Online Gambling in the Midst of COVID-19: A Nexus of Mental Health Concerns, Substance Use and Financial Stress (original) (raw)

Abstract

This study examined the emerging impact of COVID-19 on gambling during the first 6 weeks of emergency measures in Ontario, Canada. A cross-sectional online survey of 2005 gamblers, including a sub-sample of 1081 online gamblers (age 18 years and older), was administered to assess risky gambling behaviours and motivations, financial impacts from COVID-19, the influence of COVID-19 on online gambling, mental health concerns and substance use. A series of odds ratio comparisons and measures of association were carried out. Results show significant likelihood of online gambling among those classified as high-risk gamblers (according to the Problem Gambling Severity Index) and those with past experience of online gambling, though migration from land-based gambling was apparent. Among high-risk online gamblers, the most predictive risk factors included moderate and severe anxiety and depression, reduced work hours, being influenced to gamble due to COVID-19, gambling under the influence of cannabis or alcohol and risky gambling motives tied to mental health concerns, including gambling because it helps with nervousness and depression, chasing gambling losses and seeking to earn income. This study has confirmed many of the risk associations presented in emerging COVID-19-related studies and past research on global economic crisis relating to gambling risk, mental health concerns and substance use. However, unlike many past studies, the present paper takes note of all of these elements holistically and provides incremental clarity on online gambling risk factors during the pandemic, specifically.

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During COVID-19, online gambling, in particular, has become a lens through which to observe serious public health effects. Broadly speaking, the pandemic has negatively impacted many social and economic determinants of health in jurisdictions around the world. In Canada, the national statistics agency reported a 5.5% fall in employment between February and March 2020 (Statistics Canada [2020](/article/10.1007/s11469-020-00366-1#ref-CR63 "Statistics Canada (2020). Weekly update - Friday, May 1, 2020. Retrieved May 6, 2020, from https://www150.statcan.gc.ca/n1/pub/71-607-x/71-607-x2020009-eng.htm

            .")). As a result, over 10.5 million applications to the federal government’s COVID-19 financial assistance program, the Canada Emergency Response Benefit, have been submitted as of May 2020\. This wide-scale financial disruption has raised questions about the potential impacts on public health outcomes and risk factors.

Thus far, gambling behaviour during the pandemic has been characterized by stable or decreased participation, although some at-risk groups featuring vulnerability to high-risk gambling and alcohol misuse have increased their gambling activity (Håkansson [2020](/article/10.1007/s11469-020-00366-1#ref-CR27 "Håkansson, A. (2020). Changes in gambling behavior during the COVID-19 pandemic: a web survey study in Sweden. International Journal of Environmental Research and Public Health, 17(4013), 1–16. https://doi.org/10.3390/ijerph17114013

            .")). More investigation is necessary, however, as evidence has been limited by self-report research designs. At the time of writing, few studies have presented analyses of online behavioural data but do report modest online gambling activity compared with pre-pandemic levels, overall (Auer et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR4 "Auer, M., Malischnig, D., & Griffiths, M. D. (2020). Gambling before and during the COVID-19 pandemic among European regular sports settors: an empirical study using behavioral tracking data. International Journal of Mental Health and Addiction. 
              https://doi.org/10.1007/s11469-020-00327-8
              
            .")). Decreasing rates of gambling participation in some jurisdictions have been tied to a variety of factors, including the limited access to land-based venues, disruptions to professional sporting competitions, financial instability and others (Auer et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR4 "Auer, M., Malischnig, D., & Griffiths, M. D. (2020). Gambling before and during the COVID-19 pandemic among European regular sports settors: an empirical study using behavioral tracking data. International Journal of Mental Health and Addiction. 
              https://doi.org/10.1007/s11469-020-00327-8
              
            ."); Gambling Commission [2020](/article/10.1007/s11469-020-00366-1#ref-CR22 "Gambling Commission (2020). Risks arising from COVID-19 and our response. Retrieved June 13, 2020, from 
              https://www.gamblingcommission.gov.uk/news-action-and-statistics/Statistics-and-research/Covid-19-research/Risks-arising-from-Covid-19-and-our-response.aspx
              
            .")).

Although evidence is still limited, emerging discourse on secondary impacts of COVID-19 has included substance use and gambling. Many papers take note of the effects of isolation, mental health concerns, pre-existing substance use disorders and ongoing access to online gambling and some substances (Douglas et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR15 "Douglas, M., Katikireddi, S. V., Taulbut, M., McKee, M., & McCartney, G. (2020). Mitigating the wider health effects of covid-19 pandemic response. BMJ, 369(April), 1–6. https://doi.org/10.1136/bmj.m1557

            ."); Marsden et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR47 "Marsden, J., Darke, S., Hall, W., Hickman, M., Holmes, J., Humphreys, K., Neale, J., Tucker, J., & West, R. (2020). Mitigating and learning from the impact of COVID-19 infection on addictive disorders. Addiction, 115(6), 1007–1010. 
              https://doi.org/10.1111/add.15080
              
            .")). For instance, in many jurisdictions under lockdown, alcohol has remained an official essential commodity and even featured relaxed licensing for distribution, resulting in sale surges (Ahmed et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR1 "Ahmed, Z., Ahmed, O., Aibao, Z., Hanbin, S., Siyu, L., & Ahmad, A. (2020). Epidemic of COVID-19 in China and associated psychological problems. Asian Journal of Psychiatry, 51(April), 1–8. 
              https://doi.org/10.1016/j.ajp.2020.102092
              
            ."); Dubey et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR16 "Dubey, M. J., Ghosh, R., Chatterjee, S., Biswas, P., Chatterjee, S., & Dubey, S. (2020). COVID-19 and addiction. Diabetes & Metabolic Syndrome, 14(June), 817–823. 
              https://doi.org/10.1016/j.dsx.2020.06.008
              
            .")). Emerging evidence from China also note a 46.8% increase in Internet use and dependence (including a 23% increase in severe Internet addiction) as well as an increase in alcohol consumption and alcohol relapse among ex-drinkers (Sun et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR65 "Sun, Y., Li, Y., Bao, Y., Meng, S., Sun, Y., Schumann, G., Kosten, T., Strang, J., Lu, L., & Shi, J. (2020). Increased addictive Internet and substance use behavior during the COVID-19 pandemic in China. American Journal on Addictions, 29, 268–270. 
              https://doi.org/10.1111/ajad.13066
              
            .")).

International research on the 2008 financial crisis has also noted similar patterns of comorbidity, including the strong relationship between financial stress and illicit drug use, alcohol use and gambling (Dom et al. [2016](/article/10.1007/s11469-020-00366-1#ref-CR14 "Dom, G., Samochowiec, J., Evans-Lacko, S., Wahlbeck, K., Van Hal, G., & McDaid, D. (2016). The impact of the 2008 economic crisis on substance use patterns in the countries of the European Union. International Journal of Environmental Research and Public Health, 13(1), 1–11. https://doi.org/10.3390/ijerph13010122

            ."); Economou et al. [2019](/article/10.1007/s11469-020-00366-1#ref-CR17 "Economou, M., Souliotis, K., Malliori, M., Peppou, L. E., Kontoangelos, K., Lazaratou, H., Anagnostopoulos, D., Golna, C., Dimitriadis, G., Papadimitriou, G., & Papageorgiou, C. (2019). Problem gambling in Greece: prevalence and risk factors during the financial crisis. Journal of Gambling Studies, 35(4), 1193–1210. 
              https://doi.org/10.1007/s10899-019-09843-2
              
            ."); Yang et al. [2018](/article/10.1007/s11469-020-00366-1#ref-CR69 "Yang, J. C., Roman-Urrestarazu, A., & Brayne, C. (2018). Binge alcohol and substance use across birth cohorts and the global financial crisis in the United States. PLoS One, 13(6), 1–18. 
              https://doi.org/10.1371/journal.pone.0199741
              
            .")). For instance, in the European Union (EU), overall substance use fell during this crisis, although key sub-populations experienced increased levels of harmful consumption (Dom et al. [2016](/article/10.1007/s11469-020-00366-1#ref-CR14 "Dom, G., Samochowiec, J., Evans-Lacko, S., Wahlbeck, K., Van Hal, G., & McDaid, D. (2016). The impact of the 2008 economic crisis on substance use patterns in the countries of the European Union. International Journal of Environmental Research and Public Health, 13(1), 1–11. 
              https://doi.org/10.3390/ijerph13010122
              
            .")). In this and other studies, clear associations were established between alcohol-related harms and severe economic losses, characterized by unemployment (Colell et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR10 "Colell, E., Sanchez-Niubo, A., Delclos, G. L., Benavides, F. G., & Domingo-Salvany, A. (2015). Economic crisis and changes in drug use in the Spanish economically-active population. Addiction, 10, 1129–1137. 
              https://doi.org/10.1111/add.12923
              
