Exploring mHealth applications for self-management of chronic low back pain: A survey of features and benefits.

The adoption of Mobile Health (mHealth) for self-management is growing. mHealth solutions are commonly used in public healthcare and health services, where they are appreciated for their ease of use, broad reach, and wide acceptance. Chronic Low Back Pain (CLBP) is one of the most common health problems and a leading cause of disability.

Supporting mental health self-care discovery through a chatbot.

Good mental health is imperative for one's wellbeing. While clinical mental disorder treatments exist, self-care is an essential aspect of mental health. This paper explores the use and perceived trust of conversational agents, chatbots, in the context of crowdsourced self-care through a between-subjects study ( = 80).

"Leave your smartphone out of bed": quantitative analysis of smartphone use effect on sleep quality.

Smartphones have become an integral part of people's everyday lives. Smartphones are used across all household locations, including in the bed at night. Smartphone screens and other displays emit blue light, and exposure to blue light can affect one's sleep quality.

Contrasting the Expectations and Experiences Related to Mobile Health Use for Chronic Pain: Questionnaire Study.

Background: Chronic pain is a prolonged condition that deteriorates one's quality of life. Treating chronic pain requires a multicomponent approach, and in many cases, there are no "silver bullet" solutions. Mobile health (mHealth) is a rapidly expanding category of solutions in digital health with proven potential in chronic pain management.

Understanding Smartwatch Battery Utilization in the Wild.

Smartwatch battery limitations are one of the biggest hurdles to their acceptability in the consumer market. To our knowledge, despite promising studies analyzing smartwatch battery data, there has been little research that has analyzed the battery usage of a diverse set of smartwatches in a real-world setting. To address this challenge, this paper utilizes a smartwatch dataset collected from 832 real-world users, including different smartwatch brands and geographic locations.