Cognitive Distortions,Anxiety,and Depression Among Regular and Pathological Gambling Online Poker Players

Abstract

The aims were to assess cognitive distortions and psychological distress (anxiety and depression) among online poker players of different levels of gambling intensity (non-pathological gamblers [NPG], problem gamblers [PbG], and pathological gamblers [PG]), and to examine the relationship between these variables and gambling pathology. Overall, 245 regular online poker players recruited on an Internet forum completed online self-report scales assessing pathological gambling (South Oaks Gambling Screen [SOGS]), psychological distress (Hospital Anxiety and Depression Scale [HADS]) and cognitive distortions (Gambling-Related Cognition Scale). Based on their SOGS scores, poker players were ranked into three groups: NPG (n=146), PbG (n=55), and PG (n=44). All poker players appeared to be more anxious than depressive. PG exhibited higher levels of depression and anxiety than did PbG and NPG. Cognitive distortions also significantly discriminated PG from PbG and NPG. A regression model showed that the perceived inability to stop gambling, the illusion of control, depression (HADS D), and anxiety were good predictors for pathological gambling among poker players. Our results suggest that cognitive distortions play an important role in the development and maintenance of gambling pathology. This study also underlines the role of anxiety and depression in pathological gambling among poker players. It seems relevant to take these elements into account in the research, prevention, and treatment of pathological gambling poker players.

Introduction

Poker, especially online, is nowadays one of the most popular and widely practiced types of gambling,¹ mostly because of the component of skill involved in long-term success.^2,3 Although the influence of skill in poker outcomes has been debated in the literature, several recent studies have underlined the role of skill and strategy in this game. Liley and Rakow⁴ (2010) showed that mildly experienced poker players can have an accurate judgment of probabilities, leading them to make strategic decisions and perform better at poker than inexperienced players.⁵ Despite poker's increasing popularity, little is known about the specificities of pathological gambling among poker players.

Cognitive distortions play a central role in the development and maintenance of pathological gambling^6–8 (“persistent and recurrent maladaptive gambling behaviour⁹”). Erroneous gambling-related beliefs lead the gambler to deny the pattern of luck and chance of the game. Inherent in any gambling situation, irrational beliefs are present in every gambler, with a gradation in accordance with gambling intensity. In fact, research has underlined both a quantitative^8,10–13 and a qualitative¹⁴ difference between the cognitive distortions of pathological gamblers (PG) and non-pathological gamblers (NPG).

However, several studies have also highlighted that gambling is not a homogeneous activity.^15–17 Most of the studies assessing cognitive distortions in gambling are carried out either on gamblers performing laboratory tasks or on passive game gamblers. In active games, since the gamblers have some control over the game outcome,¹⁵ cognitive distortions could be different. According to some authors,^6,18 a game of skill gamblers tends to overestimate their capacity to win. In 2010, Myrseth, Brunborg, and Eidem,¹⁹ among a game of skill gamblers, found no differences in cognitive distortions between PG and NPG. Among poker players, Mitrovic and Brown²⁰ (2009) showed that cognitive distortions do not distinguish pathological from regular gamblers. However, Linnet et al²¹ (2011) showed that pathological gambling poker players and inexperienced poker players shared the same estimation bias and decision bias on a poker task. Cognitive distortions may, thus, play a different role in games of skill. Poker players may also present different irrational beliefs from chance gamblers.^21,22

The literature also shows that cognitive distortions may be influenced in their development and maintenance by negative psychological states (depression, stress, and anxiety).²³ In gambling situations, emotions interact with cognitions. Currently, depression is the disorder that is most frequently associated with addictions in general and is certainly linked to pathological gambling.^24,25 The link between anxiety and pathological gambling is also frequently established in the literature.^26,27 Among poker players, studies have shown that negative mood states (anxiety and depression) are risk factors¹ and predictors of pathological gambling.²⁸

The literature concerning the presence, nature, and influence of cognitive distortions among a game of skill gamblers is somewhat inconclusive. The issue of the specificities of gambling-related cognitive distortions among poker players remains unclear and deserves to be addressed in research that assesses specific cognitive distortions and pathological gambling simultaneously.

