Market forces: Does gambling advertising increase problem gambling?

Anyone who watched the Euro 2016 football tournament on ITV a couple of months ago will have noticed the many offers to gamble on the matches. You were encouraged to download the bookies’ mobile apps, or asked to bet-in-play and gamble responsibly. But how do we respond to gambling ads? Do they actually draw us in? Arguably the most noticeable change in the British gambling landscape since the Gambling Act came into force in September 2007 has been the large increase in gambling advertising on television. Prior to this, the only gambling ads allowed on TV were those for National Lottery products, bingo, and the football pools.

In 2013, Ofcom published their research examining the volume, scheduling, frequency and exposure of gambling advertising on British television. The findings showed that there had been a 600% increase in UK gambling advertising between 2006 and 2012 – more specifically, there were 1.39m adverts on television in 2012 compared to 152,000 in 2006. The report also showed that gambling adverts accounted for 4.1% of all advertising seen by viewers in 2012, up from 0.5% in 2006 and 1.7% in 2008.

So is the large increase having any effect on gambling and problem gambling? In 2007, prior to there being widespread gambling ads on TV, the British Gambling Prevalence Survey (BGPS) of over 9,000 people (aged 16 years and over) reported that 0.6% of them were problem gamblers. In the 2010 BGPS, the problem gambling prevalence rate had increased by half to 0.9%. Some of this increase may, arguably, have been due to increased gambling advertising. However, the latest British survey research shows that the prevalence of problem gambling is back down (to 0.5%), so perhaps increased gambling advertising hasn’t resulted in an increase of problem gambling.

Surprisingly, there is relatively little scientific evidence that advertising directly influences gambling participation and problem gambling. This is partly because demonstrating empirically that the negative effects of gambling are solely attributable to advertising is hard. For instance, a study of 1,500 people in New Zealand by Ben Amey, a governmental social science researcher at the Ministry of Internal Affairs, reported an association between participation in gambling activities and recall of gambling advertising. The study fund that over 12 months, 83% of people who had gambled between zero and three times remembered seeing gambling ads during that time. For people that had gambled four or more times, the figure was at 93%.

Last year, research colleagues from the University of Bergen in Norway and I published one of the largest studies carried out on gambling advertising. It involved more than 6,000 people and examined three specific dimensions of gambling advertising impacts: gambling-related attitudes, interest, and behavior (“involvement”); knowledge about gambling options and providers (“knowledge”); and the degree to which people are aware of gambling advertising (“awareness”). Overall, we found that impacts were strongest for the “knowledge” dimension. We also found that for all three dimensions, the impact increased with the level of advertising exposure.

We then compared the responses from problem gamblers against those of recreational (non-problem) gamblers. We found that problem gamblers were more likely than recreational gamblers to agree that gambling advertising increased their gambling involvement and knowledge, and that they were more aware of gambling advertising. In simple terms, our study showed that gambling advertising has a greater impact on problem gamblers than recreational gamblers. This indirectly supports previous research showing that problem gamblers often mention that gambling advertising acts as a trigger to their gambling.

We also found that younger gamblers were more likely than older ones to agree that advertising increased their gambling involvement and knowledge. This supports previous research showing that problem gambling is associated with stronger perceived advertising impacts among adolescents. One of the more worrying statistics reported in the Ofcom study was that children under 16 years of age were each exposed to an average of 211 gambling adverts a year (adults saw an average of 630). I am a firm believer that gambling is an adult activity and that gambling adverts should be shown only after the 9pm watershed. Unfortunately, all televised sporting events such as Euro 2016 can feature gambling ads at any time of the day, and that means that tens of thousands of schoolchildren have been bombarded with gambling ads over the last month.

Most of us who work in the field of responsible gambling agree that advertising “normalises” gambling and that all relevant governmental gambling regulatory agencies should prohibit aggressive advertising strategies, especially those that target impoverished individuals or youths. Most of the research data on gambling advertising uses self-report data (surveys, focus groups, interviews, etc.) and very little of these data provide an insight into the relationship between advertising and problem gambling. A review by the British lawyer Simon Planzer and Heather Wardle (the lead author of the last two BGPS surveys) concluded that gambling advertising is an environmental factor that has the power to shape attitudes and behaviours relating to gambling – but just how powerful it is remains unclear.

Overall, the small body of research on the relationship between gambling advertising and problem gambling has few definitive conclusions. If gambling advertising does have an effect, it appears to impact specific groups (such as problem gamblers and adolescents) but most of this research uses self-reported data that has been shown to be unreliable among gamblers.

At best, the scientific research only hints at the potential dangers of gambling ads. But in order to challenge the increasing normalisation of gambling among these most-at-risk groups, we need more robust evidence. Only then will we be able to understand the psychosocial impact of the kind of blanket advertising seen by children and adults during major sporting events such as Euro 2016.

(N.B. A version of this article was first published in The Conversation)

Dr Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (1997). Children and gambling: The effect of television coverage and advertising. Media Education Journal, 22, 25-27.

Griffiths, M.D. (2005). Does advertising of gambling increase gambling addiction? International Journal of Mental Health and Addiction, 3(2), 15-25.

Griffiths, M.D. (2010). Media and advertising influences on adolescent risk behaviour. Education and Health, 28(1), 2-5.

Griffiths, M.D. (2010). Social responsibility in marketing for online gaming affiliates. i-Gaming Business Affiliate, June/July, p.32.

Griffiths, M.D. (2013). Responsible marketing and advertising of gambling. i-Gaming Business Affiliate, August/September, 50.

Hanss, D., Mentzoni, R.A., Griffiths, M.D., & Pallesen, S. (2015). The impact of gambling advertising: Problem gamblers report stronger impacts on involvement, knowledge, and awareness than recreational gamblers. Psychology of Addictive Behaviors, 29, 483-491.

Lopez-Gonzalez, H. & Griffiths, M.D. (2016). Is European online gambling regulation adequately addressing in-play betting advertising? Gaming Law Review and Economics, in press.

Reid, J. & Griffiths, M.D. (2004). Lotteries, television advertising, and televised lottery draws, Panorama (European State Lotteries and Toto Association), 15, 8-9.

Zangeneh, M., Griffiths, M.D. & Parke, J. (2008). The marketing of gambling. In Zangeneh, M., Blaszczynski, A., and Turner, N. (Eds.), In The Pursuit Of Winning (pp. 135-153). New York: Springer.

Test augmentation: 10 reasons why ‘Pokémon Go’ is so appealing

“Pokémon Go is a free-to-play location-based augmented reality mobile game developed…Making use of GPS and the camera of compatible devices, the game allows players to capture, battle, and train virtual creatures, called Pokémon [pocket monsters] who appear on device screens as though in the real world. The game is free-to-play, although it supports in-app purchases of additional gameplay items” (Wikipedia, 2016)

Unless you’re news-shy, off-grid, and/or a hermit, you can’t fail to have noticed all the media hype surrounding Pokémon Go. My youngest son and seemingly all of is friends have been out and about enjoying playing the latest gaming phenomenon. A lot of the press stories that I have read concentrate on the allegedly ‘addictive’ properties of the game (see ‘Further reading’ below). But what makes Pokémon Go such an appealing game? Here are my top ten reasons:

(1) It’s a popular franchise with a novel twist

Pokémon is a huge franchise with lots of associated spin-offs (animates films, carton television show, card games, figures to collect, etc.). And unlike some franchises, it’s a game that appears to be popular across age and gender but various aspects of the game (such as the use of augmented reality) give the game a novel twist on most other games (by utilizing real-world locations in which players explore their neighbourhood locality or wherever they happen to be).

(2) It’s fun, free to play, easy to play, and easy to access

Unlike many popular games, you don’t need a dedicated console to play the game. There is little in the way of barriers to entry. Anyone who has a smartphone can download Pokémon Go and it can be played anywhere at any time because it is played on a mobile device in which players try to catch Pokémon at specific locations (‘PokéStops’). This means that the number of potential users is huge, even in comparison to console games. In addition, there are no complicated buttons to press or controls to use. Most importantly it’s fun and free to play (but players can buy in-game items, an area that I’ve done a bit of research on which I outlined in a previous blog).

(3) It’s nostalgic and a ‘blast from the past’

Pokémon Go features many of the early ‘classic’ Pokémon characters (the ones that you could name in a pub quiz) hailing back to the 1990s. As well as attracting new and younger players, adults who loved Pokémon as a child or teenager can now re-live some of their childhood and adolescence. In short, some players can experience something new yet familiar. A research review carried out by Dr. Constantine Sedikides and Dr. Tim Wildschut demonstrated that “nostalgia has remarkable implications for one’s future. It strengthens approach orientation, raises optimism, evokes inspiration, boosts creativity, and kindles prosociality. Far from reflecting escapism from the present, nostalgia potentiates an attainable future”. A number of online articles coomenting on the popularity of Pokémon have included quotes about the game’s nostalgic element from Dr. Jamie Madigan (author of the 2015 book Getting Gamers: The Psychology of Video Games and Their Impact on People Who Play Them). He asserted that “if nostalgia is in play, and it evokes this positive emotion…our brain can substitute the question, ‘Does this make me happy’ for ‘Is this a good game?’”

(4) It’s a social game (if you want it to be)

Back in the early and mid-2000s I published a number of studies showing that the most important reason for playing online multiplayer games was for social reasons and to connect and interact with other players. The great think about Pokémon Go is that meeting other players face-to-face is almost inevitable as the game is played outside and on the move, and it’s easy to spot other like-minded players. People can make new friendships or consolidate existing ones. Players talk to each other and can share their experiences. Some may even have shared memories that plugs into feelings of nostalgia. However, Pokémon Go players (if they so wish) can play on their own too. The game is flexible enough to adapt to the player.

(5) It features augmented reality

One of the defining features of Pokémon Go is that augmented reality is a fundamental (and arguably the main) part of the game. Augmented reality (AR) is defined as “a live direct or indirect view of a physical, real-world environment whose elements are augmented (or supplemented) by computer-generated sensory input such as sound, video, graphics or GPS [global positioning system] data”. Pokémon Go has successfully managed to embed AR into the game which some players claim makes characters feel “more alive”. An article on the phenomenon in Time magazine said that Pokémon Go provides “the illusion that wild Pokémon are out there in the real world, waiting to be caught”. There are also some claims (such as a paper by Dr. Keith Bujak and his colleagues in a paper published in a 2013 issue of the journal Computers and Education) that augmented reality can be potentially addictive. The authors claim that children are most at risk from AR addiction and assert that:

“Augmented reality does not separate the user from his reality but instead uses it and realistically transforms it…This effect can cause a high degree of surprise and curiosity in users”.

