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A Triadic Reflective-Impulsive-Interoceptive Awareness Model of General and Impulsive Information System Use: Behavioral Tests of Neuro-Cognitive Theory

Overview of attention for article published in Frontiers in Psychology, April 2016
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Title
A Triadic Reflective-Impulsive-Interoceptive Awareness Model of General and Impulsive Information System Use: Behavioral Tests of Neuro-Cognitive Theory
Published in
Frontiers in Psychology, April 2016
DOI 10.3389/fpsyg.2016.00601
Pubmed ID
Authors

Ofir Turel, Antoine Bechara

Abstract

This study examines a behavioral tripartite model developed in the field of addiction, and applies it here to understanding general and impulsive information technology use. It suggests that technology use is driven by two information-processing brain systems: reflective and impulsive, and that their effects on use are modulated by interoceptive awareness processes. The resultant reflective-impulsive-interoceptive awareness model is tested in two behavioral studies. Both studies employ SEM techniques to time-lagged self-report data from n 1 = 300 and n 2 = 369 social networking site users. Study 1 demonstrated that temptations augment the effect of habit on technology use, and reduce the effect of satisfaction on use. Study 2 showed that temptations strengthen the effect of habit on impulsive technology use, and weaken the effect of behavioral expectations on impulsive technology use. Hence, the results consistently support the notion that information technology users' behaviors are influenced by reflective and impulsive information processing systems; and that the equilibrium of these systems is determined, at least in part, by one's temptations. These results can serve as a basis for understanding the etiology of modern day addictions.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 100 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Uruguay 1 1%
Unknown 99 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 21%
Student > Master 16 16%
Student > Bachelor 11 11%
Researcher 7 7%
Student > Doctoral Student 5 5%
Other 13 13%
Unknown 27 27%
Readers by discipline Count As %
Psychology 19 19%
Business, Management and Accounting 10 10%
Computer Science 6 6%
Medicine and Dentistry 6 6%
Social Sciences 6 6%
Other 19 19%
Unknown 34 34%