Digital Traces of Behaviour Within Addiction: Response to Griffiths (2017)

Abstract

Griffiths’ (2017) response to the recent commentary piece by Ryding and Kaye (2017) on “Internet Addiction: A conceptual minefield” provided a useful critique and extension of some key issues. We take this opportunity to further build upon on one of these issues to provide some further insight into how the field of “internet addiction” (IA) or technological addictions more generally, may benefit from capitalising on behavioural data. As such, this response extends Griffiths’ (2007) points surrounding the efficacy of behavioural data previously used in studies on problematic gambling, to consider its merit for future research on IA or associated topics such as Internet Gaming Disorder (IGD) or “Smartphone addiction”. Within this, we highlight the challenges associated with utilising behavioural data but provide some practical solutions which may support researchers and practitioners in this field. These recent developments could, in turn, advance our understanding and potentially validate such concepts by establishing behavioural correlates, conditions and contexts. Indeed, corroborating behavioural metrics alongside self-report measures presents a key opportunity if scholars and practitioners are to move the field forward.

Determining Typical Smartphone Usage: What Data Do We Need?

“…4 This may be because the cognitive processes associated with compulsive use are likely to be automatic 12 and as such cannot be captured through self-report, which can only measure deliberate conscious behaviors.…”

“…This simple measure of behavior alone may prove to be more suitable for addiction-related smartphone studies in the future. 4 …”

“…2,3 Some of this research involves selfreport estimates of usage or questionnaires that may not be entirely reliable. 4 Comparatively few studies have used mobile apps, which can measure usage behavior directly. 5 With studies increasingly reliant upon such measures, the development of norms regarding the type and volume of data required to make reliable inferences about day-to-day behavior is paramount.…”

Are smartphones really that bad? Improving the psychological measurement of technology-related behaviors

“…(Ellis & Piwek, 2018). Approaches within psychology have almost exclusively focused on correlational research that involves asking people to consider their personal experience with a technology rather than measuring their actual behavior (Ellis et al, 2018a). This reflects a general trend within social psychology as a whole (Baumesiter et al, 2007;Doliński, 2018), but remains surprising when considered alongside automated systems (e.g., smartphones (Miller, 2012)) that can record human-computer interactions directly (Piwek, Ellis & Andrews, 2016).…”

“…This has recently led to a UK government enquiry concerning the effects of screen time on health (UK Parliament, 2018). However, regardless of whether research aims to focus on narrow or broad definitions of technology use, our current understanding is based around a set of popular measures that present several methodological shortcomings (Shaw, Ellis & Ziegler, 2018;Ryding & Kaye, 2017). This has become particularly pertinent as methods of investigation have remained static despite exponential changes in the availability and processing power afforded by modern technology (Shaw, Ellis & Ziegler, 2018).…”