Response trajectories of gambling severity after cognitive behavioral therapy in young-adult pathological gamblers Journal of Behavioral ROSER GRANERO1,2, SUSANA VALERO-SOLIS3, Addictions  FERNANDO FERNANDEZ-ARANDA 1,3,4 ,  MONICA  GOMEZ-PE ~ 3, LAURA MORAGAS3, NA 9 (2020) 1, 140-152 TERESA MENA-MORENO3, AMPARO DEL PINO-GUTIERREZ5, DOI: 10.1556/2006.2020.00008 ESTER CODINA3, VIRGINIA MARTÍN-ROMERA6, © 2020 The Author(s) GEMMA CASALE  3, ZAIDA AGUERA € 1,3 , ISABEL BAENAS-SOTO3, EDUARDO VALENCIANO-MENDOZA3, BERNAT MORA-MALTAS3, ISABEL SANCHEZ 3 ,   MARÍA LOZANO-MADRID , JOSE M. MENCHON3,4,7 and 3  SUSANA JIMENEZ MURCIA1,3,4p FULL-LENGTH REPORT 1 CIBER Fisiopatologia Obesidad y Nutrici on (CIBERobn), Instituto de Salud Carlos III, Barcelona, Spain 2 Departament de Psicobiologia i Metodologia, Autonomous University of Barcelona, Barcelona, Spain 3 Department of Psychiatry, Bellvitge University Hospital-IDIBELL, Barcelona, Spain 4 Department of Clinical Sciences, School of Medicine, University of Barcelona, Barcelona, Spain 5 Department of Public Health, Mental Health and Mother-Infant Nursing, University School of Nursing, University of Barcelona, Barcelona, Spain 6 Departamento de Educaci on y Psicología, Centro Universitario Cardenal Cisneros, Universidad de Alcala, Madrid, Spain 7 CIBER Salud Mental (CIBERsam), Instituto de Salud Carlos III, Barcelona, Spain Received: September 7, 2019 • Revised manuscript received: November 28, 2019; January 21, 2020 • Accepted: January 25, 2020 • Published online: April 7, 2020 ABSTRACT Background and aims: The significant increase in the prevalence of gambling disorder (GD) among young adults in recent years has attracted interest in determining therapeutic efficiency in this sector of the population. The aim of this work was to estimate the response trajectories of gambling severity during the six-month follow-up after a cognitive behavioral therapy (CBT) program in young adult patients and to identify the main variables associated with each trajectory. Methods: The sample included n 5 192 patients, aged 19–35 years old, seeking treatment for GD. Response trajectories were identified through latent class growth analysis. Results: Three trajectories emerged: T1 (n 5 118, 61.5%), composed of patients with severe GD at pre-treatment and good evolution to recovery; T2 (n 5 62, 32.3%), with patients with moderate-high GD affectation at baseline and good evolution to recovery; and T3 (n 5 12, 6.3%), with participants with severe baseline GD severity and poor evolution after CBT (Abbott, 2019). The highest risk of poor therapeutic outcomes was related to lower social index positions, high emotional distress, high scores in harm avoidance and low scores in self-directedness. Discussion and conclusions: Differences in the response trajectories at *Corresponding author. Department of short-term follow-up after CBT reveal heterogeneity in the samples including young and young-adult GD Psychiatry, Bellvitge University Hospital-IDIBELL and CIBERObn, patients. Patients’ phenotype at baseline should be considered when developing efficient, person-centered c/Feixa Llarga s/n, 08907, Hospitalet intervention programs, which should comprise strategies aimed at increasing emotional regulation capac- de Llobregat, Barcelona, Spain. ities, self-esteem and self-efficacy, with the aim of avoiding relapses in the medium-long term after therapy. Tel.: þ34 93 260 79 88; fax: þ34 93 260 76 58. E-mail: sjimenez@ bellvitgehospital.cat KEYWORDS cognitive behavioral therapy, response trajectories, gambling disorder, latent class growth analysis, personality, psychological predictors Journal of Behavioral Addictions 9 (2020) 1, 140-152 141 INTRODUCTION be depicted in the form of a vicious circle, whereby the final negative post-purchase stage generates the emotional trig- gers for the repetition of the whole cycle, which allows for Gambling disorder (GD) is defined as the uncontrollable GD to become self-reinforcing/regulating over time. CBT urge to continue gambling despite adverse consequences for programs are focused on the development and maintenance the individuals (including impaired social functioning, of coping strategies that target solving current problems and financial trouble or even comorbidity of mental and physical changing unhelpful patterns in cognitive, behavioral and diseases) (American Psychiatric Association, 2013). Recent emotional regulation, with the aim of identifying and acting systematic reviews show that GD problem behaviors are on the elements supporting the vicious circle around the present in between 0.12 and 5.8% of the population across gambling behavior. Accordingly, CBT includes the devel- different countries worldwide (Calado & Griffiths, 2016). opment of skills for learning to control and manage high- Increasing prevalences have been estimated in recent de- risk situations to