            ."); Gili et al. [2013](/article/10.1007/s11469-020-00366-1#ref-CR23 "Gili, M., Roca, M., Basu, S., McKee, M., & Stuckler, D. (2013). The mental health risks of economic crisis in Spain: evidence from primary care centres, 2006 and 2010. European Journal of Public Health, 23, 103–108. 
              https://doi.org/10.1093/eurpub/cks035
              
            ."); Harhay et al. [2014](/article/10.1007/s11469-020-00366-1#ref-CR29 "Harhay, M. O., Bor, J., Basu, S., McKee, M., Mindell, J. S., Shelton, N. J., & Stuckler, D. (2014). Differential impact of the economic recession on alcohol use among white British adults, 2004–2010. European Journal of Public Health, 24, 410–415. 
              https://doi.org/10.1093/eurpub/ckt134
              
            .")). Young adults (18–34 years) were identified as a population vulnerable to risky substance use and pronounced negative socio-economic impacts during a global financial crisis. Research evidence from Greece, Iceland and the United States (US) has also highlighted marked increases in risky gambling behaviour that was strongly associated with severe financial hardship during 2008 (Economou et al. [2019](/article/10.1007/s11469-020-00366-1#ref-CR17 "Economou, M., Souliotis, K., Malliori, M., Peppou, L. E., Kontoangelos, K., Lazaratou, H., Anagnostopoulos, D., Golna, C., Dimitriadis, G., Papadimitriou, G., & Papageorgiou, C. (2019). Problem gambling in Greece: prevalence and risk factors during the financial crisis. Journal of Gambling Studies, 35(4), 1193–1210. 
              https://doi.org/10.1007/s10899-019-09843-2
              
            ."); Olason et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR54 "Olason, D. T., Hayer, T., Brosowski, T., & Meyer, G. (2015). Gambling in the mist of economic crisis: results from three national prevalence studies from Iceland. Journal of Gambling Studies, 31(3), 759–774. 
              https://doi.org/10.1007/s10899-015-9523-4
              
            .")).

In recent months, a number of papers published on the impact of COVID-19 have focused specifically on mental health. Many of these studies have consistently shown increased anxiety, depression and other mental health conditions (Brooks et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR8 "Brooks, S. K., Webster, R. K., Smith, L. E., Woodland, L., Wessely, S., Greenberg, N., & Rubin, G. J. (2020). The psychological impact of quarantine and how to reduce it: rapid review of the evidence. The Lancet, 395(10227), 912–920. https://doi.org/10.1016/S0140-6736(20)30460-8

            ."); Gritsenko et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR26 "Gritsenko, V., Skugarevsky, O., Konstantinov, V., Khamenka, N., Marinova, T., Reznik, A., & Isralowitz, R. (2020). COVID 19 fear, stress, anxiety, and substance use among Russian and Belarusian university students. International Journal of Mental Health and Addiction, 1–7. 
              https://doi.org/10.1007/s11469-020-00330-z
              
            .")). One clinical case study from Ireland involving patients suffering from addiction noted heightened expressions of stress and anxiety as well as addictive behaviour (i.e. problem gambling) and substance misuse (Columb et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR11 "Columb, D., Hussain, R., & O’Gara, C. (2020). Addiction psychiatry and COVID-19: impact on patients and service provision. Irish Journal of Psychological Medicine, 1–15. 
              https://doi.org/10.1017/ipm.2020.47
              
            .")). These issues were compounded by increasing social isolation and the difficulty of patients in accessing physical clinics due to social distancing measures. One Chinese study (_n_ \= 7236) examining effects on anxiety, depression and sleep quality noted significantly higher prevalence of anxiety among younger adults (< 35 years) and higher levels of depression among older adults (≥ 35 years) (Huang and Zhao [2020](/article/10.1007/s11469-020-00366-1#ref-CR34 "Huang, Y., & Zhao, N. (2020). Generalized anxiety disorder, depressive symptoms and sleep quality during COVID-19 outbreak in China: a web-based cross-sectional survey. Psychiatry Research, 288(March), 112954. 
              https://doi.org/10.1016/j.psychres.2020.112954
              
            .")). Although a full understanding of key factors affecting mental health concerns relating to the COVID-19 pandemic is still emerging, some studies have identified the novel mediating effects of _fear_ and _uncertainty_ on depression, stress and anxiety and positive outlook (Ahorsu et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR2 "Ahorsu, D. K., Imani, V., Lin, C., Timpka, T., Broström, A., Updegraff, J. A., … Pakpour, A. H. (2020). Associations between fear of COVID-19, mental health, and preventive behaviours across pregnant women and husbands: an actor-partner interdependence modelling. International Journal of Mental Health and Addiction Addiction. doi 
              https://doi.org/10.1007/s11469-020-00340-x
              
            ."); Bakioğlu et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR6 "Bakioğlu, F., Korkmaz, O., & Ercan, H. (2020). Fear of COVID-19 and positivity: mediating role of intolerance of uncertainty, depression, anxiety, and stress. International Journal of Mental Health and Addiction. 
              https://doi.org/10.1007/s11469-020-00331-y
              
            .")). Other mediating factors relating to the severity of anxiety during the pandemic among college students in China have included _living in urban areas_, _family income stability_ and _living with parents_ (or close social relations) (Cao et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR9 "Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287(March), 112934. 
              https://doi.org/10.1016/j.psychres.2020.112934
              
            .")).

Studies of online gambling, in particular, have noted comorbid relationships between mental health outcomes, substance use and problem gambling (Awaworyi Churchill and Farrell [2018](/article/10.1007/s11469-020-00366-1#ref-CR5 "Awaworyi Churchill, S., & Farrell, L. (2018). The impact of gambling on depression: new evidence from England and Scotland. Economic Modelling, 68(2017), 475–483. https://doi.org/10.1016/j.econmod.2017.08.021

            ."); Gainsbury [2015](/article/10.1007/s11469-020-00366-1#ref-CR21 "Gainsbury, S. M. (2015). Online gambling addiction: the relationship between Internet gambling and disordered gambling. Current Addiction Reports, 2(2), 185–193. 
              https://doi.org/10.1007/s40429-015-0057-8
              
            ."); Hing et al. [2014](/article/10.1007/s11469-020-00366-1#ref-CR30 "Hing, N., Cherney, L., Gainsbury, S. M., Lubman, D. I., Wood, R. T., & Blaszczynski, A. (2014). Maintaining and losing control during internet gambling: a qualitative study of gamblers’ experiences. New Media & Society, 17(7), 1075–1095. 
              https://doi.org/10.1177/1461444814521140
              
            ."); LaPlante et al. [2009](/article/10.1007/s11469-020-00366-1#ref-CR39 "LaPlante, D. A., Nelson, S. E., Labrie, R. A., & Shaffer, H. J. (2009). Disordered gambling, type of gambling and gambling involvement in the British Gambling Prevalence Study 2007. European Journal of Public Health. 
              https://doi.org/10.1093/eurpub/ckp177
              
            ."); Lloyd et al. [2010a](/article/10.1007/s11469-020-00366-1#ref-CR43 "Lloyd, J., Doll, H., Hawton, K., Dutton, W. H., Geddes, J. R., Goodwin, G. M., & Rogers, R. D. (2010a). How psychological symptoms relate to different motivations for gambling: an online study of internet gamblers. Biological Psychiatry, 68(8), 733–740. 
              https://doi.org/10.1016/j.biopsych.2010.03.038
              
            ."); Scholes-Balog and Hemphill [2012](/article/10.1007/s11469-020-00366-1#ref-CR59 "Scholes-Balog, K. E., & Hemphill, S. A. (2012). Relationships between online gambling, mental health, and substance use: a review. Cyberpsychology, Behavior and Social Networking, 15(12), 688–692. 
              https://doi.org/10.1089/cyber.2012.0232
              
            ."); Wardle et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR66 "Wardle, H., Moody, A., Griffiths, M., Orford, J., & Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11(3), 339–356. 
              https://doi.org/10.1080/14459795.2011.628684
              
            .")). For example, early studies of the relationship between mental health and online gambling report much lower levels of mental health than those who never gambled online (Petry [2006](/article/10.1007/s11469-020-00366-1#ref-CR55 "Petry, N. M. (2006). Internet gambling: an emerging concern in family practice medicine? Family Practice, 23, 421–427. 
              https://doi.org/10.1093/fampra/cml005
              
            .")). Subsequent research involving university students (_n_ \= 1356) using the General Health Questionnaire confirms this association and further notes that poor outcomes can be significant in both frequent and infrequent online gamblers (Petry and Weinstock [2007](/article/10.1007/s11469-020-00366-1#ref-CR56 "Petry, N. M., & Weinstock, J. (2007). Internet gambling is common in college students and associated with poor mental health. American Journal on Addictions, 16(5), 325–330. 
              https://doi.org/10.1080/10550490701525673
              
            .")). Other studies of undergraduate students (_n_ \= 1430) in the US have found a significant statistical correlation (_p_ < 0.01) between pathological levels of gambling, problematic alcohol consumption and depression (Martin et al. [2014](/article/10.1007/s11469-020-00366-1#ref-CR48 "Martin, R. J., Usdan, S., Cremeens, J., & Vail-Smith, K. (2014). Disordered gambling and co-morbidity of psychiatric disorders among college students: an examination of problem drinking, anxiety and depression. Journal of Gambling Studies, 30(2), 321–333. 
              https://doi.org/10.1007/s10899-013-9367-8
              
