Skip to main content Method: Combating Digital Addiction via Online Peer Support Groups.

Alrobai, A., Algashami, A., Dogan, H., Corner, T., Phalp, K. T. and Ali, R., 2019. Method: Combating Digital Addiction via Online Peer Support Groups. International Journal of Environmental Research and Public Health, 16 (7), 1162.

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COPEer Combating Digital Addiction via Online Peer Support Groups.pdf - Published Version
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DOI: 10.3390/ijerph16071162


Digital addiction (hereafter DA) denotes a problematic relationship with technology described by being compulsive, obsessive, impulsive and hasty. New research has identified cases where users’ digital behaviour shows symptoms meeting the clinical criteria of behavioural addiction. The online peer groups approach is one of the strategies to combat addictive behaviours. Unlike other behaviours, intervention and addictive usage can be on the same medium; the online space. This shared medium empowers influence techniques found in peer groups, such as selfmonitoring, social surveillance, and personalised feedback, with a higher degree of interactivity, continuity and real-time communication. Social media platforms in general and online peer groups, in particular, have received little guidance as to how software design should take it into account. Careful theoretical understanding of the unique attributes and dynamics of such platforms and their intersection with gamification and persuasive techniques is needed as the ad-hoc design may cause unexpected harm. In this paper, we investigate how to facilitate the design process to ensure a systematic development of this technology. We conducted several qualitative studies including user studies and observational investigations. The primary contribution of this research is twofold: (i) a reference model for designing interactive online platforms to host peer groups and combat DA, (ii) a process model,, inspired by the participatory design approach to building Customisable Online Persuasive Ecology by Engineering Rehabilitation strategies for different groups.

Item Type:Article
Group:Faculty of Science & Technology
ID Code:32119
Deposited By: Symplectic RT2
Deposited On:01 Apr 2019 15:04
Last Modified:14 Mar 2022 14:15


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