effectively reduce the probability of cades in both sexes, with particularly disturbing incidences gambling in the future and to prevent relapses. Compared to at increasingly younger ages (Calado, Alexandre, & Griffiths, substance addictions, the CBT treatment adapted to GD may 2017; Gainsbury, Russell, Blaszczynski, & Hing, 2015). This target the addictive behavior, its underlying mechanisms epidemiological picture has led researchers to consider GD (including irrational cognitions), and financial management as an emergent public health issue, with the consequent (including potential financial problems) (Rash & Petry, burgeoning of empirical research in approaches to pre- 2014). venting and treating gambling-related problems. A wide variety of CBT programs have been developed for Similarities in the endophenotypes of substance-use dis- GD. Most of them include common elements, such as sys- orders and GD have been systematically described, leading to tematic desensitization, stimulus control, psychoeducation, craving, withdrawal, tolerance and abstinence syndrome financial counseling, cognitive restructuring techniques, and (Banz, Yip, Yau, & Potenza, 2016; Zou et al., 2017). Problem relapse prevention. As a whole, recent systematic reviews gambling is often accompanied by comorbid psychiatric and measuring the effectiveness of these programs maintain that maladaptative personality traits, as well as dysfunction of CBT is an efficient intervention plan at reducing gambling cognitive domains regulating impulsive behavior (Ioannidis, problems and related symptoms immediately following Hook, Wickham, Grant, & Chamberlain, 2019). The GD therapy, while the durability of the therapeutic usefulness is patients usually perceive multiple adverse consequences unknown (Cowlishaw et al., 2012; Merkouris, Thomas, related to the gambling activity in several areas (biological, Browning, & Dowling, 2016). But research gaps exist, as well psychological, social and financial). Some individuals accept as controversies regarding how CBT works in the treatment problematic gambling as a lifestyle and are unlikely to seek of problem gambling, which particular CBT programs are treatment (Babic et al., 2018), while others realize they have a the most effective, and what is the real usefulness of the problem, feel the need to control their urges to gamble and different CBT modalities depending on the GD profiles at seek help to stop gambling and recover. Considering this baseline (Gooding & Tarrier, 2009; Tolchard, 2017). Studies scenario, empirical evidence is required for a better under- focused on identifying the main factors contributing to both standing of the underlying mechanisms related to the onset of the effectiveness and poor outcome of CBT in GD patients problem gambling and the GD progression, with the aim of have also obtained varied results. As a whole, high dropout developing effective prevention programs addressed to highly and relapse rates (during the therapy program and in the vulnerable populations, to design reliable and valid tools to follow-up), as well as non-compliance issues, are common in measure the complete profile of the GD, and to apply precise outpatient programs (Aragay et al., 2015; Challet-Bouju, intervention plans focused on individuals’ specific needs. Bruneau, IGNACE Group, Victorri-Vigneau, & Grall- A number of studies to date have examined the effec- Bronnec, 2017). The most significant contributors to tiveness of different evidence-based treatment approaches limiting long-term adverse consequences and improving for GD, such as cognitive behavioral therapy (CBT), outcome appear to be early identification, low severity of participate in self-help groups, motivational interviewing, gambling at baseline, low severity of psychopathological mindfulness, pharmaceutical treatments in certain cases, and comorbidity, high motivation, and some personality do- novel mixed approaches (Petry, Ginley, & Rash, 2017). mains related to impulsivity (Dunn, Delfabbro, & Harvey, Cognitive behavioral models have achieved good evidence 2012). Male gender, low comorbid depression levels, lower explaining and managing GD related problems, and CBT is gambling symptom severity and higher treatment session considered a “gold standard” for the treatment of GD attendance have also been found to be the most likely and (Abbott, 2019). A number of studies describe the model/ consistent predictors of successful treatment outcomes procedure of applying CBT in the field of substance-related across multiple time points (post-treatment, short term, disorders and behavioral addictions, such as the study by An medium term and long term) (Gomez-Pe~ na et al., 2012; and colleagues, which integrates key cognitive, affective and S. Jimenez-Murcia et al., 2016, 2015; Merkouris et al., 2016). behavioral factors in differentiating phases/stages: anteced- The