            .")). Further research shows depression severity was predicted by gamblers involved in multiple online games and, to a lesser degree, but still significant, online sports betting and casino play (Lloyd et al. [2010b](/article/10.1007/s11469-020-00366-1#ref-CR44 "Lloyd, J., Doll, H., Hawton, K., Dutton, W. H., Geddes, J. R., Goodwin, G. M., & Rogers, R. D. (2010b). Internet gamblers: a latent class analysis of their behaviours and health experiences. Journal of Gambling Studies, 26(3), 387–399. 
              https://doi.org/10.1007/s10899-010-9188-y
              
            .")). Early research on the relationship between substance use and online gambling has also noted strong connections between multiple online game activities, the use of nicotine and illicit drugs and problem gambling (Lloyd et al. [2010b](/article/10.1007/s11469-020-00366-1#ref-CR44 "Lloyd, J., Doll, H., Hawton, K., Dutton, W. H., Geddes, J. R., Goodwin, G. M., & Rogers, R. D. (2010b). Internet gamblers: a latent class analysis of their behaviours and health experiences. Journal of Gambling Studies, 26(3), 387–399. 
              https://doi.org/10.1007/s10899-010-9188-y
              
            ."); McBride and Derevensky [2009](/article/10.1007/s11469-020-00366-1#ref-CR49 "McBride, J., & Derevensky, J. (2009). Internet gambling behavior in a sample of online gamblers. International Journal of Mental Health and Addiction, 7(1), 149–167. 
              https://doi.org/10.1007/s11469-008-9169-x
              
            .")). Some large prevalence studies have strengthened this field of research, which has been typically cross-sectional to date. For instance, analysis of the British Gambling Prevalence Survey data confirms that binge alcohol consumption is significantly associated with problem gambling and that the risk of gambling problems is statistically higher among those who gambled online (Griffiths et al. [2010](/article/10.1007/s11469-020-00366-1#ref-CR24 "Griffiths, M., Wardle, H., Orford, J., Sproston, K., & Erens, B. (2010). Gambling, alcohol, consumption, cigarette smoking and health: findings from the 2007 British Gambling Prevalence Survey. Addiction Research and Theory, 18(2), 208–223. 
              https://doi.org/10.3109/16066350902928569
              
            ."), [2011](/article/10.1007/s11469-020-00366-1#ref-CR25 "Griffiths, M., Wardle, H., Orford, J., Sproston, K., & Erens, B. (2011). Internet gambling, health, smoking and alcohol use: findings from the 2007 British Gambling Prevalence Survey. International Journal of Mental Health and Addiction, 9(1), 1–11. 
              https://doi.org/10.1007/s11469-009-9246-9
              
            .")). Notably, this representative data has also suggested that a large proportion of online gamblers also gamble in-person, and therefore relates gambling risk with profiles of mixed and multiple game players described previously (Wardle et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR66 "Wardle, H., Moody, A., Griffiths, M., Orford, J., & Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11(3), 339–356. 
              https://doi.org/10.1080/14459795.2011.628684
              
            .")). With regard to cannabis use and online gambling, specifically, the literature is more limited, but some evidence highlights an emergent connection between problem gambling and depression (Potenza et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR57 "Potenza, M. N., Wareham, J. D., Steinberg, M. A., Rugle, L., Cavallo, D. A., Krishnan-Sarin, S., & Desai, R. A. (2011). Correlates of at-risk/problem internet gambling in adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 50(2), 150–159.e3. 
              https://doi.org/10.1016/j.jaac.2010.11.006
              
            .")). Examinations of online poker players have also found anxiety and depression to be predictive of gambling problems (Barrault et al. [2017](/article/10.1007/s11469-020-00366-1#ref-CR7 "Barrault, S., Bonnaire, C., & Herrmann, F. (2017). Anxiety, depression and emotion regulation among regular online poker players. Journal of Gambling Studies, 33(4), 1039–1050. 
              https://doi.org/10.1007/s10899-017-9669-3
              
            ."); Hopley et al. [2012](/article/10.1007/s11469-020-00366-1#ref-CR32 "Hopley, A. A. B., Dempsey, K., & Nicki, R. (2012). Texas Hold’em online poker: a further examination. International Journal of Mental Health and Addiction, 10(4), 563–572. 
              https://doi.org/10.1007/s11469-011-9353-2
              
            ."); Mitrovic and Brown [2009](/article/10.1007/s11469-020-00366-1#ref-CR50 "Mitrovic, D. V., & Brown, J. (2009). Poker mania and problem gambling: a study of distorted cognitions, motivation and alexithymia. Journal of Gambling Studies, 25(4), 489–502. 
              https://doi.org/10.1007/s10899-009-9140-1
              
            .")).

Despite the research evidence, our holistic understanding of the intersection of risky gambling behaviours, financial crisis and stress, negative mental health outcomes and substance use has yet to consider the specific effects of online gambling during a time of increased social isolation and significant economic instability.

Methods

This paper presents findings from an online survey of gamblers (n = 2005) in the Canadian province of Ontario and a sub-sample of online gamblers (n = 1081). The survey was administered approximately 6 weeks after the province declared a state of emergency for COVID-19 (March 17, 2020). The declaration resulted in the closure of all recreational centres, public parks and playgrounds, schools, public libraries, bars, restaurants, movie theatres, concert venues and places of worship, land-based gambling venues, and extended further restrictions on non-essential work and public gatherings of 5 or more people (Office of the Premier [2020](/article/10.1007/s11469-020-00366-1#ref-CR53 "Office of the Premier (2020). Ontario prohibits gatherings of more than five people with strict exceptions. Toronto: Government of Ontario. Retrieved from https://news.ontario.ca/opo/en/2020/03/ontario-prohibits-gatherings-of-five-people-or-more-with-strict-exceptions.html

            .")).

Study Rationale

The purpose of this study was to understand the emerging impact of COVID-19 in the first 6 weeks since provincial emergency measures were declared. The focus of inquiry was on gambling behaviours, mental health concerns, substance use and online behavioural risk factors. Findings from the study were intended to rapidly advance knowledge in these areas, support follow-up research and inform the adaptation and improvement of community outreach and prevention programming.

Data Source and Collection

Data was collected from 2005 Ontarian gamblers, 18 years or older between April 21 and 28, 2020. Of the total sample, 1081 respondents confirmed their online gambling participation based off of the question: Over the past 6 weeks, have you gambled online? Respondents were recruited by Delvinia, an online survey vendor located in Toronto, Ontario, Canada. The vendor utilized the AskingCanadians panel population of over 1 million Canadians who are registered to receive survey recruitment notifications, if they meet basic inclusion criteria. As an incentive, Delvinia compensated participants through consumer point programs, such as Hudson Bay Company (HBC) Rewards, Aeroplan, VIA Preference, Petro Points as well as their internal program points that can be redeemed for Amazon e-gift cards and various prizes.

Using background information on panel members, respondents were sampled based on their age (18 years and older), if they were permanent residents of Ontario, and if they had gambled at least once in the past 12 months. Respondents were then presented with an informed consent statement outlining the question topics and their right to opt out of any or all questions at any time. The first few questions of the survey screened for the inclusion criteria again before advancing to other questionnaire items. A quota-based sampling strategy was employed to match age and gender distribution with official census data and produce a balanced sample reflective of the population (Statistics Canada [2018](/article/10.1007/s11469-020-00366-1#ref-CR62 "Statistics Canada (2018). Census profile, 2016 census: Ontario and Canada. Retrieved from https://www12.statcan.gc.ca/census-recensement/2016/dp-pd/prof/details/page.cfm?Lang=E&Geo1=PR&Code1=35&Geo2=PR&Code2=01&SearchText=Canada&SearchType=Begins&SearchPR=01&B1=All&type=0

            .")). During data collection, the survey vendor monitored the completion rate by quota-based sampling categories to ensure the final sample was balanced. Based on a 95% confidence level, the survey is estimated to have a ± 2.2% margin of error.

The survey consisted of demographic questions related to age, gender and the highest level of education completed. Age was recorded as a specific discrete number (e.g. 23 years) and later coded into a categorical variable (e.g. 18–24 years). Gender included response options for male, female, transgender, other and prefer not to answer. Educational attainment included the options no high school or General Educational Development (GED), high school or GED, trade or technical certification, bachelor’s degree, master’s degree, professional degree (e.g. law, medicine, dentistry) and doctoral degree. Respondents were also asked if their employment status and household income had been affected by COVID-19 on a 7-point Likert scale of strongly agree to strongly disagree, neither agree nor disagree and do not know.

