Flayelle, Maèva; Elhai, Jon D.; Maurage, Pierre; Vögele, Claus; Brevers, Damien; Baggio, Stéphanie; Billieux, Joël (2022). Identifying the psychological processes delineating non-harmful from problematic binge-watching: A machine learning analytical approach. Telematics and informatics, 74, p. 101880. Elsevier 10.1016/j.tele.2022.101880
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As on-demand streaming technology rapidly expanded, binge-watching (i.e., watching multiple episodes of TV series back-to-back) has become a widespread activity, and substantial research has been conducted to explore its potential harmfulness. There is, however, a need for differentiating non-harmful and problematic binge-watching. This is the first study using a machine learning analytical strategy to further investigate the distinct psychological predictors of these two binge-watching patterns. A total of 4275 TV series viewers completed an online survey assessing sociodemographic variables, binge-watching engagement, and relevant predictor variables (i.e., viewing motivations, impulsivity facets, and affect). In one set of analyses, we modeled intensity of non-harmful involvement in binge-watching as the dependent variable, while in a following set of analyses, we modeled intensity of problematic involvement in binge-watching as the dependent variable. Emotional enhancement motivation, followed by enrichment and social motivations, were the most important variables in modeling non-harmful involvement. Coping/escapism motivation, followed by urgency and lack of perseverance (two impulsivity traits), were found as the most important predictors of problematic involvement. These findings indicate that non-harmful involvement is characterized by positive reinforcement triggered by TV series watching, while problematic involvement is linked to negative reinforcement motives and impulsivity traits.
Item Type: |
Journal Article (Original Article) |
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Division/Institute: |
04 Faculty of Medicine > Medical Education > Institute of General Practice and Primary Care (BIHAM) |
UniBE Contributor: |
Baggio, Stéphanie |
Subjects: |
600 Technology > 610 Medicine & health 300 Social sciences, sociology & anthropology > 360 Social problems & social services |
ISSN: |
0736-5853 |
Publisher: |
Elsevier |
Language: |
English |
Submitter: |
Doris Kopp Heim |
Date Deposited: |
16 Nov 2022 10:39 |
Last Modified: |
18 Dec 2022 02:05 |
Publisher DOI: |
10.1016/j.tele.2022.101880 |
BORIS DOI: |
10.48350/174814 |
URI: |
https://boris.unibe.ch/id/eprint/174814 |