resistance to CBT found in many studies has also led to ents, internal-external triggers, the act of the addictive considering the inclusion of supplementary strategies to behavior (such as gambling), and post-purchase states improve emotional regulation and decrease impulsivity (An, He, Zheng, & Tao, 2017). Based on this model, GD can levels in therapeutic plans, with promising therapeutic 142 Journal of Behavioral Addictions 9 (2020) 1, 140-152 effectiveness (Mallorquí-Bague et al., 2018; Peter et al., 2019; subtypes of GD obtain benefits from the CBT programs. The Tarrega et al., 2015). research conducted by Ledgerwood and Petry aimed at Parallel to the study of the therapy outcomes, research obtaining a categorization based on the scores in anxiety, has focused on the classification of the subtypes of GD and depression and impulsivity observed that although the three its correlates. It is well known that numerous factors pathways types differed in some baseline measures contribute to the risk of developing diverse gambling [gambling level, emotional impairment, or the presence of problems, such as the presence of emotional distress, early other comorbid disorders (concurrent and lifespan)], this wins, cognitive biases related to the gambling activity, classification did not obtain predictive capacity on the impulsivity, personality traits and some sociodemographic gambling severity after the treatment (Ledgerwood & Petry, features. Different underlying mechanisms have also been 2010). Further studies exploring GD subtypes based on the related to the onset and courses of the problem gambling. problem gambling severity through treatments and follow- Subtyping GD could also contribute with new valuable ev- up should reveal different patterns of recovery and therefore idence toward precise interventions to match individuals’ contribute towards identifying the most relevant predictors needs. The three pathways model proposed by Blaszczynski of the outcomes and the progression of the gambling and Nower is nowadays one of the most referenced classi- profiles. fication systems, considered as a multi-causal framework for conceptualizing GD on the basis of three subtypes of path- Present study ological gamblers (Blaszczynski & Nower, 2002): behavioral Despite the available evidence reinforcing the effectiveness conditioned (the onset of the disorder resulted from of CBT across varied GD patients, increased attention needs repeated exposure to gambling and the course of the prob- to be given to the diverse populations and phenotypes, to the lems was consequence of the contingencies related to the mechanisms of change, medium- and long-term outcomes, gambling activity), emotionally vulnerable (the patients use and predictors of relapse prevention. In addition, there is no the gambling activity as a way to relieve aversive affective single conceptual/theoretical model of the GD subtyping states) and antisocial-impulsive (patients with high levels of that adequately accounts for the multiple factors explaining emotional dysregulation, impulsivity and neurological the onset of the gambling problems, its progression and the dysfunction). Subsequent research has examined the validity benefit of the CBT programs. of this three pathways model in samples with diverse To our knowledge, no study to date has addressed CBT composition and considering different measures for the outcomes in young and young-adult GD patients. The main definition of the latent classes. For example, Milosevic and objective of this study is to use growth curve modeling to Ledgerwood identified three GD subtypes (with differences estimate response trajectories of the GD progression during in the psychopathology state, the personality traits and the the short-term follow-up (6 months) after a group CBT motivations for gambling) in a comprehensive review of the treatment in a sample of young and young-adult GD pa- available empirical literature, and concluded that these tients. The secondary objective is to assess the discriminative profiles were parallel to the three types of gamblers defined capacity of sociodemographic and clinical profiles at base- in the pathways model (Milosevic & Ledgerwood, 2010). The line to differentiate between empirical trajectories. subsequent study conducted by Moon and colleagues also provided evidence for the validity of the three pathways model as a framework for conceptualizing GD subtypes in a METHODS sample comprising both non-treatment-seeking individuals and pathological disordered gamblers, through a hierarchical cluster analysis examining motives for the gambling activity: Participants childhood trauma, boredom proneness, risk-taking, impul- The sample of this study considered all the consecutive sivity, attention-deficit/hyperactivity disorder and antisocial treatment-seeking patients attending one hospital unit