteem and a positive correlation between physical activity and self-esteem. People with experience using wearable devices reported a higher intensity in physical activity. More than half the participants recorded biometric information for their menstrual cycles and menstrual cramps regardless of whether they were using wearable devices. Currently, healthcare applications can suggest diets and track nutritional intake, menstrual cycles, and amount of exercise, which users want simultaneously. Therefore, there is a market demand for a mobile application linked with a wearable device and tailored for female college students that could combine and manage all these data. In the future, application developers should consider the needs of female college students.

Investigating the impact of daily life context on physical activity in terms of steps information generated by wearable activity tracker.

OBJECTIVES: This study used ecological momentary assessment (EMA) to understand how the contextual factors of everyday life affect physical activity in terms of steps measured by wearable activity tracking devices and to identify what factors increase physical activity. In addition, this study investigated and analyzed the user environment and resulting contextual factors in a typical office setting. METHODS: A total of 27 office workers of Korea (70.4 % male, aged 19-44, 51.9 % married, and mostly from an information technology company) participated in this study and provided five-day EMA diary data (morning and evening) in the form of activity log data from a wearable device and attended a 45-60 min qualitative interview. In this study, a mixed-method approach (qualitative and quantitative) was used. RESULTS: This study demonstrated that contextual factors such as mood state (e.g., tired, p < 0.01), level of physical activity (e.g., vigorous, p < 0.01), and types of physical activity (e.g., using the stairs instead of elevators, p < 0.05) could affect the physical activity of the users of wearable devices in everyday life. CONCLUSION: The study contributed to a better understanding of how the contextual and environmental factors affect the physical activity of user of wearable activity trackers (WATs). These findings have practical implications for designers of such devices. In addition, these results could guide future research agendas.

Improving patient engagement by fostering the sharing of activity tracker data with providers: a qualitative study.

BACKGROUND: Activity trackers are becoming increasingly popular, but patients often hesitate to share the data from such devices with their health care providers. Researchers have shown that sharing everyday health data with physicians can foster greater patient engagement. OBJECTIVES: This research is intended to investigate activity tracker users' decisions regarding the sharing of their activity tracker data with physicians, as well as to build a stage based framework for improving patient engagement by fostering such data sharing. METHODS: Qualitative analysis of interview records of 12 adults, who had used Fitbit activity tracking devices for up to two years, identifying emotions and experiences surrounding their tendencies to share physical exercise data with a physician. RESULTS: This research used the subjects' emotions and considerations regarding the decision over whether to share exercise data with physicians to create a stage based framework with three stages: cognisance, tangible evidence and supportive feedback. CONCLUSION: The tendency to progress towards three stages with greater patient-physician engagement appears to increase with health risk profile and with reduced data privacy concerns. This framework contributes to ongoing discussions about establishing patient-practitioner engagement, based around patients' shared personal data collection.