Abstract
The obsessive usage of digital media may exhibit symptoms traditionally associated with behavioural addictions such as mood modification, salience, tolerance and conflict. The educational methods, interventions, and treatments available to prevent or control such a digital addiction are, currently, very limited. Digital Addiction (DA) is yet not formally recognised as a mental disorder by the Diagnostic and Statistical Manual of Mental Disorders. Recently, in 2018, the World Health Organization recognised gaming disorder. Fortunately, the nature of digital media can also help the hosting of methods and mechanics to combat DA, e.g. in the monitoring of online usage and enabling individuals to stay in control of it. One of the techniques proposed in the literature is Online Peer Groups platforms, towards allowing people to form a group and provide peer support to control and regulate their usage, collectively. Online peer support groups are meant to provide peer support, counselling, motivational and learning environment, and ambivalence reduction through sharing and hope installation. However, there is a lack of research about the factors influencing people with DA to accept or reject online peer support groups. In this work, we conduct user studies and explore the acceptance and rejection factors to join and participate in such DA regulation and relapse prevention method. This will help to design and introduce the method and increase its adoption.
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Acknowledgement
This work has been partially supported by the EROGamb project funded jointly by GambleAware and Bournemouth University, SSCoDA project funded by Zayed University and H2020-MSCA-RISE-2017 project, under grant agreement No. 778228 (IDEAL-CITIES) and Shaqra University in Saudi Arabia.
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Aldhayan, M., Cham, S., Kostoulas, T., Almourad, M.B., Ali, R. (2019). Online Peer Support Groups to Combat Digital Addiction: User Acceptance and Rejection Factors. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S. (eds) New Knowledge in Information Systems and Technologies. WorldCIST'19 2019. Advances in Intelligent Systems and Computing, vol 932. Springer, Cham. https://doi.org/10.1007/978-3-030-16187-3_14
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