(CBT and REBT Maybe) Functional and Dysfunctional Impulsivity in PG

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Personality and Individual Differences 43 (2007) 1829–1838

Functional and dysfunctional impulsivityin pathological gambling

Fiona Maccallum a, Alex Blaszczynski b,*, Robert Ladouceur c, Lia Nower d

a University of New South Wales, Sydney, Australiab University of Sydney, Sydney, Australia

c Laval University, Quebec, Canadad Rutgers University, New Brunswick, NJ, USA

Received 27 June 2006; received in revised form 12 June 2007; accepted 14 June 2007Available online 6 August 2007

Abstract

Impaired control leading to excessive gambling and subsequent adverse consequences is the primary fea-ture of pathological gambling. Defined as an impulse control disorder, elevated traits of impulsivity areassociated with increased levels of intensity of gambling and symptoms severity and are predictive of treat-ment dropout. However, to date, research has failed to explore the differential effects of functional and dys-functional impulsivity in gambling and the relationship between these two forms of impulsivity to treatmentcompliance and treatment outcome. This study investigates the interrelationship between functional anddysfunctional impulsivity as measured by the Dickman (1990) scale, gambling severity, substance useand depression in a clinical sample of 60 pathological gamblers seeking cognitive–behavioural therapy.Results indicate that dysfunctional impulsivity is associated with poorer response to treatment but not withtreatment completion.� 2007 Elsevier Ltd. All rights reserved.

Keywords: Impulsivity; Functional impulsivity; Dysfunctional impulsivity; Pathological gambling; Cognitive–behav-ioural treatment

0191-8869/$ - see front matter � 2007 Elsevier Ltd. All rights reserved.doi:10.1016/j.paid.2007.06.002

* Corresponding author. Tel.: +61 2 9351 7612.E-mail address: [email protected] (A. Blaszczynski).

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1830 F. Maccallum et al. / Personality and Individual Differences 43 (2007) 1829–1838

1. Introduction

Impulsivity is a predominant characteristic of widely utilized conceptual models of gambling:impulse control (American Psychiatric Association, 2000), addiction (Blume, 1987; Jacobs,1986) and obsessive–compulsive spectrum disorders (Hollander, Skodol, & Oldham, 1996). Evi-dence of elevated impulsivity scale scores have been found in samples of pathological gamblersin treatment (Blaszczynski, Steel, & McConaghy, 1997; Castellani & Rugle, 1995; Steel & Blas-zczynski, 1996) although some contradictory results have been reported in a small number ofstudies (Allcock & Grace, 1988; Langewisch & Frisch, 1998). In addition, high scores appearto be associated with correlates of behavioural impairment and psychosocial dysfunction (Steel& Blaszczynski, 1996), development of pathological gambling among adolescents (Vitaro, Arse-neault, & Tremblay, 1999), and both non-response (Gonzalez-Ibanez, Mora, Gutierrez-Maldo-nado, Ariza, & Lourido-Ferreira, 2005) and attrition (Leblond, Ladouceur, & Blaszczynski,2003) in gambling treatment settings.

Impulsivity is a multifaceted behavioural construct, characterised by deficits in self-controlexpressed as a repeated failure of self-discipline, self-regulation, or sensitivity to immediate reward(Moeller, Barratt, Dougherty, Schmitz, & Swan, 2001; Strayhorn, 2002). It is characteristicallyused to describe actions that are considered to be spontaneous, carried out without forethoughtand with disregard to their consequences, risky in nature, and often resulting in harmful outcomes(Barratt, 1983, 1985; Dickman, 1990; Eysenck & Eysenck, 1977, 1978; Green, Fristoe, & Myerson,1994; Jaspers, 1963). Variable emphasis is placed on overt behaviours, cognitive processes, speedof responding, and environmental factors as determinants of ‘‘impulsiveness’’ (Claes, Vertommen,& Braspenning, 2000), with the construct inadequately differentiated from related concepts of risk,sensation seeking and behavioural disinhibition (National Research Council, 1999). Nevertheless,Moeller et al. (2001) has proposed three basic elements that generally define impulsivity: (a)decreased sensitivity to negative consequences of behaviour; (b) rapid, unplanned reactions tostimuli before complete processing of information; and (c) lack of regard for long-termconsequences.

