The Potential of Digital Phenotyping and Mobile Sensing for Psycho-Diagnostics of Internet Use Disorders

Abstract

Purpose of Review The present paper provides an accessible overview on the potential of digital phenotyping and mobile sensing not only shedding light on the nature of Internet Use Disorders (IUD), but also to provide new ideas on how to improve psycho-diagnostics of mental processes linked to IUD. Recent Findings In detail, the psycho-diagnostic areas of prevention, treatment, and aftercare in the realm of IUDs are focused upon in this work. Before each of these areas is presented in more specificity, the terms digital phenotyping and mobile sensing are introduced against the background of an interdisciplinary research endeavor called Psychoinformatics. Obstacles to overcome problems in this emerging research endeavor—sensing psychological traits/states from digital footprints—are discussed together with risks and chances, which arise from the administration of online-tracking technologies in the field of IUDs. Summary Given the limited validity and reliability of traditional assessment via questionnaires or diagnostic interviews with respect to recall bias and tendencies to answer towards social desirability, digital phenotyping and mobile sensing offer a novel approach overcoming recall bias and other limitations of usual assessment approaches. This will not only set new standards in precisely mapping behavior, but it will also offer scientists and practitioners opportunities to detect risky Internet use patterns in a timely manner and to establish tailored feedback as a means of intervention.

The role of microtransactions in Internet Gaming Disorder and Gambling Disorder: A preregistered systematic review

“…Future measuring of actual recorded behaviours and applying digital phenotyping principles may yield promising findings, but this clearly needs support from the industry ( Montag & Rumpf, 2021 ).…”

Mining Digital Traces of Facebook Activity for the Prediction of Individual Differences in Tendencies Toward Social Networks Use Disorder: A Machine Learning Approach

“…This suggests the feasibility of implementing unobtrusive detection of individuals at risk by leveraging on users’ digital traces of online activity. Please see also a recent article discussing the potential of mobile sensing and digital phenotyping to combat Internet Use Disorders ( Montag and Rumpf, 2021 ).…”

“…Although this objective data is highly interesting, most existing social media studies dealing with SNUD rely on self-report of online activity, which may be prone to recall bias, social desirability and so forth. In particular, the study of the predictors and correlates of “Internet Use Disorders” and other related behavioral addictions could greatly benefit from the use of objective data ( Montag et al, 2017 ; Ellis et al, 2018 ; Montag and Rumpf, 2021 ). Unfortunately, the use of these types of data is still uncommon, probably due to the technical complexity of the methodological tools needed to retrieve them.…”

Safer esports for players, spectators, and bettors: Issues, challenges, and policy recommendations

“…As the early detection of problematic or addictive use patterns are of special importance, relevant measures should be provided by the industry and esports clubs following the principles of screening and the need for early intervention such as giving feedback ( Rumpf et al., 2018 ) or by the adaptation of relevant player protection practices of the gambling industry, such as introducing mandatory breaks, setting time limits, cooling-off periods, and personalized messaging ( Griffiths & Pontes, 2020 ). If possible, digital phenotyping and sensing can serve as a reliable measure to detect problematic behavior patterns ( Montag & Rumpf, 2021 ).…”