ORIGINAL RESEARCH published: 07 December 2021 doi: 10.3389/fpsyt.2021.789940 Discrete Roles for Impulsivity and Compulsivity in Gambling Disorder Gemma Mestre-Bach 1 , Trevor Steward 2 , Iris M. Balodis 3 , Elise E. DeVito 4 , Sarah W. Yip 4,5 , Tony P. George 6,7 , Brady A. Reynolds 8 , Roser Granero 9,10 , Fernando Fernandez-Aranda 9,11,12 , Susana Jimenez-Murcia 9,11,12 and Marc N. Potenza 4,5,13,14,15* 1 Health Sciences School, Universidad Internacional de La Rioja, La Rioja, Spain, 2 Melbourne School of Psychological Sciences, University of Melbourne, Parkville, VIC, Australia, 3 Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada, 4 Department of Psychiatry, Yale University School of Medicine, New Haven, CT, United States, 5 Yale Child Study Center, Yale University School of Medicine, New Haven, CT, United States, 6 Addictions Division, Centre for Addiction and Mental Health, University of Toronto, Toronto, ON, Canada, 7 Division of Brain and Therapeutics, Department of Psychiatry, University of Toronto, Toronto, ON, Canada, 8 Department of Behavioral Science, University of Kentucky, Lexington, KY, United States, 9 Ciber Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Barcelona, Spain, 10 Departament de Psicobiologia i Metodologia de les Ciències de la Salut, Universitat Autònoma de Barcelona, Barcelona, Spain, 11 Department of Psychiatry, Bellvitge University Hospital-IDIBELL, Barcelona, Spain, 12 Department of Clinical Sciences, School of Medicine and Health Sciences, University of Barcelona, Barcelona, Edited by: Spain, 13 Department of Neuroscience, Yale University School of Medicine, New Haven, CT, United States, 14 The National Víctor Martínez-Loredo, Center on Addiction and Substance Abuse, Yale University School of Medicine, New Haven, CT, United States, University of Zaragoza, Spain 15 Connecticut Mental Health Center, New Haven, CT, United States Reviewed by: Ismael Muela, University of Granada, Spain Background and Objective: Complex associations between gambling disorder (GD) Gema Alonso-Diego, and impulsivity have been identified. However, little is known regarding how compulsivity University of Oviedo, Spain associates with different impulsivity domains in GD. In this study, we examined Patrizia Velotti, Sapienza University of Rome, Italy associations between self-reported and behavioral measures of impulsivity–assessed *Correspondence: through the Barratt Impulsiveness Scale (BIS-11) and the Experiential Discounting Task Marc N. Potenza (EDT), respectively- and compulsivity-measured using the Padua Inventory and the marc.potenza@yale.edu Wisconsin Card Sorting Test (WCST), respectively-, in an adult sample with GD (N = 132, Specialty section: 94 men and 38 women, ages ranging from 18 to 69 years). GD severity was assessed This article was submitted to using the South Oaks Gambling Screen. Computational Psychiatry, a section of the journal Methods: Structural Equation Modeling was used to examine relationships between Frontiers in Psychiatry impulsivity and compulsivity measures, age, and GD severity. Received: 05 October 2021 Accepted: 15 November 2021 Results: BIS-11 non-planning and BIS-11 total scores positively correlated with GD Published: 07 December 2021 severity. The standardized coefficients for the SEM showed direct positive contributions Citation: of BIS-11 non-planning, Padua and EDT scores to GD severity. Only participants’ ages Mestre-Bach G, Steward T, directly contributed to WCST perseverative errors, and no direct or indirect effects were Balodis IM, DeVito EE, Yip SW, George TP, Reynolds BA, Granero R, found with respect to GD severity. Fernandez-Aranda F, Conclusion: The findings suggest that specific aspects of impulsivity and compulsivity Jimenez-Murcia S and Potenza MN (2021) Discrete Roles for Impulsivity contribute to GD severity. Interventions specifically targeting domains that are most and Compulsivity in Gambling relevant to GD severity may improve treatment outcomes. Disorder. Front. Psychiatry 12:789940. Keywords: gambling disorder, impulsive behaviors, compulsive behaviors, addictive behaviors, delay discounting, doi: 10.3389/fpsyt.2021.789940 set-shifting Frontiers in Psychiatry | www.frontiersin.org 1 December 2021 | Volume 12 | Article 789940 Mestre-Bach et al. Impulsivity, Compulsivity, and Gambling Disorder INTRODUCTION younger/middle adulthood, thereby reducing the degree to which delayed rewards are devalued (49). In the case of GD, research Transdiagnostically, impulsivity and compulsivity contribute has found age and GD severity