Despite awareness of these elements, most studies in gambling have characterized impulsivity asuni-dimensional, correlated with but not fully defined by negative outcomes and psychopathol-ogy. In contrast, Dickman (1990, 2000) reconceptualized impulsivity as multi-dimensional in nat-ure and comprised of two factors – functional and dysfunctional impulsivity – that interact tofoster positive or negative consequences, depending on unsuccessful outcomes in the context ofquick and non-judicious decision-making. He suggested that a proportion of individuals receiverewards for rapid decision-making abilities despite lack of accuracy, while others experience pre-dominantly negative consequences. Functional impulsivity refers to the tendency to engage in ra-pid, error-prone information processing when such a strategy is optimally beneficial. In contrast,dysfunctional impulsivity represents the tendency to engage in rapid, error-prone informationprocessing in situations where slower methodical approaches are required.

Therefore, speed of decision-making is the hallmark of high impulsives, while consequencesmeasured by the accuracy of those decisions differentiate adaptive behaviours from those nega-tively labeled ‘‘impulsive’’. Functional impulsives are described as enthusiastic, highly active,and productive risk-takers whose output compensates for lack of accuracy and precision (Dick-man, 1990). Dysfunctional impulsives, on the other hand, are careless and inattentive, greatly

F. Maccallum et al. / Personality and Individual Differences 43 (2007) 1829–1838 1831

exacerbating negative consequences resulting from deficits in planning and abilities to delay grat-ification (Dickman, 1990).

To date, no studies in gambling have differentiated dysfunctional from functional impulsivity ingamblers although the construct is of fundamental importance in understanding the relationshipbetween subtypes of impulsivity and gambling disorder. From the findings of several studies(Claes et al., 2000; Steel & Blaszczynski, 1996) and the implications arising from the PathwaysModel of problem gambling (see Blaszczynski & Nower, 2002), it can be hypothesized that prob-lem gamblers should score higher on measures of dysfunctional impulsivity than non-problemgamblers. In particular, a sub-group of gamblers with behavioral correlates such as alcohol depen-dence, non-compliance with therapeutic instructions and poor response to treatment are particu-larly likely to exhibit heightened levels of impulsivity.

The aim of the current study, therefore, is to investigate the relationship of impulsivity to treat-ment completion and decreases in post-treatment problem gambling behavior. In contrast to func-tional impulsives, it is hypothesized that individuals obtaining higher scores on a measure ofdysfunctional impulsivity would be more likely to: (a) drop out of treatment, and (b) report con-tinued gambling behavior post-treatment.

2. Method

2.1. Participants

Participants were a series of 60 consecutive applicants (44 males, 16 females) attending a cog-nitive–behavioural oriented specialised university teaching hospital pathological gambling clinicfor treatment. The gender ratio is comparable to that found among problem gamblers (AustralianGaming Council, 2007). All participants met threshold scores for probable pathological gambling(5+ symptoms) on the South Oaks Gambling Screen (SOGS) (Lesieur & Blume, 1987) problemseverity measure, with a group mean score of 12.3 (SD = 2.1; range 10–18). The mean age ofthe total sample was 38.1 years (SD = 11.0; range = 20–66 years). Males (M = 34.66,SD = 9.72) were significantly younger than female participants (M = 47.75, SD = 8.47) at thetime of the study, F(1,58) = 22.69, p < 0.01.

Approximately 43% (n = 26) of participants were employed full time, with 18% (n = 11)endorsing casual employment, and 13% (n = 8) reporting either receipt of fixed benefits or self-employment. Nearly 7% (n = 4) of the sample was unemployed and 5% (n = 3) had permanentpart time employment.

2.2. Measures

Participants referred to the Clinic were initially assessed clinically to exclude patients in whichgambling was secondary to mania, and administered a semi-structured interview, designed to elicitsocio-demographic data and gambling history. The following battery of psychometric measureswas completed immediately prior to the commencement of the first session of treatment:

The south oaks gambling scale (SOGS: Lesieur & Blume, 1987). The SOGS, a 20 item self-reportmeasure of problem gambling, is the most widely used screening instrument to detect problem


gamblers in clinical settings with a Cronbach’s alpha of 0.97. The six-month timeframe versionwas used. Modifications were made to the wording of certain items to conform to Australian gam-bling terminology; for example, substitution of the term ‘poker machine’ for ‘slot machine’.