The principal aims of this study were to assess cognitive distortions and psychological distress (depression and anxiety) among regular poker players of different levels of gambling intensity and to examine the relationship between these variables and gambling pathology.

Methods

Procedure

Participants were recruited from one of the most active Internet poker-related forum in France with permission of the Web site's webmaster. Our announcement was seen 1014 times. Subjects were invited to click on a link leading to the online questionnaire. On the first page, the goals and methods of the research were explained, while the second page was the consent form. If they agreed, participants then had access to the online questionnaires. Participants were informed that their involvement in the research was completely voluntary, that responses were anonymous, and that they were free to withdraw at any time. No payment was made for participating. Data were screened to exclude potential multiple responses. Only full protocols were used, as 47 participants did not complete the whole questionnaire.

Participants

Our sample consisted of regular online poker players (who had been playing at least once a week for a minimum duration of 1 year¹⁶). Participants were required to be more than 18 years of age.

Gamblers with any regular gambling practice other than poker were excluded (n=2). Finally, we chose not to include gamblers seeking or receiving treatment. Since only 2 percent of PG are undergoing treatment, they may not be representative of the PG population.²⁹

Measures

The Sociodemographicquestionnaire

Sociodemographic data were obtained using a questionnaire (7 items) especially designed for the study, including questions on age, marital status, and professional status.

The South Oaks Gambling Screen (SOGS).³⁰

This is a 20-item self-report questionnaire including criterion measures of the counselor's judgment of patients' gambling and DSM-III-R criteria for pathological gambling. The SOGS has proved to be a reliable instrument and is the pathological gambling screening tool that is most frequently used in research.³¹ Internal consistency is 0.86 in PG (0.69 in the general population), sensitivity rate is 0.94, and specificity rate is 0.99 (in the general population and PG).³²

The Poker questionnaire

This 16-item questionnaire was designed for the present research and investigates several aspects of poker playing. Items referred to poker itself (preferred variant, number of poker Web sites used, and preferred type of game), financial aspects (average buy-in, maximum amount played, and maximum amount won), and characteristics of gambling practice (frequency and length of gambling sessions, age of onset, and duration of gambling practice). The questionnaire was pre-tested by ten regular poker players. After a few changes, a version was obtained that all 10 poker players were judged relevant.

The Hospital Anxiety and Depression Scale (HADS).³³

This 14-item self-report scale assesses psychological distress: anxiety (7 items) and depression (7 items). Widely used in research, it provides good psychometric qualities: Internal consistency varies from 0.68 to 0.93 for anxiety and from 0.67 to 0.90 for depression.³⁴ The cutoff score for an anxiety or depression disorder is 7.

The Gambling-Related Cognition Scale (GRCS).³⁵

This 23-item self-report scale assesses five types of cognitive distortion: interpretative bias (IB), illusion of control (IC), predictive control (PC), gambling-related expectancies, and perceived inability to stop gambling (IS). Items are presented as statements, and the subject is asked to indicate the extent to which he or she agrees with each item on a seven-point Likert scale. The GRCS provides good psychometric qualities (concurrent validity, criterion-related validity, and predictive validity).³⁵

Statistical analyses

The software Statistica® (version 9) was used for the statistical analyses. Kaplan–Meyer's test was used to assess normality, and Browne–Forsythe's test was used to assess homoscedasticity. Both were satisfactory. Comparisons for continuous variables (SOGS, HADS, and GRCS) were made using a one-way analysis of variance (ANOVA), followed by post-hoc analyses (Scheffe's test). For measures of effects sizes, a partial eta-squared test was used. Post-hoc analyses (Scheffe's test) were used to control for type I error and to conduct pairwise comparisons. For categorical data, differences in percentages were compared with the Chi-square test. Pearson's correlation coefficient was used to calculate correlation, so as to determine whether there were links between variables. Multiple regressions were conducted to see whether the assessed variables had a predictive value for pathological gambling. A p-value of<0.05 was used as a test of statistical significance.

