impulsivity as a mediator in the relationship between depression and problem gambling

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Personality and Individual Differences 40 (2006) 5–15

Impulsivity as a mediator in the relationship betweendepression and problem gambling

Dave Clarke *

School of Psychology, Massey University, Albany Campus, Private Bag 102 904,

North Shore Mail Centre, New Zealand

Received 13 September 2004; accepted 6 May 2005Available online 9 August 2005

Abstract

The purpose of the study was to investigate the effect of impulsivity as a mediator in the relationshipbetween depression and problem gambling in a non-clinical sample. A questionnaire containing demo-graphic questions, the Revised South Oaks Gambling Screen (SOGS-R), a depression inventory, and theEysenck impulsiveness scale was completed by 159 New Zealand university students who gambled formoney, aged 18–49 years (mean = 27.9, SD = 10.2). Depression, impulsivity and problem gambling weresignificantly correlated (p < 0.01), after controlling for sex and age. Multiple linear regression analysis ofdata showed that impulsivity functioned as a full mediator between depression and problem gambling.The findings were related to an integrated model of problem gambling wherein the path of emotional vul-nerability (depression) to the severity of problem gambling, is mediated by an impulsive trait. Therapies forimpulse control could be supplemented with treatments which alleviate emotional depression in impulsivegamblers and thus attenuate the strengths of the effects of depression and impulsivity on problem gamblingsymptoms.� 2005 Elsevier Ltd. All rights reserved.

Keywords: Depression; Impulsivity; Problem gambling

0191-8869/$ - see front matter � 2005 Elsevier Ltd. All rights reserved.doi:10.1016/j.paid.2005.05.008

* Tel.: +64 9 414 0800x9075; fax: +64 9 441 8157.E-mail address: [email protected]

mailto:[email protected]

6 D. Clarke / Personality and Individual Differences 40 (2006) 5–15

1. Introduction

Blaszczynski and Nower (2002) have proposed an integrated pathways model of problem gam-bling, based on an extensive review of the literature and empirical research. Three groups of pro-blem gamblers were identified: (1) gamblers whose lack of control over their gambling is due tocognitive-behavioural conditioning, (2) gamblers who are biologically and emotionally vulnerablewith high levels of depression and/or anxiety, and (3) gamblers who are not only vulnerable, butalso impulsive, antisocial, and frequently addicted to other behaviours such as substance abuse.

The pathway to problem gambling for all three groups begins with ecological factors such asavailability and accessibility of gambling activities which are socially accepted, encouraged andpromoted. The first group then follows the path via classical and operant conditioning with con-comitant cognitive schemas of irrational beliefs and illusion of control, resulting in habituationand attempts to recoup losses by more gambling, to problem gambling symptoms. The gamblersin this group may initially gamble for entertainment or socialization and have fewer symptomsthan the other two groups.

The second group follows the same path, except that before getting involved in gambling andassociated conditioning, they are biologically and emotionally at risk for problem behaviours.Biologically, receptor genes and neurotransmitters are linked to reward deficiency, arousal levels,impulsivity and pathological gambling (Blum et al., 1996; cited in Blaszczynski & Nower, 2002).Emotional vulnerability arises from childhood disturbances, boredom proneness, depression and/or anxiety due to biological and psychosocial deficiencies, and poor coping and problem-solvingskills. This group escapes unpleasant physiological states by choosing monotonous gamblingactivities such as gaming machines to dissociate from their feelings, or by seeking stimulatingactivities such as increasing bets on horse racing and sports events. They are less likely to respondto treatment than the first group because of their underlying biological and psychological predis-positions toward emotional disturbances.