Self-description inventory (SDI: Dickman, 1990). The self-report SDI measure was used to as-sess personality traits of impulsivity. The measure provides scale scores for functional and dys-functional impulsivity. The functional impulsivity scale has 11 items, and the dysfunctionalscale, 12 items. The Cronbach’s alpha for the functional and dysfunctional scales was 0.74 and0.85, respectively, in a sample of college students (Dickman, 1990).

Beck depression inventory (BDI: Beck & Steer, 1987). The BDI is a 20 item widely used, reliableand valid self-report measure used to assess for the severity of depressive symptomatology overthe previous week at four levels – absent (0–9), mild (10–18), moderate (19–29) and severe (30–63). Alpha coefficients for the BDI range from 0.86 to 0.81 (Beck, Steer, & Garbin, 1988). Thismeasure was included to determine the extent to which affective disturbances rather than impul-sivity accounted for results obtained. It is well established that depression is a significant correlateof pathological gambling (Blaszczynski & McConaghy, 1988; Linden, Pope, & Jonas, 1986) andmay have the potential to effect treatment outcome by reducing motivation or capacity to engagein treatment.

Alcohol use disorders identification test (AUDIT: Saunders, Aasland, Babor, De la Fuente, &Grant, 1993). Impulsivity is associated with excessive alcohol use and alcohol use is known to im-pair rational judgement and control and increase risk-taking among gamblers (Baron & Dickerson,1999; Daghestani, Elenz, & Crayton, 1996; Kyngdon & Dickerson, 1999) and negatively impact onresponse to treatment. Given that rates of comorbid alcohol use in the vicinity of 40% are consis-tently reported in samples of pathological gamblers (Maccallum & Blaszczynski, 2002), it wasdecided to assess for level of alcohol use in this present sample. The AUDIT is a widely used 10item self-report questionnaire that provides an estimate of alcohol consumption at three levels –non-hazardous (0–7), harmful (8–15) and potential alcohol dependence (16+). Coefficient alphascores in a variety of studies range from 0.75 to 0.94 (Allen, Litten, Fertig, & Barbor, 1997).

2.3. Procedure

The study was approved by the South Western Sydney Area Health Service Ethics Committeeprior to data collection. All assessment measures were administered prior to the commencementof treatment while at one month post-treatment, we conducted a follow-up interview to assesstreatment outcome. Treatment consisted of six sessions of cognitive-behavioral therapy, each1.5 h in length over a six-week period.

Outcome was determined by clinical interview taking into consideration participants’ reportedchanges in the frequency/duration of sessions, expenditure and the level of urges, gambling behav-iour and preoccupation reported on the visual analog scale. Indices of outcome included gamblingbehaviour, urge, preoccupation and self control over gambling at one month post-treatment.

Response was assessed by the clinician using a 5-point Likert scale with anchor points rangingfrom significant relapse (substantial increase in post-treatment gambling activity compared tobase-line) to significant improvement (nil or minimal gambling behaviour or reported urge togamble relative to pre-treatment). Preoccupation and urge were assessed by responses on a visualanalog scale with wordings: ‘‘Please circle the number (from 1 to 10) which indicates the degree to


which you have been preoccupied with gambling’’ and ‘‘Please circle the number (from 1 to 10)which indicates the degree of urge to gamble you have experienced’’.

An independent interviewer attempted to contact all fifteen subjects who failed to completetreatment to obtain the reasons underlying their decision to terminate. Three participants werelost to follow-up leaving 80% (n = 12) interviewed. Reasons provided varied from the desire tocease without further treatment (n = 2), work and family commitments (n = 3), health reasons(n = 1) and dislike of treatment format (n = 6). Since the treatment consisted of only six sessions,participants were classified as non-completers if they missed two or more sessions.