to serve as the best predictors to the development, maintenance and severity of mental of individual differences in choice impulsivity (26, 52, 53). disorders, including gambling disorder (GD) (1–5). Even Regarding compulsivity, differences have been found between though impulsivity and compulsivity are distinct, multifaceted different age groups in features such as cognitive flexibility and constructs, both may involve impaired tendencies to inhibit planning, suggesting maturational and developmental impacts as or delay behaviors and may be present concurrently or at well as possible effects of cognitive aging in older samples (54, 55). different times in the same disorder (6). While impulsivity and Therefore, although associations between impulsivity, compulsivity had been hypothesized to lie at different ends of a compulsivity, age, and GD severity have been described, further continuous spectrum (7), data suggest that the constructs may be study of how impulsivity and compulsivity may relate to more orthogonal, with elevated levels of each in disorders such as clinical characteristics of GD is needed. Moreover, in GD, the GD (8). simultaneous examination of both self-reported and behavioral Impulsivity has been defined as a “predisposition toward aspects of both impulsivity and compulsivity has been scarce. rapid, unplanned reactions to internal or external stimuli Elevated impulsivity and compulsivity have been observed in with diminished regard to the negative consequences of these both self-report and behavioral measures of impulsivity and reactions to the impulsive individual or to others” (9, 10). As compulsivity and have been, at times, linked to treatment suggested by this definition, impulsivity is a complex entity outcomes (47, 48, 56–60). Although complex relationships and may include components related to pre-potent motor between impulsivity and compulsivity have been proposed disinhibition [impulsive action (11)] and difficulties in delaying (8, 56), few studies have concurrently investigated self-reported gratification [impulsive choice (12)], and each may relate to and behavioral measures of both impulsivity and compulsivity specific neurocognitive mechanisms (2, 6, 13). Impulsivity has in GD. Finally, little research has examined potential mediating been implicated in multiple psychiatric disorders and conditions, roles of these domains in relationships between age and such as attention-deficit/hyperactivity disorder (14, 15), eating GD severity. disorders (16–20), obesity (21–23), and substance-use disorders Here, we examined the interplay between self-reported and and behavioral addictions (24–26). In GD, high levels of both behavioral measures of impulsivity and compulsivity and GD impulsive action (27) and impulsive choice (26, 28) have been severity in adults with GD and used structural equation modeling observed, using self-report or behavioral measures, although (SEM) to explore associations between age and these factors. We there is a lack of consistency in explaining their association with hypothesized that GD severity levels would positively relate to GD severity (27, 29–31). GD has also been linked to impulsive both self-reported and behavioral measures of impulsivity and tendencies (32, 33). Specifically, positive and negative urgency compulsivity. We also hypothesized that age would be positively levels and lack of perseverance are dimensions that may best associated with compulsivity, as suggested by previous studies distinguish individuals with and without GD (34–36). (54, 55), and that impulsivity would show a direct positive Compulsivity has been defined as involving, “the performance association with GD severity, as previously observed (58). Finally, of repetitive and functionally impairing overt or covert behavior given these relationships, we hypothesized that age would impact without adaptive function, performed in a habitual or stereotyped impulsivity and compulsivity levels that would then impact GD fashion, either according to rigid rules or as a means of avoiding severity; in other words, impulsivity and compulsivity would perceived negative consequences” (6). Compulsivity has been mediate relationships between age and GD severity. implicated in multiple mental disorders including obsessive- compulsive disorder (37), trichotillomania (38), and anorexia MATERIALS AND METHODS nervosa (39). In GD, compulsive features have been linked to genetic factors (40), and compulsivity-related impairments Participants and Procedure in cognitive flexibility may