(6) It’s motivating

Any one who plays videogames or researches in the area knows that successful games have to be motivating to play. Rewards within Pokémon Go help players to foster achievement, and achieving goals within the game drives motivation. As an article on the Keep It Suitable website noted: “The self-confidence that arises from the achievement of a goal – catching a Pikachu – motivates people to play more and more…and ‘Pokémon Go’ players are indeed very motivated…The ease with which the reward comes every time your phone buzzes, alerting you that a Pokémon is nearby, is very basic psychological conditioning”.

(7) It involves collecting

In a number of my previous blogs I have written about the psychology of collecting and this also appears to be one of the attractions concerning all things Pokémon (in fact the Pokémon mantra has always been “Gotta catch ‘em all”). In my articles I have always referenced the work of Professor Russell Belk who has written a lot of books and papers on the topic. He was interviewed by Forbes magazine on the topic of Pokémon Go. The Forbes article noted:

“In a 1991 article published in the ‘Journal of Social Behavior and Personality’, Belk described two main types of collecting: aesthetic and taxonomic. Aesthetic collecting occurs when objects aren’t in limited supply and so adding things to your collection depends on personal preferences. This includes artwork, but not pocket monsters. ‘I expect no matter how beautiful or ugly the Pokémon is, there’s relatively little aesthetic judgment,” says Belk…’You want them all — or as many as possible’. Collecting Pokémon is a lot like building a coin or stamp collection. It involves taxonomy – the process of naming and classifying things into groups. Taxonomic collecting can end temporarily but continue later: the original Game Boy games (Pokémon Red and Pokémon Blue) featured 151 monster ‘species,’ but sequels have pushed that number over 700. If ‘Pokémon Go’ remains popular and profitable in the long term, the app’s developer will no doubt add new species. Belk adds that the desire to collect isn’t driven by a need to complete a collection. ‘You’re not striving for that closure as much as striving for bigger and better collections…That implies some social comparisons – that your collection is in some sense better than theirs.”

In the same article, reference was also made to a just published literature review (‘Extended self and the digital world’) by Professor Belk in the journal Current Opinion in Psychology. In the paper Belk claims collecting has now gone beyond physical items and can now include the collecting of digital artefacts. As Belk notes:

“Collecting digital objects can have advantages over physical possessions. While coins and stamps are kept in cabinets at home, you can store an entire collection of ‘Pokémon’ on your phone to show friends…One reason why ‘Pokémon Go’ is so popular is that it puts digital monsters in the real world. Like finding a rare book in an antique shop, this turns the discovery of Pokémon — the challenge or thrill of the chase — into a story. With augmented reality, they’ve made the ‘thrill of the hunt’ in a version where you can tweet about it, you can post about it on your website, you can carry around images of the Pokémon that you’ve collected…That’s a conversation piece, and something you can carry with you or brag about online.”

(8) It gets people active without them really knowing it

A number of articles on Pokémon Go have noted that playing the game has meant players having to go outdoors and walk miles to catch the Pokémon. In short, if you want to do well in the game, you have to get out the house and do some exercise. As one article summed up on this aspect: ‘The running meme is that Pokémon Go managed to do in 24 hours what Michelle Obama could not manage over the course of 8 years: get people outside and active…It turns out gamification of healthy activities can be done and that’s potentially a huge win for the gaming subset of our society that doesn’t exactly have the healthiest track record”. Personally, I’m not convinced that Pokémon Go is as good as more traditional ‘exergaming’ (such as playing Wii Sports) but I can’t deny that it gets people out of a sedentary routine.

(9) It’s a never-ending game

Pokémon Go is a non-linear game in which every user’s playing experience is different given that it uses the person’s individual geo-location. Like many massively multiplayer online games, there is no end to the game and some players continue playing because of FOMO (fear of missing out). Ultimately there is theoretically no limit to how many Pokémon a player can catch or how the game might evolve over time.

(10) The rewards are unpredictable

Over the years I have written countless papers talking about the role of random ratio reinforcement schedules (operant condition processes) that underlie repetitive behaviour (that in extreme cases can result in gambling and gaming addictions). In simple terms, playing a videogame or a slot machine results in intermittent and unpredictable rewards. Knowing when a reward is coming gets boring in the long run but games where the player doesn’t know when the next reward is coming (like when in the Pokémon Go game, the player will next see a Pokémon to catch). Anticipated rewards (similarly to actual rewards) also facilitate dopamine (one of the most important ‘feel good’ neurotransmitters in the human body) release in the body. In fact, a paper by Dr. Patrick Anselm and Dr. Mike Robinson published in the journal Frontiers in Behavioral Neuroscience argued that dopamine release “seems to reflect the unpredictability of reward delivery rather than reward per se” and suggests that the motivation to gamble or play videogames “is strongly (though not entirely) determined by the inability to predict reward occurrence”. In short, playing Pokémon Go can keep you playing longer than you might have originally intended.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Anselme, P. & Robinson, M.J.F. (2013) What motivates gambling behavior? Insight into dopamine’s role. Frontiers in Behavioral Neuroscience, 7, 182. doi: 10.3389/fnbeh. 2013.00182

Belk, R. W. (1991). The ineluctable mysteries of possessions. Journal of Social Behavior and Personality, 6(6), 17-55.

Belk, R. (2016). Extended self and the digital world. Current Opinion in Psychology, 10, 50-54.

Bujak, K.R., Radu, I., Catrambone, R., Macintyre, B., Zheng, R., & Golubski, G. (2013). A psychological perspective on augmented reality in the mathematics classroom. Computers & Education, 68, 536-544.

Chamary, J.V. (2016). Science explains why you’re addicted to Pokémon GO. Forbes, July, 12. Located at: http://www.forbes.com/sites/jvchamary/2016/07/12/science-collecting-pokemon/#276f49ac6d2e

Cleghorn, J. & Griffiths, M.D. (2015). Why do gamers buy ‘virtual assets’? An insight in to the psychology behind purchase behaviour. Digital Education Review, 27, 98-117.

Cole, H. & Griffiths, M.D. (2007). Social interactions in Massively Multiplayer Online Role-Playing gamers. CyberPsychology and Behavior, 10, 575-583.

Griffiths, M.D., Davies, M.N.O. & Chappell, D. (2003). Breaking the stereotype: The case of online gaming. CyberPsychology and Behavior, 6, 81-91.

Griffiths, M.D., Davies, M.N.O. & Chappell, D. (2004). Demographic factors and playing variables in online computer gaming. CyberPsychology and Behavior, 7, 479-487.

Griffiths, M.D., Davies, M.N.O. & Chappell, D. (2004). Online computer gaming: A comparison of adolescent and adult gamers. Journal of Adolescence, 27, 87-96.

Duhi, A. (2016). Caught ’em all?: Why Pokémon Go is so addicting. FSU News, July 19. Located at: http://www.fsunews.com/story/news/2016/07/19/caught-em-all-why-pokemon-go-so-addicting/87309612/

Eadiccio, L. (2016). Psychology experts explain why ‘Pokemon Go’ is so addictive. Time, July 12. Located at: http://time.com/4402123/pokemon-go-nostalgia/

Goodwin, R. (2016). Why the hell is everyone so addicted to Pokemon Go? Know Your Mobile, July 14. Located at: http://www.knowyourmobile.com/games/pokemon-go/23690/why-hell-everyone-so-addicted-pokemon-go

Keep It Suitable (2016). 10 Reasons from real users: Why is Pokemon Go so addictive? July 16. Located at: http://www.keepitusable.com/blog/?p=3579

Kubas-Meyer, A. (2016). Pokémon GO Is the most addictive gaming app ever. Daily Beast, July 11. Located at: http://www.thedailybeast.com/articles/2016/07/11/pokemon-go-is-the-most-addictive-gaming-app-ever.html

Sedikides, C., & Wildschut, T. (2016). Past forward: Nostalgia as a motivational force. Trends In Cognitive Sciences, 20(5), 319-321.

Smith, C. (2016). Science explains why you’re so addicted to Pokemon Go. BGR.com, July 13. Located at: http://bgr.com/2016/07/13/pokemon-go-game-addiction/

Wikipedia (2016). Pokémon Go. Located at: https://en.wikipedia.org/wiki/Pokémon_Go

Williams, C. (2016). Why everyone is addicted to Pokemon Go. Looper, July 14. Located at: http://www.looper.com/18330/everyone-addicted-pokemon-go/

More term warfare: Is the concept of ‘internet addiction’ a misnomer?

A recent study by Professor Phil Reed and his colleagues published in the Journal of Clinical Psychiatry provided some experimental evidence that internet addicts may be conditioned by what they view on the screen. Given that I was the first person in the world to publish an academic paper on internet addiction back in November 1996 it’s good to see that the number of studies into internet addiction has grown substantially over the last 20 years and that there are now hundreds of studies that have investigated the disorder worldwide in many different ways.

This newly published study is one of the few in the field that has investigated internet addiction from an experimental perspective (as opposed the majority that use self-report survey methods and the increasing number of neuroimaging studies examining what happens inside the brains of those who spend excessive amounts of time online).

Professor Reed’s study involved 100 adult volunteers who were deprived of internet access for four hours. The research team then asked the participants to name a colour (the first one that they could think of) and then gave them 15 minutes to access any websites that they wanted to on the internet. The research team monitored all the sites that the participants visited and after the 15-minute period they were again asked to think of the first colour that came to mind. The participants were also asked to complete various psychometric questionnaires including the Internet Addiction Test (IAT). The IAT is a 20-item test where each item is scored from 0 [not applicable] or 1 [rarely] up to 5 [always]. An example item is “How often do you check your e-mail before something else that you need to do?” Those scoring 80 or above (out of 100) are typically defined as having a probable addiction to the internet by those who have used the IAT in previous studies.

Those classed as “high problem [internet] users” on the basis of IAT scores (and who were deprived internet access) were more likely to choose a colour that was prominent on the websites they visited during the 15-minute period after internet deprivation. This wasn’t found in those not classed as internet addicts. Professor Reed said:

“The internet addicts chose a colour associated with the websites they had just visited [and] suggests that aspects of the websites viewed after a period without the net became positively valued. Similar findings have been seen with people who misuse substances, with previous studies showing that a cue associated with any drug that relieves withdrawal becomes positively valued itself. This is the first time though that such an effect has been seen for a behavioural addiction like problematic internet usage”.