Results

SOGS scores, sociodemographic data, and poker practice (Table 1)

Two hundred and forty-five (245) self-selected poker players completed the online questionnaires. In fact, 146 (59.5 percent) were NPG (assessed by an SOGS score under 3), 55 (22.4 percent) were problem gamblers (PbG) (an SOGS score between 3 and 4), and 44 (17.9 percent) were PG (an SOGS score equal to or higher than 5). The comparison of SOGS scores was significant across all groups (p<0.01).

Table 1.

SOGS Scores, Sociodemographic Data and Characteristics of Poker Practice

	NPG (n=146), mean (SD)	PbG (n=55), mean (SD)	PG (n=44), mean (SD)	All sample (n=245), mean (SD)	ANOVA (F)	p
AGE	29.60 (8.00)	28.16 (7.50)	28.86 (7.70)	29.14 (7.86)	0.70	0.49
SOGS	0.94 (0.76)	3.43 (0.50)	6.84 (2.11)	2.56 (2.49)	511.19	<0.01^*
Sessions/week	4.48 (2.28)	4.47 (2.86)	4.88 (1.91)	4.55 (2.36)	0.52	0.59
Hours/session	2.95 (1.71)	3.78 (1.81)	3.70 (1.75)	3.27 (1.78)	6.03	<0.01^*
					CHI	p
	N (%)	N (%)	N (%)	N (%)
PROFESSIONAL ACTIVITY					4.80	0.90
Full-time	76 (52.05)	29 (52.72)	22 (50.00)	127 (51.83)
Part-time	9 (6.16)	3 (5.45)	2 (4.54)	14 (5.71)
Irregular	8 (5.47)	3 (5.45)	3 (6.81)	14 (5.71)
Unemployed	14 (9.58)	9 (16.36)	3 (6.81)	26 (10.61)
Student	31 (21.23)	10 (18.18)	11 (25.00)	52 (21.22)
Other	8 (5.47)	1 (1.81)	3 (6.81)	12 (4.89)
SOCIO-PROFESSIONAL CATEGORY					16.12	0.09
Artisans	9 (6.16)	5 (9.09)	3 (6.81)	17 (6.93)
Executives	50 (34.24)	13 (23.63)	14 (31.81)	77 (31.42)
Intermediate prof.	13 (8.90)	3 (5.45)	5 (11.36)	21 (8.57)
Employees	35 (23.97)	16 (29.09)	3 (6.81)	54 (22.04)
Workmen	2 (1.36)	3 (5.45)	4 (9.09)	9 (3.67)
Other	37 (25.34)	15 (27.27)	15 (34.09)	67 (27.34)
FAMILY SITUATION					2.59	0.62
Single	80 (54.79)	35 (63.63)	28 (63.63)	143 (58.36)
Couple	63 (43.15)	19 (34.54)	16 (36.36)	98 (40.00)
Divorced	3 (2.05)	1 (1.81)	0 (0.00)	4 (1.63)
CHILDREN	36 (24.65)	13 (23.63)	10 (22.72)	59 (24.08)	0.07	0.96

p<0.05.

NPG, non-pathological gamblers; PbG, problem gamblers; PG, pathological gamblers; ANOVA, analysis of variance; Intermediate prof, Intermediate profession.

Among participants, only seven were women (2.8 percent). Since the prevalence and characteristics of pathological gambling may be different between men and women,³⁶ a statistical analysis was conducted to determine whether the women in our sample obtained significantly different scores from the men. Since the presence of women did not have any impact on the results, they were retained in the sample.