personality (Moon, Lister, Milosevic, & Ledgerwood, 2017). specializing in GD and other behavioral addictions in Bar- The research by Nower et al. derived three empirical sub- celona (Spain), who fulfilled the following inclusion criteria: types of disordered gamblers roughly corresponding to the fulfill diagnostic criteria for GD, male gender and chrono- subtypes of the three pathways model, ranging from a sub- logical age within the range of 18 to 35 years old. Exclusion group with a lower level of gambling activity and psycho- criteria were having an intellectual disability or severe pathology to one with high levels of gambling problem mental disorder (such as schizophrenia or other psychotic severity and comorbid psychiatric disorders (Nower, Mar- disorders or bipolar disorder). Women were also excluded tins, Lin, & Blanco, 2013). Finally, the recent study by Devos from this work because their low frequency in the treatment and colleagues conducting a classification analysis using unit and the specific GD profiles in women made it more impulsivity traits and gambling-related cognitions as in- appropriate individual CBT programs (instead the group dicators, also identified three clusters aligned with the three CBT format analyzed in this work). pathways model among a sample composed of gamblers The age range from 18 to 35 years was considered as an recruited from the community and treatment-seeking inclusion criterion since the aim of the study was to obtain pathological gamblers (Devos et al., 2020). But to our empirical trajectories for the therapy response after CBT knowledge, few studies have examined how the putative among middle-age patients. Although there is no complete Journal of Behavioral Addictions 9 (2020) 1, 140-152 143 consensus regarding the boundary limits for considering Symptom Checklist-90 Items-Revised (SCL-90-R) (Derogatis, young-, middle- and older-age in the health sciences, many 1994). This instrument is a self-report tool used for measuring studies carried out in the problem gambling area consider global psychopathology through 90 items structured in nine that this is the period from late adolescence (age 18 corre- symptom dimensions (obsessive-compulsive, depression, anxi- sponds to legal adulthood) to one’s late twenties or early ety, hostility, interpersonal sensitivity, phobic anxiety, somati- thirties. Prevalence studies internationally have reported that zation, paranoid ideation and psychoticism) and three individuals in this age group tend to have the highest rates of composite indexes [the global severity index (GSI), the positive problem gambling, and have usually chosen 35 years of age symptom total, and the positive symptom distress index]. Good as an upper bound limit (Grande-Gosende, L opez-N ~ez, un psychometric properties have been reported in Spanish samples García-Fernandez, Derevensky, & Fernandez-Hermida, (Derogatis, 1997). In our study, the GSI index was employed as 2019; Petry, 2002). a measure of global psychopathology, with an excellent internal The final sample of participants included n 5 192 par- consistency in our sample equal to a 5 0.97. ticipants who completed the CBT program, with a mean Temperament and Character Inventory-Revised (TCI-R) chronological age of 29.7 years (SD 5 4.1) and a mean age of (C R Cloninger, 1999). This instrument is a 240-item tool for onset of the GD of 21.1 years (SD 5 4.7). Many participants measuring personality, structured in four temperament di- were single (n 5 112, 58.2%), had a primary (n 5 83, 43.2%) mensions (novelty seeking, harm avoidance, reward depen- or secondary (n 5 95, 49.5%) education level, and held dence and persistence) and three character scales mean-low (n 5 78, 40.6%) or low (n 5 68, 35.4%) socio- (cooperativeness, self-directedness and self-transcendence). economic levels. The first two columns in Table 2 contain The adapted Spanish version has reported good psycho- the frequency distributions for all the variables analyzed in metric indexes (Gutierrez-Zotes et al., 2004). In our sample, the study for the whole sample. internal consistency ranged from adequate to excellent (a 5 The number of dropouts during the follow-up was n 5 55: 0.72 for novelty seeking to a 5 0.88 for persistence). risk of dropout 5 28.6%, a value consistent with prospective Other sociodemographic and clinical variables. Additional studies carried out in the gambling area (Challet-Bouju et al., data were obtained through a semi-structured face-to-face 2017). No statistical differences in the sociodemographics and clinical interview (see description in: (Susana Jimenez- the clinical state at baseline were found comparing patients Murcia, Aymamí, Gomez-Pe~  na, Alvarez-Moya, & Vallejo, who completed all the follow-up versus those who dropped 2006)). The main addictive-related variables analyzed in this out (sex: c2(df 5 2)52.77, P 5 .251; education: c2(df 5 2)51.22, study are the age of GD onset, the duration of the addiction, P 5 0.543; socioeconomic position index: c2(df 5 3)52.82, and social status (measured through Hollingshead’s index) P 5 0.420, employment status: c2(df 5 2)50.03, P 5 0.863, (Hollingshead, 2011). chronological age: F(df 5 1;190)50.76, P 5 0.385, age of onset of the gambling problems: F(df 5 1;190)51.10, P 5 0.297, duration of the gambling problems: F(df 5 1;190)52.07, P 5 0.152, CBT program number of DSM-5 criteria for GD: F(df 5 1;190)50.51, P 5 In the present study, CBT was implemented as a time-limited 0.478, SOGS total score: F(df 5 1;190)51.54, P 5 0.216, and technique of 16 weekly sessions lasting 90 minutes each, in SCL-90R GSI: F(df 5 1;190)50.57, P 5 0.540). group (averaging approximately 10 patients per group). The final aims were to achieve full recovery (defined as the definitive abstinence from all types of gambling), to reduce patients’ arousal levels in the presence of stimuli that trigger Measures the urge to gamble, to increase their self-control, to regulate Diagnostic Questionnaire for Pathological Gambling Ac- their negative emotions and to improve their self-efficacy and cording to DSM Criteria (Stinchfield, 2003). This is a 19-item their expectations of recovery. The full protocol is available tool for assessing DSM-IV (American Psychiatric Associa- directly from the corresponding author of the manuscript. tion, 2000) criteria for GD, as well as the DSM-5 (American Patients received the protocols CBT outpatient program Psychiatric Association, 2013) criteria for this clinical con- in the Hospital Unit. The program was presented and dition. The original version achieved good psychometric developed by a qualified CBT, a clinician expert on prob- properties, as did the Spanish adaptation used in this study lematic gambling and GD. Prior to the beginning of the (S. Jimenez-Murcia et al., 2009). In our sample, the internal program, patients received group psychoeducation focused consistency was adequate (Cronbach’s alpha a 5 0.75). on the following topics: a) conceptualization of the GD South Oaks Gambling Screen (SOGS) (Lesieur & Blume, (providing knowledge about the endophenotype, the onset 1987). This instrument is a common tool to assess GD and course/progression of the disorder, and vulnerability severity, structured in 20 items that measure cognitive, and protective factors); b) explaining the rationale behind emotional and other behavior strongly related to gambling CBT; c) patients learning to identify their dysfunctional problems. The Spanish adaptation of this tool showed good thoughts and feelings related to the gambling activity; high internal consistency (Cronbach’s alpha a 5 0.94) and d) explaining problem-solving techniques and cognitive good test–retest reliability (r 5 0.98) (Echebur ua, Baez, restructuring techniques to generate alternative functional Fernandez, & Paez, 1994). In our sample, internal consis- thoughts and feelings of wellbeing (including relaxation tency was adequate (a 5 0.79). procedures); and e) patients learning stimulus control 144 Journal of Behavioral Addictions 9 (2020) 1, 140-152 Figure 1. Flowchart/scheme with the CBT program in the study procedures [such as money management, self-exclusion long-term effectiveness in GD samples (S. Jimenez-Murcia (from both land-based and online gambling) and avoidance et al., 2017; Susana Jimenez-Murcia et al., 2007, 2016, 2015). of potential triggers]. Patients were also encouraged to ask a close relative (or significant other) to act as a co-therapist, to Procedure help them with all the relapse prevention techniques. Psychological measures were obtained by experienced psy- Prior to the CBT program, participants also received chologists with more than 15 years of clinical knowledge of column sheets to complete (daily completion is required). this disorder. Columnar sheets included the following topics: situations The data analyzed in this work correspond to a longi- where participants felt unwell (sad, anxious, irritable), be- tudinal design comprising the assessment before the start of haviors related to gambling, automatic thoughts, an objec- the CBT program, immediately following CBT, and monthly tive examination of those automatic thoughts (including during the 6 months period following the program. counterevidence), adaptive thoughts, and changes in feeling and behavior. Statistical analyses During the 16 treatment sessions, patients applied CBT techniques, completed the column sheets and held group Mplus8 for Windows was used to perform the study’s sta- discussions by exchanging questions and opinions regarding tistical analyses, which combined two different approaches: the progression of the therapy (mainly, they review the person-centered and variable-centered procedures. Person- column sheets, evaluate the cognitive restructuring