While this is an interesting finding there are some major shortcomings both from a methodological standpoint and from a more conceptual angle. Firstly, the number of high problem internet users that were deprived internet access for four hours comprised just 12 individuals so the sample size was incredibly low. Secondly, the individuals classed as high problem internet users had IAT scores ranging from 40 to 72. In short, it is highly unlikely that any of the participants were actually addicted to the internet. Thirdly, although the IAT is arguably the most used screen in the field, it has questionable reliability and validity and is now very out-dated (having been devised in 1998) and does not use the criteria suggested for Internet Disorder in the latest (fifth) edition of the American Psychiatric Association’s Diagnostic and Statistical Manual of Mental Disorders (DSM-5). Using more recently developed instruments such as our own Internet Disorder Scale would have perhaps overcome some of these problems.

There are also much wider problems with the use of the term ‘internet addiction’ as most studies in the field have really investigated addictions on the internet rather than to the internet. For instance, individuals addicted to online gaming, online gambling or online shopping are not internet addicts. They are gambling addicts, gaming addicts or shopping addicts that are using the medium of the internet to engage in their addictive behaviour. There are of course some activities – such as social networking – that could be argued to be a genuine type of internet addiction as such activities only take place online. However, the addiction is to an application rather than the internet itself and this should be termed social networking addiction rather than internet addiction. In short, the overwhelming majority of so-called internet addicts are no more addicted to the internet than alcoholics are addicted to the bottle.

A shorter version of this article was first published in The Conversation

Dr Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. & Kuss, D.J. (2015). Online addictions: The case of gambling, video gaming, and social networking. In Sundar, S.S. (Ed.), Handbook of the Psychology of Communication Technology (pp.384-403). Chichester: Wiley-Blackwell.

Griffiths, M.D., Kuss, D.J. & Demetrovics, Z. (2014). Social networking addiction: An overview of preliminary findings. In K. Rosenberg & L. Feder (Eds.), Behavioral Addictions: Criteria, Evidence and Treatment (pp.119-141). New York: Elsevier.

Griffiths, M.D., Kuss, D.J., Billieux J. & Pontes, H.M. (2016). The evolution of internet addiction: A global perspective. Addictive Behaviors, 53, 193–195.

Griffiths, M.D. & Pontes, H.M. (2014). Internet addiction disorder and internet gaming disorder are not the same. Journal of Addiction Research and Therapy, 5: e124. doi:10.4172/2155-6105.1000e124.

Kuss, D.J. & Griffiths, M.D. (2015). Internet Addiction in Psychotherapy. Basingstoke: Palgrave Macmillan.

Kuss, D.J., Griffiths, M.D., Karila, L. & Billieux, J. (2014). Internet addiction: A systematic review of epidemiological research for the last decade. Current Pharmaceutical Design, 20, 4026-4052.

Osborne, L. A., Romano, M., Re, F., Roaro, A., Truzoli, R., & Reed, P. (2016). Evidence for an internet addiction disorder: internet exposure reinforces color preference in withdrawn problem users. Journal of Clinical Psychiatry, 77(2), 269-274.

Pontes, H.M., Kuss, D.J. & Griffiths, M.D. (2015). The clinical psychology of Internet addiction: A review of its conceptualization, prevalence, neuronal processes, and implications for treatment. Neuroscience and Neuroeconomics, 4, 11-23.

Pontes, H.M., Szabo, A. & Griffiths, M.D. (2015). The impact of Internet-based specific activities on the perceptions of Internet Addiction, Quality of Life, and excessive usage: A cross-sectional study. Addictive Behaviors Reports, 1, 19-25.

Career to the ground: A brief overview of our recent papers on workaholism

Following my recent blogs where I outlined some of the papers that my colleagues and I have published on mindfulness, Internet addiction, gaming addiction, sex addiction, responsible gambling, shopping addiction, exercise addiction, and youth gambling, here is a round-up of papers that my colleagues and I have published on workaholism and work addiction over the last few years.

Andreassen, C.S., Griffiths, M.D., Hetland, J. & Pallesen, S. (2012). Development of a Work Addiction Scale. Scandinavian Journal of Psychology, 53, 265-272.

• Research into excessive work has gained increasing attention over the last 20 years. Terms such as “workaholism,””work addiction” and “excessive work” have been used interchangeably. Given the increase in empirical research, this study presents the development of the Bergen Work Addiction Scale (BWAS), a new psychometrically validated scale for the assessment of work addiction. A pool of 14 items, with two reflecting each of seven core elements of addiction (i.e., salience, mood modification, tolerance, withdrawal, conflict, relapse, and problems) was initially constructed. The items were then administered to two samples, one recruited by a web survey following a television broadcast about workaholism (n=11,769) and one comprising participants in the second wave of a longitudinal internet-based survey about working life (n=368). The items with the highest corrected item-total correlation from within each of the seven addiction elements were retained in the final scale. The assumed one-factor solution of the refined seven-item scale was acceptable (root mean square error of approximation=0.077, Comparative Fit Index=0.96, Tucker-Lewis Index=0.95) and the internal reliability of the two samples were 0.84 and 0.80, respectively. The scores of the BWAS converged with scores on other workaholism scales, except for a Work Enjoyment subscale. A suggested cut-off for categorization of workaholics showed good discriminative ability in terms of working hours, leadership position, and subjective health complaints. It is concluded that the BWAS has good psychometric properties.

Andreassen, C.S., Griffiths, M.D., Hetland, J., Kravina, L., Jensen, F., & Pallesen, S. (2014). The prevalence of workaholism: A survey study in a nationally representative sample of Norwegian employees. PLoS ONE, 9(8): e102446. doi:10.1371/journal.pone.0102446.

• Workaholism has become an increasingly popular area for empirical study. However, most studies examining the prevalence of workaholism have used non-representative samples and measures with poorly defined cut-off scores. To overcome these methodological limitations, a nationally representative survey among employees in Norway (N = 1,124) was conducted. Questions relating to gender, age, marital status, caretaker responsibility for children, percentage of full-time equivalent, and educational level were asked. Workaholism was assessed by the use of a psychometrically validated instrument (i.e., Bergen Work Addiction Scale). Personality was assessed using the Mini-International Personality Item Pool. Results showed that the prevalence of workaholism was 8.3% (95% CI= 6.7–9.9%). An adjusted logistic regression analysis showed that workaholism was negatively related to age and positively related to the personality dimensions agreeableness, neuroticism, and intellect/imagination. Implications for these findings are discussed.

Quinones, C. & Griffiths, M.D. (2015). Addiction to work: recommendations for assessment. Journal of Psychosocial Nursing and Mental Health Services, 10, 48-59.

• Workaholism was first conceptualized in the early 1970s as a behavioral addiction, featuring compulsive use and interpersonal conflict. The current article briefly examines the empirical and theoretical literature over the past four decades. In relation to conceptualization and measurement, how the concept of workaholism has worsened from using dimensions based on anecdotal evidence, ad-hoc measures with weak theoretical foundation, and poor factorial validity of multidimensional conceptualizations is highlighted. Benefits of building on the addiction literature to conceptualize workaholism are presented (including the only instrument that has used core addiction criteria: the Bergen Work Addiction Scale). Problems estimating accurate prevalence estimates of work addiction are also presented. Individual and sociocultural risk factors, and the negative consequences of workaholism from the addiction perspective (e.g., depression, burnout, poor health, life dissatisfaction, family/relationship problems) are discussed. The current article summarizes how current research can be used to evaluate workaholism by psychiatric–mental health nurses in clinical practice, including primary care and mental health settings.

Karanika-Murray, M., Pontes, H.M., Griffiths, M.D. & Biron, C. (2015). Sickness presenteeism determines job satisfaction via affective-motivational states. Social Science and Medicine, 139, 100-106.

• Introduction: Research on the consequences of sickness presenteeism, or the phenomenon of attending work whilst ill, has focused predominantly on identifying its economic, health, and absenteeism outcomes, in the process neglecting important attitudinal-motivational outcomes. Purpose: A mediation model of sickness presenteeism as a determinant of job satisfaction via affective-motivational states (specifically engagement with work and addiction to work) is proposed. This model adds to the current literature, by focussing on (i) job satisfaction as an outcome of presenteeism, and (ii) the psychological processes associated with this. It posits sickness presenteeism as psychological absence and work engagement and work addiction as motivational states that originate in that. Methods: An online survey on sickness presenteeism, work engagement, work addiction, and job satisfaction was completed by 158 office workers. Results: The results of bootstrapped mediation analysis with observable variables supported the model. Sickness presenteeism was negatively associated with job satisfaction. This relationship was fully mediated by both engagement with work and addiction to work, explaining a total of 48.07% of the variance in job satisfaction. Despite the small sample, the data provide preliminary support for the model. Conclusions: Given that there is currently no available research on the attitudinal consequences of sickness presenteeism, these findings offer promise for advancing theorising in this area.

Quinones, C., Griffiths, M.D. & Kakabadse, N. (2016). Compulsive Internet use and workaholism: An exploratory two-wave longitudinal study. Computers in Human Behavior, 60, 492-499.

• Workaholism refers to the uncontrollable need to work and comprises working compulsively (WC) and working excessively (WE). Compulsive Internet Use (CIU), involves a similar behavioural pattern although in specific relation to Internet use. Since many occupations rely upon use of the Internet, and the lines between home and the workplace have become increasingly blurred, a self-reinforcing pattern of workaholism and CIU could develop from those vulnerable to one or the other. The present study explored the relationship between these compulsive behaviours utilizing a two-wave longitudinal study over six months. A total of 244 participants who used the Internet as part of their occupational role and were in full-time employment completed the online survey at each wave. This survey contained previously validated measures of each variable. Data were analysed using cross-lagged analysis. Results indicated that Internet usage and CIU were reciprocally related, supporting the existence of tolerance in CIU. It was also found that CIU at Time 1 predicted WC at Time 2 and that WE was unrelated to CIU. It is concluded that a masking mechanism appears a sensible explanation for the findings. Although further studies are needed, these findings encourage a more holistic evaluation and treatment of compulsive behaviours.

Orosz, G., Dombi, E., Andreassen, C.S., Griffiths, M.D. & Demetrovics, Z. (2016). Analyzing models of work addiction: Single factor and bi-factor models of the Bergen Work Addiction Scale. International Journal of Mental Health and Addiction, in press.