Mental health concerns were captured using the Patient Health Questionnaire (PHQ-9) for depression screening and the General Anxiety Disorder (GAD-7) questionnaire (Homans 2012; Lowe et al. [2008](/article/10.1007/s11469-020-00366-1#ref-CR46 "Lowe, B., Decker, O., Muller, S., Brahler, E., Schllberg, D., Herzog, W., & Herzberg, P. Y. (2008). Validation and standardization of the generalized anxiety disorder screener (GAD-7) in the general population. Medical Care, 46(3), 266–274. https://doi.org/10.1097/mlr.0b013e318160d093

            ."); Spitzer et al. [2006](/article/10.1007/s11469-020-00366-1#ref-CR61 "Spitzer, R. L., Kroenke, K., Williams, J. J. B. W., & Lo, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of Internal Medicine, 166(10), 1092–1099. 
              https://doi.org/10.1001/archinte.166.10.1092
              
            .")). Both instruments are prompted by the same question: _Over the last 2 weeks, how often have you been bothered by any of the following problems?_ The PHQ-9 is the depression sub-scale of the PHQ, which is itself a self-administered version of the Primary Care Evaluation of Mental Disorders (PRIME-MD) diagnostic instrument for common mental disorders (Homans [2012](/article/10.1007/s11469-020-00366-1#ref-CR31 "Homans, W. (2012). The validity of the PHQ-9 and the GAD-7 for screening depressive and anxiety disorders in sick-listed workers. Utrecht University."); Kroenke et al. [2001](/article/10.1007/s11469-020-00366-1#ref-CR36 "Kroenke, K., Spitzer, R. L., & Williams, J. B. (2001). The PHQ-9: validity of a brief depression severity measure. Journal of General Internal Medicine, 16(9), 606–613. 
              https://doi.org/10.1046/j.1525-1497.2001.016009606.x
              
            .")). This sub-scale includes 9 items from the _Diagnostic and Statistical Manual of Mental Disorders_, 4th edition (DSM-IV) criteria for depression (e.g. _little interest or pleasure in doing things_, _feeling tired or having little energy_, _feeling down_, _depressed or hopeless_) that are scored from 0 to 3 and totally 0 to 27\. The total scores are interpreted based on depression severity including _non-minimal_ (0–4), _mild_ (5–9), _moderate_ (10–14), _moderately severe_ (15–19) and _severe_ (20–27). This tool has been thoroughly validated, demonstrating high sensitivity (88%) and specificity (88%) for major depressive symptoms and high internal consistency (Cronbach’s alpha = 0.86–0.89) (American Psychiatric Association [2011](/article/10.1007/s11469-020-00366-1#ref-CR3 "American Psychiatric Association. (2011). Patient Health Questionnaire (PHQ-9 & PHQ-2). Retrieved June 19, 2020, from 
              https://www.apa.org/pi/about/publications/caregivers/practice-settings/assessment/tools/patient-health#:~:text=Thediagnosticvalidityofthe,ithassoundpsychometricproperties
              
            .")).

The GAD-7 assesses symptoms of anxiety using 7 items from the DSM-IV for generalized anxiety disorder (e.g. feeling nervous, anxious or on edge, not being able to stop or control worrying, trouble relaxing) (Homans 2012; Spitzer et al. [2006](/article/10.1007/s11469-020-00366-1#ref-CR61 "Spitzer, R. L., Kroenke, K., Williams, J. J. B. W., & Lo, B. (2006). A brief measure for assessing generalized anxiety disorder: the GAD-7. Archives of Internal Medicine, 166(10), 1092–1099. https://doi.org/10.1001/archinte.166.10.1092

            .")). The scale is scored in a range from 0 to 21 and interpreted by the categories _non-minimal_ (0–4), _mild_ (5–9), _moderate_ (10–14) and _severe_ (15–21). At the threshold score of 10, the GAD-7 has a sensitivity of 89% and a specificity of 82% (Kroenke et al. [2007](/article/10.1007/s11469-020-00366-1#ref-CR37 "Kroenke, K., Spitzer, R., & Williams, J. (2007). Anxiety disorders in primary care: prevalence, impairment, comorbidity, and detection. Annals of Internal Medicine, 146(5), 317–342. 
              https://doi.org/10.7326/0003-4819-146-5-200703060-00004
              
            .")).

In addition, respondents were asked if they had experienced a mental health concern any time prior to COVID-19, be it self-diagnosed or diagnosed by a professional clinician. This question included several response options reflecting mental health disorders commonly associated with problem gambling, including depression, stress and anxiety, impulse control issues and addiction_—_another option was also included that could be filled with further details (Coman et al. [1997](/article/10.1007/s11469-020-00366-1#ref-CR12 "Coman, G. J., Burrows, G. D., & Evans, B. J. (1997). Stress and anxiety as factors in the onset of problem gambling: implications for treatment. Stress Medicine, 13(4), 235–244. https://doi.org/10.1002/(SICI)1099-1700(199710)13:4<235::AID-SMI748>3.0.CO;2-4

            ."); Hounslow et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR33 "Hounslow, V., Smith, D., Battersby, M., & Morefield, K. (2011). Predictors of problem gambling severity in treatment seeking gamblers. International Journal of Mental Health and Addiction, 9(6), 682–695. 
              https://doi.org/10.1007/s11469-010-9292-3
              
            ."); Lightsey and Hulsey [2002](/article/10.1007/s11469-020-00366-1#ref-CR42 "Lightsey, O. R., & Hulsey, C. D. (2002). Impulsivity, coping, stress, and problem gambling among university students. Journal of Counseling Psychology, 49(2), 202–211. 
              https://doi.org/10.1037/0022-0167.49.2.202
              
            .")). Additional response options allowed respondents to answer with “I’m not sure” and “No, I have not”.

Substance use was assessed through three questions, including one on the consumption of alcohol and cannabis during the period of emergency measures (i.e. In the past 6 weeks, have you used any of the following substances?). Two other questions asked if substance use had increased as compared with the period before emergency measures (i.e. Please respond to the following statement: In the past 6 weeks, I have consumed more substances than I did before this time period.) and, lastly, if individuals had gambled online under the influence of a substance (i.e. In the past 6 weeks, have you ever gambled under the influence of the following substances?).

Various questions were also posed on the topic of gambling behaviours, including typical participation, recent online participation and if COVID-19 had any influence in decisions to gamble online (e.g. Please respond to the following statement: Emergency measures implemented due to COVID-19 influenced my decision to gamble online over the past 6 weeks). Key items were pulled from the Gambling Motives Questionnaire, including (1) because it helps when feeling nervous or depressed and (2) to win back money lost gambling (Lambe et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR38 "Lambe, L., Mackinnon, S. P., & Stewart, S. H. (2015). Validation of the gambling motives questionnaire in emerging adults. Journal of Gambling Studies, 31(3), 867–885. https://doi.org/10.1007/s10899-014-9467-0

            ."); Stewart and Zack [2008](/article/10.1007/s11469-020-00366-1#ref-CR64 "Stewart, S. H., & Zack, M. (2008). Development and psychometric evaluation of a three-dimensional Gambling Motives Questionnaire. Addiction, 103(July), 103–112. 
              https://doi.org/10.1111/j.1360-0443.2008.02235.x
              
            .")). A third motive, _to earn income_, was also assessed based on its strong monetary focus and distinct association with risky gambling (Lee et al. [2007](/article/10.1007/s11469-020-00366-1#ref-CR40 "Lee, H.-P., Chae, P. K., Lee, H.-S., & Kim, Y.-K. (2007). The five-factor gambling motivation model. Psychiatry Research, 150(1), 21–32."); Nower and Blaszczynski [2010](/article/10.1007/s11469-020-00366-1#ref-CR52 "Nower, L., & Blaszczynski, A. (2010). Gambling motivations, money-limiting strategies, and precommitment preferences of problem versus non-problem gamblers. Journal of Gambling Studies, 26, 361–372. 
              https://doi.org/10.1007/s10899-009-9170-8
              
            .")) and risky online gambling in particular (Mulkeen et al. [2017](/article/10.1007/s11469-020-00366-1#ref-CR51 "Mulkeen, J., Abdou, H. A., & Parke, J. (2017). A three stage analysis of motivational and behavioural factors in UK internet gambling. Personality and Individual Differences, 107, 114–125.")). These items were selected to reflect additional emphasis and characteristics of gambling under the influence of mental health concerns (i.e. depression and anxiety), as noted previously, as well as escape from and desired relief of financial stress (Wood and Griffiths [2007](/article/10.1007/s11469-020-00366-1#ref-CR68 "Wood, R. T. A., & Griffiths, M. D. (2007). A qualitative investigation of problem gambling as an escape-based coping strategy. Psychology and Psychotherapy, 80, 107–125. 
              https://doi.org/10.1348/147608306X107881
              
            .")).

