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Predictors of Acceptance and Rejection of Online Peer Support Groups as a Digital Wellbeing Tool.

McAlaney, J., Aldhayan, M., Almourad, M.B., Cham, S. and Ali, R., 2020. Predictors of Acceptance and Rejection of Online Peer Support Groups as a Digital Wellbeing Tool. In: WorldCIST'20: Trends and Innovations in Information Systems and Technologies, 07-10 April 2020, Budva, Montenegro, 95 - 107.

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Predictors of Acceptance and Rejection of Online Peer Support Groups as a Digital Wellbeing Tool - 334.pdf - Accepted Version
Available under License Creative Commons Attribution Non-commercial.


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DOI: 10.1007/978-3-030-45697-9_10


© 2020, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG. Digital media usage can be problematic; exhibiting symptoms of behavioural addiction such as mood modification, tolerance, conflict, salience, withdrawal symptoms and relapse. Google Digital Wellbeing and Apple Screen Time are examples of an emerging family of tools to help people have a healthier and more conscious relationship with technology. Peer support groups is a known technique for behaviour change and relapse prevention. It can be facilitated online, especially with advanced social networking techniques. Elements of peer support groups are being already embedded in digital wellbeing tools, e.g. peer comparisons, peer commitments, collective usage limit-setting and family time. However, there is a lack of research about the factors influencing people acceptance and rejection of online peer support groups to enhance digital wellbeing. Previous work has qualitatively explored the acceptance and rejection factors to join and participate in such groups. In this paper, we quantitatively study the relationship between culture, personality, self-control, gender, willingness to join the groups and perception of their usefulness, on such acceptance and rejection factors. The qualitative phase included two focus groups and 16 interviews while the quantitative phase consisted of a survey (215 participants). We found a greater number of significant models to predict rejection factors than acceptance factors, although in all cases the amount of variance explained by the models was relatively small. This demonstrates the need to design and, also, introduce such technique in a contextualised and personalised style to avoid rejection and reactance.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:Online Peer Groups; Digital Addiction; Digital Wellbeing; Behavioural Change
Group:Faculty of Science & Technology
ID Code:34124
Deposited By: Symplectic RT2
Deposited On:10 Jun 2020 15:05
Last Modified:14 Mar 2022 14:22


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