Abstract
Introduction
Mobile phone use at night is associated with worse sleep quality. It may also be associated with daytime productivity, possibly via anxiety.
Methods
Data were obtained from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) study, including N=1007 adults age 22–60. Mobile device use in bed was assessed as the frequency that participants reported: a device in the bedroom, use of the device in bed, texting, emails, internet browsing, calls, and/or social networking in bed, being woken up by the device in a planned (alarm) or unplanned (alert/call/message) way, and checking the phone at night. Each of these were coded as “never,” “rarely,” or “often.” Work productivity was assessed with the Well-Being Assessment of Productivity (WBA-P; scores 0–22 measure productivity loss). Regressions with WBA-P score as outcome and mobile phone variables as predictors were adjusted for age, sex, race/ethnicity, education, and income level. Post-hoc analyses included GAD7 score to examine the mediating role of anxiety.
Results
The presence of a device was not associated with productivity loss, but frequent use (“often”) was (B=1.26,p=0.01). Increased productivity loss was also seen in those who frequently (“often”) sent texts (B=1.20,p=0.008), browsed internet (B=1.14,p=0.01), emailed (B=2.09,p<0.0005), called (B=1.42,p=0.004), and used social media (B=1.26,p=0.004). Productivity loss was associated with being woken by a call/alert “rarely” (B=1.20,p=0.001) or “often” (B=1.72,p=0.005), but not by alarm. Checking the phone at night “rarely” (B=0.89,p=0.01) and “often” (B=1.73,p<0.0005) were also associated with productivity loss. When anxiety was entered into the model, all relationships except those with frequent emails and calls in bed became nonsignificant.
Conclusion
Anxiety may be the underlying cause for both increased mobile phone usage and reduced productivity. Reducing anxiety levels may indirectly aid in decreasing nighttime mobile phone use and increasing daytime productivity.
Support
The SHADES study was funded by R21ES022931
Dr. Grandner is supported by R01MD011600
Understanding the Challenges of Mobile Phone Usage Data