• Work addiction (‘workaholism’) has become an increasingly studied topic in the behavioral addictions literature and had led to the development of a number of instruments to assess it. One such instrument is the Bergen Work Addiction Scale (BWAS). However, the BWAS has never been investigated in Eastern-European countries. The goal of the present study was to examine the factor structure, the reliability and cut-off scores of the BWAS in a comprehensive Hungarian sample. This study is a direct extension of the original validation of BWAS by providing results on the basis of representative data and the development of appropriate cut-off scores. The study utilized an online questionnaire with a Hungarian representative sample including 500 respondents (F = 251; Mage = 35.05 years) who completed the BWAS. A series of confirmatory factor analyses were carried out leading to a short, 7-item first-order factor structure and a longer 14-item seven-factor nested structure. Despite the good validity of the longer version, its reliability was not as high as it could have been. One-fifth (20.6 %) of the Hungarians who used the internet at least weekly were categorized as work addicts using the BWAS. It is recommended that researchers use the original seven items from the Norwegian scale in order to facilitate and stimulate cross-national research on addiction to work.

Andreassen, C.S., Griffiths, M.D., Sinha, R., Hetland, J. & Pallesen, S. (2016). The relationships between workaholism and symptoms of psychiatric disorders: A large-scale cross-sectional study. PLoS ONE, 11(5): e0152978. doi:10.1371/journal. pone.0152978.

• Despite the many number of workaholism studies, large-scale studies have been lacking. The present study utilized an open web-based cross-sectional survey assessing symptoms of psychiatric disorders and workaholism among 16,426 workers (M_age=37.3 years, SD₌11.4, range=16-75 years). Participants were administered the Adult ADHD Self-Report Scale, the Obsession-Compulsive Inventory-Revised, the Hospital Anxiety and Depression Scale, and the Bergen Work Addiction Scale, along with additional questions examining demographic and work-related variables. Analyses of variance revealed significant workaholism group differences in terms of age, marital status, education, professional position, work sector, occupation, and annual income. No gender differences were found, except in a logistic regression analysis, indicating that women had a greater risk than men of being categorized as workaholics. Correlations between all psychiatric symptoms and workaholism were significant and positively correlated. Workaholism comprised the dependent variable in a four-step linear multiple hierarchical regression analysis as well as in a logistic regression analysis. In the linear regression analysis demographics (age, gender, and marital status) explained 0.8% of the variance in workaholism. The mental health variables (ADHD, OCD, anxiety, and depression) explained between 1.9% and 11.9% of the variance. In an adjusted logistic regression analysis, all psychiatric symptoms were positively associated with workaholism. Although most effect sizes were relatively small, the study’s findings expand our understanding of possible mental health predictors of workaholism, and sheds new light on the reality of adult ADHD in work life. The study’s implications, strengths, and shortcomings are also discussed.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (2005). Workaholism is still a useful construct Addiction Research and Theory, 13, 97-100.

Griffiths, M.D. (2011). Workaholism: A 21^st century addiction. The Psychologist: Bulletin of the British Psychological Society, 24, 740-744.

Griffiths, M.D. & Karanika-Murray, M. (2012). Contextualising over-engagement in work: Towards a more global understanding of workaholism as an addiction. Journal of Behavioral Addictions, 1(3), 87-95.

Karanika-Murray, M., Duncan, N., Pontes, H. & Griffiths, M.D. (2015). Organizational identification, work engagement, and job satisfaction. Journal of Managerial Psychology, 30, 1019-1033.

Shonin, E., Van Gordon, W., & Griffiths M.D. (2014). The treatment of workaholism with Meditation Awareness Training: A case study. Explore: Journal of Science and Healing, 10, 193-195.

Views news: A brief look at the ‘Problem Series Watching Scale’

A few weeks ago I published the third of three articles on ‘box set bingeing’ (people like myself who sit and watch a whole television series at once either on DVD or on television catch-up services). Not long after writing the last article, a paper was published in the Journal of Behavioral Addictions about the development of a new psychometric instrument that assesses problematic television series watching – the Problematic Series Watching Scale (PSWS) – developed by Dr. Gabor Orosz and his colleagues at Eötvös Loránd University in Budapest (Hungary). The authors noted that:

“[Problematic series watching] might be a relevant issue for many people because accessing series by downloading or streaming is (a) very cheap (or free), (b) it is available for almost everyone who has broadband Internet access, (c) it does not depend on a certain place and time (i.e. playing squash depends on a certain place and time), (d) series have a high variety – everyone can find one which fits his/her interest, (e) they are not age- and socio-economic status-dependent, (f) it does not take effort to watch them, [and] (g) and they are constructed to be highly enjoyable and often contain cliffhangers which motivate the viewer to continue. These characteristics are highly similar to the ones mentioned by Cooper (1998) regarding Internet and pornography…In our research, we aimed to differentiate problematic series watching from the concept of television addiction as we focused on the content of the problematic use (series watching) rather than on the medium through which the problematic use happens (television). In our research, we observed problematic series watching which could be done either through a television (i.e. classical TV series) or a screen attached to a computer (i.e. Netflix)”.

The new scale was developed with over 1,100 participants and was based on my ‘addiction components model’ and comprised the following questions which can each be answered ‘never’, ‘rarely’, ‘sometimes’, ‘often’ and ‘always’. Each of the six items taps into a criterion for addiction (i.e., salience, tolerance, mood modification, withdrawal, conflict, and relapse). More specifically, the questions asks During the last year, how often have you:

• Thought of how you could free up more time to watch series? [Salience]
• Spent much more time watching series than initially intended? [Tolerance]
• Watched series in order to reduce feelings of guilt, anxiety, helplessness and depression? [Mood modification]
• Been told by others to cut down on watching series without listening to them? [Relapse]
• Become restless or troubled if you have been prohibited from watching series? [Withdrawal]
• Ignored your partner, family members, or friends because of series watching? [Conflict]

For those of you interested in the psychometric properties, the scale had good factor structure and reliability.

“Respondents watch series more than one hour per day which is more than one-fifth of their free time which indicated that series watching might be an important free time activity. However, the amount of free time one has is not associated with PSWS scores. Women had higher scores on PSWS and respondents with higher education had lower scores on it…Given the lack of empirical research on series watching, we supposed that it might be similar to other problematic screen-related behaviors (e.g. online gaming, Internet or Facebook use)… Other possible covariates could be examined in the future such as loneliness or urgency. Also, further investigation is needed whether extensive series watching can lead to health and psychosocial problems…PSWS scores are positively related with time spent on series watching, whereas the amount of free time does not have an effect on PSWS scores. In the more and more digitalized world there are many forces which encourage people watching online series. In the light of these changes, research on problematic series watching will be increasingly relevant”.

The authors also acknowledged that problematic television series watching doesn’t appear to affect many people and that we should be careful of pathologizing everyday behaviours as behavioural addictions (a criticism that has been made against some of my own research papers more recently – with ‘dance addiction’ and ‘study addiction’ being the most obvious ones).

Dr. Orosz and his colleagues have also just published another paper on problematic series watching in the journal Personality and Individual Differences. This second paper examined correlates of passion toward screen-based activities (i.e., problematic series watching and Facebook use). The paper included two studies comprising young adults (Study 1 with 256 individuals, and Study 2 with 420 individuals) who completed the Passion Scale with respect to their series watching and Facebook use as well as examining impulsivity. The Passion Scale comprises two types of passion – obsessive passion (negative, pressured, and controlling) and harmonious passion (positive, flexible, and related to intrinsic motivation). The results showed that impulsivity predicted obsessive (but not harmonious) passion, and that obsessive passion was positively associated with Facebook overuse whereas harmonious passion was positively associated with series watching. They concluded that it was the type of passion underlying the involvement in excessive screen-based activity that determines what’s experienced by the individual.

My argument has always been that depending upon the definition of ‘addiction’ used, almost any activity can be potentially addictive if constant rewards and reinforcement are in place. The watching of DVD or television box sets can certainly be rewarding and reinforcing but I imagine most people are like myself in that they occasionally experience negative consequences as a result of the activity (lack of sleep due to going to bed very late, or ignoring family members while watching an episode or four of your favourite programmes) but that overall the problems are short-lived and have few long-term consequences.

[I ought to note that I have recently been working with Dr. Orosz in the area of workaholism and that we recently published a paper in the topic in the International Journal of Mental Health and Addiction – see ‘Further reading’ below).

Dr Mark Griffiths, Professor of Behavioural Addictions, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Atroszko, P.A., Andreassen, C.S., Griffiths, M.D. & Pallesen, S. (2015). Study addiction – A new area of psychological study: Conceptualization, assessment, and preliminary empirical findings. Journal of Behavioral Addictions, 4, 75–84.

Atroszko, P.A., Andreassen, C.S., Griffiths, M.D. & Pallesen, S. (2016). Study addiction: A cross-cultural longitudinal study examining temporal stability and predictors of its changes. Journal of Behavioral Addictions, DOI: 10.1556/2006.5.2016.024

Bates, D. (2015). Watching TV box-set marathons is warning sign you’re lonely and depressed – and will also make you fat. Daily Mail, January 29. Located at: http://www.dailymail.co.uk/health/article-2931572/Love-marathon-TV-session-warning-sign-lonely-depressed.html

Cooper, A. (1998). Sexuality and the Internet: Surfing into the new millennium. CyberPsychology and Behavior, 1(2), 187–193.

Daily Edge (2014). 11 signs of you’re suffering from a binge-watching problem. Located at: http://www.dailyedge.ie/binge-watching-problem-signs-1391910-Apr2014/

Kompare, D. (2006). Publishing flow DVD Box Sets and the reconception of television. Television & New Media, 7(4), 335-360.

Maraz, A., Urbán, R., Griffiths, M.D. & Demetrovics Z. (2015). An empirical investigation of dance addiction. PloS ONE, 10(5): e0125988. doi:10.1371/journal.pone.0125988.

Orosz, G., Bőthe, B., & Tóth-Király, I. (2016). The development of the Problematic Series WatchingScale (PSWS). Journal of Behavioral Addictions, 5(1), 144-150.

Orosz, G., Dombi, E., Andreassen, C.S., Griffiths, M.D. & Demetrovics, Z. (2016). Analyzing models of work addiction: Single factor and bi-factor models of the Bergen Work Addiction Scale. International Journal of Mental Health and Addiction, DOI 10.1007/s11469-015-9613-7

Orosz, G., Vallerand, R. J., Bőthe, B., Tóth-Király, I., & Paskuj, B. (2016). On the correlates of passion for screen-based behaviors: The case of impulsivity and the problematic and non-problematic Facebook use and TV series watching. Personality and Individual Differences, 101, 167-176.