Finally, various questions were posed to capture gambling risk, including the validated nine-item Problem Gambling Severity Index (PGSI) (Currie et al. [2013](/article/10.1007/s11469-020-00366-1#ref-CR13 "Currie, S. R., Hodgins, D. C., & Casey, D. M. (2013). Validity of the Problem Gambling Severity Index interpretive categories. Journal of Gambling Studies, 29(2), 311–327. https://doi.org/10.1007/s10899-012-9300-6

            ."); Ferris and Wynne [2001a](/article/10.1007/s11469-020-00366-1#ref-CR19 "Ferris, J., & Wynne, H. (2001a). The Canadian Problem Gambling Index: final report. Ottawa, Ontario."), [b](/article/10.1007/s11469-020-00366-1#ref-CR20 "Ferris, J., & Wynne, H. (2001b). Problem Gambling Severity Index. Ottawa, Ontario."); Lopez-Gonzalez et al. [2018](/article/10.1007/s11469-020-00366-1#ref-CR45 "Lopez-Gonzalez, H., Estévez, A., & Griffiths, M. D. (2018). Spanish validation of the Problem Gambling Severity Index: a confirmatory factor analysis with sports bettors. Journal of Behavioral Addictions, 7(3), 814–820. 
              https://doi.org/10.1556/2006.7.2018.84
              
            .")). This tool scores total responses in a range of 0 to 27 and interprets them according to four categories, including _non-problem gambling_ (0), _low-risk gambling_ (1–2), _moderate-risk gambling_ (3–7) and _high-risk gambling_ (8–27). The PGSI has shown satisfactory reliability (Cronbach’s alpha = 0.84) (Ferris and Wynne [2001a](/article/10.1007/s11469-020-00366-1#ref-CR19 "Ferris, J., & Wynne, H. (2001a). The Canadian Problem Gambling Index: final report. Ottawa, Ontario."), [b](/article/10.1007/s11469-020-00366-1#ref-CR20 "Ferris, J., & Wynne, H. (2001b). Problem Gambling Severity Index. Ottawa, Ontario.")), though its non-problem gambling and high-risk gambling categories have the most predictive values (Currie et al. [2013](/article/10.1007/s11469-020-00366-1#ref-CR13 "Currie, S. R., Hodgins, D. C., & Casey, D. M. (2013). Validity of the Problem Gambling Severity Index interpretive categories. Journal of Gambling Studies, 29(2), 311–327. 
              https://doi.org/10.1007/s10899-012-9300-6
              
            .")).

Data Analysis

A general descriptive analysis was conducted and included frequencies, proportions and other summary statistics for key variables. A series of cross-tabulated chi-square tests, odds ratios and 95% confidence intervals were also carried out to compare relevant discrete, dichotomous variables. The level of statistical significance was set at p < 0.05. Key comparisons included those who engaged in online gambling during the 6 weeks since emergency measures were instituted, and those who did not gamble online. Additional analysis was carried out on the sub-sample of online gamblers (n = 1081) comparing high-risk gamblers to non-high-risk gamblers as well as an examination of high-risk gambling motives.

Results

Demographic Characteristics

Males and females in the sample were equally distributed at approximately 50% each with 0.2% reporting as “other”. The average age was 48 (17.2-year standard deviation) and ranged from 18 to 89 years. Educational achievement consisted of no high school or GED diploma (1.5%), high school or GED diploma (20.6%), trade or technical certification (19.4%), bachelor’s degree (36.7%), master’s degree (12.6%), professional degree (e.g. law, medicine, dentistry, pharmacy) (7.5%) and doctoral degree (7.5%).

Gambling Behaviours and Risk

Among the entire sample of 2005 gamblers, approximately 54% had gambled online during the period of emergency measures. In contrast, typical gambling behaviour reported for the past 12 months was predominantly land-based only (76.7%), followed by a mix of land-based and online (13.6%) and online only (9.7%).

Within the full sample, the majority of respondents were classified as non-problem gamblers (71.7%) and low-risk gamblers (14.2%), according to the PGSI scale. Moderate-risk gamblers (6.5%) and high-risk gamblers (7.6%) made up the remainder of respondents. Tests of reliability for the nine items of the PGSI scale revealed high internal consistency (Cronbach’s alpha = 0.95).

Impact of COVID-19

Nearly half of the sample (47%) reported some form of employment disruption attributed to COVID-19. Among this cohort, 16% reported lost employment, 7.6% reported reduced work hours, 19.3% reported a shift to working full-time from home and 4.1% reported a shift to working part-time from home. Approximately one-quarter reported no changes in their full-time (19.3%) or part-time (3.2%) employment or work. One-fifth (20.1%) indicated they were not employed or looking for employment—over 50% of these individuals were retirement aged (65 years or older).

Exactly half of the total sample reported their household income had been negatively affected by COVID-19.

Mental Health

Approximately one-third of gamblers noted they had experienced a mental health concern any time prior to COVID-19—19.5% self-diagnosed and 13% diagnosed by a professional clinician. Anxiety and depression were the most reported conditions among self-diagnosed (85.2%, 54.7%) and clinically diagnosed (71.3%, 67.8%) respondents, respectively.

The GAD-7 questionnaire revealed 43.6% of the sample did not have notable symptoms of anxiety. The remaining respondents were classified as having mild anxiety (30.7%), moderate anxiety (16.1%) and severe anxiety (9.6%). Among the total sample of gamblers (n = 2005), this scale instrument demonstrated excellent internal consistency (Cronbach’s alpha = 0.93).

The PHQ-9 questionnaire found that 44.2% had no serious symptoms of depression. The balance of the sample was characterized by mild depression (29.1%), moderate depression (14.5%), moderately severe depression (8.4%) and severe depression (3.8%). Scale reliability for this instrument demonstrated high internal consistency (Cronbach’s alpha = 0.91).

Substance Use

The majority of gamblers reported consuming alcohol (68.7%) during the first 6 weeks after provincial emergency measures. Among these respondents, 40.7% confirmed that their alcohol consumption had increased during this period of time, as compared with the time preceding emergency measures.

Cannabis use (16.4%) was less prevalent among gamblers, relative to alcohol consumption. However, of those reporting cannabis use, 48.6% reported increased consumption compared with the time preceding emergency measures.

Online Gambling Compared with Non-online Gambling

Several significant differences emerged between those who gambled online during emergency measures and those who did not (as shown in Table 1). Males were more likely to gamble online (n = 598, 55.3%; OR = 1.62, p < 0.001) than females (n = 477, 44.1%; OR = 0.61, p < 0.001). Younger adults were much more likely to have gambled online, including 18–24-year-olds (n = 138, 12.8%; OR = 1.34, p = 0.041) and 25–44-year-olds (n = 392, 36.3%; OR = 1.32, p = 0.004), whereas seniors (65+ years) had much lower odds of online gambling (n = 196, 18.1%; OR = 0.69, p = 0.001).

Table 1 Odds ratios for online gambling status based on selected key factors (N = 2005)

Full size table

Gamblers who typically played only at land-based venues were less likely to gamble online during the period of emergency measures (n = 666, 61.6%; OR = 0.10, p < 0.001), though they made up the majority of online gamblers. Typical online only gamblers (n = 173, 16%; OR = 8.19, p < 0.001) and those reporting a mix of land-based and online plays in the past 12 months (n = 242, 22.4%; OR = 8.31, p < 0.001) had similarly high likelihood of online gambling during the 6 weeks of emergency measures.

Non-problem gamblers were half as likely to gamble online than other risk categories (n = 709, 65.6%; OR = 0.51, p < 0.001). Moderate-risk gamblers had about twice the odds of gambling online during the period of emergency measures (n = 89, 8.2%; OR = 1.88, p = 0.001), and high-risk gamblers had nearly 9 times the odds (n = 138, 12.8%; OR = 8.87, p < 0.001).

Those with no symptoms of anxiety (GAD-7: n = 437, 40.4%; OR = 0.76, p = 0.002) and no symptoms of depression (PHQ-9: n = 435, 40.2%; OR = 0.71, p < 0.001) had decreased odds of gambling online. In contrast, those with moderate anxiety (GAD-7: n = 193, 17.9%; OR = 1.33, p < 0.022) had slightly greater odds of online gambling. Those with symptoms of moderately severe depression (PHQ-9: n = 110, 10.2%; OR = 1.69, p = 0.002) and severe depression (PHQ-9: n = 57, 5.3%; OR = 2.52, p < 0.001) were even more likely to have gambled online during emergency measures.

Comparative analysis of those who gambled online and those who did not failed to reveal extensive differences in COVID-19 financial impacts or substance use. Among the limited significant findings, negative impact on household income attributed to COVID-19 featured a positive association with online gambling (n = 564, 52.2%; OR = 1.21, p = 0.033). Respondents who reported increased alcohol use during the first 6 weeks of emergency measures also had slightly increased likelihood of online gambling (n = 320, 43.2%; OR = 1.25, p = 0.042).

However, young adults (18–24 years) did experience greater and more significant financial impacts from COVID-19, overall and among those who gambled online, relative to older cohorts. Overall, 37.6% of young adults reported lost employment (n = 229; OR = 396, 95% CI = 2.93–5.35, p < 0.001) and 65.5% experienced negative impact on household income (OR = 2.06, 95% CI = 1.54–2.75). Among young adults who gambled online, 40.6% reported lost employment (n = 138; OR = 4.23, 95% CI = 2.88–6.23, p < 0.001) and 68.1% experienced negative impact on household income (OR = 2.15, 95% CI = 1.47–3.14, p < 0.001).

