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J Behav Addict. 2017 Dec 1;6(4):472-489. doi: 10.1556/2006.6.2017.083.

Connected to TV series: Quantifying series watching engagement.

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1 Doctoral School of Psychology, ELTE Eötvös Loránd University , Budapest, Hungary.
2 Institute of Psychology, ELTE Eötvös Loránd University , Budapest, Hungary.
3 Institute of Cognitive Neuroscience and Psychology, Research Centre for Natural Sciences, Hungarian Academy of Sciences , Budapest, Hungary.


Background and aims Television series watching stepped into a new golden age with the appearance of online series. Being highly involved in series could potentially lead to negative outcomes, but the distinction between highly engaged and problematic viewers should be distinguished. As no appropriate measure is available for identifying such differences, a short and valid measure was constructed in a multistudy investigation: the Series Watching Engagement Scale (SWES). Methods In Study 1 (NSample1 = 740 and NSample2 = 740), exploratory structural equation modeling and confirmatory factor analysis were used to identify the most important facets of series watching engagement. In Study 2 (N = 944), measurement invariance of the SWES was investigated between males and females. In Study 3 (N = 1,520), latent profile analysis (LPA) was conducted to identify subgroups of viewers. Results Five factors of engagement were identified in Study 1 that are of major relevance: persistence, identification, social interaction, overuse, and self-development. Study 2 supported the high levels of equivalence between males and females. In Study 3, three groups of viewers (low-, medium-, and high-engagement viewers) were identified. The highly engaged at-risk group can be differentiated from the other two along key variables of watching time and personality. Discussion The present findings support the overall validity, reliability, and usefulness of the SWES and the results of the LPA showed that it might be useful to identify at-risk viewers before the development of problematic use.


Series Watching Engagement Scale (SWES); TV series watching; exploratory structural equation modeling (ESEM); latent profile analysis (LPA); problematic use; series watching engagement

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