When Behavioural Addictions collide: A comparison of problem Internet Gamblers with non Internet Gamblers

Transcription

1 When Behavioural Addictions collide: A comparison of problem Internet Gamblers with non Internet Gamblers Dr Marcus PJ Tan, BSc MBBS MRCPsych Psychiatry NIHR Academic Clinical Fellow, ST3 in collaboration with the National Problem Gambling Clinic, London

2 Outline of Presentation Behavioural VS Substance misuse addictions: similarities and differences. A brief history of internet addiction. Problem Gambling and Internet Addiction: current research. Our Findings. Conclusion.

3 Addictions? Whereas the concept of abnormal patterns of substance use have existed since Aristotle and Alexander the Great the idea that this is similar to non substance related activities only emerged recently (Marks 1990: non chemical addictions ). Current research suggests the two share similar neurobiological mechanisms. Serotonin, Glutamate, Dopamine, Noradrenaline, Opioids all implicated. fmri results: diminished vmpfc activation Pathological gambling and alcohol dependence have shared genetic vulnerabilities They are also thought to share similar symptoms of excessive use, namely: tolerance to use, increased salience, withdrawal symptoms, and use despite harm.

4 Some objections to the concept of behavioural addictions. Disagreements regarding diagnostic construct. How is one meant to interpret these signs in different disorders? The stated symptoms of withdrawal and tolerance tend to involve metaphorical use of the terms, or coarse behavioural criteria (Pies 2009). So what constitutes tolerance to use, withdrawal symptoms, etc? Where to draw the line between normal passion and abnormal addiction? Cultural differences in perceptions of normality. Atheoretical, confirmatory approaches that rely solely on these coarse symptoms runs the risk of overpathologizing normal behaviours (Billieux et al 2015). Potential overlap with existing diagnoses? Mental disorder usually more common in patients.

5 The case of Internet Addiction Young s (1998) study on 396 dependent internet users, that eventually gave rise to the Internet Addiction Test. Inpatient facilities specialising in its treatment have been opened in Asia. Specialist clinics have also begun to appear in USA, UK. Prevalance studies have found it to vary from ~1% to >10%, depending on factors like: Age (almost all studies focus on adolescent population) Presence of psychiatric comorbidity (tends to increase it) Locality and?cultural factors (usually more in Asian countries) Controversy on diagnostic constructs: separate or not with gaming? DSM 5: Internet gaming disorder as a disorder for further consideration. ICD 11 beta draft: Gaming disorder, with subclassifiers of predominantly online or predominantly offline The criteria for both disorders are very similar, and share many features with substance misuse.

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7 Addicted TO the internet, or an Addiction BECAUSE of the internet? Internet addiction as addiction to a medium (Starcevic and Abojaoude). Is the medium inseparable from the addiction? How much of a role does the internet have in causing the addictive behaviour?

8 On Problem Gambling and Internet Addiction 17% of ALL British adults have gambled online (Gambling survey data 2015). But only 0.7% of gamblers are problem gamblers (British 2015 census data) And NONE of the studies have been conducted on the problem gambling population. The internet s role in the addictive process: anonymity, increased interactivity, accessibility, convenience e.g. with digital money and feeling they are not spending real money. Head to head comparisons with Internet and non Internet gamblers suggest differences based on their preferred medium and engagement with gambling. But these can define online gamblers as those who have gambled online at least once in the past 12 months. The findings are thus less relevant to the clinical population of problem online gamblers. Does the internet cause disordered gambling? Most studies find online gamblers are more likely to report disordered gambling behaviour (Gainsbury 2015). Although the association might be explainable by other variables (Philander and MacKay s 2014 study that utilised ordered regression).