involve difficulty in learning from The sample was comprised of 132 participants who met criteria mistakes and implementing alternative problem-solving methods for GD. They were recruited at a University in the Problem (41–44). During performance of attentional set-shifting tasks like Gambling Clinic through advertisements. Individuals 18 years the Wisconsin card sorting test (WCST) (45), worse performance or older with a diagnosis of DSM-IV pathological gambling as (less flexibility or more compulsivity) has been observed in determined by structured clinical interview (Structured Clinical individuals with GD vs. those without, as reflected in more Interview for Pathological Gambling) were included (61). The perseverative errors (46). Moreover, self-reported compulsivity sample included all consecutive subjects who met criteria for has been positively associated with GD severity, linked to GD during the recruitment period (October, 2006 to November, poor control over gambling-related thoughts and behaviors, and 2015). associated with poorer treatment outcomes (47, 48). Changes in decision-making processes and impulsivity Measures dimensions are affected by neurodevelopment across the lifespan Clinical Characteristics (49–51). More specifically, it has been postulated that greater South Oaks Gambling Screen (SOGS) maturation of mesolimbic circuitry and cognitive control systems This questionnaire (62) includes 20 items assessing the frequency, occur with development from childhood/adolescence through presence and severity of gambling-related activities (scores Frontiers in Psychiatry | www.frontiersin.org 2 December 2021 | Volume 12 | Article 789940 Mestre-Bach et al. Impulsivity, Compulsivity, and Gambling Disorder range from 0 to 20). This questionnaire discriminates between steepness of the delay-discounting curve and was used as a probable non-problem gambling (from 0 to 2), probable measure of choice impulsivity. A higher k represents higher problem gambling (from 3 to 4), and probable pathological choice impulsivity. Curve-fitting was conducted using Prism 5 gambling (from 5 to 20), with higher scores being indicative of (GraphPad software). We assessed the proportion of choices for greater problem-gambling severity. The SOGS is a widely used each delay interval [delayed choice ratio = delayed choice/total instrument to screen for gambling problems in research and choice] and compared higher-impulsivity and lower-impulsivity clinical settings, and has been used as a measure of GD severity subjects (dichotomized by median k). (63). Internal consistency obtained in the study was Cronbach’s alpha α = 0.742. Compulsivity The Padua Inventory Impulsivity The Padua Inventory (66, 67) is a 60-question self-report The Barratt Impulsiveness Scale (BIS-11) instrument that assesses presence and severity of obsessive The BIS-11 (64) is a 30-item, self-report instrument that includes and compulsive symptomatology. The inventory contains four three subscales: (1) attentional, (2) motor, and (3) non-planning. factors: impaired control over mental activities, which assesses Item responses range from 1 to 4 (Rarely/Never, Occasionally, ruminations and exaggerated doubts; fear of contamination; Often, Almost Always/Always). It has demonstrated adequate checking; and impaired control over motor activities which test-retest reliability (Spearman’s ρ = 0.83) and acceptable measures urges and worries of losing control over motor internal consistency (α = 0.83), with a score of 72 or higher behaviors. The Padua Inventory has shown high test-retest representing high impulsivity (64). Internal consistency obtained reliability, high internal consistency, and good convergence in the study was Cronbach’s α = 0.736. validity with other instruments assessing obsessive and compulsive symptomatology (66, 67). Internal consistency Experiential Discounting Task (EDT) obtained in the study was Cronbach’s α = 0.967. The EDT is a computerized task to assess choice impulsivity, in which subjects experience chose smaller, sooner and certain The Wisconsin Card Sorting Test (WCST) rewards vs. larger, later, and probabilistic rewards in real time The Wisconsin Card Sorting Test (WCST) (45) is a set- (65). Subjects completed four session blocks associated with shifting task designed to assess cognitive flexibility. We used the different time delays, three of which involved choices between WCST and scored performance as described previously (68, 69). an adjusting and certain amount (initially, $0.15) that was The WCST assesses tendencies