The mean age for all samples was 29.14 (SD=7.86). There was no significant difference in the sociodemographic data between the three groups.

A pairwise comparison using Scheffe's test (Table 2) shows that NPG gamble for significantly less time than do PbG (p<0.01) and PG (p=0.04).

Table 2.

Comparisons Between Groups (Scheffe's Test) on Each Scale

	NPG/PbG	NPG/PG	PG/PbG
	P	p	p
Age	0.51	0.86	0.90
SOGS	<0.01^*	<0.01^*	<0.01^*
Sessions/week	0.99	0.61	0.68
Hours/session	<0.01^*	0.04^*	0.97
HADS total	0.31	<0.01^*	<0.01^*
HADS anxiety	0.53	<0.01^*	<0.01^*
HADS depr.	0.39	<0.01^*	<0.01^*
GRCS	<0.01^*	<0.01^*	0.07
IB	0.01^*	0.03^*	0.99
IC	0.04^*	<0.01^*	0.02^*
PC	<0.01^*	<0.01^*	0.91
GE	0.60	0.99	0.76
IS	0.02^*	<0.01^*	<0.01^*

p<0.05.

Scale and questionnaire results (Tables 2 and 3)

Anxiety and depression (HADS)

The HADS results show that poker players, irrespective of their intensity of gambling, have higher levels of anxiety than of depression (p<0.01). However, the average score for anxiety (7.93) among PG is just above the cutoff score (7) for an anxiety disorder, while their depression score (M=5.06) is below the cutoff score (7) for a depressive disorder.

Table 3.

Scale Results and Comparisons Using Analysis of Variance

	NPG (n=146), mean (SD)	PbG (n=55), mean (SD)	PG (n=44), mean (SD)	Total (n=245), mean (SD)	ANOVA (F)	p
HADS total	6.71 (3.89)	7.74 (3.36)	13.00 (6.18)	8.07 (4.87)	36.50	<0.01^*
HADS anxiety	4.36 (2.71)	4.87 (2.17)	7.93 (3.93)	5.11 (3.15)	26.48	<0.01^*
HADS depr.	2.34 (2.05)	2.85 (2.15)	5.06 (3.24)	2.95 (2.53)	23.06	<0.01^*
GRCS	61.45 (14.68)	69.74 (15.14)	76.70 (15.22)	66.05 (15.94)	219.85	<0.01^*
IB	14.79 (4.76)	17.01 (4.94)	16.97 (4.59)	15.68 (4.88)	6.28	0.02^*
IC	6.22 (3.03)	7.61 (3.41)	9.54 (4.74)	7.13 (3.68)	16.07	<0.01^*
PC	14.17 (4.89)	16.83 (5.39)	17.29 (6.08)	15.33 (5.40)	8.84	<0.01^*
GE	13.58 (3.99)	12.90 (4.23)	13.59 (4.85)	13.43 (4.20)	0.54	0.57
IS	12.92 (5.48)	15.36 (6.02)	19.65 (6.05)	14.68 (6.22)	24.01	<0.01^*

p<0.05.

HADS, Hospital Anxiety and Depression Scale; HADS Depr., Depression; GRCS, Gambling-Related Cognition Scale; IB, interpretative bias; IC, illusion of control; PC, predictive control; GE, gambling-related expectancies; IS, inability to stop gambling.

When the three groups are compared, the ANOVA results show a significant difference for the HADS total (F_2,242=36.5; effect size=612.62; p<0.01) as well as for the two subscales: anxiety (F_2,242=26.48; effect size=217.45; p<0.01) and depression (F_2,242=23.06; effect size=125.29; p<0.01). A more specific mean comparison using Scheffe's test shows that both subscales (anxiety and depression) significantly discriminate the three groups of gamblers: PG obtain significantly higher scores than PbG (p<0.01 for anxiety and depression) and NPG (p<0.01 for both subscales). In fact, 29 percent of PG present a depressive disorder, and 56 percent of them present an anxiety disorder.

