Time distortion when users at-risk for social media addiction engage in non-social media tasks.

BACKGROUND There is a growing concern over the addictiveness of Social Media use. Additional representative indicators of impaired control are needed in order to distinguish presumed social media addiction from normal use. AIMS (1) To examine the existence of time distortion during non-social media use tasks that involve social media cues among those who may be considered at-risk for social media addiction. (2) To examine the usefulness of this distortion for at-risk vs. low/no-risk classification. METHOD We used a task that prevented Facebook use and invoked Facebook reflections (survey on self-control strategies) and subsequently measured estimated vs. actual task completion time. We captured the level of addiction using the Bergen Facebook Addiction Scale in the survey, and we used a common cutoff criterion to classify people as at-risk vs. low/no-risk of Facebook addiction. RESULTS The at-risk group presented significant upward time estimate bias and the low/no-risk group presented significant downward time estimate bias. The bias was positively correlated with Facebook addiction scores. It was efficacious, especially when combined with self-reported estimates of extent of Facebook use, in classifying people to the two categories. CONCLUSIONS Our study points to a novel, easy to obtain, and useful marker of at-risk for social media addiction, which may be considered for inclusion in diagnosis tools and procedures.

[1]  Mark D. Griffiths,et al.  IN STUDENTS : PREVALENCE AND RISK FACTORS 1 Internet addiction in students : Prevalence and risk factors , 2014 .

[2]  Ofir Turel,et al.  Quitting the use of a habituated hedonic information system: a theoretical model and empirical examination of Facebook users , 2015, Eur. J. Inf. Syst..

[3]  M. Potenza,et al.  A cognitive-behavioral model of Internet gaming disorder: theoretical underpinnings and clinical implications. , 2014, Journal of psychiatric research.

[4]  M. Griffiths,et al.  Environmental Research and Public Health Social Networking Sites and Addiction: Ten Lessons Learned , 2022 .

[5]  S. Grondin Timing and time perception: A review of recent behavioral and neuroscience findings and theoretical directions , 2010, Attention, perception & psychophysics.

[6]  A. Bechara,et al.  Examination of Neural Systems Sub-Serving Facebook “Addiction” , 2014, Psychological reports.

[7]  Matthieu J Guitton,et al.  Internet addiction assessment tools: dimensional structure and methodological status. , 2013, Addiction.

[8]  Erik Butler,et al.  Felt Time: The Psychology of How We Perceive Time , 2016 .

[9]  G. Dong,et al.  Impaired inhibitory control in ‘internet addiction disorder’: A functional magnetic resonance imaging study , 2012, Psychiatry Research: Neuroimaging.

[10]  Thaddeus Birchard CBT for Compulsive Sexual Behaviour: A guide for professionals , 2015 .

[11]  J. Perriot,et al.  Précarité sociale et perception du temps, impact sur le sevrage tabagique , 2011 .

[12]  P. Fraisse Perception and estimation of time. , 1984, Annual review of psychology.

[13]  Thomas R. Kirchner,et al.  Effects of smoking urge on temporal cognition. , 2005, Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors.

[14]  Yang-Han Lee,et al.  Time distortion associated with smartphone addiction: Identifying smartphone addiction via a mobile application (App). , 2015, Journal of psychiatric research.

[15]  PEI-LUEN PATRICK RAU,et al.  Time Distortion for Expert and Novice Online Game Players , 2006, Cyberpsychology Behav. Soc. Netw..

[16]  Hamed Qahri Saremi,et al.  Problematic Use of Social Networking Sites: Antecedents and Consequence from a Dual-System Theory Perspective , 2016, J. Manag. Inf. Syst..

[17]  Shalini Chandra,et al.  Technostress creators and job outcomes: theorising the moderating influence of personality traits , 2015, Inf. Syst. J..

[18]  C. S. Andreassen,et al.  Development of a Facebook Addiction Scale , 2012, Psychological reports.

[19]  Omar Rosas,et al.  Compulsive Use of Social Networking Sites in Belgium: Prevalence, Profile, and the Role of Attitude Toward Work and School , 2014, Cyberpsychology Behav. Soc. Netw..

[20]  M. Griffiths,et al.  The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study. , 2016, Psychology of addictive behaviors : journal of the Society of Psychologists in Addictive Behaviors.

[21]  Alexander Serenko,et al.  Integrating Technology Addiction and Use: An Empirical Investigation of Online Auction Users , 2011, MIS Q..

[22]  M. Paulus,et al.  Decision making, impulsivity and time perception , 2008, Trends in Cognitive Sciences.

[23]  Ofir Turel,et al.  Excess social media use in normal populations is associated with amygdala-striatal but not with prefrontal morphology , 2017, Psychiatry Research: Neuroimaging.

[24]  M. Griffiths,et al.  ‘Internet Addiction’: A Critical Review , 2006, International Journal of Mental Health and Addiction.

[25]  Ofir Turel,et al.  A Triadic Reflective-Impulsive-Interoceptive Awareness Model of General and Impulsive Information System Use: Behavioral Tests of Neuro-Cognitive Theory , 2016, Front. Psychol..

[26]  W. Bickel,et al.  Predictors of delay discounting among smokers: education level and a Utility Measure of Cigarette Reinforcement Efficacy are better predictors than demographics, smoking characteristics, executive functioning, impulsivity, or time perception. , 2015, Addictive behaviors.

[27]  Alexander Serenko,et al.  The benefits and dangers of enjoyment with social networking websites , 2012, Eur. J. Inf. Syst..

[28]  Jian-hua Wang,et al.  Energy Reduction Effect of the South-to-North Water Diversion Project in China , 2017, Scientific Reports.

[29]  M. Griffiths,et al.  Problematic Social Media Use: Results from a Large-Scale Nationally Representative Adolescent Sample , 2017, PloS one.

[30]  Ofir Turel,et al.  Social Networking Site Use While Driving: ADHD and the Mediating Roles of Stress, Self-Esteem and Craving , 2016, Front. Psychol..

[31]  D. Karaiskos,et al.  P02-232 - Social Network Addiction : a New Clinical Disorder? , 2010, European Psychiatry.

[32]  Taiki Takahashi,et al.  Psychophysics of time perception and intertemporal choice models , 2008 .

[33]  A. Bechara,et al.  Brain anatomy alterations associated with Social Networking Site (SNS) addiction , 2017, Scientific Reports.

[34]  J. Erblich,et al.  Reward dependence moderates smoking-cue- and stress-induced cigarette cravings. , 2014, Addictive behaviors.