Gaming Disorder Across the Lifespan: A Scoping Review of Longitudinal Studies

Abstract

Gaming disorder is a mental disorder characterized by impaired control over gaming behaviors resulting in the escalation of gaming despite significant negative consequences and functional impairments. Although research efforts investigating gaming disorder are expanding, there is a need conceptualize this disorder from a developmental framework to identify trajectories of this disorder across the lifespan. This scoping review aims to synthesize empirical evidence for the development of gaming disorder. The search of four databases led to the identification of 57 eligible studies identifying antecedents (n = 33), consequences (n = 24), and variables having reciprocal relationships with GD (n = 9). The temporal stability of GD differed based on age and study duration, ranging from 20% to 84%. Commonly reported risk factors for GD include emotion dysregulation and negative self-esteem, with depressive symptoms, inattentive symptoms and social isolation being reciprocally associated with GD. Consequences of GD include increases in anxiety, poor parental relationships and decreases in life satisfaction and academic performance. Overall, results from this review suggests that various psychosocial factors interact to influence the development of GD across the lifespan, while certain consequences may maintain GD symptomatology.

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Gaming Disorder Across the Lifespan: A Scoping Review of Longitudinal Studies
Jérémie Richard, Caroline Temcheff, & Jeffrey Derevensky
International Centre for Youth Gambling Problems and High-Risk Behaviors, Department of Educational and Counselling
Psychology, McGill University, Montreal, Quebec, Canada
BACKGROUND DISCUSSION & IMPLICATIONS
OBJECTIVES
Contact: jeremie.richard@mail.mcgill.ca
Richard, J., Temcheff, C., & Derevensky, J. (2020).
Gaming disorder across the lifespan: A scoping review
of longitudinal studies. Current Addiction Reports 7(4),
561-587. doi:10.1007/s40429-020-00339-3
Gaming disorder (GD): a pattern of persistent or recurrent
gaming behavior over at least 12 months, characterized by
impaired control over gaming behaviors, increasing priority
given to gaming, and a continuation/escalation of gaming
despite negative consequences (WHO, 2019)
Prevalence rates of GD: 0.7% to 27.5% globally, greater rates of
GD among youth [2]
GD as progressive and differing developmentally [3-7]
Four developmental models of GD:
1. Benarous and colleagues (2019) internalized and externalized
pathway to GD from childhood to early adulthood
2. Lee, Lee, and Choo (2017) typology of GD based on the
pathways model for problem gambling: (1) socially conditioned,
(2) emotionally vulnerable, & (3) impulsive/aggressive
3. Paulus and colleagues (2018) integrated model of internal
(e.g., structural brain differences, inattention, impulsivity) and
external (e.g., peer/familial influences, game-related) predictors
of GD
4. Brand and colleagues (2016; 2019) Interaction of Person-
Affect-Cognition-Execution (I-PACE) model of addictive
behaviors: predisposing characteristics interact with affective,
cognitive and executive processes to predict GD
Objectives
(1) Identify and evaluate longitudinal evidence for the temporal
trajectories, risk factors and consequences of GD across the lifespan
(2) Evaluate existing developmental models of GD
(3) Synthesize evidence into comprehensive conceptual model
Research Questions
(i) What is the temporal stability of GD?
(ii) What are risk factors/antecedents of GD?
(iii) What are the consequences/outcomes of GD?
(iv) What factors have reciprocal relationships with GD across time?
n
SELECTED REFERENCES
LITERATURE REVIEW
Inclusion Criteria
1. Peer-reviewed (EN/FR)
2. Longitudinal studies; > 1 timepoint
3. Include problem/disordered
gaming as dependent variable (DV)
4. Any bio-psycho-social predictor of
problem/disordered gaming
Database Search
PsychINFO, MEDLINE,
PubMed & Scopus
Articles published between
January 2000 and January 2020
Keywords
A. “video game”; “problem* use of video games”; “problem* video game use”;
“problem* gaming”; “excessive gaming”; “internet gaming disorder”; “gaming
disorder”; “video game addiction”; “gaming addiction”
B. (biological keywords) OR (neurological keywords) OR (cognitive keywords) OR
