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      Connected to TV series: Quantifying series watching engagement

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          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).


          In Study 1 ( N Sample1 = 740 and N Sample2 = 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.


          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.


          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.

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          From alpha to omega: a practical solution to the pervasive problem of internal consistency estimation.

          Coefficient alpha is the most popular measure of reliability (and certainly of internal consistency reliability) reported in psychological research. This is noteworthy given the numerous deficiencies of coefficient alpha documented in the psychometric literature. This mismatch between theory and practice appears to arise partly because users of psychological scales are unfamiliar with the psychometric literature on coefficient alpha and partly because alternatives to alpha are not widely known. We present a brief review of the psychometric literature on coefficient alpha, followed by a practical alternative in the form of coefficient omega. To facilitate the shift from alpha to omega, we also present a brief guide to the calculation of point and interval estimates of omega using a free, open source software environment. © 2013 The British Psychological Society.
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                Author and article information

                Journal of Behavioral Addictions
                J Behav Addict
                Akadémiai Kiadó (Budapest )
                26 December 2017
                December 2017
                : 6
                : 4
                : 472-489
                [ 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
                Author notes
                [* ]Corresponding author: István Tóth-Király; Institute of Psychology, ELTE Eötvös Loránd University, Izabella utca 46, Budapest H-1064, Hungary; Phone: +36 20 582 9949; E-mails: tothkiralyistvan@ ; toth-kiraly.istvan@
                © 2017 The Author(s)

                This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited.

                Page count
                Figures: 1, Tables: 9, Equations: 0, References: 115, Pages: 18
                Funding sources: IT-K was supported by the ÚNKP-17-3 New National Excellence Program awarded by the Hungarian Ministry of Human Capacities. GO was supported by the Hungarian Research Fund (NKFI PD 116686, FK 124225).
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