The third group consists of emotionally and biologically vulnerable gamblers who display impul-sivity, antisocial behaviour and, frequently, substance abuse (Petry, 2000). They are the most likelyof the groups to have entrenched problem gambling symptoms and the most difficult to treat. Forthis group, Blaszczynski and his colleagues (Blaszczynski, Steel, &McConaghy, 1997; Steel & Blas-zczynski, 2002) have provided strong empirical evidence for an ‘‘impulsivity-psychopathy’’ con-struct which they purport mediates the effects of emotional and biological vulnerability onseverity of gambling behaviour. Mediation implies that as depression increases, the number ofproblem gambling symptoms increase but through impulsivity. However, they did not test statis-tically for the mediating effect of impulsivity on the relation between vulnerability and problemgambling symptoms, or for the interaction effect of depression and impulsivity accounting forgreater variance in problem gambling symptoms than the main effects of these two variables.

Baron and Kenny (1986) have provided several guidelines for investigating empirically the ef-fects of a mediator on a statistically predictive relationship. When individual differences are in-volved, a mediator represents a property or stable characteristic of a person that transformsthe predictor variables in some way. For impulsivity to function as a mediator in the path fromdepression to problem gambling, two conceptual relationships are assumed: (1) depression pre-cedes problem gambling, rather than vice-versa, and (2) problem gambling is not a cause ofimpulsivity.

D. Clarke / Personality and Individual Differences 40 (2006) 5–15 7

In the present investigation, the focus was on the third path of the integrated model linking thepredisposition of depression and the trait of impulsivity to problem gambling symptoms. Depres-sion is frequently found among problem gamblers in a wide range of countries (e.g., Abbott, 2001;Getty, Watson, & Frisch, 2000; Gupta & Derevensky, 1998; Lopez Viets, 2001; Murray, 1993;Raviv, 1993). Problem gamblers have more symptoms of depression than non-problem gamblers.The question then arises whether a chronic state of depression and impulsivity precedes problemgambling, or if gambling problems with concomitant personal and financial difficulties lead todepression and impulsivity. For impulsivity, Vitaro, Arseneault, and Tremblay (1999) have shownin a prospective design with children that impulsivity is a predictor of problem gambling, and notvice-versa. Much of the research linking impulsivity to problem gambling has been based on clin-ical samples rather than groups in the community. Blaszczynski et al. (1997) suggested that therelationship should be examined also among gamblers who do not seek treatment from helpingagencies.

Conversely, chronic depression may be an emotional reaction to financial and other problemsresulting from excessive gambling and losses. Losing is a depressing experience, but for most peo-ple is only temporary following unexpected losses. For example, Hills, Hill, Mamone, and Dic-kerson (2001) showed in an experiment that compared with occasional gamblers, regulargamblers were significantly unhappier when losing. However, most of the research supports thehypothesis that given the appropriate conducive environment, a depressed person can be inducedinto gambling as one way of relieving chronic depression (Abbott & Volberg, 1996; Griffiths,1995; Gupta & Derevensky, 1998; Raviv, 1993). For example, Gupta and Derevensky (1998) haveshown through path analysis that for adolescents, depression is a predictor rather than a conse-quent of problem gambling. Hence, people who are predisposed to depression may find gamblingactivities which temporarily lift the depression or induce a feeling of well-being. But when thedepression sets in again, they seek out the activities which previously relieved the depressionand its accompanying anxiety. For some biologically and emotionally vulnerable individuals,the gambling becomes addictive via conditioning processes.

In their research with the impulsivity-psychopathy construct, Blaszczynski and his associates(Blaszczynski et al., 1997; Steel & Blaszczynski, 2002) have not specifically tested for the mediat-ing effect of the relationship between depression and problem gambling using the criteria of Baronand Kenny (1986). Hence, it was the purpose of the present study to ascertain if the associationbetween depression and problem gambling could be mediated indirectly via an impulsive person-ality trait, and if depression interacts with impulsivity to predict problem gambling. Following thethird path outlined by Blaszczynski and Nower (2002), what is proposed is that depression islinked to problem gambling via impulsivity, and that this effect can be detected in a sample ofgamblers who are selected from a community group, as suggested by Blaszczynski et al. (1997).

