Abstract: Due to advances in technology being made at an exponential rate, organisations are attempting to compete with one another by utilising state-of-the-art technology to provide innovative products and services that encourage use. However, there is no moral code to inform sensitive technology design, a consequence of which is the emergence of so-called technology addiction. While addiction as a term is problematic, increasing evidence suggests that related-conditions present implications for the individual, for organisations and for wider society. In this research, a consideration of the potentially addictive elements of technology indicates that it can be possible to reverse engineer these systems, as it were, to promote the development of new behaviours, which can enable the individual to abstain from overuse. Utilising smartphones to deliver digital behavioural change interventions can leverage abundant data touchpoints to provide highly tailored treatment, in addition to allowing for enhanced monitoring and accuracy. To inform understanding of this contemporary phenomenon, the literature on addiction has been reviewed, along with the literature on persuasion architecture to inform an understanding of techniques that lend themselves to overuse and how these can be leveraged to promote recovery. From which, the authors have developed a proposed model to inform the practice of those operating in the domains of computer science.

Andrew Kear and Sasha L. Folkes. “Digital Technology Disorder: Justification and a Proposed Model of Treatment”. International Journal of Advanced Computer Science and Applications (IJACSA) 9.8 (2018). http://dx.doi.org/10.14569/IJACSA.2018.090882

@article{Kear2018,
title = {Digital Technology Disorder: Justification and a Proposed Model of Treatment},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2018.090882},
url = {http://dx.doi.org/10.14569/IJACSA.2018.090882},
year = {2018},
publisher = {The Science and Information Organization},
volume = {9},
number = {8},
author = {Andrew Kear and Sasha L. Folkes}
}