Social Networking Addiction – Is Excessive Use of the Internet and Social Media a Behavioural Addiction?

SOCIAL MEDIA AND SOCIAL NETWORKING

Social media or SNS addiction is not listed in the Diagnostic and Statistical Manual of Mental Disorders, 5^th edition, (DSM-V) or the International Classification of Diseases, 11th edition. Therefore, caution is advised as substantial evidence is not currently available. The absence of established definitions also hampers guidance to diagnosis and management strategies.

• Internet Use Disorder was considered for the DSM-V; however, only Internet Gaming Disorder was included in the DSM-V (section 3).
• Read more on Internet Addiction Disorder.

Although social media or SNS addiction are not listed in the DSM-V, the literature already includes the following terms: social networking addiction, social media addiction, and social media disorder, along with the more specific terminologies of Facebook dependence, Facebook addiction disorder, and Twitter addiction.

In addition, social media and social networking terminologies tend to be used interchangeably in the literature, even though there are nosological differences. In brief, social networking can be considered to be a subset of social media [Kuss and Griffiths, 2017]:

• Social media sites – Where users can produce, share and collaborate on user content. e.g. YouTube, Wikipedia, and Second Life.
• Social networking sites – Virtual communities where users have an individual public profile and can engage in social networking connections, e.g. Facebook, Instagram, and Snapchat.

To further complicate these definitions, Facebook has grown to be more than just an SNS with a range of social media activities now available.

Therefore, for this article, we will refer to SNS addiction as the definitional parameter of social networking but with the caveat that labelling it as an addiction encompasses compulsion and problematic use.

SOCIAL NETWORKING SITE (SNS) ADDICTION

Engagement in excessive social networking has been suggested to be mediated by the fear of missing out (FOMO), smartphone addiction, and nomophobia (irrational fear of being without your mobile phone). [Bragazzi and Del Puente 2014]; [Oberst et al, 2017]

These specific constructs may help explain the link between SNS addiction and its psychopathological consequences; however, the causal relationship between these constructs and an established theoretical model requires further study.

From a clinical perspective, SNS addiction had been suggested to be based on either a social skill model, a cognitive-behavioural model, or a socio-cognitive model [Turel and Serenko, 2012]:

• Social skill model – Individuals use SNS for social networking rather than face-to-face, possibly due to those individuals having low self-presentation skills.
• Cognitive-behavioural model – The lack of executive control over motivational drives that are linked to reward-seeking can contribute to poor decision making to engage SNS.
• Socio-cognitive model – Social networking produces a positive outcome expectation, resulting in excessive use in the absence of self-regulation.

Alternatively, the more generalised biopsychosocial framework for SNS addiction states that SNS addiction results from a combination of mood modification, salience, tolerance, withdrawal symptoms, conflict and relapse. [Griffiths, 2005]

Neurobiology of SNS Use Disorder: 

Understanding the neurobiology of SNS use disorder would require extrapolation of research from internet use disorder (IUD) due to the scarcity of research specifically on the neurobiology of SNS Use Disorder.

IUD and SUD may share specific underlying neurobiological mechanisms with some differences. [Park et al. 2017]

IUD is associated with structural or functional impairments in the Orbitofrontal cortex (OFC), dorsolateral Prefrontal cortex (PFC), Anterior Cingulate Cortex (ACC), and PCC regions, which are involved in the processing of reward, motivation, memory, and cognitive control. In addition, IUD is also associated with impairment of dopamine D2 receptor function, associated with dysregulation in the OFC.

Adolescents are especially vulnerable due to an extended prefrontal cortex development time compared to that of the limbic system results in weakened inhibition from the side of the cortical regions toward underlying subcortical structures, resulting in more prominent impulsivity, which contributes to high-risk behaviour.  [Tereshchenko & Kasparov, 2019]

THE BERGEN FACEBOOK ADDICTION SCALE

There has been a substantial amount of research on addiction to Facebook specifically, which in the literature has been termed by some as Facebook Addiction Disorder (FAD). [Brailovskaia and Margraf, 2017]

Although there are other SNS addictions– particularly with photo sharing through Instagram – this emerging behavioural addiction is accurately defined by the typical characteristics of the biopsychosocial model. [Andreassen et al., 2012]; [Koc and Gulyagci, 2013]

The Bergen Facebook Addiction Scale (BFAS) is a relatively new psychometric tool that encompasses the biopsychosocial model and can investigate human behaviour associated with Facebook use. [Andreassen et al., 2012]

The scale covers six questions, and participants are to answer either (1) very rarely, (2) rarely, (3) sometimes, (4) often, and (5) very often. If a participant were to score often or very often on four out of the following six questions, then this would suggest that they are addicted to Facebook:

1. You spend a lot of time thinking about Facebook or planning how to use it.
2. You feel an urge to use Facebook more and more.
3. You use Facebook in order to forget about personal problems.
4. You have tried to cut down on the use of Facebook without success.
5. You become restless or troubled if you are prohibited from using Facebook.
6. You use Facebook so much that it has had a negative impact on your job/studies.

However, this scale is limited by its subjective self-reporting nature. For instance, a similar internet addiction questionnaire has been suggested to report a false positive up to 91% of the time. [Maraz et al., 2015]

Plus, given the multi-faceted nature of addictive behaviours, it seems unlikely that a simple description of its symptoms could recognise and conceptualise the dysfunctional nuances that cause the psychological distress of addiction. [Billieux et al., 2015]

Therefore, to improve accuracy and reproducibility, it has been recently proposed that a multidisciplinary team of academic clinicians and industrial partners need to work together on large-scale longitudinal studies. Of note, partners such as Facebook are being urged to share their increasingly large datasets through the Social Data Science Accelerator. [Przbylski, 2018]

SUMMARY

Social networking online is a highly prevalent activity that can have adverse mental health outcomes associated with addiction.

Based on currently available empirical evidence, excessive use of SNS suggests a link to symptoms that are characteristic of a substance use disorder.

However, in the absence of a DSM-V classification, more research is warranted to determine the compulsive traits, the types of activities, and the treatment interventions that may be effective.

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