A Psychometric Comparison of the Internet Addiction Test, the Internet-Related Problem Scale, and Self-Diagnosis

By Laura Widyanto, Mark D. Griffiths, Vivienne Brunsden. Cyberpsychology, Behavior, and Social Networking, 2011

309 citations recorded by the source corpus.

Subfields: Communication, Education, Sociology and Political Science

View Paper: https://www.semanticscholar.org/paper/d1e099c8f7060ed901b8d993ff74532339897826

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Citations in the corpus

The measurement of Internet addiction: A critical review of existing scales and their psychometric properties (2014, methodology): “…2013 Spain .79 525 14.1 .9 Internet Related Problem Scale (IRPS) Armstrong et al., 2000 362 Substance dependence 20 10 Armstrong et al., 2000 Australia .87 52 – 1.2 20 4 Widyanto et al., 2008 UK .62– .84 79 36.6 .2 20 10 Widyanto et al., 2011 UK .60– .90 225 25.2 .4 Internet Usage Scale (IUS)…”
Video Game Addiction: Past, Present and Future (2012, background): “Despite this major shortcoming, recent research by Widyanto, Griffiths and Brunsden [38] reported that a person’s self-diagnosis of whether they were addicted to the Internet or not correlated highly with more standardized measures of Internet addiction.”
Assessment of internet gaming disorder in clinical research: Past and present perspectives (2014, background): “since this measure is highly associated with more standardized measures of internet addiction (38).”
The Effects of Boredom, Loneliness, and Distress Tolerance on Problem Internet Use Among University Students (2016, background): “While these groups are clearly important, a much larger proportion of the population potentially experiences negative (problematic) outcomes due to more moderate and normative internet use (Widyanto et al. 2011).”
Too human and not human enough: A grounded theory analysis of mental health harms from emotional dependence on the social chatbot Replika (2022, background): “It shares many affinities with technology dependency; both are marked by continued engagement despite harms (van den Eijnden et al., 2016; Wang et al., 2015; Widyanto et al., 2011) and they appear correlated to each other, suggesting similar drivers (Estevez et al., 2017).”