9 Gacha games: Internet addiction, gaming addiction, gambling addiction, or all of the above? Gacha = from the Japanese gachapon capsule machines. Money is spent to obtain one of a predefined set of goods, where the most desirable item is usually the rarest. This model has been used with great success in games played on a smartphone, where real money is spent for a chance at obtaining a video game s most desirable something (e.g. powerups, special weapons, characters, etc). I consider these distinct from games that guarantee something in return for real money the gambling aspect is absent. Over half (58%) of the games in the U.S. top grossing 100 list (ios) use gachas in gameplay. Over one third (37%) of the games outside top grossing 100 also feature this mechanic. A famous case for one popular gacha game involved US$6065 spent in one night to obtain a limited time character (from Bloomberg technology news report, Nakamura 2016). How should an addiction to gacha games be classified? As gambling: they are games of chance? As internet: the specific appeal of the internet/technology in making these games attractive, e.g. the accessibility of smartphones? As games: psychological drives to obtain the character/etc operate within the context of gaming models, e.g. drive to succeed via a powerful weapon corresponds with Bartle s Killer player type?

10 The current study: methods Data from problem gamblers collected from referrals to the National Problem Gambling Clinic, UK. Patients were asked via questionnaire about the forms and types of gambling they CURRENTLY use, and their status as online gamblers classified accordingly: None = not using online gambling All = exclusively online gamblers. Some = gamblers who used both modalities. Online gambling included gambling on PC, laptop, mobile, tablet. Administered IAT, UCLA Loneliness Scale, LSNS 18, PGSI, CORE 10, PHQ 9, GAD 7. All these questionnaires administered before start of treatment. The study is thus novel in that it: Directly compares two different behavioural addictions that are interrelated. Does this in the patient population (as opposed to the general public).

11 Caveats to our results Small sample size! The sample is exclusively problem gamblers, and thus distinct from studies assessing the general public. The study has NOT been designed to test causation.

12 IAT This was developed by US researcher Dr Kimberley Young in It is recognised as the first validated questionnaire for this purpose, and has since been translated into several different questionnaires The current version is scored as follows: NORMAL RANGE 0 30 points MILD points MODERATE points SEVERE points N/B: some versions omit does not apply as a score.

13 Do Online Problem Gamblers show more symptoms of Internet Addiction than non online problem gamblers? This feels an important consideration, given that the IAT was developed for general internet users, and not gamblers. It is also interesting considering that Young s test was not used on the gambling population; neither were smartphone/tablets as available back then. We noted higher mean values in the all group than the none group; and the data spread for all also seems higher. However, the overall score remains well below the severe cutoff the test has been established for. As such, while there may be some difference in internet usage between the two groups, even problem online gamblers are not displaying signs of internet addiction.

14 UCLA loneliness scale This was designed as a subjective measure of feelings of loneliness and social isolation. It has undergone 2 revisions since its first release. Higher scores mean the person feels MORE lonely. No specified cutoffs.

15 Do Online Problem Gamblers feel more lonely than non online problem Gamblers? Loneliness is associated with internet use (Amichai and Ben 2002), particularly with social uses of the internet (e.g. chat, , etc. Morahan and Schumacher 2003), but also for more general entertainment (Whitty and McLaughlin 2005). These studies of the general public suggest that loneliness causes people to engage with the internet more. Just as gambling could begin as a social activity, but evolve to become isolating as problems escalate (Fabiansson 2006). Despite a larger spread of data in the all group, the mean values do not seem too different.

16 LSNS 18 These 18 questions seek to obtain an objective measure of social connectedness. This is distinct from the UCLA scale s subjective measure. Higher scores mean more social connectedness. No cutoffs. The scale does NOT include a section for online associations.

17 Are online problem gamblers more or less well connected than non online gamblers? This objective measure of social connectedness is distinct from the UCLA scale. The mean scores are not all that different.

18 PGSI questionnaire 9 items taken from a 31 item Canadian Problem Gambling Index. Cutoffs are: 0: no problem gambling 1 2: Low level of problems with few or no identified negative consequences 3 7: Moderate level of problems leading to some negative consequences 8 27 or more: Problem gambling with negative consequences and a possible loss of control

19 Are online problem gamblers more severe gamblers? Most studies find online gamblers are more likely to report disordered gambling behaviour, however few studies have been done on patient problem gambling population. Our all group has a relatively lower mean, though the large spread of data is also noted. Regardless, ALL groups have scored above the cutoff for problem gambling.

