General Bayesian Network in Performing Micro-reality Mining with Mobile Phone Usage Data for Device Personalization

2012 ◽  
pp. 381-388
Author(s):  
Seong Wook Chae ◽  
Jungsik Hwang ◽  
Kun Chang Lee
Keyword(s):  
Bayesian Network ◽  
Mobile Phone ◽  
Reality Mining ◽  
Mobile Phone Usage ◽  
Usage Data

Mobile Phone Etiquette in Nigeria

2011 ◽  
pp. 527-538
Author(s):  
Aniebiet I. Ntui ◽  
Nkoyo B. Edem
Keyword(s):  
Mobile Phone ◽  
Mobile Phones ◽  
Mobile Telephony ◽  
Direct Observations ◽  
Mobile Phone Usage ◽  
Usage Data

There has been tremendous growth in the mobile telephony industry in Nigeria in recent years. This evolving technology has given rise to concerns over the etiquette governing mobile phone usage. This study was undertaken to better understand levels of knowledge of Nigerians about etiquettes of mobile phone usage. Data were collected through interviews, direct observations and questionnaire from 861 randomly selected mobile phone users residing in diverse streets of Calabar municipality. The study revealed that the levels of knowledge of Nigerians about etiquette of mobile phone usage is high but users refuse to conform; that the etiquette that should be up held include volume of the ringing tone should be low, pleasant and not annoy others; mobile phones are not used while driving. The implication of is that non compliance with mobile phone etiquettes poses a serious threat and distraction to others. Based on the findings, recommendations which would increase levels of knowledge of and compliance with the etiquette of mobile phone usage in Nigeria were set forth.

scholarly journals 0013 Mobile Device Use in Bed and Relationships to Work Productivity: Impact of Anxiety

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A5-A5
Author(s):  
A Gozar ◽  
A Seixas ◽  
L Hale ◽  
C Branas ◽  
M Barrett ◽  
...  
Keyword(s):  
Mobile Phone ◽  
Mobile Device ◽  
Productivity Loss ◽  
Work Productivity ◽  
Well Being ◽  
Mobile Phone Use ◽  
Mediating Role ◽  
Mobile Phone Usage ◽  
Device Use ◽  
Healthy Activity

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

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