to shift cognitive strategies in delivered immediately or a standard amount ($0.30) that was response to altering conditions, and in so doing, assesses strategic delayed and probabilistic (35%). For the other session, there planning, organized searching and the use of environmental was no delay (0 s), and the reward ($0.30; probability, 35%) feedback to modify cognitive approaches. The test consists of 128 was delivered immediately. Choice options were indicated by cards that vary according to three attributes: the number, color, the “illumination” of light bulbs on the screen. The immediate and shape of their elements. Participants are instructed to sort amount (right side of screen) was adjusted in value in that the cards in piles beneath four reference cards that vary in these the amount increased by a set percentage following a delayed same dimensions. The only feedback given to the participant is standard choice but decreased following an immediate choice. the word “right” or “wrong” after each sorting. Initially, color The delayed standard amount (left side of screen) was not is the correct sorting category, and positive feedback is given adjustable. The standard option choice resulted in a wait only if the card is placed in the pile with the same color. of a specified delay (0, 7, 14, and 28 s). If the money was After 10 sequential correct answers the categorization criteria delivered, it could be transferred to the “bank” by clicking on change. Thus, only classifications that match the new category the “illuminated” bank image, which resulted in coin delivery will result in positive feedback. Participants must learn to change from a coin dispenser. Therefore, participants received real time the sorting categories according to the feedback they receive. The feedback based on their decisions. For each choice block, subjects test ends after all cards are sorted, or after six full categories made choices until an indifference point was reached, defined as are completed. The number of trials completed, the percentage choosing each option (i.e., immediate and delayed) three times of perseverative errors (i.e., failures to change sorting strategy within six consecutive choice trials—thus keeping the adjusting after negative feedback) and the percentage of non-perseverative amount constant over those six choices. After an indifference errors are recorded. point was established or the delayed option was chosen 15 times (reflecting minimal discounting), the session ended. The remaining sessions (i.e., 7, 14, and 28 s) were completed in Statistical Analysis ascending order. Statistical analysis was conducted with Stata17 for Windows The plots of the indifference curves (normalized indifference (70). First, associations between impulsivity and compulsivity point plotted for each delay interval) for each individual were measures and GD severity (SOGS total score) were estimated fit with either an exponential (VS = VAe – kd) or a hyperbolic through bivariate Pearson correlation coefficients (r). Due (VS = VA/1 + kd) function where the subjective value (VS) to strong associations between r-coefficients and sample size was a modification of the actual value (VA) by the delay in determining statistical significance, |r| > 0.10–0.24 was (d) and a discount constant (k). The k-value represents the considered a low effect size, |r| > 0.24–0.37 was considered a Frontiers in Psychiatry | www.frontiersin.org 3 December 2021 | Volume 12 | Article 789940 Mestre-Bach et al. Impulsivity, Compulsivity, and Gambling Disorder moderate effect size and |r| > 0.37 was considered a large effect obtained in the correlation matrix. The joint test measuring the size (71). invariance of the structural parameters by gender obtained non- Second, the associations between impulsivity-compulsivity significant results (χ2 = 13.02, p = 0.162), indicating that the measures and GD severity were evaluated through path analysis, path analysis did no significant difference between men and a straightforward extension of multiple regression modeling women (that is, gender did not have a moderating role in the SEM used with the aim to estimate the magnitude and significance paths). Adequate fitting was obtained for the SEM: χ2 = 7.06 (p of hypothesized associations into a set of variables, including = 0.530), RMSEA = 0.002, CFI = 0.998, TLI = 0.999, and SRMR mediational links (direct and indirect effects) (72). Path analysis = 0.053. Global predictive capacity for the model was 18%. The in this study was used as a case of structural