3. Results

3.1. Demographics

Males reported they first began gambling around age 17, in contrast to females who reportedfirst gambling at approximately age 21, F(1,58) = 4.61, p < 0.05. Males reported commencingcommercial betting at age 19, in contrast to females who were aged around 26 when first bettingat a gambling venue, F(1,58) = 9.25, p < 0.01. Table 1 provides descriptive statistics for age andduration of gambling and problem gambling for the overall sample.

A majority of participants (85%, n = 51) endorsed electronic gaming machines as their primaryform of problem gambling; 10% (n = 6) endorsed horse-racing and the remaining 1.7% (n = 1),keno, casino table games and/or sports betting. These rates are consistent with those found insamples of treatment seeking problem gamblers in Australia: 87% for electronic gaming machines;10% for horse racing, and 3% on casino card games (Australian Gaming Council, 2007; p. 171).Nearly 92% (n = 55) of the sample indicated their primary form as their exclusive form of gam-bling. Overall gambling debt at time of assessment varied from zero to $400,000 (M = $18,136,SD = $57,690). Half of the participants (51.7%, n = 31) reported a debt of less than $2,000, while27% (n = 16) indicated a debt of more than $10,000.

3.2. Impulsivity, depression, and alcohol use

The study investigated the relationship of functional and dysfunctional impulsivity by gender todepression and alcohol use. Descriptive statistics for the functional (FI) and dysfunctional (DI)scales of the SDI, the BDI, and the AUDIT for males and females are listed in Table 2.

Table 1Age and duration of gambling and problem gambling for n = 60 pathological gamblers

Mean SD Min. Max.

Age of gambling onset 17.8 7.7 6.0 54.0Age of onset, commercial gambling 21.0 7.8 12.0 54.0Age of onset, problem type of gambling 24.13 9.9 13.0 60.0Years acknowledged gambling problem 4.5 4.7 0.05 24.0Days since last gambled 10.2 11.5 1.0 56.0

Table 2Mean scores on SDI, BDI and AUDIT by gender

N FI mean (SD) DI mean (SD) BDI mean (SD) AUDITa mean (SD)

Male 44 6.4 (2.5) 5.4 (3.1) 13.4 (8.4) 6.2 (4.5)Female 16 4.8 (3.7) 5.2 (3.4) 18.1 (9.6) 4.1 (4.3)

Total 60 5.9 (2.9) 5.4 (3.2) 14.7 (8.9) 5.6 (4.5)

a = 54 (males 38, females 16).


Participants reported significantly higher FI (t = 3.46, p < 0.01) and DI (t = 9.93, p < 0.001)scale scores compared to normative data derived from a general population sample in a studyby Claes et al., 2000. However, there were no significant differences between males and femaleson either functional, F(1,58) = 3.49, p = 0.067, or dysfunctional, F(1,58) = 0.04, p = 0.829,impulsivity in the current study.

Separate analyses of variance conducted on the BDI and AUDIT scores revealed no significantdifferences in mean scores for males and females on either measure. Mean scores on the BDI(M = 14.67; SD = 8.93) placed participants within the mild-moderate range of depressive symp-tomatology while mean AUDIT scores (M = 5.57; SD = 4.55) placed participants in the non-haz-ardous drinking category, with only six participants reporting a problem with alcohol.

3.3. Impulsivity and treatment completion

The relationship between pre-treatment impulsivity and completion of treatment at one-monthfollow-up assessment was investigated. For purposes of this study, participants missing more thanone treatment session were classified as non-completers: fifteen (25%) of 60 participants were clas-sified as such using this criterion, a rate consistent with that reported in gambling studies in gen-eral (Leblond et al., 2003). The mean FI and DI scores for treatment completers and non-completers are provided in Table 3.

There were no significant differences detected on the SOGS, BDI, Audit or the FI and DIimpulsivity scale scores between treatment completers and non-completers although there was atendency in the expected direction for non-completers (F(1,58) = 6.64, p < 0.061) to have higherDI scale scores.

