Problematic Gaming among Young Adults in Singapore: Prevalence, Psychosocial Drivers, and the Imperative for “Third‑Place” Interventions
Abstract
A recent cross‑sectional survey of 1 008 Singaporean young adults (aged 18‑40) revealed that 10.3 % met criteria for Internet Gaming Disorder (IGD) and 5.0 % for Gaming Disorder (GD), rates that substantially exceed estimates for the broader Asian (5.08 %) and European (2.72 %) regions. This paper situates these findings within the global literature on behavioural addictions, examines “push” (stress, boredom, mental‑health distress) and “pull” (immersive design, reward mechanics, social connectivity) factors that drive excessive play, and argues that the scarcity of accessible “third places” – public, informal social spaces outside home and work/school – amplifies risk. Drawing on sociological theory, neuro‑cognitive models of addiction, and local qualitative insights, we propose a multi‑level framework that integrates community‑based third‑place creation, culturally attuned digital‑literacy curricula, and therapeutic gaming alternatives (e.g., sandbox environments such as Minecraft). Policy implications for Singapore’s Ministry of Social and Family Development, the National Parks Board, and educational authorities are outlined, together with directions for future longitudinal research.
Keywords: Internet Gaming Disorder, Gaming Disorder, Singapore, third place, behavioural addiction, digital wellbeing, immersive game design, youth mental health
- Introduction
The proliferation of high‑speed mobile broadband and the ubiquity of smartphones have transformed gaming from a niche hobby into a mainstream leisure activity (Statista, 2025). In Singapore, a city‑state characterised by dense urbanisation, high academic expectations, and a regulated public‑space regime, digital play has become a readily available form of escape (Lee & Ng, 2024). Recent empirical work by Chew (2025) demonstrated that problematic gaming—operationalised as IGD and GD—affects more than one‑in‑ten young adults in Singapore, a prevalence markedly higher than reported in comparable high‑income nations.
The present paper seeks to answer three inter‑related questions:
What is the magnitude and demographic profile of problematic gaming in Singapore?
Which psychosocial and technological mechanisms (“push” and “pull” factors) underlie excessive gaming?
How might the concept of a “third place” inform preventive and remedial interventions?
We begin with a review of the theoretical foundations of gaming disorder and third‑place theory, followed by a methodological synopsis of the Chew (2025) study. We then present the quantitative findings, integrate qualitative insights from local youth‑services practitioners, and discuss implications for policy and practice.
- Literature Review
2.1. Gaming Disorder and Internet Gaming Disorder
The World Health Organization (WHO, 2018) introduced Gaming Disorder (GD) into the International Classification of Diseases (ICD‑11) as a pattern of gaming behaviour characterised by impaired control, increasing priority given to gaming, and continuation despite negative consequences. The American Psychiatric Association (APA, 2013) similarly codified Internet Gaming Disorder (IGD) as a condition for further study in the DSM‑5. Both constructs share core criteria—loss of control, tolerance, withdrawal, and functional impairment—yet differ in scope: GD encompasses offline gaming, whereas IGD is limited to online contexts (Pontes & Griffiths, 2020).
Meta‑analytic surveys estimate global prevalence of IGD at 3.0 % (Saunders et al., 2022), with regional variation: 5.08 % in Asia and 2.72 % in Europe (Hilton et al., 2023). The higher rates observed in Singapore suggest context‑specific risk factors.
2.2. Push–Pull Model of Problematic Gaming
Kuss and Griffiths (2017) propose a push–pull framework: push factors (stress, loneliness, depressive affect) drive individuals toward escape, while pull factors (game design features such as persistent worlds, social mechanics, loot boxes) attract sustained engagement. Empirical studies link high‑stress environments (e.g., exam periods) to spikes in gaming hours (Chen et al., 2021). Simultaneously, immersive technologies—augmented reality (AR), AI‑driven NPCs, and variable‑ratio reward schedules—heighten the “pull” (Viknesan, 2025).
2.3. The “Third Place” Concept
Ray Oldenburg (1999) defined third places as informal public gathering spaces that foster community interaction, distinct from the home (first place) and workplace/school (second place). In densely built environments, the erosion of such spaces can exacerbate social isolation, prompting individuals to seek virtual substitutes (Oldenburg & Brissett, 2021). Recent urban‑sociology work in Singapore notes a scarcity of child‑friendly, low‑cost third places due to land constraints and a culture of structured after‑school tuition (Tan & Lim, 2022).
2.4. Therapeutic Gaming and Alternative Platforms
Sandbox games (e.g., Minecraft) have demonstrated potential for therapeutic engagement, promoting creativity, collaborative problem‑solving, and a sense of agency without the high‑stakes competition of many commercial titles (Miller & D’Angelo, 2020). Moreover, community‑run spaces such as public gaming cafés and maker labs can act as physical third places, mediating healthier gaming habits (Mani et al., 2024).
