Category Archives: Online addictions
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 (Mage=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 21st 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.
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.
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.