3.4. Impulsivity and treatment outcome

Estimates of clinical outcome at one-month were obtained for 93% (n = 42) of the 45 treatmentcompleters. The first author rated each participant’s response to treatment based on informationregarding changes in expenditure, frequency and duration of sessions, and responses to a visualanalogue scale rating current urges and preoccupation elicited during follow-up interviews. Thefirst author was not blind to the treatment received. Using clinical judgements, participants wereclassified into one of the following categories: (1) deterioration in their condition, i.e., gamblingsessions/expenditure/urges showed evidence of an increase; (2) no change in patterns of gambling;(3) evidence of moderate improvement, i.e., reduction in expenditure, frequency, and/or durationbut continued levels of excessive gambling and persistent urges; (4) significant improvement, absti-

Table 3Mean SOGS, FI, DI, BDI, AUDIT scores for treatment completers and non-completers

Completers N = 45 mean (SD) Non-completers N = 15 mean (SD)

SOGS 12.1 (2.1) 13.1 (2.1)FI 6.0 (3.0) 5.7 (2.5)DI 5.0 (3.2) 6.7 (3.0)BDI 14.6 (9.0) 14.7 (9.3)AUDIT 5.2 (4.4) 7.2 (4.9)


nence, minimal gambling (less than AUD$10.00 once per week or less), reported urge or impairedcontrol.

Table 4 presents the descriptive statistics for the psychometric scale scores for participants clas-sified for each of the clinical outcome rating groups. No participant reported his or her conditiondeteriorated at post-treatment follow-up assessment. By combining the participants reportingmoderate and great improvement, a positive response rate of 78% was found for the total sample.

A series of ANOVAs were conducted to identify statistically significant differences among out-comes (no change, moderate improvement, great improvement, non-completers) and scale scoresfor SOGS, BDI, AUDIT, FI, and DI. Overall, only BDI (F(3,52) = 3.1, p = 0.035) and DI (F (3,52) = 3.8, p = 0.016) scores differed significantly. Post-hoc Bonferroni pairwise comparisonsfound that depression levels were higher among those who improved only moderately as com-pared to those who greatly improved post treatment. In contrast, DI appeared to have a negativeinfluence on treatment outcome. Bonferroni comparisons indicated that those who dropped out oftreatment had significantly higher DI scores than those who showed great improvement, thoughdifferences between other groups were non-significant.

3.5. Depression, substance use and treatment outcome

Lower pre-treatment BDI scores were associated with a better response to treatment,F(3,52) = 3.09, p = 0.035. Participants rated as showing great improvement obtained significantlylower BDI scores compared to those rated as having no-change (t = 2.5, df = 27, p = 0.021) ormoderate improvement (t = 2.8, df = 31, p = 0.009). The remaining comparisons were non-signif-icant. The mean BDI score for greatly improved participants (M = 10.0; SD = 7.8) fell just abovethe scale’s normal or asymptomatic score range of 0–9. The mean score for the moderately im-proved group (M = 18.2; SD = 8.8) was at the high end of the mild-moderate range (10–18) while

Table 4Pre-treatment mean SOGS, SDI, BDI and AUDIT scale scores and clinically rated outcome (N = 42)

SOGS mean(SD)

Functional mean(SD)

Dysfunctional mean(SD)

BDI mean(SD)

AUDIT mean(SD)

Greatly improved (n = 20) 11.9 (2.2) 5.6 (2.9) 3.8 (2.9) 10.0 (7.8) 4.3 (3.2)Moderately improved (n = 13) 12.2 (1.8) 5.8 (3.0) 5.9 (2.5) 18.2 (8.8) 7.7 (6.1)No change (n = 9) 11.9 (1.7) 8.2 (2.7) 6.6 (2.7) 17.8 (8.2) 3.7 (3.6)Non-completers (n = 14) 12.9 (2.2) 5.9 (2.5) 6.7 (3.1) 14.6 (9.6) 7.2 (4.9)


the no-change group (M = 19.1; SD = 7.6) fell within the moderate to severe range for depression(19–29). Depression scores did not correlate with either FI or DI scale scores.

The study found no relationship between outcome and AUDIT scores, likely due to the smallnumber of self-reported problem drinkers in the sample (n = 6).