2. Method

2.1. Participants

The sample consisted of 180 students who were enrolled in an introductory psychology courseat the Albany campus of Massey University. Six of the students had never gambled, and 15 of the


gamblers did not provide sufficient data for the current analysis. Thus, there were 159 students whohad gambled for money at least once on any activity in the past 12 months, and their data were usedin the analysis. There were 127 women and 32 men. The age distribution was moderately skewed(0.98), with no outliers. Ages ranged from 18 to 49 years, with an average age of 27.86 (SD = 10.24)years. Seventy-four percent of the sample identified themselves as Caucasian or New ZealandEuropean, 14% as M�aori or Pacific Islander, and 7.5% as Asian. Most of the participants (84%)were in the average and above average socioeconomic groups. The sample thus consisted predom-inately of young, female, Caucasian adults with moderate to high socioeconomic status.

2.2. Measures

2.2.1. Revised South Oaks Gambling Screen (SOGS-R)Problem gambling is typically defined by three or more symptoms on the widely-used South

Oaks Gambling Screen (SOGS; Abbott & Volberg, 1996, 1999; Lesieur & Blume, 1987), whichis based on DSM-III-R criteria. The SOGS-R is similar to the original 20-item, self-report SOGS,except that it surveys over a limited time frame (Abbott & Volberg, 1999; Ladouceur, Arsenault,Dube, Freeston, & Jacques, 1997). It asks questions on a ‘‘yes–no’’ basis about problems associ-ated with gambling in the last 12 months, and in one�s lifetime. It is also more reliable and pro-duces fewer false negatives than the SOGS (Abbott, 2001). Nine of the 20 items in the originalSOGS are sources of borrowing money. For the SOGS-R used in the present study, the nine itemswere collapsed into one: ‘‘Have you borrowed money or stolen in order to bet or to cover gam-bling debts in the past 12 months?’’ Thus, only 12 items measured distinct symptoms of problemgambling, with a maximum score of 12. Abbott and Volberg (1996) have provided some supportfor the reliability and validity of the SOGS-R with New Zealand samples. For the present sample,the coefficient of internal consistency was 0.94.

2.2.2. Depression symptom inventoryThe inventory is an existing instrument developed with medical inpatients and outpatients, and

respondents in cross-sectional surveys in New York State (Bell, LeRoy, & Stephenson, 1982) toascertain levels of emotional depression in the community. It was used rather than the Beckdepression inventory (BDI; Beck, Ward, Mendelson, Mock, & Erbaugh, 1961), because theBDI was designed to assess the severity of depression in clinically diagnosed groups (Davison& Neale, 2001), whereas the depression symptom inventory is more applicable for non-clinicalpopulations. Each of the 18 items is rated on a five-point scale, from ‘‘often’’ to ‘‘never’’, withscores ranging from 0 to 72. For the present study, item one was re-worded from ‘‘Do you feelin good spirits?’’ to ‘‘Do you have a feeling of well-being?’’, to avoid M�aori connotations relatingto the spirits of their ancestors; and item 18 from ‘‘How does the future look to you?’’ to ‘‘Doesyour future seem uncertain to you?’’ to make sense in terms of the rating scale. The modifieddepression scale had an internal consistency coefficient of 0.82 for the present sample.

2.2.3. Eysenck impulsiveness scaleImpulsivity was defined by the impulsiveness scale (Eysenck & Eysenck, 1991). It consists of 19

items (e.g., ‘‘Would you take drugs which may have strange or dangerous effects?’’), correlatessignificantly with Psychoticism for both sexes, and provides some measure of the impulsivist-


pathological construct (Steel & Blaszczynski, 1996). For men, it correlates with Extraversion, andfor women, with Neuroticism. The coefficient of internal consistency for the present sample was0.73.

2.3. Procedure

To demonstrate statistically the mediating effect of impulsivity on the path from depression toproblem gambling, four conditions must be met (Baron & Kenny, 1986). First, depression must beassociated with impulsivity and secondly with problem gambling. Thirdly, impulsivity must be re-lated to problem gambling. Fourthly, when impulsivity is controlled, there must be a statisticallysignificant reduction in the effect of depression on problem gambling. If the relation is reduced tonon-significant levels, full mediation is demonstrated. Partial mediation occurs when the correla-tion between depression and problem gambling is reduced but still significant. If a mediating effectis present, then path analysis would be conducted to estimate the direct and indirect effects ofdepression on problem gambling, with impulsivity as the mediating variable (Pedhazur, 1997).