equation modeling path diagram indicated a direct positive contribution of BIS-11 (SEM), with the maximum-likelihood estimation method of non-planning, Padua Inventory total, and EDT-k scores to GD parameter estimation and evaluating goodness-of-fit through severity. Participants’ ages only positively contributed to WCST standard statistical measures [including the root mean square perseverative errors, and no direct or indirect effects were found error of approximation (RMSEA), Bentler’s Comparative Fit with respect to GD severity. Index (CFI), the Tucker-Lewis Index (TLI), and the standardized root mean square residual (SRMR)] (73). Adequate model fit was considered non-significant by chi-square (χ2 ) tests and if the DISCUSSION following criteria were met (73): RMSEA < 0.08, TLI > 0.9, CFI > 0.9, and SRMR < 0.1. The global predictive capacity of the The first aim of the present study was to examine associations model was measured by the coefficient of determination (CD). between impulsivity, compulsivity, and GD severity in adults The study model included impulsivity-compulsivity measures with GD. The second goal was to explore the mediating roles and age as endogenous variables and SOGS total score (i.e., of impulsivity and compulsivity levels between age and GD GD severity) as the exogenous variable. Due to the large set severity by means of a path analysis. GD severity was positively of observed variables, with the aim to achieve adequate fitting correlated with self-reported impulsivity (BIS-11 non-planning and a parsimonious model, a pre-selection of the best measures and BIS-11 total scores). The standardized coefficients for the for the impulsivity-compulsivity constructs was done through SEM showed a direct positive contribution of self-reported stepwise multiple regression (the SOGS total score was defined impulsivity (BIS-11 non-planning), behavioral impulsivity (EDT as the criterion and the remaining clinical variables as potential scores) and self-reported compulsivity (Padua total scores) to predictors). In addition, a multi-group SEM was tested in the GD severity. Participants’ age only significantly contributed to study, including gender as a group variable with the aim to assess behavioral compulsivity (WCST perseverative errors), and no the invariance of the structural coefficients. effects were found with respect to GD severity. Regarding impulsivity, behavioral choice impulsivity (assessed RESULTS using EDT-k) correlated with self-reported impulsivity (assessed using the BIS-11 and correlating with BIS-11 attentional and Sample Description motor impulsivity subscales, and total score). Previous studies The frequency distribution of the sociodemographic and clinical have found weak or no relationships between most facets variables of the study are included in Table 1. Most participants of motor and choice impulsivity (74, 75). This may partly were male (71.2%), White (60.6%), and single (58.3%). Age range be explained by the discrepancies between behavioral and in the study was 18–69 years-old, and SOGS total score was self-report measures of impulsivity-related assessments (76), between 5 and 20. questioning whether these different tools assess the facets of impulsivity they are intended to measure (77, 78). Alternatively, Correlations Between Variables as prior studies have not examined groups with GD, it is possible Table 2 contains the correlation matrix with coefficients between that these forms of impulsivity are more closely related in the study variables. Associations with effect sizes in the moderate individuals with GD than in the general population. to high range are marked in bold. GD severity positively The present findings suggest that self-reported and correlated with BIS-11 non-planning and BIS-11 total scores. behavioral measures of compulsivity are not highly EDT-k values were also positively correlated with BIS-11 scores, correlated. Many instruments assessing compulsivity are except for non-planning (the EDT-AUC index was negatively based on conceptualizations of obsessive-compulsive correlated with the EDT-k values). Age was positively related disorder (OCD) and may not be ideal for considering with WCST measures (older age was associated with worse compulsivity as a transdiagnostic construct (79, 80), due cognitive performance). All remaining significant associations to, among other things, the clinical and neurobiological were between subscales of the same questionnaires. differences between GD and OCD (81). However, like impulsivity, compulsivity is