In fact, the severity of gambling practice (SOGS) appears to be positively linked to anxiety (r=0.42; p<0.05) and depression (r=0.45; p<0.05).

Cognitive distortions (GRCS)

Among NPG and PbG, the most intense cognitive distortion is the IB; whereas among PG, the highest scores are found for the IS.

Cognitive distortions (GRCS total) appear to discriminate the three groups significantly (F_2,242=20.06; Effect size=4411.67; p<0.01). Scheffe's test confirms this result: There is a gradation in cognitive distortion intensity (except gambling related expectancies) according to the intensity of the gambling practice. IB and PC are significantly lower among NPG than PbG (p=0.01 for IB; p<0.01 for PC) and PG (p=0.03 for IB; p<0.01 for PC).

Both the IC and the IS significantly discriminate the three groups: Their intensity increases as gambling severity rises. Thus, PG have higher scores on these two subscales than do PbG (p=0.02 for IC, p<0.01 for IS). These distortions are most significantly correlated to the intensity of gambling practice (r=0.29 for IC, r=0.41 for IS; p<0.05).

Cognitive distortions (GRCS total) are also positively correlated to negative psychological states (HADS total) (r=0.26, p<0.05), in particular the perceived IS (r=0.38, p<0.05).

Multiple regression

A multiple regression model, including cognitive distortions, anxiety, and depression, shows that these variables account for 36 percent of the variance in SOGS scores (Adjusted R²=0.34; F(7.237)=19.081; p<0.001). The best predictors for SOGS scores in this model are the perceived IS (β=0.26; p<0.001), the IC (β=0.23; p<0.001), depression (β=0.20; p<0.001), and anxiety (β=0.15; p=0.01).

Part correlations are significant for anxiety (r=0.25; R²=0.21; p<0.001) and depression (r=0.28; R²=0.21; p<0.001).

Discussion

Despite poker's increasing popularity, only a few researchers have studied the characteristics of this type of gambler. In our sample, the prevalence of pathological gambling was 17.9 percent, which was similar to the result found by Wood et al.¹ (2007), but higher than that found by Hopley and Nicki²⁸ (2010). We also found that 22.4 percent of the sample are PbG. The three groups of gamblers do not display any differences in their sociodemographic data. PG gamble for significantly longer than NPG do. However, the longest gambling sessions are reported by PbG: They last 3.78 hours on average, just above PG (3.70).

Cognitive distortions are thought to play a central role in the development and maintenance of pathological gambling. Nevertheless, among a game of skill gamblers, two studies^19,20 have found that cognitive distortions do not discriminate PG and NPG. However, both these studies used the Gambler's Belief Questionnaire,³⁷ a scale known to be reliable but which only measures two types of cognitive distortion (IC and luck/perseverance).

Nevertheless, Linnet et al.²¹ (2011) showed that pathological gambling poker players and inexperienced poker players performed worse at the task than did experienced poker players. They suggest that pathological gambling poker players do not have a lack of probability estimation³⁸ but are likely, and willing, to engage in risky gambles.²¹ This may be explained by Sévigny and Ladouceur's³⁹ double-switching concept (2003): PG may vacillate between two cognitive states: One focused on an objective and rational view of the odds, and the other centered on information about the activity and outcomes.

In our study, we used the GRCS,³⁵ which assesses five types of cognitive distortion. Unlike Myrseth et al.¹⁹ (2010) and Mitrovic and Brown²⁰ (2009), we found that cognitive distortions significantly discriminate PG, PbG, and NPG among poker players. In our study, NPG have lower scores for IB (reframing gambling outcomes that would encourage continued gambling despite losses) and PC (means by which the subject can predict gambling outcomes) than PbG and PG. Only gambling-related expectancies do not discriminate the three groups of gamblers, suggesting that, irrespective of the severity of the gambling, all poker players share the same expectations about their gambling practice: to demonstrate one's worth, receive approval and social acceptance from others, rebel, relieve negative emotions, try to beat the odds, experience gambling-related excitement, reduce boredom, and have fun.³⁵

