Table 1.
Synthesis of relevant data collected from the studies included in the review
| Author/year | Type of study | Sample size (N), Gender (%), Mean age (SD) | Country and time | Time spent on gaming, M(SD) | Gaming assessment measure | Mental Health measures | COVID- 19-related measures | Prevalence | Main findings of the study |
|---|---|---|---|---|---|---|---|---|---|
| Balhara et al. (2020) | Cross-sectional study | 128 participants; 59.4% females; age: M = 19.6 (1.9) | India, during the lockdown | Increased gaming group: median = 2.5, IQR = 1.25-5 hours/day Not increased gaming group: median = 1, IQR = 0-1 hours/ day | Internet Gaming Disorder Scale Short Form-9 (IGDS9-SF) | Depression (PHQ-9); Anxiety (GAD-7) | COVID-19-related stress (non-validated VAS1 scale | A diagnosis of IGD could be made for 14.84% participants (20% and 9.52% for “increased” and “not increased” gaming groups, respectively). | No significant association between depression/anxiety and gaming increasing. Participants with moderateor- severe anxiety had an association with the change in gaming behavior. COVID- 19-related stress was not significantly different between those who increased and did not increase gaming. |
| Chang et al. (2022) | Cross-sectional study | 1,305 participants; 41.5% females; age: M = 15.16 (1.66) | China, June- July 2020 | N.R.2 | Internet Gaming Disorder Scale Short Form-9 (IGDS9-SF) | Depression, Anxiety, Stress (DASS-21) | N.R.2 | Normative Gamers (30.9%), Addictive Gamers (4.1%), Occasional Gamers (42.4%), Problematic Gamers (22.7%) | Compared to “normative gamers”, depression was associated with “addictive”, “occasional” and “problematic” classes. Anxiety was positively associated with “problematic” class. No significant associations between stress and gaming. |
| Chen et al. (2022) | Longitudinal study | 980 participants; 82.90% females; age: M = 34.76 (8.22) | China, November 2021– January 2022 | N.R.2 | Internet Gaming Disorder Scale Short Form-9 (IGDS-SF9) | Psychological distress (DASS- 21) | N.R.2 | N.R.2 | Positive association between psychological distress and problematic gaming. |
| Claesdotter- Knutsson et al. (2022) | Cross-sectional study | 1,501 participants; 48.5% females; age groups: 16-24 (16.4%), 25-39 (30.8%), 40-59 (32.1%), ≥60 (20.7%) | Sweden,Mar-21 | N.R.2 | Game Addiction Scale for Adolescents (GASA) | Psychological distress (Kessler- 6 scale) | Changes in personal behavior (e.g., alcohol consumption, exercise habits). | Addicted/problem gamers (6.4%), Engaged gamers (5.8%), No problem (87.8%) | The major increase of gaming was reported in the age group of 16-39 years. Psychological distress was associated with gaming increasing in all age groups analyzed together and in 25-39-year-old age group. Increased gaming was related to drinking less alcohol and exercising less. |
| Cudo et al. (2022) | Cross- sectional study | 652 participants; 35.7% females; age: M = 28.77 (7.18) | Poland, during the COVID-19 pandemic | N.R.2 | Internet Gaming Disorder Scale Short Form (IGDS-SF9) | Depressive symptoms (PHQ-9); loneliness (De Jong Loneliness Scale); selfcontrol (BSCS) | N.R.2 | N.R.2 | Positive relationship between depressive symptoms and gaming disorders. Positive relationship between loneliness and gaming disorders only for males. Negative relationship between self-control and gaming disorders. Motives for gaming mediate the relationship between depressive symptoms/selfcontrol and gaming disorder only for males |
| Elhai et al. (2021 | Cross- sectional study | 812 participants; 50.1% females; age: M = 44.45 (17.21) | United States and Canada, May 2020 | N.R.2 | GD test (GDT) | Health anxiety (SHAI) | N.R.2 | N.R.2 | Significant positive relationships were found between GD severity and health anxiety/perceived negative consequences of illness. |
| Fazeli et al. (2020) | Cross- sectional study | 1,512 participants; 43.6% females; age: M = 15.51 (2.75) | Iran, May – August 2020 | 68.12 (±39.83) minutes/day during weekends | Internet Gaming Disorder Scale- Short Form (IGDS9-SF) | Depression, anxiety, and stress (DASS- 21); Level of insomnia (ISI); Quality of life (PedsQLTM 4.0 SF15 | N.R.2 | #NAME? | IGD is positively associated with depression, anxiety, stress and insomnia, and negatively related to quality of life (adolescents reports). IGD indirectly influenced insomnia and quality of life through depression and anxiety |
| Fernandes et al. (2020) | Cross- sectional study | 185 participants; 65.76% females; age: M = 21.59 (2.60) | Mexico, India, Indonesia, Philippines, Malaysia, UK, During the pandemic | Before COVID-19: 0.73 (6.86) hours/ day; During COVID-19: 1.54 (2.13) hours/day | Game Addiction Scale (GAS) | UCLA Loneliness scale (ULS- 8); Depression (K10) | N.R.2 | N.R.2 | Higher score on gaming addiction is associated with higher score on depression and loneliness and lower scores on sleep quality |
