Digital addiction increases loneliness, anxiety and depression, new study suggests

Electronic devices represent an important of most people’s lives, allowing us to stay connected  at all times. The downside of that convenience is that many of us are also addicted to the constant pings, chimes, vibrations and other alerts from our devices, unable to ignore new emails, texts and images. In a new study published in NeuroRegulation, San Francisco State University Professor of Health Education Erik Peper and Associate Professor of Health Education Richard Harvey argue that overuse of smart phones is just like any other type of substance abuse.

International Conference on Behavioral Addiction 23-25 April 2018

The  Conference on Behavioral Addiction held in Cologne, Germany from the 23rd to the 25th of April 2018 represented a great opportunity to get an overview of the latest research results on non-substance related addiction. Experts in the field of behavioral addictions presented their work related to problematic internet use, gambling and gaming addiction.

We selected the following studies in the field of Problematic internet Use and  Social media addiction.

Social media addiction

10 lessons learned DARIA KUSSInternational Gaming Research Unit, Psychology Department, Nottingham Trent University, Nottingham, UK; E-Mail:

Social media have gained increasing popularity in the last decade, allowing users to connect with others who share similar interests. The perceived need to be online may result in compulsive use of social media, and in some cases this can lead to symptoms and consequences traditionally associated with substance-related addictions. This talk will outline our current knowledge of social media addiction by referring to ten lessons learned from recent empirical research on the topic. These ten lessons include the following: (1) social networking and social media are not the same; (2) social networking is eclectic; (3) social networking is a way of being; (4) individuals can become addicted to social media; (5) Facebook addiction is only one example of social media addiction; (6) fear of missing out (FOMO) may be part of social media addiction; (7) smartphone addiction may be part of social media addiction; (8) nomophobia may be part of social media addiction; (9) there are sociodemographic differences in social media addiction; and (10) there are methodological issues with current research on social media addiction. Implications for research and treatment will be discussed.


Understanding Internet addiction disorder 20 years later

KIMBERLY S. YOUNG Center for Internet Addiction, Russell J. Jandoli School of Journalism and Mass Communication, St. Bonaventure University, Olean, NY, United States; E-Mail:

This presentation examines the changes in Internet addiction disorder (IAD) over the past 20 years since it was first identified in 1995. It gives a broad background of the history and growth of this rapidly evolving field. As a new disorder, symptoms and subtypes of IAD will be discussed along with validated assessment tools such as the IAT that measure the condition in terms of mild, moderate, and severe symptoms. The presentation also explores evidenced-based treatments such as CBT-IA and addresses the next digital generation impacted by addictive use of technology and the Internet. As schools have rushed to supply their classrooms with computers, children often have unlimited and encouraged access to technology; therefore, this presentation describes the social, cognitive, and academic problems that result from children and adolescents who spend excessive time in front of screens. This presentation looks at new concerns about how young is too young for children to go online and strategies that some schools are using to focus on prevention and how they are adapting policies to be “screen smart”.


A study on the relationship between personality factors and internet addiction among young adults


Background and aims: Problematic internet addiction or excessive internet use has become more and more common worldwide, yet, there are few systematic studies on personality traits that are associated with internet addiction. The aim of the current study was to investigate the relationship between internet addiction and personality using the five-factor model of personality traits. Methods: Participants were 247 adults mean age 26.43 years, 188 males and 71 females, who used the internet at least three times a day. They filled in a demographic questionnaire, the Big Five Inventory, and Young’s Internet Addiction Scale (IAT). Results: There were no differences between male and females on IAT scores. Multiple regression analysis revealed that big-five personality factors contributed significantly to ratings of inter- net addiction and explained 16% of the variance. While neuroticism, agreeableness and con- scientiousness significantly contributed to the variance of excessive internet use, extraversion and openness did not. Conclusions: This study extends our knowledge regarding the factors that contribute to problematic internet use. Individuals who are prone to be more neurotic, less agreeable and less conscientiousness are more addicted to the internet. This evidence supports previous evidence for the contribution of personality factors to the manifestation of problematic internet use.


Internet-communication disorder:
The role of emotional competence, neuroticism, and expectancies


*General Psychology: Cognition and Center for Behavioral Addiction Research (CeBAR), University of Duisburg-Essen, Duisburg, Germany; E-Mail:

Background: Using online-communication applications excessively despite negative conse- quences is referred to as Internet-communication disorder (ICD). Recent theoretical models assume personal predispositions (e.g. neuroticism), affective responses, and cognitions (e.g. expectancies) to interactively predict specific Internet-use disorders. Empirical studies illus- trated that expectancies mediate the effect of predispositions on ICD. Furthermore, specific competences emerged to be important mediators, particularly in a preventive manner. To inves- tigate further protective mechanisms mediating the effect between predispositions and ICD, this study additionally focuses on emotional competences, namely regulation/control of one’s emotions (RCE). Methods: Participants (N = 211) answered the short-Internet-Addiction-Test, the Internet-Use-Expectancies-Scale (both modified for Internet-communication), and ques- tionnaires assessing neuroticism and RCE. Results: The structural equation model shows that RCE predicts ICD, which is partially mediated by avoidance-expectancies. Furthermore, RCE fully mediated the effect of neuroticism on ICD. Hence, the whole model indicated a full me- diation path between neuroticism, RCE, avoidance-expectancies and ICD, explaining 29.5% of ICD symptoms’ variance. Conclusions: The results illustrate that individuals with neurotic tendencies and diminished abilities to regulate/control emotions show higher expectancies to avoid negative feelings online, which in turn predicts higher ICD tendencies. This emphasizes the importance of improving specific competences, particularly self-regulative competences, to prevent from an excessive use of online-communication applications.