The interaction effect was tested by hierarchical regression analysis, as suggested by Baron andKenny (1986). The order of entry was depression and impulsivity, and then their interaction(depression · impulsivity). Before testing for the interaction, the scores for depression and impul-sivity were ‘‘centered’’ by subtracting their respective sample means from all individuals� scores,thus producing revised sample means of zero. The procedure, suggested by Aiken and West(1991), was to eliminate the possible effects of multicollinearity between first order terms of themain independent variables and the higher order interaction term.

3. Results

Prior to inferential analysis, the data for each scale were examined for outliers and for assump-tions of normality. Age and SOGS-R scores were skewed, so that square root transformations ofthe scores were computed to reduce the number of outliers and to approximate normal distribu-tions for the frequency data (Tabachnick & Fidell, 1996). For the impulsiveness scale and thedepression inventory, the distributions of data were within normal ranges and raw data were usedin the computations.

3.1. Characteristics of the sample

According to the criterion of scores of three or greater on the SOGS-R, 26 of the 159 gamblers(16%) were classified as problem gamblers. There were proportionately equivalent numbers ofmale (6 of 32) and female (20 of 127) problem gamblers, v2 (1, N = 159) = 0.28, p > 0.05. Com-pared with the average depression score (mean = 23.40, SD = 12.12, N = 342) on the same scalefor a New Zealand normative sample (Clarke & Jensen, 1997), the students� average score(mean = 27.70, SD = 9.62) was significantly higher, t(499) = 3.84, p < 0.001. A one-way MANO-VA revealed no significant differences between men�s and women�s mean scores on depression,impulsiveness, and problem gambling symptoms, Wilks� lambda = 0.97, F(3, 155) = 1.87,p > 0.05. Similarly, there were no significant differences in means for ethnicity, Wilks�


lambda = 0.91, F(9, 355.48) = 1.51, and socioeconomic status, Wilks� lambda = 0.97, F(6,308) = 0.87, ps > 0.05.

The students� mean scores on the Eysenck impulsiveness scale were significantly greater thanthe means for the Manual�s normative sample in the 20–29 year age group. The women�s meanscore (mean = 10.11, SD = 3.83) was higher than the normative mean for young women(mean = 9.02, SD = 4.19, N = 191), t(316) = 2.35, p < 0.05. Similarly, the men�s mean score(mean = 11.03, SD = 4.02) was higher than the normative mean for young men (mean = 7.93,SD = 4.12, N = 97), t(127) = 3.71, p < 0.001.

3.2. Effects of impulsivity

Table 1 depicts the intercorrelations among the variables, their means and standard deviations.All of the variables are significantly related to one another. The zero-order correlations are pre-sented below the diagonal; partial correlations in which the effects of sex and age have been con-trolled are above the diagonal. As can be seen in Table 1, there was almost no change insignificance or value after controlling for sex and age. Hence, the data for sex and age groups werecombined for succeeding analysis, thus increasing statistical power and reducing the possibility ofmulticollinearity in the regression analysis (Tabachnick & Fidell, 1996).

The first step in testing for the mediating effect of impulsivity was to demonstrate that depres-sion is significantly related to impulsivity. The zero-order correlation of 0.48 noted in Table 1 pro-vides initial support for this effect. The results of the regression analysis predicting problemgambling symptoms as a function of depression and mediated by impulsivity appear in Table2. All four of the conditions specified by Baron and Kenny (1986) were met: (1) variations in levelsof depression significantly accounted for variations in impulsivity (B = 0.20), F(1, 158) = 47.81,p < 0.001, (2) the relationship between depression and problem gambling was initially significant(B = 0.02), F(1, 158) = 10.49, p = 0.001, (3) variations in impulsivity significantly accounted forvariations in problem gambling symptoms (B = 0.04), t = 2.14, p < 0.05, and (4) with impulsivityin the equation, the unstandardized regression coefficient for depression on problem gambling wasreduced significantly from 0.02 to 0.01, F(1, 157) = 4.57, p < 0.05. Further, because the latter coef-ficient (0.01) was not significant (p > 0.05), impulsivity had a full mediating effect on the predic-tion of problem gambling symptoms from depression.