Spangler, T. (2013). Poll of online TV watchers finds 61% watch 2-3 episodes in one sitting at least every few weeks. Variety, December 13. Located at: http://variety.com/2013/digital/news/netflix-survey-binge-watching-is-not-weird-or-unusual-1200952292/

Sussman, S., & Moran, M.B. (2013). Hidden addiction: Television. Journal of Behavioral Addictions, 2(3), 125-132.

Walton-Pattison, E., Dombrowski, S.U. & Presseau, J. (2016). ‘Just one more episode’: Frequency and theoretical correlates of television binge watching. Journal of Health Psychology, doi:1359105316643379

Back tracking: A brief look at using big data in gambling research

I’ve been working in the area of gambling for nearly 30 years and over the past 15 years I have carrying out research into both online gambling and responsible gambling. As I have outlined in previous blogs, one of the new methods I have been using in my published papers is online behavioural tracking. The chance to carry out innovative research in both areas using a new methodology was highly appealing – especially as I have used so many other methods in my gambling research (including online and offline surveys, experiments in laboratories and ecologically valid settings, offline focus groups, online and offline case study interviews, participant and non-participation observation, secondary analysis of survey data, and analysis of various forms of online data such as those found in online forums and online diary blogs).

Over the last decade there has been a big push by gambling regulators for gambling operators to be more socially responsible towards its clientele and this has led to the use of many different responsible gambling (RG) tools and initiatives such as voluntary self-exclusion schemes (where gamblers can ban themselves from gambling), limit setting (where gamblers can choose how much time and/or money they want to lose while gambling), personalized feedback (where gamblers can get personal feedback and advice based on their actual gambling behaviour) and pop-up messages (where gamblers receive a pop-up message during play that informs them how long they have been playing or how much money that have spent during the session).

However, very little is known about whether these RG tools and initiatives actually work, and most of the research that has been published relies on laboratory methods and self-reports – both of which have problems as reliable methods when it comes to evaluating whether RG tools work. Laboratory experiments typically contain very few participants and are carried out in non-ecologically valid settings, and self-reports are prone to many biases (including social desirability and recall biases). Additionally, the sample sizes are also relatively small (although bigger than experiments).

The datasets to analyse player behaviour are huge and can include hundreds of thousands of online gamblers. Given that my first empirical paper on gambling published in the Journal of Gambling Studies in 1990 was a participant observational analysis of eight slot machine gamblers at one British amusement arcade, it is extraordinary to think that decades later I have access to datasets beyond anything I could have imagined back in the 1980s when I began my research career. The data analysis is carried with my research colleague Michael Auer who has a specific expertise in data mining and we use traditional statistical tests to analyse the data. However, the hardest part is always trying to work out which parameters to use in assessing whether the RG tool worked or not. The kind of data we have includes how much time and money that players are spending on the gambling website, and using that data we can assess to what extent the amount of time and money decreases as a result of using limit setting measures, or receiving personalized feedback or a pop-up message.

One of the biggest problems in doing this type of research in the gambling studies field is getting access to the data in the first place and the associated issue of whether academics should be working with the gambling industry in the first place. The bottom line is that we would never have been able to undertake this kind of innovative research with participant sizes of hundreds of thousands of real gamblers without working in co-operation with the gambling industry. (It should also be noted that the gambling companies in question did not fund the research but provided simply provided access to their databases and customers). In fact, I would go as far as to say the research would have been impossible without gambling industry co-operation. Data access provided by the gambling industry has to be one of the key ways forward if the field is to progress.

Unlike other consumptive and potentially addictive behaviours (smoking cigarettes, drinking alcohol, etc.), researchers can study real-time gambling (and other potentially addictive behaviours like video gaming and social networking) in a way that just cannot be done in other chemical and behavioural addictions (e.g., sex, exercise, work, etc.) because of online and/or card-based technologies (such as loyalty cards and player cards). There is no equivalent of this is the tobacco or alcohol industry, and is one of the reasons why researchers in the gambling field are beginning to liaise and/or collaborate with gambling operators. As researchers, we should always strive to improve our theories and models and it appears strange to neglect this purely objective information simply because it involves working together with the gambling industry. This is especially important given the recent research by Dr. Julia Braverman and colleagues published in the journal Psychological Assessment using data from gamblers on the bwin website showing that self-recollected information does not match with objective behavioural tracking data.

The great thing about online behavioural tracking data collected from gamblers is that it is totally objective (as it provides a true record of what every gambler does click-by-click), is collected from real world gambling websites (so is ecologically valid), and has large sample sizes (typically tens of thousands of online gamblers). There of course some disadvantages, the main ones being that the sample is unrepresentative of all online gamblers (as the data only comes from gamblers at one website) and nothing is known about the person’s gambling activity at other websites (research has shown that online gamblers typically gamble at a number of different websites and not just one). Despite these limitations, the analysis of behavioural tracking data (so-called ‘big data’) is a reliable and cutting-edge way to assess and evaluate online gambling behaviour and to assess whether RG tools actually work in real world gambling settings with real online gamblers in real time.

To get access to such data you have to cultivate a trusting relationship with the data providers. It took me years to build up trust with the gambling industry because researchers who study problem gambling are often perceived by the gambling industry to be ‘anti-gambling’ but in my case this wasn’t true. I am ‘pro-responsible gambling’ and gamble myself so it would be hypocritical to be anti-gambling. My main aim in my gambling research is to protect players and minimise harm. Problem gambling will never be totally eliminated but it can be minimised. If gambling companies share the same aim and philosophy of not wanting to make money from problem gamblers but to make money from non-problem gamblers, then I would be prepared to help and collaborate.

You also need to be thick-skinned. If you are analysing any behavioural tracking data provided by the gambling industry, then you need to be prepared for others in the field criticizing you for working in collaboration with the industry. Although none of this research is funded by the industry, the fact that you are collaborating is enough for some people to accuse you of not being independent and/or being in the pockets of the gambling industry. Neither of these are true but it won’t stop the criticism. Nor will it stop me from carrying on researching in this area using datasets provided by the gambling industry.

Dr. Mark Griffiths, Professor of Gambling Studies, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Auer, M. & Griffiths, M.D. (2013). Behavioral tracking tools, regulation and corporate social responsibility in online gambling. Gaming Law Review and Economics, 17, 579-583.

Auer, M. & Griffiths, M.D. (2013). Voluntary limit setting and player choice in most intense online gamblers: An empirical study of gambling behaviour. Journal of Gambling Studies, 29, 647-660.

Auer, M. & Griffiths, M.D. (2014). Personalised feedback in the promotion of responsible gambling: A brief overview. Responsible Gambling Review, 1, 27-36.

Auer, M. & Griffiths, M.D. (2014). An empirical investigation of theoretical loss and gambling intensity. Journal of Gambling Studies, 30, 879-887.

Auer, M. & Griffiths, M.D. (2015). Testing normative and self-appraisal feedback in an online slot-machine pop-up message in a real-world setting. Frontiers in Psychology, 6, 339. doi: 10.3389/fpsyg.2015.00339.

Auer, M. & Griffiths, M.D. (2015). Theoretical loss and gambling intensity (revisited): A response to Braverman et al (2013). Journal of Gambling Studies, 31, 921-931.

Auer, M. & Griffiths, M.D. (2015). The use of personalized behavioral feedback for problematic online gamblers: An empirical study. Frontiers in Psychology, 6, 1406. doi: 10.3389/fpsyg.2015.01406.

Auer, M., Littler, A. & Griffiths, M.D. (2015). Legal aspects of responsible gaming pre-commitment and personal feedback initiatives. Gaming Law Review and Economics, 6, 444-456.

Auer, M., Malischnig, D. & Griffiths, M.D. (2014). Is ‘pop-up’ messaging in online slot machine gambling effective? An empirical research note. Journal of Gambling Issues, 29, 1-10.

Auer, M., Schneeberger, A. & Griffiths, M.D. (2012). Theoretical loss and gambling intensity: A simulation study. Gaming Law Review and Economics, 16, 269-273.

Braverman, J., Tom, M., & Shaffer, H. J. (2014). Accuracy of self-reported versus actual online gambling wins and losses. Psychological Assessment, 26, 865-877.

Griffiths, M.D. (1990). Addiction to fruit machines: A preliminary study among males. Journal of Gambling Studies, 6, 113-126.

Griffiths, M.D. & Auer, M. (2011). Approaches to understanding online versus offline gaming impacts. Casino and Gaming International, 7(3), 45-48.

Griffiths, M.D. & Auer, M. (2015). Research funding in gambling studies: Some further observations. International Gambling Studies, 15, 15-19.

Watch this space: Another look at box-set bingeing

Regular readers of my blog will know that I have both a professional and personal interest in ‘box set binging’ – people like myself who sit and watch a whole television series at once either on DVD or on television catch-up services (see my two previous articles on the topic here and here). In my previous blogs on the topic I noted there was a lack of published academic research on the topic. However, a new study on the phenomenon – ‘Just one more episode’: Frequency and theoretical correlates of television binge watching’ – has just been published by Emily Walton-Pattison and her colleagues in the Journal of Health Psychology. The paper argues that binge watching may have detrimental health implications and that binge watching has impulsive aspects. As the authors noted in their paper:

“With the emergence of online streaming television services, watching television has never been so easy and a new behavioural phenomenon has arisen: television binge watching, that is, viewing multiple episodes of the same television show in the same sitting. Watching television is the most widespread leisure-time sedentary activity in adults (Wijndaele et al., 2010), involving little metabolic activity (Hu et al., 2003). In the United Kingdom, over one-third of adults spend at least four hours a day watching television (Stamatakis et al., 2009). Up to 33% of men and 45% of women in the United Kingdom fail to achieve recommended physical activity levels (Craig and Mindell, 2014). As lack of physical activity is the fourth leading mortality risk factor (World Health Organization, 2010), identifying factors that pre- vent achieving health-protective levels of physical activity remains important Furthermore, sedentary behaviour is linked with adverse health outcomes independently of physical activity (Veerman et al., 2012). Time spent watching television is also linked with obesity and reduced sleep time (Vioque et al., 2000). Understanding the factors that lead to watching television at ‘binge’ levels may help to target interventions to reduce sedentary activity and obesity rates and improve sleep hygiene”.