High-Risk Gambling Among Online Gamblers

Within the sub-sample of respondents who gambled online during emergency measures (n = 1081), several significant associations with high-risk gambling status emerged (as shown in Table 2). Males had a higher likelihood of being high-risk gamblers (n = 91, 65.9%; OR = 1.67, p = 0.007) while females had a lower likelihood (n = 44, 31.9%; OR = 0.55, p = 0.002). Respondents aged 25–44 had the greatest odds of high-risk gambling status (n = 86, 62.3%; OR = 3.44, p < 0.001), whereas those aged 45–64 years (n = 25, 18.1%; OR = 0.41, p < 0.001) and 65+ years (n = 6, 4.3%; OR = 0.18, p < 0.001) had much lower odds of high-risk gambling.

Table 2 Odds ratios for PGSI high-risk gambling and associated factors among online players (N = 1081)

Full size table

Assessments of both anxiety and depression shared a positive linear relationship with gambling risk. Respondents who were screened as having no symptoms of anxiety (GAD-7: n = 9, 6.5%; OR = 0.084, p < 0.001) or depression (PHQ-9: n = 11, 8.0%; OR = 0.11, p < 0.001) had the lowest likelihood of high-risk gambling status. Those presenting moderate anxiety (GAD-7: n = 55, 39.9%; OR = 3.87, p < 0.001) and severe anxiety (GAD-7: n = 33, 23.9%; OR = 3.26, p < 0.001) had over 3 times the odds of being classified as high-risk gamblers. Similarly, those screened with moderately severe depression (PHQ-9: n = 38, 27.5%; OR = 4.60, p < 0.001) and severe depression (PHQ-9: n = 22, 15.9%; OR = 4.92, p < 0.001) had nearly 5 times the odds of being high-risk gamblers.

Negative financial impacts attributed to COVID-19 were significant features of high-risk gamblers in the online cohort. Those who reported losing their employment (n = 35, 25.4%; OR = 1.77, p = 0.007) or having work hours reduced (n = 22, 15.9%; OR = 2.44, p = 0.001) had greater odds of high-risk gambling status than other respondents whose employment was not so affected. Respondents who reported that emergency measures influenced their decision to gamble online also had a higher likelihood of high-risk gambling (n = 70, 50.7%; OR = 2.49, p < 0.001).

Cannabis use was associated with high-risk gambling among online players (n = 46, 33.3%; OR = 2.71, p < 0.001). Those reporting gambling online while under the influence of cannabis had over 9 times the odds of being high-risk gamblers (n = 21, 17.8%; OR = 9.47, p < 0.001).

Alcohol use among online gamblers was not significantly associated with high-risk gambling, though increased alcohol consumption during the first 6 weeks following the declaration of emergency measures was (n = 52, 59.1%; OR = 2.07, p = 0.001). Most notable, those gambling online under the influence of alcohol had nearly 9 times the odds of being classified as high-risk gamblers (n = 53, 44.9%; OR = 8.81, p < 0.001).

Three self-reported gambling motives stood out as being most predictive of high-risk gambling status among online gamblers. Gambling to earn income (n = 56, 40.6%; OR = 9.70, p < 0.001), to win back money lost gambling (n = 58, 42.0%; OR = 21.33, p < 0.001) and because it helps when feeling nervous or depressed (n = 46, 33.3%; OR = 20.93, p < 0.001) all had the highest odds for high-risk gambling status. Further analysis of these gambling motives revealed significant associations with elevated forms of anxiety and depression, negative financial impacts due to COVID-19 and problematic gambling under the influence of substances (as shown in Table 3). Tests of scale reliability for these three gambling motives demonstrated good internal consistency (Cronbach’s alpha = 0.83).

Table 3 Association of elevated anxiety and depression, COVID-19 financial impacts and problematic substance use and high-risk gambling motives among online gamblers (N = 1081)

Full size table

Discussion

COVID-19 has had a turbulent effect on the lives of Canadians, including gamblers in Ontario and especially those who play online. This research has contributed new insights into the effects of public health emergency measures, including increased isolation and the closure of multiple services and businesses. It has also reinforced many of the emerging findings on the secondary effects of COVID-19.

Discourse on the secondary impacts of COVID-19 has focused on the effects of isolation, substance use, online gambling and other online behaviours (Douglas et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR15 "Douglas, M., Katikireddi, S. V., Taulbut, M., McKee, M., & McCartney, G. (2020). Mitigating the wider health effects of covid-19 pandemic response. BMJ, 369(April), 1–6. https://doi.org/10.1136/bmj.m1557

            ."); Marsden et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR47 "Marsden, J., Darke, S., Hall, W., Hickman, M., Holmes, J., Humphreys, K., Neale, J., Tucker, J., & West, R. (2020). Mitigating and learning from the impact of COVID-19 infection on addictive disorders. Addiction, 115(6), 1007–1010. 
              https://doi.org/10.1111/add.15080
              
            .")). Only very recently has evidence begun to reflect these concerns, primarily as they relate to increased alcohol consumption and Internet use and dependence (Sun et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR65 "Sun, Y., Li, Y., Bao, Y., Meng, S., Sun, Y., Schumann, G., Kosten, T., Strang, J., Lu, L., & Shi, J. (2020). Increased addictive Internet and substance use behavior during the COVID-19 pandemic in China. American Journal on Addictions, 29, 268–270. 
              https://doi.org/10.1111/ajad.13066
              
            .")). Similarly, Martin et al. ([2014](/article/10.1007/s11469-020-00366-1#ref-CR48 "Martin, R. J., Usdan, S., Cremeens, J., & Vail-Smith, K. (2014). Disordered gambling and co-morbidity of psychiatric disorders among college students: an examination of problem drinking, anxiety and depression. Journal of Gambling Studies, 30(2), 321–333. 
              https://doi.org/10.1007/s10899-013-9367-8
              
            .")) point to a pronounced relationship between problematic alcohol consumption and disordered gambling in their study of college students (_n_ \= 1430) in the US. The evidence presented herein adds additional weight to this discourse by reporting increased alcohol as well as cannabis consumption during the period of study and establishing a significant comorbid relationship between co-occurring substance use, online gambling and high-risk gambling status. Specifically, gambling under the influence of alcohol or cannabis increased the odds of high-risk gambling status by approximately 9 times (_p_ < 0.001). This appears to be a novel finding as the extant literature has to date featured limited examination of online gambling under the influence of alcohol and other substances. Though, the effects of pathological gambling and substance use have been compared and show similarities with respect to impulsivity and compulsivity in decision-making tasks (Leeman and Potenza [2012](/article/10.1007/s11469-020-00366-1#ref-CR41 "Leeman, R. F., & Potenza, M. N. (2012). Similarities and differences between pathological gambling and substance use disorders: a focus on impulsivity and compulsivity. Psychopharmacology, 219(2), 469–490. 
              https://doi.org/10.1007/s00213-011-2550-7
              
            ."); Settles et al. [2012](/article/10.1007/s11469-020-00366-1#ref-CR60 "Settles, R. E., Fischer, S., Cyders, M. A., Combs, J. L., Gunn, R. L., & Smith, G. T. (2012). Negative urgency: a personality predictor of externalizing behavior characterized by neuroticism, low conscientiousness, and disagreeableness. Journal of Abnormal Psychology, 121(1), 160–172. 
              https://doi.org/10.1037/a0024948
              
            .")).

The impact of COVID-19 on mental health has also been a topic of considerable interest and current research activity. Recent evidence has largely highlighted the associations that anxiety and depression appear to have with fear, uncertainty, pre-existing history of addiction and substance use (Ahorsu et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR2 "Ahorsu, D. K., Imani, V., Lin, C., Timpka, T., Broström, A., Updegraff, J. A., … Pakpour, A. H. (2020). Associations between fear of COVID-19, mental health, and preventive behaviours across pregnant women and husbands: an actor-partner interdependence modelling. International Journal of Mental Health and Addiction Addiction. doi https://doi.org/10.1007/s11469-020-00340-x

            ."); Bakioğlu et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR6 "Bakioğlu, F., Korkmaz, O., & Ercan, H. (2020). Fear of COVID-19 and positivity: mediating role of intolerance of uncertainty, depression, anxiety, and stress. International Journal of Mental Health and Addiction. 
              https://doi.org/10.1007/s11469-020-00331-y
              
            ."); Gritsenko et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR26 "Gritsenko, V., Skugarevsky, O., Konstantinov, V., Khamenka, N., Marinova, T., Reznik, A., & Isralowitz, R. (2020). COVID 19 fear, stress, anxiety, and substance use among Russian and Belarusian university students. International Journal of Mental Health and Addiction, 1–7. 
              https://doi.org/10.1007/s11469-020-00330-z
              