Table 1Means, standard deviations, and zero-order correlations (N = 159)

Variable Depression Impulsivity Problem gambling

Depression – 0.48*** 0.26***

Impulsivity 0.48*** – 0.26***

Problem gambling 0.25** 0.26*** –Mean 27.70 10.29 1.09SD 9.62 3.88 2.12

Note: Pearson product-moment correlations appear below the diagonal; partial correlations controlling for sex and age,above the diagonal. All tests are one-tailed.** p < 0.01.*** p < 0.001.

Table 2Hierarchical regression analysis for direct, indirect and interaction effects of depression on problem gambling symptomsvia impulsivity (N = 159)

Variable B SE B b Partial R2

(1) Regression of impulsivity on depression (R2 = 0.23)Constant 1.40 1.31Depression 0.20*** 0.03 0.48 0.23

(2) Regression of problem gambling symptoms on depression (R2 = 0.06)Constant �0.46 0.33Depression 0.02*** 0.01 0.25 0.06

(3) Regression of problem gambling symptoms on impulsivity and depression (R2 = 0.09)Constant �0.50 0.32Depression 0.01 0.01 0.16 0.02Impulsivity 0.04* 0.02 0.19 0.03Indirect 0.09Spurious 0.08Depression · impulsivity 0.00 0.00 0.02 0.00

* p < 0.05.*** p < 0.001.


Table 2 also shows the results of the interaction effect of depression and impulsivity on problemgambling symptoms, after the introduction of the main effects. There was no significant increase(DR2 = 0.00) in variance explained by the interaction effect, F(1, 155) = 0.16, p > 0.05.

The results of the third regression in Table 2 show the proportion of the total effect of depres-sion (0.25) on problem gambling symptoms, consisting of the direct effect (0.16) and the indirecteffect through impulsivity (0.09). Therefore, as a mediator, impulsivity accounted for 36% of thetotal effect of depression on problem gambling symptoms. For multiple and multiple partial cor-relations, Cohen (1992) has tabled a standardized measure of association (f) which is independentof the original measurement units. An f2 of 0.02 is considered a small effect size, and 0.15 a me-dium effect size. For the third regression, an R2 of 0.09 yields an f2 of 0.10. Hence, the total effectof depression on problem gambling via impulsivity was close to medium. The statistical power to

0.48*** 0.19*

0.16Depression Problem Gambling

Impulsivity

0.77

0.91

Fig. 1. Path model and standardized regression coefficients depicting the role of impulsivity in mediating the effects ofdepression on problem gambling symptoms. Note. Residuals appear in circles. *p < 0.05; ***p < 0.001.


detect significance at the 0.05 level was at least 80% for small to medium effect sizes. However,because all the coefficients are positive and because of measurement error in the mediator dueto less than perfect reliability of the Eysenck impulsiveness scale with the present sample(a = 0.73), there is probably an underestimate of the effect of impulsivity on problem gamblingand an overestimate of the effect of depression on problem gambling (Baron & Kenny, 1986).

Fig. 1 presents the path analysis for the mediating model (Pedhazur, 1997). The standardizedpath coefficients (b�s) show the direction and magnitude of the effects of depression and impulsiv-ity on problem gambling symptoms. The coefficients depicting the paths from depression toimpulsivity (0.48, p < 0.001) and from impulsivity to problem gambling symptoms (0.19,p < 0.05) were significant, but the coefficient from depression to problem gambling symptomswas not (0.16, p > 0.05).

4. Discussion and conclusion

Compared with six-month problem gambling rates among general populations in New Zealand(1.3%), and in Australia, the United States of America, Canada and Sweden, ranging from 1.2%to 6.6% of the populations (Abbott & Volberg, 1999), the rate of 16% in the university sample wasextremely high, even when taking into consideration that the SOGS-R measured problems over atwelve-month period. The present sample was also more depressed and impulsive than earlier nor-mative samples.