The study involved 86 people who completed an online survey that assessed (among other things) outcome expectations (assessed via six attitudinal items such as ‘Watching more than two episodes of the same TV show in the same sitting over the next 7 days will lead me to be physically healthier’), proximal goals (assessed via one question ‘On how many days do you intend to watch more than two episodes of the same TV show in the same sitting over the next 7 days?’), self-efficacy (assessed via five attitudinal items such as ‘I am confident that I can stop myself from watching more than two episodes of the same TV show if I wanted to’), anticipated regret (assessed via two items – ‘If I watched more than two episodes of the same TV show in the same sitting in the next 7 days, I would feel regret’ and ‘If I watched more than two episodes of the same TV show in the same sitting in the next 7 days I would later wish I had not’), goal conflict (with two items such as ‘How often does it happen that because of watching more than two episodes of the same TV show in the same sitting, you do not invest as much time in other pursuits as you would like to?’), goal facilitation (assessed via three items such as ‘Watching more than two episodes of the same TV show in the same sitting in the next 7 days will help/facilitate my participation in regular physical activity’), and self-reported binge watching over the last week (defined as “watching more than two episodes of the same TV show in one sitting”), as well as noting various demographic details (age, gender, marital status, number of children, and body mass index).

The study found that their participants reported binge watching at least once a week (an average of 1.42 days/week) and that binge watching was predicted most by intention and outcome expectations. Automaticity, anticipated regret, and goal conflict also contributed to binge watching. Based on their results, the authors noted:

“The findings have implications for theory development and intervention…The role of automaticity suggests that interventions aiming to address problematic binge watching (e.g. due to increased sedentary activity) could consider techniques that address automaticity. For example, some online streaming services include in-built interruptions after a number of consecutive episodes have been viewed. There would be opportunities to harness these interruptions. Goal conflict findings indicated that participants who reported more binge watching also reported that binge watching undermined other goal pursuits. Linking such findings to an intervention addressing anticipated regret could provide a useful opportunity…Drawing upon the addiction literature in relation to other types of binge behaviours may further refine potential appetitive and loss of control features that may extend from addictive behaviours with a binge potential, such as eating, sex and drugs, to binge watching”.

Obviously the study relied on self-reports among a small sample of television viewers but given that this is the first-ever academic study of binge watching, it provides a basis for further research to be carried out. As in my own research into gambling where we have begun to use tracking data provided by gambling companies, the authors also note that such objective measures could also be used in the field of researching into television binge watching:

“[Future research] could include using objective measures of binge watching including ecological momentary assessment, ambient sound detection, recording and/or partnering with streaming firms or software-based monitoring. Further insight into binge watching could make a distinction between television show-specific factors, such as genre, length, real-time versus on-demand services, as well as contextual factors (e.g., where binge watching occurred, with whom and when) and assess the association between binge watching and health outcomes including physical activity, eating and sleep hygiene”.

This is one of the first times I can end one of my articles by saying that this is literally a case of “watch this space”!

Dr Mark Griffiths, Professor of Behavioural Addictions, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Bates, D. (2015). Watching TV box-set marathons is warning sign you’re lonely and depressed – and will also make you fat. Daily Mail, January 29. Located at: http://www.dailymail.co.uk/health/article-2931572/Love-marathon-TV-session-warning-sign-lonely-depressed.html

Craig, R. & Mindell, J. (2014). Health Survey for England 2013. London: The Health & Social Care Information Centre.

Daily Edge (2014). 11 signs of you’re suffering from a binge-watching problem. Located at: http://www.dailyedge.ie/binge-watching-problem-signs-1391910-Apr2014/

Griffiths, M.D. (1995). Technological addictions. Clinical Psychology Forum, 76, 14-19.

Hu, F.B., Li, T.Y., Colditz, G.A., et al. (2003) Television watching and other sedentary behaviors in rela- tion to risk of obesity and type 2 diabetes mellitus in women. JAMA, 289, 1785–1791.

Kompare, D. (2006). Publishing flow DVD Box Sets and the reconception of television. Television & New Media, 7(4), 335-360.

Spangler, T. (2013). Poll of online TV watchers finds 61% watch 2-3 episodes in one sitting at least every few weeks. Variety, December 13. Located at: http://variety.com/2013/digital/news/netflix-survey-binge-watching-is-not-weird-or-unusual-1200952292/

Stamatakis, E., Hillsdon, M., Mishra, G., et al. (2009) Television viewing and other screen-based entertainment in relation to multiple socioeconomic status indicators and area deprivation: The Scottish Health Survey 2003. Journal of Epidemiology & Community Health, 63, 734–740.

Sussman, S., & Moran, M.B. (2013). Hidden addiction: Television. Journal of Behavioral Addictions, 2(3), 125-132.

Veerman, J.L., Healy, G.N., Cobiac, L.J., et al. (2012) Television viewing time and reduced life expec- tancy: A life table analysis. British Journal of Sports Medicine, 46, 927–930.

Vioque, J., Torres, A. & Quiles, J. (2000) Time spent watching television, sleep duration and obesity in adults living in Valencia, Spain. International Journal of Obesity, 24, 1683–1688.

Walton-Pattison, E., Dombrowski, S.U. & Presseau, J. (2016). ‘Just one more episode’: Frequency and theoretical correlates of television binge watching. Journal of Health Psychology, doi:1359105316643379

Wijndaele, K., Brage, S., Besson, H., et al. (2010) Television viewing time independently predicts all-cause and cardiovascular mortality: The EPIC Norfolk study. International Journal of Epidemiology, 40, 150–159.

Pressing the right buttons: The positives of playing video games

Whether playing video games has negative effects is something that has been debated for 30 years, in much the same way that rock and roll, television, and even the novel faced much the same criticisms in their time. Purported negative effects such as gaming addiction, increased aggression, and various health consequences such as obesity and repetitive strain injuries tend to get far more media coverage than the positives. I know from my own research examining both sides that my papers on video game addiction receive far more publicity than my research into the social benefits of, for example, playing online role-playing games.

However there is now a wealth of research which shows that video games can be put to educational and therapeutic uses, as well as many studies which reveal how playing video games can improve reaction times and hand-eye co-ordination. For example, research has shown that spatial visualisation ability, such as mentally rotating and manipulating two- and three-dimensional objects, improves with video game playing.

To add to this long line of studies demonstrating the more positive effects of video games is a study in the Proceedings of the National Academy of Sciences by Vikranth Bejjanki and colleagues. Their paper demonstrates that the playing of action video games – the sort of fast-paced, 3D shoot-em-up beloved of doomsayers in the media – confirms what other studies have revealed, that players show improved performance in perception, attention, and cognition.

In a series of experiments on small numbers of gamers (10 to 14 people in each study), the researchers reported that gamers with previous experience of playing such action video games were better at perceptual tasks such as pattern discrimination than gamers with less experience. In another experiment, they trained gamers that had little previous experience of playing action games, giving them 50 hours practice. It was showed that these gamers performed much better on perceptual tasks than they had prior to their training. The paper concludes:

“The enhanced learning of the regularity and structure of environments may act as a core mechanism by which action video game play influences performance in perception, attention, and cognition”.

In my own papers, I have pointed out many features and qualities that make video games potentially useful. For instance, in an educational context, video games can be fun and stimulating, which means it’s easier to maintain a pupil’s undivided attention for longer. Because of the excitement, video games may also be a more appealing way of learning than traditional methods for some.

Video games have an appeal that crosses many demographic boundaries, such as age, gender, ethnicity, or educational attainment. They can be used to help set goals and rehearse working towards them, provide feedback, reinforcement, self-esteem, and maintain a record of behavioural change. Their interactivity can stimulate learning, allowing individuals to experience novelty, curiosity and challenge that stimulates learning. There is the opportunity to develop transferable skills, or practice challenging or extraordinary activities, such as flight simulators, or simulated operations. Because video games can be so engaging, they can also be used therapeutically. For instance, they can be used as a form of physiotherapy as well as in more innovative contexts. A number of studies have shown that when children play video games following chemotherapy they need fewer painkillers than others.

Video games can have great educational potential in addition to their entertainment value. Games specifically designed to address a specific problem or teach a specific skill have been very successful, precisely because they are motivating, engaging, interactive, and provide rewards and reinforcement to improve. But the transferability of skills outside the game-playing context is an important factor. What’s also clear from the scientific literature is that the negative consequences of playing almost always involve people that are excessive video game players. There is little evidence of serious acute adverse effects on health from moderate play.

A version of this article was first published in The Conversation.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Bejjanki, V. R., Zhang, R., Li, R., Pouget, A., Green, C. S., Lu, Z. L., & Bavelier, D. (2014). Action video game play facilitates the development of better perceptual templates. Proceedings of the National Academy of Sciences, 111(47), 16961-16966.

Cole, H. & Griffiths, M.D. (2007). Social interactions in Massively Multiplayer Online Role-Playing gamers. CyberPsychology and Behavior, 10, 575-583.

Griffiths, M.D. (1997). Video games and clinical practice: Issues, uses and treatments. British Journal of Clinical Psychology, 36, 639-641.

Griffiths, M.D. (2002). The educational benefits of videogames Education and Health, 20, 47-51.

Griffiths, M.D. (2003). The therapeutic use of videogames in childhood and adolescence. Clinical Child Psychology and Psychiatry, 8, 547-554.

Griffiths, M.D. (2004). Can videogames be good for your health? Journal of Health Psychology, 9, 339-344.

Griffiths, M.D. (2005). Video games and health. British Medical Journal, 331, 122-123.

Griffiths, M.D. (2005). The therapeutic value of videogames. In J. Goldstein & J. Raessens (Eds.), Handbook of Computer Game Studies (pp. 161-171). Boston: MIT Press.

Griffiths, M.D. (2010). Adolescent video game playing: Issues for the classroom. Education Today: Quarterly Journal of the College of Teachers, 60(4), 31-34.

Griffiths, M.D., Kuss, D.J., & Ortiz de Gortari, A. (2016). Videogames as therapy: An updated selective review of the medical and psychological literature. International Journal of Privacy and Health Information Management, in press.

Griffiths, M. D., Kuss, D.J., & Ortiz de Gortari, A. (2013). Videogames as therapy: A review of the medical and psychological literature. In I. M. Miranda & M. M. Cruz-Cunha (Eds.), Handbook of research on ICTs for healthcare and social services: Developments and applications (pp.43-68). Pennsylvania: IGI Global.

Griffiths, M.D. & Sutton, M. (2013). Proposing the Crime Substitution Hypothesis: Exploring the possible causal relationship between excessive adolescent video game playing, social networking and crime reduction. Education and Health, 31, 17-21.

