Mobile manifestations of alertness

Abstract

Our body clock causes considerable variations in our behavioral, mental, and physical processes, including alertness, throughout the day. While much research has studied technology usage patterns, the potential impact of underlying biological processes on these patterns is under-explored. Using data from 20 participants over 40 days, this paper presents the first study to connect patterns of mobile application usage with these contributing biological factors. Among other results, we find that usage patterns vary for individuals with different body clock types, that usage correlates with rhythms of alertness, that app use features such as duration and switching can distinguish periods of low and high alertness, and that app use reflects sleep interruptions as well as sleep duration. We conclude by discussing how our findings inform the design of biologically-friendly technology that can better support personal rhythms of performance.

Patient Perspectives on Self-Management Technologies for Chronic Fatigue Syndrome

“…However, these methods of data collection require user effort in order to log data, and Study 3 showed that this effort may be particularly problematic for people with ME/CFS because it can contribute to feelings of fatigue. Future work could therefore explore the potential for fully automated fatigue logging, such as through wearable and 'cognitive personal informatics' devices like EEG [23], or by using patterns of smartphone app use to infer a user's state [53].…”

Is a SIMPLe smartphone application capable of improving biological rhythms in bipolar disorder?

“…In this regard, Murnane et al found that smartphones usage in healthy controls is closely correlated to chronotype, alertness, and sleep (Murnane et al, 2016). Moreover, Runyan et al found that the use of smartphone applications improve self-awareness, which is widely suggested as a key positive behaviour change factor (Runyan et al, 2013).…”

News or social media? Socio-economic divide of mobile service consumption

“…More precisely, we filter out weekends and French holidays (25 May and 5 June in the period considered), and we keep observations during home hours (from 20.00 to 7.00) on weekdays. There is evidence that app usage peaks from 20.00 [ 34 ], and that online consumption is more or less homogeneous throughout the day [ 35 ]. Although there could be important differences in traffic during the day for individuals, we believe that our aggregate consumption data by area are highly representative of the daily online consumption of the population of the area.…”