Although the lowest scores in all groups are those of the IC (belief that one can influence gambling outcomes via skill, ability, or knowledge), it seems, nevertheless, that this cognitive distortion is the one, along with the perceived IS, which is the most strongly linked to gambling severity. In fact, both of them are good predictors of pathological gambling. The IC, thus, seems to play an important role in pathological gambling among poker players. Our results also suggest that the more the gambler experiences gambling-related difficulties, the more he thinks he is unable to stop gambling. This result is not really surprising, as one of the criteria of pathological gambling is the fact that the gambler thinks he cannot stop or control his gambling practice. Moreover, the fact that poker is a game where skill plays an important role may favor the installation of cognitive distortions: Players may tend to attribute their win to their skill and their loss, to bad luck. This element raises the issue of the addictive potential of poker: The skill component of the game may not only attract players but also enhance cognitive distortions and, therefore, potential gambling pathology.

Cognitive distortions also appear to be linked to anxiety and depression, as previously shown by Oei, Lin, and Raylu²³ (2008). Similar to Hopley and Nicki²⁸ (2010), we found that problem gambling among poker players can be predicted by negative psychological states (depression and anxiety).

However, depression scores and the prevalence of depressive disorders among PG (29 percent) appear to be relatively low compared with the literature data.^24,25 Although depression significantly discriminates the three groups of gamblers, the level of these mood disorders is not of clinical relevance. In our sample, the gamblers were not seeking treatment and may, thus, experience less severe gambling problems and, therefore, lower depression levels than the treatment-seeking PG studied in most research. Moreover, this difference may be related to the type of the game: Pathological card gamblers exhibit lower depression scores than do other PG.^16,17 Our results also underline the importance of anxiety among poker players. However, as for depression, the average anxiety scores are below the cutoff scores for a disorder except for PG (56 percent of whom met the criteria for an anxiety disorder).

Previous studies have also found that anxiety mirrors pathological gambling severity^25,26 and is a risk factor for pathological gambling,²⁷ including among poker players.²⁸ The results of our study are consistent with the literature but do not allow us to determine whether anxiety is primary, secondary, or co-occurring with pathological gambling. Further studies should investigate these links more accurately. Nevertheless, although anxiety scores are significantly higher than depression scores, the multiple regression model suggests that depression plays a greater role in pathological gambling than anxiety, as it constitutes a better predictor.

This study focuses on online poker players. It has several limitations that should be taken into account for the interpretation and generalization of the results. First, it is an online study, with self-selected participants, who may not be totally representative of the poker player population. The online survey did not allow us to include a hetero-evaluation screening of problem gambling, such as the DSM-IV-TR⁹ (2004) criteria. This could have been useful, given that the SOGS is known to favor false positives, especially in the general population.³² The prevalence of pathological gambling in the present sample may, thus, be lower than the 17 percent we found.

Despite these limitations, the present study offers interesting results and research perspectives. We have found that poker players, regardless of their gambling severity, are more likely to be anxious than depressive. Further research should investigate more specifically the role of anxiety in the development and maintenance of pathological gambling among poker players.

We have also found that cognitive distortions are linked to gambling severity, especially the IC. In games of skill, such as poker, it would be interesting to conduct further research about the specificity of the IC. Moreover, the literature data^22,38 suggest that cognitive distortions may result from gambling problems. Future research is needed to determine the temporal occurrence of cognitive distortions and pathological gambling.

These findings may also have some implications for the treatment of pathological gambling poker players: The importance of anxiety, as well as cognitive distortions, should be taken into account in therapy. In poker, information and education about what the gambler can and cannot control could be useful not only for pathological gambling treatment but also for preventive action.

Author Disclosure Statement

No competing financial interests exist.