20 Core 10 Stands for Clinical Outcomes in Routine Evaluation. 10 items drawn from a larger questionnaire commonly used in the evaluation of psychological therapies. Cutoffs: A score of 10 or below indicates a score in the non clinical range.

21 CORE 10: Do online problem gamblers have more or less psychiatric symptoms? Both problem gambling (Lloyd et al 2010) and problematic internet use (Cao et al 2011) are associated with psychological symptoms. However, the relationship likely operates in both ways: in that psychological problems are both motivation for disordered gambling/internet use, just as they are made worse by it. In this measure of general psychiatric symptoms, the all group was found to have a lower score, along with a downward trend. We also note the lowest mean score to be above the threshold for clinical significance.

22 PHQ 9 This popular questionnaire on the symptoms of depression has been validated for use in UK primary care. Cutoffs for Depression Severity: 0 4 none, 5 9 mild, moderate, moderately severe, severe.

23 PHQ 9: Are online gamblers more or less depressed? Positive associations between PGSI score and DSM IV based depression score in a population based sample (Churchill and Farrell 2017). However, our sample found lower PHQ 9 scores in the online gamblers. We also note the mean scores to be just above the cutoff for mild depression.

24 GAD 7 A validated questionnaire for anxiety. Cutoffs: 0 4 none 5 9 mild, moderate, severe

25 GAD 7: Are online problem gamblers more or less anxious? >11% of pathological gamblers have generalised anxiety disorder, 22% with panic disorder, 52% with a specific phobia (USA census data, from Shaffer 2012). Anxiety is closely related with social uses of the internet (e.g. chat, social media, social online games), however fewer studies have investigated its relationship with more generalised internet use. Our study found relatively lower scores in GAD 7 in the all group.

26 Other general findings of note None of the differences were statistically significant on (the Kruskal Wallis) difference tests. Note small sample size. The some group had the largest spread of data, seeming to span the range of values from both the none and all groups. As a group that participates in both online and non online gambling, this probably reflects how the group includes both the predominantly online, and the predominantly offline gamblers.

27 Current Conclusions There seems to be a different profile between exclusively online gamblers and nononline gamblers, while the partially online gambler group seemed to have participants drawn from both groups. In particular, we note the online group to have a positive PGSI but a negative IAT score: which suggests they are more gamblers than internet addicts, with internet addiction seeming to refer to more general use of the internet. We also note that the online gambler group seemed to fare better, in particular on scales measuring psychiatric symptom severity. That said, both groups seemed to score within the threshold value, suggesting that this is not a reflection of online gambling being less harmful. The results could paint a picture of online gambling as a hidden disorder. Online gamblers might be more able to hide their addiction by unobtrusive use of their smartphone and displaying less noticeable symptoms and functional impact; compared to non online gambling that requires physical attendance at the gambling venue.?diagnostic implications: gambling disorder too broad a category. Further research to examine what other features in gambling disorder are of relevance.

28 Current Conclusions Internet Addiction is NOT a homogenous entity. and neither is Gaming Addiction.

29 Behavioural Addictions needs a Holistic Approach (it s not that difficult ) BIO Genetic influence Differences in brain chemistry Different patterns in brain activation PSYCHO Their own health beliefs and exploratory model RE addiction (Dinos et al 2017) Differences in attentional bias, reward seeking, salience of behaviours. SOCIAL Personal relationships: family, socially, online Relationship with the industry that markets the behaviour: ads Cultural perceptions of the behaviour

30 Special Thanks Dr Alison Battersby for telling me about the prize Dr Henrietta Bowden Jones for her support The NIHR for practical support that made this work possible and you for listening. Any Questions??