(psychological and emotion-related keywords) OR (addiction and substance use
keywords) OR (social and environmental keywords) OR (demographic keywords) OR
(psychopathological and temporal keywords) OR (method keywords)*
Identification
Records identified through database
searching (n = 4578)
Duplicate Removal
Records kept after duplicates removed
(n = 4215)
Title/Abstract Screening
Number of articles excluded (n = 4095)
Number of articles included (n = 120)
Final Inclusion
57 studies included in the final qualitative synthesis
Full-Text Exclusion (n = 63)
Literature reviews (n = 22)
Treatment studies (n = 28)
General Internet use/addiction (n = 8)
Gaming without GD measure (n = 2)
Questionnaire development (n = 1)
Combination of other behavioral addictions (n = 1)
Neurological comparison (n = 1)
Longitudinal findings provide mixed evidence for each
developmental model
Certain theoretically established predictors of GD
have not been investigated longitudinally (e.g.,
attachment style, childhood adversity, substance use)
Limited attempts to map the developmental processes
and age-based trajectories of these various factors
across the lifespan
Suggestions for future research:
•Replication studies based on consistent and
psychometrically sound measurement tools
•Longitudinal research across time periods > 5 years
•Research in populations > 40 years of age
Practical implications:
•Developmentally appropriate treatment and
prevention initiatives
•Clinical utility in assessment, case conceptualization,
treatment planning and decision making
1. World Health Organization. (2019). International statistical classification of diseases and related health problems (11th Revision).
https://icd.who.int/browse11/l-m/en
2. Kuss, D. J., & Griffiths, M. D. (2012). Internet gaming addiction: A systematic review of empirical research. Int J Ment Health Addict, 10(2),
278-296.
3. Feng, W., Ramo, D. E., … Bourgeois, J. A. (2017). Internet gaming disorder: Trends in prevalence 1998-2016. Addict Behav, 75, 17–24.
4. Loeber, R., Farrington, D., … van Kammen, W. (1998). Multiple risk factors for multi-problem boys: Co-occurrence of delinquency,
substance use, attention deficit, conduct problems, physical aggression, covert behavior, depressed mood, and shy/withdrawn behavior. In: R.
Jessor (Ed.), New perspectives on adolescent risk behavior (pp. 90-149). New York, NY, US: Cambridge University Press.
5. Benarous, X., Morales, P., … Cohen, D. (2019). Internet gaming disorder in adolescents with psychiatric disorder: Two case reports using a
developmental framework. Front Psychiatry, 10(336). doi:10.3389/fpsyt.2019.00336
6. Lee, S.-Y., Lee, H. K., & Choo, H. (2017). Typology of Internet gaming disorder and its clinical implications. Psych Clin Neuro, 71(7), 479-491.
7. Blaszczynski, A., & Nower, L. (2002). A pathways model of problem and pathological gambling. Addiction, 97(5), 487-499.
8. Paulus, F. W., Ohmann, S., … Popow, C. (2018). Internet gaming disorder in children and adolescents: A systematic review. Dev Med & Child
Neuro, 60(7), 645-659.
9. Brand, M., Wegmann, E., … Potenza, M. N. (2019). The Interaction of Person-Affect-Cognition-Execution (I-PACE) model for addictive
behaviors: Update, generalization to addictive behaviors beyond internet-use disorders, and specification of the process character of addictive
behaviors. Neuro Biobehav Rev, 104, 1-10.
10. Brand, M., Young, K. S., … Potenza, M. N. (2016). Integrating psychological and neurobiological considerations regarding the development
and maintenance of specific Internet-use disorders: An Interaction of Person-Affect-Cognition-Execution (I-PACE) model. Neuro Biobehav Rev,
71, 252-266.
RESULTS & CONCEPTUAL MODEL
Consultation of References
From review articles (n = 4)
From included articles (n = 1)
•Data collected from 13 countries (e.g., China, Netherlands, Australia, United States, Singapore, Germany, Norway…)
•49% of studies entirely or predominantly male; 51% representative of both males and females
•49% of studies sampled children and/or adolescents; 41% late-adolescent/emerging adult; 10% adults
•The temporal stability of GD ranged between 20% and 84% over periods ranging from one to five years
Comprehensive Conceptual Model for the
Development of GD
Across the lifespan, various biological, psychological
and social factors converge to influence GD.
Interactions between risk factors and outcomes across
developmental periods.