Direct Measurements of Smartphone Screen-Time: Relationships with Demographics and Sleep.

BACKGROUND: Smartphones are increasingly integrated into everyday life, but frequency of use has not yet been objectively measured and compared to demographics, health information, and in particular, sleep quality. AIMS: The aim of this study was to characterize smartphone use by measuring screen-time directly, determine factors that are associated with increased screen-time, and to test the hypothesis that increased screen-time is associated with poor sleep. METHODS: We performed a cross-sectional analysis in a subset of 653 participants enrolled in the Health eHeart Study, an internet-based longitudinal cohort study open to any interested adult (≥ 18 years). Smartphone screen-time (the number of minutes in each hour the screen was on) was measured continuously via smartphone application. For each participant, total and average screen-time were computed over 30-day windows. Average screen-time specifically during self-reported bedtime hours and sleeping period was also computed. Demographics, medical information, and sleep habits (Pittsburgh Sleep Quality Index-PSQI) were obtained by survey. Linear regression was used to obtain effect estimates. RESULTS: Total screen-time over 30 days was a median 38.4 hours (IQR 21.4 to 61.3) and average screen-time over 30 days was a median 3.7 minutes per hour (IQR 2.2 to 5.5). Younger age, self-reported race/ethnicity of Black and "Other" were associated with longer average screen-time after adjustment for potential confounders. Longer average screen-time was associated with shorter sleep duration and worse sleep-efficiency. Longer average screen-times during bedtime and the sleeping period were associated with poor sleep quality, decreased sleep efficiency, and longer sleep onset latency. CONCLUSIONS: These findings on actual smartphone screen-time build upon prior work based on self-report and confirm that adults spend a substantial amount of time using their smartphones. Screen-time differs across age and race, but is similar across socio-economic strata suggesting that cultural factors may drive smartphone use. Screen-time is associated with poor sleep. These findings cannot support conclusions on causation. Effect-cause remains a possibility: poor sleep may lead to increased screen-time. However, exposure to smartphone screens, particularly around bedtime, may negatively impact sleep.

Automatically captured sociability and sleep quality in healthy adults.

Sleep and social interactions have been shown to have a considerable public health impact. However, little is known about how these affect each other in healthy individuals. This research is first to propose the exploration of the bidirectional relationship between technologically sensed sleep quality and quantified face-to-face social interactions. We detail a pilot study designed to study the relationship of sociability and sleep quality, both measured and perceived, of healthy adults. We capture real-world social interactions and measure sleep in a naturalistic setting using wireless sensing technologies. We find that it may not be the device-defined sleep quality (ZQ score) but our perceived sleep quality which affects our following day's sociability. Further, we also find perceived sleep quality is more strongly correlated to normalized ZQ scores than the actual scores. These intriguing insights raise several questions on how an individual's social life could be affected by sleep and indicate the usefulness of mobile sensing technologies in understanding public health phenomena.

Sleep, mood and sociability in a healthy population.

Sleep and mood problems have a considerable public health impact with serious societal and significant financial effects. In this work, we study the relationship between these factors in the everyday life of healthy young adults. More importantly, we look at these factors from a social perspective, studying the impact that couples have on each other and the role that face-to-face interactions play. We find that there is a significant bi-directional relationship between mood and sleep. More interestingly, we find that the spouse's sleep and mood may have an effect on the subject's mood and sleep. Further, we find that subjects whose sleep is significantly correlated with mood tend to be more sociable. Finally, we observe that less sociable subjects show poor mood more often than their more sociable contemporaries. These novel insights, especially those involving sociability, measured from quantified face-to-face interaction data gathered through smartphones, open up several avenues to enhance public health research through the use of latest wireless sensing technologies.

Trust evaluation in health information on the World Wide Web.

The impact of health information on the web is mounting and with the Health 2.0 revolution around the corner, online health promotion and management is becoming a reality. User-generated content is at the core of this revolution and brings to the fore the essential question of trust evaluation, a pertinent problem for health applications in particular. Evolving Web 2.0 health applications provide abundant opportunities for research. We identify these applications, discuss the challenges for trust assessment, characterize conceivable variables, list potential techniques for analysis, and provide a vision for future research.