3.6. Discussion

Consistent with the literature, the results of this study found that, compared to communitysamples, pathological gamblers seeking treatment are characterised by elevated impulsivity scalescores, suggesting a deficit in inhibitory control and capacity to delay gratification (Castellani &Rugle, 1995; Steel & Blaszczynski, 1998; Vitaro et al., 1999). Gambling is a complex behaviourinvolving a series of critical decision points that ultimately determine the initiation, length, dura-tion and intensity of individual sessions. Irrational and erroneous cognitive schemas overestimat-ing the probability of winning, coupled with traits of impulsivity, combine to increase thelikelihood of that gamblers will make spontaneous decisions to initiate gambling sessions, con-tinue gambling longer than intended, withdraw additional funds, participate in last minutechanges in bet selection, and obtain money through illegal means. Factors, such as substanceuse (Kyngdon & Dickerson, 1999) and depression (McCormick, Russo, Ramirez, & Taber,1984) further weaken inhibitory control and increase the propensity for impulsive decisions thatresult in prolonged sessions.

As indicated by earlier studies (Blaszczynski et al., 1997; Steel & Blaszczynski, 1996), impulsiv-ity is an important variable associated with severity of problem gambling and treatment outcome.In this study, gamblers with lower levels of dysfunctional impulsivity reported a better response totreatment and a non-significant trend to complete treatment as compared to those with higherscores on the trait. These findings could be interpreted to suggest that dysfunctional impulsivity,a trait similar to the ‘‘narrow impulsivity’’ (the inability to act with forethought and deliberation)measured by the Eysenck impulsivity scale (Eysenck & Eysenck, 1977), fosters impaired controlbut that functional impulsivity may represent a beneficial trait. In this regard, previous studieshave reported on the concept of impulsivity as a uni-dimensional construct without regard tothe possibility that the trait may be comprised of both functional and dysfunctional elements. Un-der certain conditions, functional impulsivity may represent a protective trait, reducing the netimpact of errors with a series of quick and calculated adaptive decision in the gambling situation;for example, mathematically inclined blackjack players may be impulsive and quick-acting, buttheir overall propensity for odds calculation, card counting or hole carding combined with sus-tained attention over time minimizes the impact of losses in favour of accumulated wins over time.Dysfunctional impulsivity, defined as the propensity to respond quickly, carelessly and with inat-tentiveness, may constitute a trait that contributes to the exacerbation of negative consequencesare a result of an individual’s inability to plan, reflect on the implications of actions and delaygratification in an adaptive manner (Dickman, 1990).

It is argued, therefore, that greater attention should be directed toward the differentiation ofthese subtypes of impulsivity with respect to their effect on treatment attrition and treatment out-comes. On the basis of the present results, dysfunctional impulsivity and depression scores wereassociated with poorer response to treatment with dysfunctional impulsivity but not depressionlinked to a greater likelihood of attrition. Effective clinical management, then, should not only


ensure that participants are assessed and treated for depression but that they are also assessed forimpulsivity and instructed in strategies to identify and manage impulses that could lead to earlytermination from treatment.

The relationship of depression, impulsivity and outcome is complex; high Beck DepressionInventory scores measuring the presence of point-in-time symptoms are associated with a poorresponse to treatment. These findings suggest counsellors should screen all clients for currentdepression and those exhibiting such symptoms should be offered additional interventions aimedat improving mood.

Interestingly, there was no strong relationship between level of harmful alcohol use and out-come. This finding is contrary to expectations and claims that comorbid substance use acts asa barrier to treatment and a relapse factor for problem gambling. However, given the small num-ber of participants reporting alcohol problems and short follow-up timeframe, this finding canonly be offered as a tentative conclusion until the long-term data is analysed and the studyreplicated.

Limitations of the study include a small sample size, a self-selected clinical sample, and the ab-sence of a control group. Future research is needed to explore these variables in a sample of indi-viduals with and without gambling problems to further evaluate the relationship of functional anddysfunctional impulsivity to gambling disorder. Also, additional studies should utilize a controlgroup to evaluate the effectiveness of interventions that target forms of impulsivity in improvingoverall treatment outcomes.

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Documents

(CBT and REBT Maybe) Functional and Dysfunctional Impulsivity in PG