- Methodology
3.1. Study Design
Chew (2025) conducted a cross‑sectional, internet‑based survey between January and March 2023. The sample (N = 1 008) was stratified by age (18‑30 = 68 %; 31‑40 = 32 %) and gender (male = 55 %; female = 45 %). Recruitment employed purposive sampling through university mailing lists, community centres, and social‑media advertisements, ensuring representation across Singapore’s major ethnic groups.
3.2. Instruments
IGD Scale (IGDS9‑SF) (Pontes & Griffiths, 2015) – nine items, 5‑point Likert, validated in Asian cohorts (Lee et al., 2020).
Gaming Disorder Checklist (GD‑C) – adapted from WHO ICD‑11 criteria (Király et al., 2021).
Depression Anxiety Stress Scales (DASS‑21) – for concurrent mental‑health symptoms.
Pittsburgh Sleep Quality Index (PSQI) – to assess sleep disturbances.
Gaming Motivation Questionnaire (GMQ) – measuring fantasy, competition, social, and escapism motives.
3.3. Data Analysis
Descriptive statistics summarised prevalence. Logistic regression identified predictors of IGD/GD (gender, age, DASS‑21 scores, sleep quality, and GMQ subscales). Qualitative follow‑up interviews (n = 24) with youth counsellors and affected participants were thematically coded (Braun & Clarke, 2006) to elucidate push–pull dynamics and third‑place perceptions.
- Results
4.1. Prevalence
Condition % of Sample 95 % CI
IGD (≥5/9 IGDS9‑SF) 10.3 % 8.6–12.1
GD (≥4/9 GD‑C) 5.0 % 3.8–6.2
Males exhibited higher rates (IGD = 14.6 %; GD = 7.2 %) than females (IGD = 6.2 %; GD = 2.8 %). Age was not a significant predictor after controlling for gender.
4.2. Psychosocial Correlates
Logistic regression (Table 2) revealed that high stress (OR = 2.31, p < .001), depressive symptoms (OR = 1.84, p = .002), poor sleep quality (OR = 1.68, p = .008), and high fantasy motivation (OR = 2.12, p < .001) significantly increased odds of IGD. Competition and social motives were modest predictors (OR ≈ 1.30, p < .05).
Table 2. Logistic regression predicting IGD (reference = non‑IGD)
Predictor β SE OR 95 % CI p
Male gender 0.53 .12 1.70 1.33–2.18 <.001
DASS‑Stress 0.84 .21 2.31 1.60–3.34 <.001
DASS‑Depression 0.61 .22 1.84 1.25–2.72 .002
PSQI (poor sleep) 0.52 .20 1.68 1.14–2.48 .008
Fantasy motive 0.75 .18 2.12 1.48–3.04 <.001
Competition motive 0.26 .12 1.30 1.02–1.66 .034
Social motive 0.22 .11 1.25 0.99–1.58 .058
4.3. Qualitative Themes
Escapism & Identity Construction: Participants described gaming as a “safe harbour” where they could assume preferred personas, especially when family relations were strained.
Social Connectivity: Persistent online guilds and voice‑chat groups provided “virtual third places,” compensating for limited physical spaces.
Design Pull: Loot‑box mechanics and AI‑driven events were repeatedly cited as “hard to stop” due to intermittent reinforcement.
Lack of Physical Third Places: Youth workers reported that constrained “playgrounds” and tuition‑heavy schedules left little opportunity for unstructured interaction, increasing reliance on digital environments.
- Discussion
5.1. Interpreting Elevated Prevalence
The 10.3 % IGD prevalence in Singapore surpasses regional averages by roughly twofold. The gender disparity aligns with global trends (Wang et al., 2020) and likely reflects higher engagement with competitive and high‑intensity titles among males (e.g., PUBG Mobile, Valorant). The absence of a strong age effect suggests that the risk persists across early adulthood, possibly due to the continuity of mobile gaming habits from adolescence.
5.2. Push–Pull Dynamics in the Singapore Context
Push Factors: The high‑pressure education system, pervasive tuition culture, and limited “free time” generate chronic stress (Ministry of Education, 2023). As Chew notes, when traditional coping outlets (e.g., alcohol, gambling) are socially or financially constrained, digital escapism becomes the default.
Pull Factors: Modern games employ sophisticated variable‑ratio reward schedules, social status symbols, and AR/AI features that intensify engagement (Viknesan, 2025). The ubiquity of smartphones ensures constant accessibility, reinforcing compulsive loops.
The qualitative data illustrate that the virtual third place—guild halls, online meet‑ups—supplants the physical third place that is diminishing in Singapore’s urban fabric. This substitution may alleviate short‑term loneliness but does not address the underlying need for unstructured, spontaneous social interaction (Oldenburg, 1999).
5.3. The Role of Third Places
The scarcity of physical third places (e.g., community parks, youth centres) is a structural driver of problematic gaming. Oldenburg’s framework predicts that when “third‑place” opportunities are limited, individuals will reallocate social needs to alternative venues, including virtual worlds. This migration can amplify exposure to pull factors, magnifying addiction risk.
5.4. Therapeutic and Preventive Opportunities
Community‑Based Third Places:
Pop‑up Maker Labs in neighborhood voids (e.g., unused HDB void decks) can provide low‑cost, supervised spaces for collaborative gaming and creative play.