Griffiths, M.D. & Sutton, M. (2015). Screen time and crime: The ‘Crime Substitution Hypothesis’ revisited. Education and Health, 33, 85-87.

Loud and proud: A psychological (and personal) look at the ‘Sin of Pride’

A number of years ago, I was asked to write an article on “The Sin of Pride” for the British Psychological Society. Before writing that article, I knew very little about the topic. To me it was the title of an record album by The Undertones that I bought in 1983 when I was 16 years old from Castle Records in Loughborough. I perhaps learned a bit more about it when I watched 1995 film ‘Seven’ directed by David Fincher and starring Brad Pitt (which coincidentally just happens to be one of my all-time favourite films).

After agreeing to write the article I did a bit of research on the subject (which admittedly meant I did a quick Google search followed by a more considered in-depth search on Google Scholar). While I’m no expert on the topic I can at least have a decent pub conversation about it if anyone is prepared to listen. Just to show my complete ignorance, I wasn’t even aware that the sin of pride was the sin of all sins (although I could in a pub quiz be relied upon to name the seven deadly sins).

I was asked to write on this topic because I was seen as someone who is very proud of the work that I do (and for the record, I am). However, I have often realized that just because I am proud of things that I have done in my academic career it doesn’t necessarily mean others think in the same way. In fact, on some occasions I have been quite taken aback by others’ reactions to things that I have done for which I feel justifiably proud (but more of that later).

At a very basic level, the sin of pride is rooted in a preoccupation with the self. However, in psychological terms, pride has been defined by Dr. Michael Lewis and colleagues in the International Journal of Behavioral Development as “a pleasant, sometimes exhilarating, emotion that results from a positive self-evaluation” and has been described by Dr. Jessica Tracy and her colleagues (in the journal Emotion) as one the three ‘self-conscious’ emotions known to have recognizable expressions (shame and embarrassment being the other two). From my reading of the psychological literature, it could perhaps be argued that pride has been regarded as having a more positive than negative quality, and (according to a paper in the Journal of Economic Psychology by my PhD supervisors – Professor Paul Webley and Professor Stephen Lea) is usually associated with achievement, high self-esteem and positive self-image – all of which are fundamental to my own thinking. My reading on the topic has also led to the conclusion that pride is sometimes viewed as an ‘intellectual’ or secondary emotion. In practical (and psychological) terms, sin is either a high sense of one’s personal status or ego, or the specific mostly positive emotion that is a product of praise or independent self-reflection.

One of the most useful distinctions can be made about sin (and is rooted in my own personal experience), is what Lea and Webley distinguish as ‘proper pride’ and ‘false pride’. They claim that:

“Proper pride is pride in genuine achievements (or genuine good qualities) that are genuinely one’s own. False pride is pride in what is not an achievement, or not admirable, or does not properly belong to oneself. Proper pride is associated with the desirable property of self-esteem; false pride with vanity or conceit. Proper pride is associated with persistence, endurance and doggedness; false pride with stubbornness, obstinacy and pig-headedness.”

As I noted above, there have been times when I have been immensely proud of doing something only for friends and colleagues to be appalled. ‘Proper pride’ as Lea and Webley would argue. One notable instance was when I wrote a full-page article for The Sun on ‘internet addiction’ published in August 1997. I originally wanted to be a journalist before I became a psychologist, and my journalist friends had always said that to get a full-page ‘by line’ in the biggest selling newspaper in the UK was a real achievement. I was immensely proud – apart from the headline that a sub-editor had dubbed my piece ‘The Internuts’ – and showed the article to whoever was around.

I had always passionately argued (and still do) that I want my research to be disseminated and read by as many people as possible. What was better than getting my work published in an outlet with (at the time) 10 million readers? My elation was short-lived. One close colleague and friend was very disparaging and asked how I could stoop so low as to “write for the bloody Sun?” Similar comments came from other colleagues and I have to admit that I was put off writing for the national tabloids for a number of years. (However, I am now back writing regularly for the national dailies and am strong enough to defend myself against the detractors).

In 2006, I was invited to the House of Commons by the ex-Leader of the Conservative Party, Iain Duncan-Smith and invited to Chair his Centre For Social Justice Working Party on Gambling and write a report as part of the Conservative Party’s ‘Breakdown Britain’ initiative. Anyone who knows me will attest that my political leanings are left of centre and that I working with the Conservatives on this issue was not something I did without a lot of consideration. I came to the conclusion that gambling was indeed a political issue (rather than a party political issue) and if the Conservative Party saw this as an important issue, I felt duty bound to help given my research experience in the area. I spent a number of months working closely with Iain Duncan-Smith’s office and when the report was published I was again very proud of my achievement.

However, as soon as the report came out I received disbelieving and/or snide emails asking how I could have “worked with the Conservatives”. I have spent years trying to put the psychosocial impact of gambling on the political agenda. If I am offered further opportunities by those with political clout, I won’t think twice about taking them. I am still immensely proud of such actions despite what others may think.

Pride is ultimately a subjective experience and the two personal experiences that I outlined above will not put me off doing what I want to do. I shall continue to engage in activities where I think my work can have an impact and shall work with (and write for) those that can help me disseminate my research findings to as many people as possible.

Dr Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Averill, J.R. (1991). Intellectual emotions. In: C.D. Spielberger, I.G. Sarason, Z. Kulesar & G.L. van Heck (Eds.), Stress and Emotion: Anger, Anxiety and Curiosity [Vol. 14] pp.3-16. New York: Hemisphere.

Griffiths, M.D. (1997). The internuts (internet addiction). The Sun, August 13, p.6.

Griffiths, M.D. (2007). Gambling addiction in the UK. In K. Gyngell (Ed.), Breakdown Britain: Ending the Costs of Social Breakdown (pp.393-426). London: Social Justice Policy Group.

Kemper, T.D. (1987). How many emotions are there? Wedding the social and autonomic components. American Journal of Sociology, 93, 263-289.

Lawler, E.J. (1992). Affective attachments to nested groups: A choice-process theory. American Sociological Review, 57, 327-339.

Lea, S.E.G. & Webley, P. (1997). Pride in economic psychology. Journal of Economic Psychology, 18, 323-340.

Lewis, M., Takai-Kawakami, K., Kawakami, K., & Sullivan, M. W. (2010). Cultural differences in emotional responses to success and failure. International Journal of Behavioral Development, 34, 53-61

Tracy, J.L., Robins, R.W. & Schriber, R.A. (2009). Development of a FACS-verified set of basic and self-conscious emotion expressions. Emotion, 9, 554-559.

You bet! A brief overview of our recent papers on youth gambling

Following my recent blogs where I outlined some of the papers that my colleagues and I have published on mindfulness, Internet addiction, and gaming addiction, here is a round-up of recent papers that my colleagues and I have published on adolescent gambling.

Calado, F., Alexandre, J. & Griffiths, M.D. (2014). Mom, Dad it’s only a game! Perceived gambling and gaming behaviors among adolescents and young adults: An exploratory study. International Journal of Mental Health and Addiction, 12, 772-794.

• Gambling and gaming are increasingly popular activities among adolescents. Although gambling is illegal in Portugal for youth under the age of 18 years, gambling opportunities are growing, mainly due to similarity between gambling and other technology-based games. Given the relationship between gambling and gaming, the paucity of research on gambling and gaming behaviors in Portugal, and the potential negative consequences these activities may have in the lives of young people, the goal of this study was to explore and compare the perceptions of these two behaviors between Portuguese adolescents and young adults. Results from six focus groups (comprising 37 participants aged between 13 and 26 years) indicated different perceptions for the two age groups. For adolescents, gaming was associated with addiction whereas for young adults it was perceived as a tool for increasing personal and social skills. With regard to gambling, adolescents associated it with luck and financial rewards, whereas young adults perceived it as an activity with more risks than benefits. These results suggest developmental differences that have implications for intervention programs and future research.

Delfabbro, P.H., King, D.L. & Griffiths, M.D. (2014). From adolescent to adult gambling: An analysis of longitudinal gambling patterns in South Australia. Journal of Gambling Studies, 30, 547-563.

• Although there are many cross-sectional studies of adolescent gambling, very few longitudinal investigations have been undertaken. As a result, little is known about the individual stability of gambling behaviour and the extent to which behaviour measured during adolescence is related to adult behaviour. In this paper, we report the results of a 4-wave longitudinal investigation of gambling behaviour in a probability sample of 256 young people (50 % male, 50% female) who were interviewed in 2005 at the age of 16–18 years and then followed through to the age of 20–21 years. The results indicated that young people showed little stability in their gambling. Relatively few reported gambling on the same individual activities consistently over time. Gambling participation rates increased rapidly as young people made the transition from adolescence to adulthood and then were generally more stable. Gambling at 15–16 years was generally not associated with gambling at age 20–21 years. These results highlight the importance of individual-level analyses when examining gambling patterns over time.

Canale, N., Vieno, A., Griffiths, M.D., Rubaltelli, E., Santinello, M. (2015). Trait urgency and gambling problems in young people: the role of decision-making processes. Addictive Behaviors, 46, 39-44.

• Although the personality trait of urgency has been linked to problem gambling, less is known about psychological mechanisms that mediate the relationship between urgency and problem gambling. One individual variable of potential relevance to impulsivity and addictive disorders is age. The aims of this study were to examine: (i) a theoretical model associating urgency and gambling problems, (ii) the mediating effects of decision-making processes (operationalized as preference for small/immediate rewards and lower levels of deliberative decision-making); and (iii) age differences in these relationships. Participants comprised 986 students (64% male; mean age = 19.51 years; SD = 2.30) divided into three groups: 16–17 years, 18–21 years, and 22–25 years. All participants completed measures of urgency, problem gambling, and a delay-discounting questionnaire involving choices between a smaller amount of money received immediately and a larger amount of money received later. Participants were also asked to reflect on their decision-making process. Compared to those aged 16–17 years and 22–25 years, participants aged 18–21 years had a higher level of gambling problems and decreased scores on lower levels of deliberative decision-making. Higher levels of urgency were associated with higher levels of gambling problems. The association was mediated by a lower level of deliberative decision-making and preference for an immediate/small reward. A distinct pathway was observed for lower levels of deliberative decision-making. Young people who tend to act rashly in response to extreme moods, had lower levels of deliberative decision-making, that in turn were positively related to gambling problems. This study highlights unique decision-making pathways through which urgency trait may operate, suggesting that those developing prevention and/or treatment strategies may want to consider the model’s variables, including urgency, delay discounting, and deliberative decision-making.