| Formosa et al. (2022) | Two cross-sectional studies | Study 1: 212 participants; 39.6% females; age: M = 28.36 (9.14) Study 2: 329 participants; 22.5% females; age: M = 27.44 (8.49) | Australia, Canada; Study 1: December 2019 – March 2020; Study 2: April-June 2020 | Study 1: 15.48 (13.00) hours/week Study 2: 20.43 (14.89) hours/week | Both study 1 and 2: Addiction subscale of the Addiction- Engagement Questionnaire; Obsessive and Harmonious Passion scale. | Satisfaction with life (Satisfaction with Life scale); Subjective Vitality (Subjective vitality scale); Psychological distress (K6) | N.R.2 | N.R.2 | Prior to COVID-19, it seems passion for videogames influenced problematic game play but did not extend to more general well-being (satisfaction with life, vitality, psychological distress). In contrast, during COVID-19, people’s passion for videogame play is able to positively influence well-being (i.e. greater vitality, reduced psychological distress), even among players who may be engaged in games in a more obsessive and rigid manner. |
| Giardina et al. (2021) | 664 participants; 8.7% females; age: M = 23.59 (6.27) | Italy, February – March 2020 | Before COVID-19: 20.20 (16.3) hours/ week; During COVID-19: 22.51 (16.50) hours/ week; Overall: 21.47 (16.46) hours/week | Internet Gaming Disorder Test- 10 (IGDT-10); Videogames Involvement Scale (VIS) | Depression and Anxiety (DASS- 21) | N.R.2 | N.R.2 | Gaming for social compensation mitigated the experienced depression and anxiety during the COVID-19 pandemic, whereas maladaptive gaming patterns could constitute a vulnerability factor deserving clinical attention. | |
| Hall et al. (2021) | Cross-sectional study | 1,144 participants; 43.6% females; age: M = 31.4 (10.5) | Australia, Aotearoa New Zealand and US; April 2020 | N.R.2 | Internet Gaming Disorder Checklist (IGDC) | Contamination concern (Revised Padua- Inventory contamination subscale) | N.R.2 | N.R.2 | Contamination concern is associated with higher excessive gaming. People may be engaging with video games to manage their contamination concerns about the COVID-19 pandemic. |
| Ismail et al. (2021) | Cross-sectional study | 237 participants; 69.6% females; age: Median = 21.00 (IQR = 3.0) | Malaysia, November – December 2020 | N.R.2 | Internet Gaming Disorder Scale – Short Form (IGDS9-SF) | Anxiety (DASS- 21) | N.R.2 | A diagnosis of IGD could be made for 2.5% participants. | The prevalence of IGD remained as low as the rates reported prior to the pandemic. No significant association between anxiety and IGD. |
| Jouhki et al. (2022) | Longitudinal study | 1,022 participants; 48.4% females, .03 other gender; age: M = 49.50 | Finland, April 2021 – May 2022 | N.R.2 | Internet Gaming Disorder Test (IGDT) | Psychological Distress (MHI-5) | N.R.2 | N.R.2 | Participants experiencing psychological distress were less involved in excessive gaming. |
| Kim, Nam, & Keum (2022) | Longitudinal study | 4,968 participants; gender N.R.; age: range = 13-14 years | Australia, 2021-2022 | N.R.2 | Internet Gaming Disorder Scale – Short Form (IGDS9-SF) | Anxiety (PROMIS-A) | N.R.2 | 15% and 16% in adolescents aged 13 and 14 years, respectively | Higher anxiety levels were associated with higher gaming disorder 12 months later and vice versa. |
| Pattanaseri et al. (2022) | Cross-sectional study | 224 participants; 50.5% females; age: Median = 21.02 [20.02, 21.11] | Thailand, March – October 2020 | N.R.2 | Game Addiction Screening Test (GAST) | Depression (PHQ-9) | N.R.2 | The prevalence of game addiction was 4.5% | Game addiction was not found to be an independent risk factor for depression. |
| Rogier et al. (2021) | Longitudinal study | 1,323 participants; 77.3% females; age: M = 35.51 (13.91) | Italy, After national lockdown | N.R.2 | Internet Gaming Disorder Scale– Short-Form (IGDS9-SF) | Loneliness (UCLA) | N.R.2 | N.R.2 | Loneliness levels at T1 significantly and positively predicted gaming addiction levels at T2, controlling for gaming frequency at T1. |
| Sallie et al. (2021) | Cross-sectional study | 1,344 participants; 24.2% females; age: M = 28.93 (12.46) | United Kingdom, United States and Other; May 2020 | Before quarantine: 6.76 (13.2) hours/ week; During quarantine: 9.92 (15.39) hours/week | Internet Gaming Disorder Scale- Short Form (IGDS9-SF) | Hospital Anxiety and Depression Scale (HADS) | COVID- 19-related stress factors (ad-hoc questions | N.R.2 | Greater OG severity scores during quarantine were associated with psychological factors such as greater depression and anxiety. COVID-19_reated stress factors were associated with greater severity of OG. |