Earlier studies (Abbott & Volberg, 1996; Steel & Blaszczynski, 1996) have reported that theprevalence of problem gambling is greater for males than for females. However, recent researchin New Zealand with university students (Clarke, 2003) and with a representative sample of thenational population (Abbott, Volberg, & Ronnberg, 2004) discovered that the rates of currentproblem gambling were not significantly different between the sexes. Possible reasons for the sig-nificant increase for women include the proliferation of electronic gaming machines in clubs anddrinking establishments.

The results can be related to Blaszczynski and Nower (2002) pathways model of problem gam-bling. Following the third path in the model, the personality construct of impulsivity mediated theeffects of depression on problem gambling symptoms. Previous research with the construct (e.g.,Blaszczynski et al., 1997) found its presence among pathological gamblers in treatment. The pres-ent study, consistent with recommendations by Blaszczynski et al. (1997) for research with impul-sivity among gamblers in non-clinical groups, showed that the construct is also operational in atleast one non-representative community group, the present sample.

Depressed people who are impulsive could relieve their depression in other ways such as sub-stance abuse or antisocial behaviour. Introduction to excessive behaviours can come through fam-ily members, friends, advertising or opportunities to indulge (Abbott & Volberg, 2000). However,for problem gambling, depression and impulsivity did not interact together to account for pro-blem gambling beyond the main effects. As depression increased, the number of problem gamblingsymptoms increased but through impulsivity.

Based on the model and on previous research (Abbott & Volberg, 1996; Gupta & Derevensky,1998; Griffiths, 1995; Raviv, 1993), it was assumed in the present study that emotional depressioncan lead to problem gambling symptoms, rather than vice-versa. Depression was conceptualized,


not as a causal or biological factor, but as a psychosocial antecedent of problem gambling in thepathways model. If depression, impulsivity and problem gambling are merely covariates, thenfrom the present findings, the covariance between depression and problem gambling disappearswhen impulsivity is controlled (James & Brett, 1984). For therapy, the implication then is thatdealing with impulsivity may be sufficient to weaken the depression-problem gambling link forthe third group of impulsive gamblers with biological and emotional predispositions towardaddictive behaviours.

Some of the problem gamblers in the present sample might have been in treatment, but thatpossibility was not ascertained. To generalize the results further, Steel and Blaszczynski (2002)suggested that epidemiological research with the constructs be carried out in the general popula-tion. It would also be necessary to control for levels of treatment and intervention. Longitudinalresearch with appropriately controlled intervention programmes could help clarify the nature ofthe relationships among the three variables, depression, impulsivity and problem gambling.

Steel and Blaszczynski (2002) have proposed specific treatments for biologically and emotion-ally vulnerable gamblers in the second group, and for the impulsive gamblers with similar vulner-abilities in the third group. The second group, who gamble to escape depression and anxiety, needto learn coping skills and ways of dealing with sources of stress. The impulsive group may respondto intensive, long-term cognitive-behavioural therapies for impulse control. Because of biologicaldeficits, both groups possibly require medication to control their neurological chemistry. The find-ings in the present investigation suggest that because depression affects impulsivity, it may beappropriate to treat the depression experienced by problem gamblers or other addicts in additionto treating their impulsivity. Recently, cognitive-behavioural methods that aim to change problemgamblers� erroneous beliefs such as superstitions and illusions of control of their gambling behav-iour have been used (Ladouceur, Sylvain, Boutin, & Doucet, 2002). It is suggested by the presentauthor that other cognitive therapy methods that treat emotional depression may also be fruitful.For example, Beck�s therapies have helped depressed people break their maladaptive, cyclicalthought patterns of negative beliefs and hopelessness (Beck, 1995). The combined effects of thecognitive-behavioural therapies may be synergic, because lowering depressive symptoms may alsolower the impulsion to escape those symptoms.

Acknowledgement

This research was supported by a grant from the Massey University Research Fund and infor-mation from the Problem Gambling Foundation of New Zealand.

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