References

Wood

, Griffiths

, Parke

. Acquisition, development and maintenance of online poker playing in a student sample. Cyberpsychology and Behaviour, 2007; 10:354–363.

Shead

, Hodgins

, Scharf

. Differences between poker players and non-poker-playing gamblers. International Gambling Studies, 2008; 8:167–178.

Browne

. Going on tilt: frequent poker players and control. Journal of Gambling Behavior, 1989; 5:3–21.

Liley

, Rakow

. Probability estimation in poker: a qualified success for unaided judgment. Journal of Behavioural Decision Making, 2010; 23:496–526.

St-Germain

, Tenenbaum

. Decision-making and thought processes among poker players. High Abilities Studies, 2011; 22:3–17.

Walker

. 1992. The psychology of gambling. Sydney: Pergamon Press.

Ladouceur

, Walker

. 1996. A cognitive perspective on gambling. Salkovskis

. Trends in cognitive and behavioural therapies. New York: Wiley, 89–120.

Miller

, Currie

. A Canadian population level analysis of the role of irrational gambling cognitions and risky gambling practices as correlates of gambling intensity and pathological gambling. Journal of Gambling Studies, 2008; 24:257–274.

American Psychiatric Association. 2004. DSM-IV-TR: Diagnostic and statistical manual of mental disorders. Washington, DC: Author.

10.

Griffiths

. The role of cognitive bias and skill in fruit machine gambling. British Journal of Psychology, 1994; 85:351–369.

11.

Joukhador

, Maccallum

, Blaszczynski

. Differences in cognitive distortions between problem and social gamblers. Psychological Reports, 2003; 92:1203–1214.

12.

Delfabbro

, Lahn

, Grabosky

. It's not what you know but how you use it: statistical knowledge and adolescent problem gambling. Journal of Gambling Studies, 2006; 22:179–193.

13.

Toneatto

, Blitz-Miller

, Calderwood

et al. Brief report: cognitive distortions on heavy gambling. Journal of Gambling Studies, 1997; 13:253–266.

14.

Källmen

, Andersson

, Andren

. Are irrational beliefs and depressive mood more common among problem gamblers than non-gamblers? a survey study of Swedish problem gamblers and controls. Journal of Gambling Studies, 2008; 24:441–450.

15.

Bonnaire

, Lejoyeux

, Dardennes

. Sensation seeking in a French population of pathological gamblers: comparison with regular and non-gamblers. Psychological Reports, 2004; 94:1361–1371.

16.

Bonnaire

, Bungener

, Varescon

. Subtypes of French pathological gamblers: comparison of sensation seeking, alexithymia and depression scores. Journal of Gambling Studies, 2009; 25:455–471.

17.

Petry

. A comparison of treatment seeking pathological gamblers based on preferred gambling activity. Addiction, 2003; 98:645–655.

18.

Cantinotti

, Ladouceur

, Jacques

. Sports betting: can gamblers beat randomness? Psychology of Addictive Behaviors, 2004; 18:143–147.

19.

Myrseth

, Brunborg

, Eidem

. Differences in cognitive distortions between pathological and non-pathological gamblers with preferences for chance or skill games. Journal of Gambling Studies, 2010; 26:561–569.

20.

Mitrovic

, Brown

. Poker mania and problem gambling: a study of distorted cognitions, motivation and alexithymia. Journal of Gambling Studies, 2009; 25:489–502.

21.

Linnet

, Froslev

, Ramsgaard

et al. Impaired probabilities estimation and decision making in pathological gambling poker players. Journal of Gambling Studies, 2012; 28:113–122.

22.

Linnet

, Gebauer

, Shaffer

et al. Experienced poker players differ from inexperienced poker players in estimation bias and decision bias. Journal of Gambling Issues, 2010; 24:86–101.

23.

Oei

, Lin

, Raylu

. The relationship between gambling cognitions, psychological states and gambling: a cross-cultural study of Chinese and Caucasians in Australia. Journal of Cross-cultural Psychology, 2008; 39:147–161.