Problematic internet use and associated disorders among college students in France


Introduction: The objectives of the study were to identify the prevalence of Problematic in- ternet use (PIU) and associated non substance use disorder among college students in France. Methods: A cross-sectional study was conducted in Rouen (France). The students filled our a self-questionnaire: smoking, alcohol consumption (AUDIT test and binge drinking), eat- ing disorders (SCOFF), gambling disorder (ICJE), online compulsive buying (Echeburua), hyperactivity disorder (ARSR and WURS) and socioeconomic data. PIU was assessed by the Internet Addiction Test. Results: A total of 1044 college students were included (68,6% of fe- male) with a mean age of 20.7 years (Standard Deviation = 4.1). Prevalence of PIU was 4.7%, 95% CI (2.8-5.2). Among the sample, 5.7% of students have a hyperactivity disorder, 5.0% a moderate or high gambling, 4.2% a food addiction and 13.2% a online compulsive buying. After multivariate analysis, PIU was significantly associated with male gender (AOR=1.60; p<0.001), hyperactivity disorder (A0R = 3.57; p<0.0001), gambling (AOR = 2.21; p<0.001), eating disorder (AOR = 2.66; p<0.0001) and online compulsive buying (AOR = 2.38; p<0.001). Discussion: College students are affected by PIU. The associations between psy- chiatric disorders and PIU indicate that the evaluation of a university student presenting PIU should include a careful assessment of comorbid psychiatric disorders


Non-problematic, risky and problematic internet use of Swiss youths


Swiss youths use digital media more and more intense as the JAMES-study shows (Waller, Willemse, Genner, Suter & Süss, 2016). The JAMES-studies are conducted every other year since 2010 and survey the media use of Swiss 12 to 19 year olds in a representative sample. In addition to the questions about their regular media use, in 2016 the 1`049 youths filled out the short version of the internet addiction scale (sIAT) (Brand, Laier & Young, 2014). This allowed to get a prevalence rate of non-problematic (80%), risky (11.5%), problematic/ pathological (8.5%) internet use and to see how these three groups can be described in de- mographic aspects and in their behavior online and offline. There were no significant differ- ences between demographic subgroups. Neither were there differences in the offline leisure activities. Youths with a risky or problematic internet use used their smartphones and tablets significantly more than the other 80%, especially with audiovisual contents. They also played significantly more videogames. Problematic and risky internet users were significantly more often victims of cyberbullying and consumed and distributed more violent media content than the non-problematic Internet users. Some protective factors were identified: Playing music, painting and spending time with pets but also reading newspaper.


Facebook addiction – the role of the self-system components


University of Warmia and Mazury in Olsztyn, Poland; E-Mail:

Background: The self can be treated as a system with several components which interact mutually and determine a person’s functioning. In presented research it was assumed that self- system components and their specific profiles may be responsible for presence of Facebook addiction (FA) symptoms. Methods: The self-system components were measured with: the Self-Concept Clarity Scale, the Social Self-Esteem Inventory, the Self-Regulation Questionnaire and the Self-Monitoring Scale. FA was assessed with the Scale of Excessive Use of So- cial Networking Sites. The study included 576 Facebook users (university students and high school pupils, mean age 18.94 years, 52.43% of women). Results: The model verified by the linear regression analysis was significant (R2 = 0.13). FA was predicted significantly by two self-system components: self-regulation and self-concept clarity, and social role of a pupil. Three groups of Facebook users were extracted in the cluster analysis: (1) strong self-system without FA, (2) weak self-system with FA, (3) weak self-system without FA. Conclusions: Further studies on different self-system components are needed for better understanding their relation to FA and its dynamics.

Hooked: How to Build Habit-Forming Products by Nir Eyal

This book explains how different apps have been designed to be addictive. The more time we use them, the more personal information we give to be used for commercial purposes or to influence our political choices.

“The tech industry needs a new ethical bar. Google’s motto, “Don’t be evil,” is too vague. The Golden Rule, “Do unto others as you would have them do unto you,” leaves too much room for rationalization.

I’d argue that what we ought to be saying is, “Don’t do unto others what they would not want done to them.” But how can we know what users do and don’t want?

I humbly propose the “regret test.”

…If users would regret taking the action, the technique fails the regret test and shouldn’t be built into the product, because it manipulated people into doing something they didn’t want to do. Getting people to do something they didn’t want to do is no longer persuasion — it’s coercion.

So how do we tell if people regret using a product? Simple! We ask them.”