Carran, M. & Griffiths, M.D. (2015). Gambling and social gambling: An exploratory study of young people’s perceptions and behavior. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 33(1), 101-113.

• Background and aims: Gambling-type games that do not involve the spending of money (e.g., social and ‘demo’ [demonstration] gambling games, gambling-like activities within video games) have been accused in both the legal and psychological literature of increasing minors’ propensity towards prohibited forms of gambling thus prompting calls for gambling regulation to capture address such games and subject them to age restrictions. However, there is still a shortage of empirical data that considers how young people experience monetary and non-monetary gambling, and whether they are sufficiently aware of the differences. Methods: Data was collected from 23 qualitative focus groups carried out with 200 young people aged between 14 and 19 years old in schools based in London and Kent. As the study was exploratory in nature, thematic analysis was adopted in order to capture how pupils categorise, construct, and react to gambling-like activities in comparison to monetary forms of gambling without the constrains of a predetermined theoretical framework. Results: Despite many similarities, substantial differences between monetary and non-monetary forms of gambling were revealed in terms of pupils’ engagement, motivating factors, strengths, intensity, and associated emotions. Pupils made clear differentiation between non-monetary and monetary forms of gambling and no inherent transition of interest from one to the other was observed among participants. Only limited evidence emerged of ‘demo’ games being used as a practice ground for future gambling. Conclusion: For the present sample, non-monetary forms of gambling presented a different proposition to the real-money gambling with no inherent overlap between the two. For some the ‘softer’ form minimised the temptation to try other forms of gambling that they were not legally allowed to engage in, but ‘demo’ games may attract those who already want to gamble. Policy implications: Regulators must recognise and balance these two conflicting aspects.

Griffiths, M.D. (2015). Adolescent gambling and gambling-type games on social networking sites: Issues, concerns, and recommendations. Aloma: Revista de Psicologia, Ciències de l’Educació i de l’Esport, 33(2), 31-37.

• Research indicates that compared to the general population, teenagers and students make the most use of social networking sites (SNSs). Although SNSs were originally developed to foster online communication between individuals, they now have the capability for other types of behaviour to be engaged in such as gambling and gaming. The present paper focuses on gambling and the playing of gambling-type games via SNSs and comprises a selective narrative overview of some of the main concerns and issues that have been voiced concerning gambling and gambling-type games played via social network sites. Overall, there is little empirical evidence relating to the psychosocial impact of adolescents engaging in gambling and gambling-type activities on SNSs, and the evidence that does exist does not allow definitive conclusions to be made. However, it is recommended that stricter age verification measures should be adopted for social games via SNSs particularly where children and adolescents are permitted to engage in gambling-related content, even where real money is not involved.

Canale, N., Vieno, A., Griffiths, M.D., Marino, C., Chieco, F., Disperati, F., Andriolo, S., Santinello, M. (2016). The efficacy of a web-based gambling intervention program for high school students: A preliminary randomized study. Computers in Human Behavior, 55, 946-954.

• Early onset in adolescent gambling involvement can be a precipitator of later gambling problems. The aim of the present study was to test the preliminary efficacy of a web-based gambling intervention program for students within a high school-based setting. Students attending a high school in Italy (N= 168) participated in the present study (58% male – age, M = 15.01; SD = 0.60). Twelve classes were randomly assigned to one of two conditions: intervention (N = 6; 95 students) and control group (N = 6; 73 students). Both groups received personalized feedback and then the intervention group received online training (interactive activities) for three weeks. At a two-month follow-up, students in the intervention group reported a reduction in gambling problems relative to those in the control group. However, there were no differences in gambling frequency, gambling expenditure, and attitudes toward the profitability of gambling between the two groups. In addition, frequent gamblers (i.e., those that gambled at least once a week at baseline) showed reductions in gambling problems and gambling frequency post-intervention. Frequent gamblers that only received personalized feedback showed significantly less realistic attitudes toward the profitability of gambling post-intervention. The present study is the first controlled study to test the preliminary efficacy of a web-based gambling intervention program for students within a high school-based setting. The results indicate that a brief web-based intervention delivered in the school setting may be a potentially promising strategy for a low-threshold, low-cost, preventive tool for at-risk gambling high school students.

Canale, N., Griffiths, M.D., Vieno, A., Siciliano, V. & Molinaro, S. (2016). Impact of internet gambling on problem gambling among adolescents in Italy: Findings from a large-scale nationally representative survey. Computers in Human Behavior, 57, 99-106.

• Aims: The primary aim of the present study was to understand the impact of online gambling on gambling problems in a large-scale nationally representative sample of Italian youth, and to identify and then further examine a subgroup of online gamblers who reported higher rates of gambling problems. Design: Data from the ESPAD^®Italia2013 (European School Survey Project on Alcohol and Other Drugs) Study were used for analyses of adolescent Internet gambling. Setting: Self-administered questionnaires were completed by a representative sample of high school students, aged 15–19 years. Participants: A total of 14,778 adolescent students. Measurements: Respondents’ problem gambling severity; gambling behavior (participation in eight different gambling activities, the number of gambling occasions and the number of online gambling occasions, monthly gambling expenditure); Socio-demographics (e.g., family structure and financial status); and control variables were measured individually (i.e., use of the Internet for leisure activities and playing video games). Findings: Rates of problem gambling were five times higher among online gamblers than non-online gamblers. In addition, factors that increased the risk of becoming a problem online gambler included living with non-birth parents, having a higher perception of financial family status, being more involved with gambling, and the medium preferences of remote gamblers (e.g., Internet cafes, digital television, and video game console). Conclusions: The online gambling environment may pose significantly greater risk to vulnerable players. Family characteristics and contextual elements concerning youth Internet gambling (e.g., remote mediums) may play a key role in explaining problem online gambling among adolescents.

Pallesen, S., Hanss, D., Molde, H., Griffiths, M.D. & Mentzoni, R.A. (2016). A longitudinal study of factors explaining attitude change towards gambling among adolescents. Journal of Behavioral Addictions, 5, 59–67

• Background and aims: No previous study has investigated changes in attitudes toward gambling from under legal gambling age to legal gambling age. The aim of the present study was therefore to investigate attitudinal changes during this transition and to identify predictors of corresponding attitude change. Methods: In all 1239 adolescents from a national representative sample participated in two survey waves (Wave 1; 17.5 years; Wave 2; 18.5 years). Results: From Wave 1 to Wave 2 the sample became more acceptant toward gambling. A regression analysis showed that when controlling for attitudes toward gambling at Wave 1 males developed more acceptant attitudes than females. Neuroticism was inversely related to development of acceptant attitudes toward gambling from Wave 1 to Wave 2, whereas approval of gambling by close others at Wave 1 was positively associated with development of more acceptant attitudes. Continuous or increased participation in gambling was related to development of more acceptant attitudes from Wave 1 to Wave 2. Conclusions: Attitudes toward gambling became more acceptant when reaching legal gambling age. Male gender, approval of gambling by close others and gambling participation predicted development of positive attitudes toward gambling whereas neuroticism was inversely related to development of positive attitudes toward gambling over time.

Ciccarelli, M., Griffiths, M.D., Nigro, G., & Cosenza, M. (2016). Decision-making, cognitive distortions and alcohol use in adolescent problem and non-problem gamblers: An experimental study. Journal of Gambling Studies, in press.

• In the psychological literature, many studies have investigated the neuropsychological and behavioral changes that occur developmentally during adolescence. These studies have consistently observed a deficit in the decision-making ability of children and adolescents. This deficit has been ascribed to incomplete brain development. The same deficit has also been observed in adult problem and pathological gamblers. However, to date, no study has examined decision-making in adolescents with and without gambling problems. Furthermore, no study has ever examined associations between problem gambling, decision-making, cognitive distortions and alcohol use in youth. To address these issues, 104 male adolescents participated in this study. They were equally divided in two groups, problem gamblers and non-problem gamblers, based on South Oaks Gambling Screen Revised for Adolescents scores. All participants performed the Iowa gambling task and completed the Gambling Related Cognitions Scale and the alcohol use disorders identification test. Adolescent problem gamblers displayed impaired decision-making, reported high cognitive distortions, and had more problematic alcohol use compared to non-problem gamblers. Strong correlations between problem gambling, alcohol use, and cognitive distortions were observed. Decision-making correlated with interpretative bias. This study demonstrated that adolescent problem gamblers appear to have the same psychological profile as adult problem gamblers and that gambling involvement can negatively impact on decision-making ability that, in adolescence, is still developing. The correlations between interpretative bias and decision-making suggested that the beliefs in the ability to influence gambling outcomes may facilitate decision-making impairment.

Dr. Mark Griffiths, Professor of Behavioural Addiction, International Gaming Research Unit, Nottingham Trent University, Nottingham, UK

Further reading

Griffiths, M.D. (1995). Adolescent Gambling. London: Routledge.

Griffiths, M.D. (2002). Gambling and Gaming Addictions in Adolescence. Leicester: British Psychological Society/Blackwells.

Griffiths, M.D. (2003). Adolescent gambling: Risk factors and implications for prevention, intervention, and treatment. In D. Romer (Ed.), Reducing Adolescent Risk: Toward An Integrated Approach (pp. 223-238). London: Sage.

Griffiths, M.D. (2010). Asian national adolescent gambling surveys: Methodological issues, protocols, and advice. Asian Journal of Gambling Issues and Public Health, 1, 4-18.

Griffiths, M.D. (2011). Adolescent gambling. In B. Bradford Brown & Mitch Prinstein (Eds.), Encyclopedia of Adolescence (Volume 3) (pp.11-20). San Diego: Academic Press.

Griffiths, M.D. (2013). Adolescent gambling via social networking sites: A brief overview. Education and Health, 31, 84-87.

Griffiths, M.D. & Linsey, A. (2006). Adolescent gambling: Still a cause for concern? Education and Health, 24, 9-11.

Griffiths, M.D. & Parke, J. (2010). Adolescent gambling on the Internet: A review. International Journal of Adolescent Medicine and Health, 22, 59-75.

Hayer, T. & Griffiths, M.D. (2015). The prevention and treatment of problem gambling in adolescence. In T.P. Gullotta & G. Adams (Eds). Handbook of Adolescent Behavioral Problems: Evidence-based Approaches to Prevention and Treatment (Second Edition) (pp. 539-558). New York: Kluwer.