likely a multifaceted construct Path Analysis that includes several conceptually and empirically separable The standardized coefficients for the SEM are included in the features, such as attentional bias/disengagement or failures diagram in Figure 1, and the complete results of the model testing in contingency-related cognitive flexibility during habit direct, indirect, and total effects are included in Table 3. The learning (2, 6). As such, each assessment could be measuring EDT-k values were selected for the EDT task based on the results different features that may link to clinical characteristics Frontiers in Psychiatry | www.frontiersin.org 4 December 2021 | Volume 12 | Article 789940 Mestre-Bach et al. Impulsivity, Compulsivity, and Gambling Disorder TABLE 1 | Sample description (N = 132). Sociodemographics n Perc. Gender Female 38 28.8% Male 94 71.2% Race White 60.6% Black 36.4% Other 3.0% Marital status Single 77 58.3% Married 22 16.7% Separated-divorced 33 25.0% Education level Postgraduate 6 4.5% College graduate 25 18.9% Some college without diploma 52 39.4% High school diploma/GED 45 34.1% Less than High School 4 3.0% Chronological age Min Max Mean SD Age (years); 18 69 42.77 12.25 Clinical measures Min Max Mean SD GD: SOGS total score 5 20 12.10 4.03 WCST trials completed 68 128 102.06 22.04 WCST % perseverative errors 4 44 12.91 8.19 WCST % non-perseverative errors 3 47 14.54 8.85 Padua impaired-control over mental activities 0 44 8.62 10.52 Padua fear of contamination 0 39 9.07 8.94 Padua checking 0 24 5.15 6.25 Padua impaired-control over motor activities 0 17 1.60 3.29 Padua total score 0 107 24.44 24.37 BIS-11 attentional 8 31 15.53 4.08 BIS-11 motor 13 39 24.46 5.19 BIS-11 non-planning 14 40 26.21 5.08 BIS-11 total 38 102 66.20 11.91 EDT k-delay discountinga −0.03 2.50 0.027 0.28 EDT AUC indexa 0.11 0.47 0.195 0.04 a Median and SD are reported for this measure. Min, minimum; Max, maximum; SD, standard deviation; GD, gambling disorder; SOGS, South Oaks Gambling Screen; WCST, Wisconsin Card Sorting Test; BIS-11, Barratt Impulsiveness Scale; EDT, Experiential discounting task. in unique fashions. Results of the partial correlation and GD severity (58). The seemingly discrepant results may matrix and the SEM showed that none of the impulsivity be due to differing characteristics of the samples studied (e.g., dimensions were associated with compulsivity measures sociodemographic or clinical characteristics, cultural contexts) in the present study. This finding supports the notion or other factors, and more research is warranted to examine that both are separate constructs, as suggested by previous these possibilities. data (82). The SEM also showed a direct positive contribution of The present study also assessed associations between compulsivity to GD severity, although only the total score on the impulsivity, compulsivity, and GD severity. The SEM showed Padua Inventory had a significant association with GD severity. a direct positive contribution of impulsivity (BIS non-planning Previous studies suggest that performance differences linked to and EDT-k) to GD severity. While prior studies have found no compulsivity may be associated with the development and the correlation between specific dimensions of impulsivity (assessed maintenance of GD symptomatology. The cognitive inflexibility with the BIS-11) and GD severity (83), others have found that or the tendency to perseverate on a behavior could, for example, only high attentional and motor impulsivity BIS-11 scores had increase the risk for developing GD behavior; alternatively, significant associations with GD severity (84), and others have compulsivity could be a consequence of GD (46). Longitudinal found, as in the present study, an association between impulsivity studies are needed to test these possibilities further. Frontiers in Psychiatry | www.frontiersin.org 5 December 2021 | Volume 12 | Article 789940 Mestre-Bach et al. Impulsivity, Compulsivity, and Gambling Disorder TABLE 2 | Correlations between the variables of the study. 