            .")). In the present study, those screened for moderate and severe forms of anxiety (25.7%) and depression (12.6%) were more likely to gamble online during the first 6 weeks of emergency measures and be classified as high-risk gamblers. This finding is a confirmation of past studies that have established the relationship between anxiety and depression and problematic gambling (Barrault et al. [2017](/article/10.1007/s11469-020-00366-1#ref-CR7 "Barrault, S., Bonnaire, C., & Herrmann, F. (2017). Anxiety, depression and emotion regulation among regular online poker players. Journal of Gambling Studies, 33(4), 1039–1050. 
              https://doi.org/10.1007/s10899-017-9669-3
              
            ."); El-Guebaly et al. [2006](/article/10.1007/s11469-020-00366-1#ref-CR18 "El-Guebaly, N., Patten, S. B., Currie, S., Williams, J. V. A., Beck, C. A., Maxwell, C. J., & Wang, J. L. (2006). Epidemiological associations between gambling behavior, substance use & mood and anxiety disorders. Journal of Gambling Studies, 22(3), 275–287. 
              https://doi.org/10.1007/s10899-006-9016-6
              
            .")). Among Ontarians who had gambled online, high-risk gambling was even more strongly tied to severe forms of anxiety and depression, financial disruption, co-occurring substance use and risky gambling motives. Conversely, the absence of symptoms of anxiety and depression appeared to have a protective effect on high-risk gambling among those who had gambled online. Recent evidence from China have presented potential mediators of severity relating to mental health concerns, such as anxiety, including urban living, income stability and cohabitation (Cao et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR9 "Cao, W., Fang, Z., Hou, G., Han, M., Xu, X., Dong, J., & Zheng, J. (2020). The psychological impact of the COVID-19 epidemic on college students in China. Psychiatry Research, 287(March), 112934. 
              https://doi.org/10.1016/j.psychres.2020.112934
              
            .")). Financial stress, in particular, has been found to be a catalyst for mental health concerns and problematic gambling in previous representative population studies from the US (Ronzitti et al. [2017](/article/10.1007/s11469-020-00366-1#ref-CR58 "Ronzitti, S., Kraus, S. W., Hoff, R. A., & Potenza, M. N. (2017). Stress moderates the relationships between problem-gambling severity and specific psychopathologies. Psychiatry Research, 259(3), 254–261. 
              https://doi.org/10.1016/j.physbeh.2017.03.040
              
            .")). In the present study, those who gambled online appeared more deeply affected by COVID-19’s financial impact.

Research on the financial effects impacting gamblers during COVID-19, specifically, is still emerging. Although, the findings of this study support past research on the 2008 global economic crisis that have noted a strong relationship between risky gambling and financial hardship (Olason et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR54 "Olason, D. T., Hayer, T., Brosowski, T., & Meyer, G. (2015). Gambling in the mist of economic crisis: results from three national prevalence studies from Iceland. Journal of Gambling Studies, 31(3), 759–774. https://doi.org/10.1007/s10899-015-9523-4

            .")). In the current study, approximately half of all respondents reported disruptions to employment and negative impact on household income attributed to COVID-19\. In both cases, online gamblers felt this impact more substantially, although only greater negative effect on household income was significant (_p_ \= 0.033). However, young adults (18–24 years) who gambled online were 2 to 4 times as likely to have experienced negative impact on household income and lost employment than older cohorts, respectively. Past studies also point out that young adults experiencing financial hardship are more susceptible to problematic gambling and substance use (Colell et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR10 "Colell, E., Sanchez-Niubo, A., Delclos, G. L., Benavides, F. G., & Domingo-Salvany, A. (2015). Economic crisis and changes in drug use in the Spanish economically-active population. Addiction, 10, 1129–1137. 
              https://doi.org/10.1111/add.12923
              
            ."); Gili et al. [2013](/article/10.1007/s11469-020-00366-1#ref-CR23 "Gili, M., Roca, M., Basu, S., McKee, M., & Stuckler, D. (2013). The mental health risks of economic crisis in Spain: evidence from primary care centres, 2006 and 2010. European Journal of Public Health, 23, 103–108. 
              https://doi.org/10.1093/eurpub/cks035
              
            ."); Harhay et al. [2014](/article/10.1007/s11469-020-00366-1#ref-CR29 "Harhay, M. O., Bor, J., Basu, S., McKee, M., Mindell, J. S., Shelton, N. J., & Stuckler, D. (2014). Differential impact of the economic recession on alcohol use among white British adults, 2004–2010. European Journal of Public Health, 24, 410–415. 
              https://doi.org/10.1093/eurpub/ckt134
              
            ."); Olason et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR54 "Olason, D. T., Hayer, T., Brosowski, T., & Meyer, G. (2015). Gambling in the mist of economic crisis: results from three national prevalence studies from Iceland. Journal of Gambling Studies, 31(3), 759–774. 
              https://doi.org/10.1007/s10899-015-9523-4
              
            .")). Negative impact on household income was also correlated with online gambling (_p_ < 0.05) as well as being influenced to gamble online due to COVID-19 (_p_ < 0.001). Those who were influenced by COVID-19 to gamble online also had up to 2 times the odds of being either moderate- or high-risk gamblers. Economou et al.’s ([2019](/article/10.1007/s11469-020-00366-1#ref-CR17 "Economou, M., Souliotis, K., Malliori, M., Peppou, L. E., Kontoangelos, K., Lazaratou, H., Anagnostopoulos, D., Golna, C., Dimitriadis, G., Papadimitriou, G., & Papageorgiou, C. (2019). Problem gambling in Greece: prevalence and risk factors during the financial crisis. Journal of Gambling Studies, 35(4), 1193–1210. 
              https://doi.org/10.1007/s10899-019-09843-2
              
            .")) study of the effects of economic crisis in Greece also reflects the association between financial hardship and problem gambling. The authors also note that the odds of experiencing problem gambling can be increased for those who started gambling during the economic crisis. While the present study did not measure this phenomenon exactly, findings show that a substantial proportion of online gamblers (61.6%) had typically only played in-person over the past 12 months, indicating a partial migration of land-based players to a new, unfamiliar online environment. However, these players had much lower odds of being high-risk gamblers (_n_ \= 666, 8%; OR = 0.34, 95% CI = 0.23–0.49, _p_ < 0.001), indicating that experience with land-based play may have a protective effect, even if online gambling is a less familiar platform, or perhaps participation was characterized by less risky games, such as lottery.

Broadly speaking, this research has reaffirmed relationships articulated in past research on risky online gambling and comorbidities, including mental health concerns and substance use (Awaworyi Churchill and Farrell [2018](/article/10.1007/s11469-020-00366-1#ref-CR5 "Awaworyi Churchill, S., & Farrell, L. (2018). The impact of gambling on depression: new evidence from England and Scotland. Economic Modelling, 68(2017), 475–483. https://doi.org/10.1016/j.econmod.2017.08.021

            ."); Gainsbury [2015](/article/10.1007/s11469-020-00366-1#ref-CR21 "Gainsbury, S. M. (2015). Online gambling addiction: the relationship between Internet gambling and disordered gambling. Current Addiction Reports, 2(2), 185–193. 
              https://doi.org/10.1007/s40429-015-0057-8
              
            ."); Hing et al. [2014](/article/10.1007/s11469-020-00366-1#ref-CR30 "Hing, N., Cherney, L., Gainsbury, S. M., Lubman, D. I., Wood, R. T., & Blaszczynski, A. (2014). Maintaining and losing control during internet gambling: a qualitative study of gamblers’ experiences. New Media & Society, 17(7), 1075–1095. 
              https://doi.org/10.1177/1461444814521140
              
            ."); LaPlante et al. [2009](/article/10.1007/s11469-020-00366-1#ref-CR39 "LaPlante, D. A., Nelson, S. E., Labrie, R. A., & Shaffer, H. J. (2009). Disordered gambling, type of gambling and gambling involvement in the British Gambling Prevalence Study 2007. European Journal of Public Health. 
              https://doi.org/10.1093/eurpub/ckp177
              
            ."); Lloyd et al. [2010a](/article/10.1007/s11469-020-00366-1#ref-CR43 "Lloyd, J., Doll, H., Hawton, K., Dutton, W. H., Geddes, J. R., Goodwin, G. M., & Rogers, R. D. (2010a). How psychological symptoms relate to different motivations for gambling: an online study of internet gamblers. Biological Psychiatry, 68(8), 733–740. 
              https://doi.org/10.1016/j.biopsych.2010.03.038
              
            ."); Scholes-Balog and Hemphill [2012](/article/10.1007/s11469-020-00366-1#ref-CR59 "Scholes-Balog, K. E., & Hemphill, S. A. (2012). Relationships between online gambling, mental health, and substance use: a review. Cyberpsychology, Behavior and Social Networking, 15(12), 688–692. 
              https://doi.org/10.1089/cyber.2012.0232
              
            ."); Wardle et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR66 "Wardle, H., Moody, A., Griffiths, M., Orford, J., & Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11(3), 339–356. 
              https://doi.org/10.1080/14459795.2011.628684
              