24.

Lorains

, Cowlishaw

, Thomas

. Prevalence of comorbid disorders in problem and pathological gamblers: systematic review of population survey. Addiction, 2011; 106:490–498.

25.

Won Kim

, Grant

, Eckert

et al. Pathological gambling and mood disorders: clinical associations and treatment implication. Journal of Affective Disorders, 2006; 92:109–116.

26.

El Guebaly

, Patten

, Currie

et al. Epidemiological associations between gambling behavior, substance use and mood and anxiety disorders. Journal of Gambling Studies, 2006; 22:275–287.

27.

Ste-Marie

, Gupta

, Derevensky

. Anxiety and social stress related to adolescent gambling behaviors and substance use. Journal of Child and Adolescent Substance Abuse, 2006; 15:55–76.

28.

Hopley

, Nicki

. Predictive factors of excessive online poker playing. Cyberpsychology, Behavior and Social Networking, 2010; 13:379–385.

29.

Bagby

, Vachon

, Bulmash

et al. Pathological gambling and the five-factor model of personality. Personality and Individual Differences, 2007; 43:873–880.

30.

Lesieur

, Blume

. The South Oaks Gambling Screen: a new instrument for the identification of pathological gambling. Journal of American Psychiatry, 1987; 14:1184–1188.

31.

Shaffer

, Hall

, Vander Bilt

. Estimating the prevalence of disordered gambling behaviors in the United States and Canada: a research synthesis. American Journal of Public Health, 1999; 89:1369–1378.

32.

Stinchfield

. Reliability, validity and classification accuracy of the South Oaks Gambling Screen (SOGS) Addictive Behaviors, 2002; 27:1–19.

33.

Snaith

. The hospital anxiety and depression scale. Health and Quality of Life Outcomes, 2003; 1:1–4.

34.

Bjelland

, Dahl

, Haug

et al. The validity of the hospital anxiety and depression scale: an updated literature review. Journal of Psychosomatic Research, 2002; 52:69–77.

35.

Raylu

, Oei

. The gambling related cognitions scale (GRCS): development, confirmatory factor validation and psychometric properties. Addiction, 2004; 99:757–769.

36.

Petry

, Stinson

, Grant

. Comorbidity of DSM-IV pathological gambling and other psychiatric disorders: results from the national survey on alcohol and related conditions. Journal of Clinical Psychiatry, 2005; 66:564–574.

37.

Steenbergh

, Meyers

, May

et al. Development and validation of the Gambler's beliefs questionnaire. Psychology of Addictive Behaviors, 2002; 2:143–149.

38.

Lambos

, Delfabbro

. Numerical reasoning ability and irrational beliefs in problem gambling. International Gambling Studies, 2007; 7:157–171.

39.

Sévigny

, Ladouceur

. Gamblers' irrational thinking about chance events: the ‘double switching’ concept. International Gambling Studies, 2003; 3:149–161.

Cognitive Distortions,Anxiety,and Depression Among Regular and Pathological Gambling Online Poker Players

Abstract

Abstract

Introduction

Methods

Procedure

Participants

Measures

The Sociodemographicquestionnaire

The South Oaks Gambling Screen (SOGS). 30

The Poker questionnaire

The Hospital Anxiety and Depression Scale (HADS). 33

The Gambling-Related Cognition Scale (GRCS). 35

Statistical analyses

Results

SOGS scores, sociodemographic data, and poker practice (Table 1)

Scale and questionnaire results (Tables 2 and 3)

Anxiety and depression (HADS)

Cognitive distortions (GRCS)

Multiple regression

Discussion

Author Disclosure Statement

References

The South Oaks Gambling Screen (SOGS).³⁰

The Hospital Anxiety and Depression Scale (HADS).³³

The Gambling-Related Cognition Scale (GRCS).³⁵