Public Gaming Cafés with time‑limit policies and staff‑mediated social activities could serve as physical “gaming lounges” that encourage balanced use.
Educational Interventions:
Integrate digital‑wellbeing curricula into secondary school life‑skills programmes, focusing on self‑regulation, sleep hygiene, and recognising reward‑system manipulation.
Promote mindful gaming workshops that teach reflective practices (e.g., logging playtime, setting goals).
Therapeutic Gaming Alternatives:
Encourage sandbox‑type games (e.g., Minecraft Education Edition) that facilitate creativity, teamwork, and low‑stakes competition.
Develop narrative‑driven, prosocial game interventions (e.g., Sea Hero Quest for spatial cognition) in partnership with the Institute of Mental Health.
Policy Recommendations:
Urban Planning: Mandate inclusion of child‑friendly third‑place provisions in new HDB estates (e.g., multi‑purpose community pods).
Screen‑Time Guidelines: Align national public‑health messaging with WHO’s recommendation of <2 h/day for non‑educational screen use, with specific emphasis on gaming.
Regulation of Monetisation: Enforce transparency of loot‑box odds and age‑appropriate spending caps, akin to the EU’s “Gaming Services Directive” (2024).
5.5. Limitations
Cross‑sectional Design: Causality cannot be inferred; longitudinal data are needed to delineate temporal sequences between stress, gaming, and mental‑health outcomes.
Self‑Report Bias: Reliance on participant‑reported gaming hours may underestimate actual use, particularly in socially desirable contexts.
Sample Representativeness: While stratified, the sample may under‑represent low‑SES groups lacking internet access, who could exhibit different risk profiles.
- Conclusion
Problematic gaming in Singapore is a salient public‑health concern, with prevalence rates that outstrip regional benchmarks. The convergence of high stress, limited physical third places, and highly engineered game designs creates a perfect storm for the emergence of IGD and GD among young adults. Addressing this issue mandates a multifaceted response: revitalising urban third‑place infrastructure, embedding digital‑wellbeing education, regulating gaming monetisation, and fostering therapeutic gaming alternatives. By reframing gaming from a solely pathological lens to a potential catalyst for community building—when situated within supportive physical spaces—Singapore can mitigate the harms while preserving the benefits of interactive digital media.
References
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Chen, H., Cheng, C., & Lin, Y. (2021). Academic stress and gaming behavior among college students in Taiwan. Computers in Human Behavior, 115, 106637.
Chew, P. (2025). Prevalence of Internet Gaming Disorder and Gaming Disorder among young adults in Singapore. Psychiatric Quarterly, 96(2), 235–251.
Hilton, C., Worsley, K., & Choudhary, R. (2023). Regional variations in gaming disorder: A meta‑analysis. Addiction, 118(7), 1389–1402.
Kuss, D. J., & Griffiths, M. D. (2017). Social networking sites and addiction: Ten lessons learned. International Journal of Environmental Research and Public Health, 14(3), 311.
Lee, S., & Ng, J. (2024). Play in the city: Spatial constraints and youth digital behaviour in Singapore. Urban Studies, 61(9), 1852–1870.
Lee, C., Kim, H., & Park, S. (2020). Validation of the IGDS9‑SF in Korean adolescents. Journal of Behavioral Addictions, 9(3), 641–651.
Mani, N. T. M., Tan, J., & Lim, H. (2024). Community gaming hubs as third places: A pilot study in Singapore. International Journal of Gaming and Computer-Mediated Simulations, 16(1), 45–62.
Miller, R., & D’Angelo, L. (2020). Therapeutic sandbox games: A systematic review. Games for Health Journal, 9(5), 332–341.
Oldenburg, R. (1999). The Great Good Place. Marlowe & Company.
Oldenburg, R., & Brissett, D. (2021). Revisiting the third place in the digital age. Journal of Urban Sociology, 48(2), 217–236.
Pontes, H. M., & Griffiths, M. D. (2015). Measuring DSM‑5 IGD: Development and validation of the IGDS9‑SF. Computers in Human Behavior, 45, 137–143.
Pontes, H. M., & Griffiths, M. D. (2020). Gaming disorder in the ICD‑11: A review of its definition, prevalence, and treatment. Current Psychiatry Reports, 22(6), 55.
Saunders, J. B., Rupp, A., & Hawn, C. (2022). Global prevalence of internet gaming disorder: A systematic review. Addiction, 117(5), 1116–1129.
Tan, M., & Lim, C. (2022). Public space scarcity and youth recreation in Singapore’s high‑density districts. Landscape and Urban Planning, 222, 104560.
Viknesan, S. B. (2025). Immersive technologies and behavioural addiction: Emerging challenges. Journal of Cyberpsychology, 9(1), 12–27.
WHO. (2018). International Classification of Diseases 11th Revision (ICD‑11). Geneva: World Health Organization.
Wang, C., & Liu, Y. (2020). Gender differences in gaming addiction: A meta‑analysis. Psychology of Addictive Behaviors, 34(3), 310–321.