            .")). Notably, this research adds to the limited evidence showing significant associations between cannabis use, online gambling and mental health concerns—particularly depression (Potenza et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR57 "Potenza, M. N., Wareham, J. D., Steinberg, M. A., Rugle, L., Cavallo, D. A., Krishnan-Sarin, S., & Desai, R. A. (2011). Correlates of at-risk/problem internet gambling in adolescents. Journal of the American Academy of Child and Adolescent Psychiatry, 50(2), 150–159.e3. 
              https://doi.org/10.1016/j.jaac.2010.11.006
              
            .")). For instance, evidence presented herein separately show that high-risk gambling was predicted by moderately severe and severe depression as well as cannabis use and gambling under the influence of cannabis. In addition, previous prevalence study analysis showing a typical mix of land-based and online plays among individuals indicating online gambling behaviours was evident in the current study (Wardle et al. [2011](/article/10.1007/s11469-020-00366-1#ref-CR66 "Wardle, H., Moody, A., Griffiths, M., Orford, J., & Volberg, R. (2011). Defining the online gambler and patterns of behaviour integration: evidence from the British Gambling Prevalence Survey 2010. International Gambling Studies, 11(3), 339–356. 
              https://doi.org/10.1080/14459795.2011.628684
              
            .")). In this case, over 60% of the sample had technically migrated from self-reported land-based-only play in the past 12 months to gambling online during the period of emergency measures. Further study is required to understand if respondents understood typical land-based-only gambling as being strictly exclusive or simply a general distinction as well as the number of games played and its relationship with gambling risk.

Finally, those indicating they gambled online because it helps when feeling nervous or depressed, to win back money lost gambling and to earn income had increased odds of high-risk gambling status between 9- and 21-times that of gamblers who did not endorse these motives (p < 0.001). These findings compliment past research highlighting the risk of problem gambling among those endorsing these motives (Lambe et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR38 "Lambe, L., Mackinnon, S. P., & Stewart, S. H. (2015). Validation of the gambling motives questionnaire in emerging adults. Journal of Gambling Studies, 31(3), 867–885. https://doi.org/10.1007/s10899-014-9467-0

            ."); Nower and Blaszczynski [2010](/article/10.1007/s11469-020-00366-1#ref-CR52 "Nower, L., & Blaszczynski, A. (2010). Gambling motivations, money-limiting strategies, and precommitment preferences of problem versus non-problem gamblers. Journal of Gambling Studies, 26, 361–372. 
              https://doi.org/10.1007/s10899-009-9170-8
              
            .")). As mentioned previously, these motives were intended to reflect key mental health factors (i.e. anxiety and depression) as well as escape from and relief of financial stress (Wood and Griffiths [2007](/article/10.1007/s11469-020-00366-1#ref-CR68 "Wood, R. T. A., & Griffiths, M. D. (2007). A qualitative investigation of problem gambling as an escape-based coping strategy. Psychology and Psychotherapy, 80, 107–125. 
              https://doi.org/10.1348/147608306X107881
              
            .")). For example, the 2008 economic crisis in Iceland saw increased likelihood of gambling if individuals had experienced financial difficulties (Olason et al. [2015](/article/10.1007/s11469-020-00366-1#ref-CR54 "Olason, D. T., Hayer, T., Brosowski, T., & Meyer, G. (2015). Gambling in the mist of economic crisis: results from three national prevalence studies from Iceland. Journal of Gambling Studies, 31(3), 759–774. 
              https://doi.org/10.1007/s10899-015-9523-4
              
            .")). The present study has linked these motives to comorbid mental health concerns, substance use while gambling and financial vulnerabilities due to COVID-19\. For instance, all three of these motives featured strong predictive relationships with moderate and severe symptoms of anxiety and depression. Variously, these motives were also associated with COVID-19-related financial impacts, including reduced work hours, lost employment and negative impact on household income. These motives also significantly increased the odds of gambling under the influence of alcohol and cannabis, an association that has typically been highlighted in adolescent gambling and not online gambling among a general population (Hammond et al. [2014](/article/10.1007/s11469-020-00366-1#ref-CR28 "Hammond, C. J., Pilver, C. E., Rugle, L., Steinberg, M. A., Mayes, L. C., Malison, R. T., Krishnan-Sarin, S., Hoff, R. A., & Potenza, M. N. (2014). An exploratory examination of marijuana use, problem-gambling severity, and health correlates among adolescents. Journal of Behavioral Addictions, 3(2), 90–101. 
              https://doi.org/10.1556/JBA.3.2014.009
              
            ."); Welte et al. [2004](/article/10.1007/s11469-020-00366-1#ref-CR67 "Welte, J. W., Barnes, G. M., Wieczorek, W. F., & Tidwell, M.-C. (2004). Simultaneous drinking and gambling: a risk factor for pathological gambling. Substance Use & Misuse, 39(9), 1405–1422. 
              https://doi.org/10.1081/JA-120039397
              
            .")).

Limitations

As a cross-sectional online panel survey, the data is not able to provide causal assessment of the key associations identified. Self-reported behaviours are also prone to a degree of response bias which is a typical limitation of survey methods and designs. Although questions assessing anxiety and depression as well as gambling risk have been validated and shown to be reliable, other questions relating to COVID-19’s impact on financial well-being and substance use have not been previously vetted. In addition, the inclusion of selected questions from the Gambling Motives Questionnaire, instead of the entire validated instrument, limits the broader understanding of gambling motives and may give the impression negative gambling bias. The intention in this case was to reflect the influence of mental health concerns and financial stress that are a focus on this study. As such, the inclusion of the motive to earn income, added a monetary distinction not represented in the full Gambling Motives Questionnaire and is particularly relevant to risky online gambling (Mulkeen et al. 2017).

Despite these limitations, this survey has rapidly delivered key insights during a critical moment in human history on social dynamics and public health determinants that clearly merit further study. As such, this study will soon be followed up by another linking the same respondents at a future time. Follow-up research will carefully examine potential changes in behaviours and comorbidities as the pandemic evolves and as gambling changes with the resumption of professional sports and the widespread re-opening of land-based venues.

Conclusion

This study has confirmed many of the risk associations presented in past research on global economic crisis, gambling risk, mental health concerns and substance use. However, unlike many past studies, the present paper takes note of all of these elements together and provides a clear emphasis on online gambling. Together, the strength of high-risk gambling motives in predicting problematic gambling status, mental health concerns, financial difficulties and risky substance use among online gamblers was a novel insight worth further exploration. Overall, COVID-19’s unique effect of creating significant population health impacts, financial disruptions and changes in social interaction and recreation adds importance to this study’s findings and raises key questions. For instance, future studies may benefit from observing changes in online gambling behaviours and associated risk factors during the pandemic or how the eventual re-opening of land-based venues may affect gambling sentiments and behaviours. Further examination of government and industry response to COVID-19 and gambling harm prevention will also be critical to understanding these complex phenomena. Knowledge from this and other studies of the impact of COVID-19 on online gambling and various comorbidities should also serve to inform decision-makers on harm prevention and mitigation efforts, as already indicated by some experts in the field (Király et al. [2020](/article/10.1007/s11469-020-00366-1#ref-CR35 "Király, O., Potenza, M. N., Stein, D. J., King, D. L., Hodgins, D. C., Saunders, J. B., Griffiths, M. D., Gjoneska, B., Billieux, J., Brand, M., Abbott, M. W., Chamberlain, S. R., Corazza, O., Burkauskas, J., Sales, C. M. D., Montag, C., Lochner, C., Grünblatt, E., Wegmann, E., Martinotti, G., Lee, H. K., Rumpf, H. J., Castro-Calvo, J., Rahimi-Movaghar, A., Higuchi, S., Menchon, J. M., Zohar, J., Pellegrini, L., Walitza, S., Fineberg, N. A., & Demetrovics, Z. (2020). Preventing problematic internet use during the COVID-19 pandemic: consensus guidance. Comprehensive Psychiatry, 100, 1–4. https://doi.org/10.1016/j.comppsych.2020.152180

            .")).

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Funding

The Responsible Gambling Council allocated funding for this project to support program needs assessment for its community outreach and prevention programs. These programs are funded by the Ontario Ministry of Health and Long-Term Care’s Problem Gambling Prevention Fund.

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  1. Centre for the Advancement of Best Practices, The Responsible Gambling Council, 205-411 Richmond Street East, Toronto, Ontario, M5A 3S5, Canada
    Alex Price

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The author is employed by the Responsible Gambling Council (RGC), a not-for-profit organization, as a Senior Researcher, which administered funding for this project. The author is also a member of the Ontario Gambling Research Society and has received funding from Carleton University in Ottawa, Ontario, Canada, to conduct follow-up research on this study as a co-investigator.

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All procedures performed in this study involving human participants were in accordance with the ethical standards of Carleton University’s Research Ethics Board and with the 1975 Helsinki Declaration.

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Price, A. Online Gambling in the Midst of COVID-19: A Nexus of Mental Health Concerns, Substance Use and Financial Stress.Int J Ment Health Addiction 20, 362–379 (2022). https://doi.org/10.1007/s11469-020-00366-1

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