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Summary Notes Risk behavior Lecture 2
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College 2 - Risk behaviorPart 1: internet-related addictions among adolescents
The number of young people (18-25) that perceives themselves as being addicted to their
smartphone has increased from 19% in 2015 to 29% in 2017.
Chapter of Sussman: differentiation between substance addiction and behavioral addiction.
Gaming is an example of behavioral addiction, cannabis is an example of substance
addiction. The two biggest groups of seeking addiction care among adolescents is cannabis
and second game addiction.
DSM-5 (2013) introduced the categories “Substance-related and Addictive Disorders” and
“Non-substance-related disorders” (this category is also about behavioral addiction).
Gambling Disorder: only officially recognized condition in the DSM-5 subsection “Non-
substance-related disorders”. (the only behavioral addiction recognized as an addiction in
the DSM-5).
Internet Gaming Disorder included in the Appendix of the DSM-5 as a condition warranting
more clinical research before considering it as a formal disorder.
Since the DSM-5 recognition of behavioural addictions, there is an expanding body of
research classifying rather common behaviours as possible behavioural addiction.
Problem with this new category of “non-substance-related disorders”, hard to say which
behavior is indeed addictive. This development may be a threat to the credibility of the field
of behavioural addictions. There is also the risk of (over)pathologizing and stigmatizing
common behaviours.
Proposition of a new definition of behavioral addictions (Kardefelt-Winther et al., 2017)
Proposed definition: “Repeated behaviour leading to significant harm or distress of a
functionally impairing nature, which is not reduced by the person and persists over a
significant period of time.”
Is there sufficient empirical basis to regard gaming and social media use as potentially
addictive behaviors?
There is not enough knowledge to make causal assumptions. Because almost all studies are
cross-sectional, so the causality of the variables are not being researched.
Empirical state-of-the-art: Internet Gaming Disorder (IGD): Only three longitudinal studies:
two found that symptoms of IGD negatively affected psychosocial functioning (Gentile et al.,
2011; Lemmens et al., 2011). One found no significant effect.
Social Media Disorder (SMD): Few (only cross-sectional) studies Until now, no longitudinal
studies that investigated the impact of SMD! So no causal effect has been shown yet.
Digital Youth Project (uu)
Between 700 - 2000 participants (12-17 years) 5 annual measurements between 2015-2019,
, longitudinal study with online questionnaires in classroom setting. How do these adolescents
perceive themself? → 50% of the 12-16 year old adolescents perceive themselves
to be (at least a bit) addicted to social media. (DYP, 2018)
Four predictor variables
Intensity of use
1. Weekly hours spent gaming (2 items)
2. Frequency of social media use (on a daily basis) (6 items)
Symptoms of addictive use
3. Symptoms of Internet Gaming Disorder (9 items DSM-5 appendix; (Lemmens et al., 2015)
Appendix DSM-5 (2013): Internet Gaming Disorder: a condition warranting more clinical
research before considering it as a formal disorder. Meeting 5 or more criteria from 9 criteria
= disordered use.
4. Symptoms of Social Media Disorder (same 9 items; Van den Eijnden et al., 2016)
Internet Gaming Disorder and Social Media Disorder
• Loss of control / Persistence
• Preoccupation
• Conflict
• Withdrawal symptoms
• Escape / coping
• Tolerance
• Problems
• Deception
• Displacement
Outcome variables
Life satisfaction (7 items, SWSL, Diener et al., 1985)
• “I am satisfied with my life”
Perceived social competence (5 –items, CSBA; Harter, 1988)
• “I find it hard to get friends on whom I can count”
School grades (GPA’s as provided by schools)
• The average of the followed exam courses
Symptoms of internet game disorder predict a negative effect on the perceived social
competence and life satisfaction.
Small effect: social media usage has a positive effect on the perceived social competence
but a negative effect on their school grades.
Weekly hours gaming has a positive effect of perceived social competence.
Symptoms of Social Media Disorder has a negative effect on the life satisfaction. (And a
negative effect on school grades for girls only).
Conclusions
- Intensity of game and social media use: small effects, both positive and negative.
- Symptoms of Internet Gaming Disorder and Social Media Disorder both seem to
have serious negative implications for adolescents’ psychosocial functioning.
- IGD: less socially skilled, more lonely/ isolated.
- SMD: less happy (strong effects).
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