| Savolainen et al. (2022) | Cross-sectional study | 1,530 participants; 49.41% females, 0.26% other; age: M = 46.67 (16.42) | Finland, April 2021 | N.R.2 | Internet Gaming Disorder Test (IGDT) | Mental health problems (MHI-5) | COVID-19 anxiety (adapted STAI-6). | 1% of the total sample had a gaming disorder | Higher COVID-19 anxiety and incidence of mental health issues were associated with higher online gaming problems. |
| Shrestha et al. (2020) | Cross-sectional study | 377 participants; 52.3% females; age: M = 20.85 (1.75) | Nepal, July- August 2020 | 95 (36.6): < 1 hour/ day 104 (40.0): 1-2 hours/day 31 (11.9): 3-4 hours/day 30 (11.5): > 4 hours/day | Internet Gaming Disorder Short Form-9 (IGDS9- SF) | Depression (PHQ-9); Generalized Anxiety Disorder (GAD- 7) | N.R.2 | A diagnosis of IGD could be made for 8.5% participants | Higher depression scores and anxiety scores were significantly associated with greater scores on the IGD. Participants reported an increase in gaming behavior in order to cope with stress caused by the COVID-19 pandemic. |
| Teng et al. (2021) | Longitudinal study | 903 participants (only adolescents are considered for the review); 49.3% females; age: N.R. | China, October 2019 – May 2020 | N.R.2 | Internet Gaming Disorder Short Form-9 (IGDS9- SF) | Depression (CES-D); Anxiety (STAI) | Perceived COVID-19 impacts on life domains (self-report questions) | N.R.2 | Depressive and anxiety symptoms were significant predictors of video game use and internet gaming disorder. Perceived COVID-19 impacts were predictors of IGD. |
| Ting & Essau (2021) | Cross-sectional study | 178 participants; 82% females; age: M = 22.56 (2.93) | Malaysia, September- October 2020 | Before the pandemic: M = 0.95 (2.2) hours/ day; During the pandemic: M = 1.33 (2.8) hours/day | Gaming Addiction Scale (GAS) | Self-regulation (SSRQ); general distress (K6) | COVID-19 related anxiety (FCV- 19S); | 4.5% of the participants could be defined as monothetic gamers (i.e., “pathological gaming”) | Gaming was positively related to COVID-19 related anxiety and psychological distress, and negatively related to self-regulation. |
| Volpe et al. (2022) | Cross-sectional study | 1,385 participants; 62.5% females; age : M = 32.5 (12.9) | Italy, May– September 2020 | 4.2 (9.8) hours/ week | Internet Gaming Disorder Short Form-9 (IGDS9- SF) | Depression, anxiety, and stress (DASS- 21); Social motivation and behavior (SASS) | N.R.2 | A diagnosis of IGD could be made for 13.8% participants | COVID-related general, depressive, anxiety and stress symptomatology are negatively related to Problematic Internet gaming disorder and play a significant mediation role in the relationship between gaming and other types of problematic internet use. |
| Wu et al. (2022) | Retrospective study | 5,268 participants; 47.4% females; age: Median = 27 (IQR = 22, 35) | China, May – August 2020 | Before COVID-19: Median = 30 minutes/day (IQR = 10, 60). After the lifting of lockdowns: median 40 minutes/ day (IQR = 10, 100) | Internet Gaming Disorder Short Form-9 (IGDS9- SF) | Depression, anxiety and stress (DASS-21) | N.R.2 | A diagnosis of IGD could be made for 5% participants | Gamers with increased gaming behavior showed higher degrees of stress, anxiety, and depression than those without increased gaming behavior. |
| Yang et al. (2021) | Cross-sectional study | 177 participants; 52.5% females; Age groups: 18-25 (26.0%), 26-35 (14.1%), 36-45 (15.8%), 46-55 (10.2%), 56-65 (19.2%), >65 (11.9%), refused to answer (2.8) | China, May 2020 | Pre-COVID-19: 1.81 hours/day; During COVID-19: 3.29 hours/day | 9-item DSM-5 IGD symptoms checklist | Loneliness (De Jong Gierveld Loneliness Scale) | Post-traumatic stress (modified PTSD-8); Boredom (modified Multidimensional State Boredom Scale). | A diagnosis of IGD could be made for 9.7% participants | Boredom and emotional loneliness were significantly and positively associated with IGD symptoms. No significant relationship between PTSD and gaming. Boredom positively mediated the associations between time spent on gaming and IGD. |
| Zaman et al. (2022) | Cross-sectional study | 618 participants; 32.5% females; age: M = 24.53 (5.02) | Pakistan, June – July 2020 | N.R.2 | Gaming addiction scale (GAS) | Sleep quality (PSQI) | N.R.2 | Addicted Gamers (12.5%), Problem Gamers (44.3%), Engaged Gamers (5.7%), Normal Gamers (37.5%) | Participants with gaming addiction had significantly poorer subjective sleep quality, higher sleep disturbance, lesser sleep duration, and higher daytime dysfunction. |