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 1 SOGS total score 0.08 −0.01 0.04 −0.01 −0.03 −0.07 −0.02 −0.04 0.13 0.21 0.24† 0.26† 0.06 0.07 0.14 2 WCST trials completed 0.72† 0.78† 0.10 0.03 0.08 −0.03 0.07 0.00 −0.14 0.02 −0.05 0.04 −0.05 0.36† 3 WCST perseverative 0.66† 0.16 0.10 0.13 0.03 0.14 −0.07 −0.18 −0.03 −0.12 0.02 −0.08 0.33† errors 4 WCST 0.17 0.03 0.15 0.04 0.13 −0.01 −0.11 0.02 −0.04 0.10 −0.12 0.32† non-perseverative errors 5 Padua impaired-control 0.54† 0.80† 0.66† 0.92† 0.21 0.01 0.01 0.08 −0.02 −0.13 −0.04 over mental activities 6 Padua fear of 0.57† 0.31† 0.79† 0.04 −0.10 −0.19 −0.11 0.01 −0.12 −0.06 contamination 7 Padua checking 0.47† 0.87† 0.09 0.05 −0.13 −0.01 0.04 −0.18 −0.10 8 Padua impaired-control 0.65† 0.20 0.04 −0.02 0.08 0.02 −0.04 −0.14 over motor activities 9 Padua total score 0.16 −0.01 −0.11 0.00 0.01 −0.15 −0.08 10 BIS attentional 0.56† 0.48† 0.79† 0.25† −0.06 −0.12 11 BIS motor 0.55† 0.86† 0.28† −0.07 −0.11 12 BIS non-planning 0.83† 0.16 −0.07 0.01 13 BIS total 0.27† −0.08 −0.08 14 EDT k-delay −0.58† −0.08 discounting 15 EDT AUC index 0.01 16 Age (years) † Bold: effect size into the moderate (|R| > 0.24) to high range (|R| > 0.37). Sample size: N = 132. SOGS, South Oaks Gambling Screen; WCST, Wisconsin Card Sorting Test; BIS-11, Barratt Impulsiveness Scale; EDT, Experiential discounting task. FIGURE 1 | Path diagram with structural equation modeling showing standardized coefficients (N = 132). Continuous parameter: significant parameter. Dash line, non-significant parameter; BIS-11, Barratt Impulsiveness Scale; EDT, Experiential discounting task; WCST, Wisconsin Card Sorting Test; SOGS, South Oaks Gambling Screen; Persev., perseverative. The finding that not all measures of compulsivity showed and development of GD than compulsivity, as found in other an association with GD severity coincides with previous behavioral addictions (24), although more studies are needed to studies, which did not find an association between the WCST examine these relationships, especially in a longitudinal fashion. performance and GD severity (82). These results suggest that Finally, sex and age are two sociodemographic factors that impulsivity may contribute more strongly to the acquisition should be considered in relationships between impulsivity, Frontiers in Psychiatry | www.frontiersin.org 6 December 2021 | Volume 12 | Article 789940 Frontiers in Psychiatry | www.frontiersin.org Mestre-Bach et al. TABLE 3 | Structural Equation Modeling: direct, indirect and total effects. Direct effects Indirect effects Total effects B SE (B) z p St (B) B SE (B) z p St (B) B SE (B) z p St (B) PADUA Age Female 0.075 0.322 0.23 0.816 0.039 * – 0 0.075 0.322 0.23 0.816 0.039 Male −0.160 0.218 −0.74 0.462 −0.079 −0.160 0.218 −0.74 0.462 −0.079 SOGS PADUA Female 0.051 0.034 1.51 0.048 0.240 * – 0 0.051 0.034 1.51 0.048 0.240 Male 0.060 0.016 −0.62 0.047 0.234 0.060 0.016 −0.62 0.047 0.234 BIS-11-non plan Female 0.305 0.123 2.47 0.014 0.376 * – 0 0.305 0.123 2.47 0.014 0.376 Male 0.112 0.086 1.3 0.045 0.134 0.112 0.086 1.3 0.045 0.134 EDT-k Female 3.890 2.502 1.55 0.040 0.223 * – 0 3.890 2.502 1.55 0.040 0.223 Male 2.139 2.188 −0.98 0.038 0.101 2.139 2.188 −0.98 0.038 0.101 WCST-persev. Female 0.031 0.098 0.32 0.750 0.055 * – 0 0.031 0.098 0.32 0.750 0.055 Male −0.069 0.051 −1.37 0.172 −0.150 −0.069 0.051 −1.37 0.172 −0.150 Age Female −0.023 0.064 −0.36 0.721 −0.056 0.009 0.047 0.19 0.848 0.022 −0.014 0.068 −0.2 0.839 −0.034 Male 0.070 0.034 2.07 0.039 0.227 −0.012 0.014 −0.87 0.386 −0.040 0.057 0.032 1.77 0.077 0.186 BIS-11-non plan Age Female 0.016 0.084 0.19 0.853 0.031 * – 0 0.016 0.084 0.19 0.853 0.031 Male −0.024 0.039 −0.61 0.539 −0.066 −0.024 0.039 −0.61 0.539 −0.066 EDT-k Age Female −0.002 0.004 −0.59 0.558 −0.097 * – 0 −0.002 0.004 −0.59 0.558 −0.097 Male −0.002 0.002 −1.05 0.293 −0.112 −0.002 0.002 −1.05 0.293 −0.112 7 WCST-persev. Age Female 0.298 0.110 2.7 0.007 0.410 * – 0 0.298 0.110 2.7 0.007 0.410 Male 0.211 0.067 3.13 0.002 0.318 0.211 0.067 3.13 0.002 0.318 B, coefficient. SE, standard error; St (B), standardized coefficient; *Parameter estimates constrained to be equal across groups. Sample size: N = 132. SOGS, South Oaks Gambling Screen; BIS-11, Barratt Impulsiveness Scale; EDT, Experiential discounting task; WCST, Wisconsin Card Sorting Test; persev., perseverative; non-plan, non-planning. Impulsivity, Compulsivity, and Gambling Disorder December 2021 | Volume 12 | Article 789940 Mestre-Bach et al. Impulsivity, Compulsivity, and Gambling Disorder compulsivity, and GD severity (26, 51, 85–87). The present study a greater focus on new instruments considering compulsivity did not observe differences between men and women in the SEM. within a transdiagnostic framework (95) and that are not as Age significantly contributed to WCST perseverative errors, focused on OCD may produce findings that could help to clarify consistent with previous findings by identifying a reduction in relationships with compulsivity in GD populations (79). cognitive flexibility at older ages (54, 55). However, age was not directly associated with any impulsivity measures, as in previous CONCLUSIONS studies, reaffirming that impulsivity is a complex construct and suggesting that more studies focused on compulsivity-related This study provides greater understanding of how impulsivity cognitive domains may be needed (51). and compulsivity may relate to GD severity. Our findings suggest impulsivity and compulsivity are multifaceted and separable Clinical Implications constructs and not all impulsivity and compulsivity domains These findings have multiple clinical implications. The relate equally to GD severity. The findings suggest that these utility of categorical classifications has been questioned two multifactorial constructs deserve greater attention in both (88), and transdiagnostic features may link more closely to research and clinical settings. Interventions specifically targeting biological constructs (89, 90). For example, impulsivity has domains that are most relevant to the maintenance of GD may been found to link to insular, amygdalar, and hippocampal help improve treatment outcomes. structures across individuals with GD, those with cocaine- use disorder and those with neither (91). As suggested (9), clinical data focusing on impulsivity and compulsivity may DATA AVAILABILITY STATEMENT be used to shift toward a more dimensional framework of psychiatric diagnosis and treatment. This approach may lead The raw data supporting the conclusions of this article will be to improvements in treatment, especially as changes in both made available by the authors, without undue reservation. impulsivity and compulsivity have been linked to treatment outcomes in GD (47, 48, 92). A dimensional perspective also ETHICS STATEMENT addresses the critical heterogeneity in the neurobiology of addictions and may help to identify biomarkers suitable for The studies involving human participants were reviewed and assessment and helpful for advancing personalized medicine approved by Yale School of Medicine Human Investigations approaches (93). Committee. The patients/participants provided their written informed consent to participate in this study. Limitations and Future Research The present study has limitations. First, our sample included participants with GD who were not seeking treatment, and AUTHOR CONTRIBUTIONS this may limit the generalizability of the results to different GM-B drafted the manuscript. MP oversaw study design and clinical populations. Future research should include a treatment- data collection. IB, ED, SY, TG, and BR contributed to study seeking sample, as well as a healthy control group, to assess design or data collection. GM-B, TS, RG, FF-A, SJ-M, and MP possible differences in these domains between groups. Similarly, planned analyses or conducted analyses. All authors approved examining the validity of these results to other addictions the manuscript. would be another useful contribution for clinicians, as suggested previously (94). Second, the cross-sectional design does not allow for inferences to be made regarding causality or changes FUNDING in impulsivity and compulsivity over the course of GD. Longitudinal studies are needed to examine these relationships. MP’s involvement was supported by a National Center for Future studies focused on impulsivity, compulsivity, and age Responsible Gaming Center of Excellence grant and by the of onset of GD would be helpful in order to examine whether Connecticut Council on Problem Gambling and the Connecticut a switch from impulsivity (in early stages of the addiction Department of Mental Health and Addiction Services. GM-B course) to compulsivity exists (10, 46). Third, clinical factors of was supported by a FUNCIVA postdoctoral grant. This the participants, such as gambling preferences (data on most research was funded by Ministerio de Ciencia, Innovación y preferred/problematic form of gambling were not available), Universidades (grant RTI2018-101837-B-100), FIS PI20/132, and comorbidities, and pharmacological treatments, were not taken FIS PI17/01167, which received aid from the Instituto Salud into account, and they could be associated with performance Carlos III (Ministerio de Sanidad, Servicios Sociales e Igualdad). on both the self-reported instruments and the behavioral tasks The research was also funded by the Delegación del Gobierno used to assess impulsivity and compulsivity. 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Frontiers in Psychiatry | www.frontiersin.org 11 December 2021 | Volume 12 | Article 789940