tech- centered methods are typically used to identify groups of niques and discussed problem-solving techniques). The cli- individuals who share some specific attributes (characteris- nicians reviewed the column sheets providing contextual tics) and to address questions related to group similarities in explanations and advice on the column methods to complete patterns of development/courses. In contrast, variable- them during the following weeks. Participants also improved centered approaches are classical methodological procedures their understanding of the cognitive restructuring and used to describe the associations between variables and are problem-solution techniques by consulting with the CBT suited for addressing the relative contribution of the inde- clinician expert any doubts regarding response prevention pendent features (predictors) on the dependent outcomes techniques. A summary of the learned skills during CBT was (criteria). In this work, the person-centered approach was also given in each session. Within approximately four implemented through response trajectories analysis and was months the CBT program is completed. employed to determine if subgroups of patients exist based After the CBT program, and over the next 6 months, on the prospective dynamics of GD severity after the ther- follow-up sessions were held with the patients. The changes apeutic intervention and, in such cases, empirically catego- in the gambling behavior and in the whole psychological rizing the individuals into common classes. Next, after state, as well as the learned skills, were evaluated in the establishing the response trajectories, these empirical groups follow-up. (“latent classes”) were compared through variable-centered Figure 1 with the flowchart/scheme of the CBT program methods with the aim of assessing how sociodemographic in the study. Different studies have shown its short- and and clinical variables predict GD severity trajectories. Journal of Behavioral Addictions 9 (2020) 1, 140-152 145 Latent class growth analysis (LCGA) was employed to differences and Cohen’s h for proportion differences obtain the empirical GD response trajectories based on (h-coefficients were based on the arcsine transformations for gambling severity between post-treatment and 6 months after the proportions estimated in the groups). The effect size the final intervention. LCGA is a model included within was considered poor-low for jdj > 0.20, mild-moderate for growth-mixture-modeling (GMM) techniques, characterized jdj > 0.50 and large-high for jdj > 0.80 (the same boundary by fixing to zero the variance/covariance estimates within a limits were considered in interpreting h-coefficients) (Kelley class under the assumption that individuals grouped in the & Preacher, 2012). Increases in Type-I errors due to multiple class are homogeneous. Methods used in this study were statistical comparisons were controlled with Simes’ correc- conducted following GRoLTS guidelines (van de Schoot, tion method, a familywise error rate stepwise procedure that Sijbrandij, Winter, Depaoli, & Vermunt, 2017). The trajec- offers a more powerful test than the classical Bonferroni tories were estimated for the variable SOGS-total score correction (Simes, 1986). (considered in this research as a measure of gambling prob- lem severity) registered during the first 6 months after Ethics completion of the CBT program (seven measurements per participant were used for the grouping: the post-treatment The study procedures were carried out in accordance with assessment and the next 6 monthly post-evaluations). the Declaration of Helsinki. The University Hospital of Because of the strong association between the decreases in Bellvitge’s Ethics Committee of Clinical Research approved problem severity and the initial (baseline) state, the estima- the study (reference: PR241/11), and all patients provided tion procedure included baseline SOGS-total as a covariate. signed informed consent. The GMM was employed (TYPE 5 MIXTURE, in Mplus syntax), defining the robust maximum likelihood (MLR) estimator in the Analysis command (Enders & Bandalos, RESULTS 2001; Graham, 2009) and using Lo-Mendell-Rubin (Lo, Mendell, & Rubin, 2001) as a measure to determine the Table 1 contains the goodness-of-fit indexes for the candi- number of classes. The selection of the number of trajectories date models obtained in the LCGA, with a number of tra- was based on the following criteria (Nylund, Asparouhov, & jectories between 1 and 4 latent classes (trajectories). Muthen, 2007): a) the lowest Akaike information criterion Solution models for more than three classes were not (AIC), Bayesian information criterion (BIC), Lo-Mendell- considered due to the small group size to allow for subse- Rubin adjusted likelihood ratio test (LMR-LRT) and the quent statistical comparisons (the four-classes model defined bootstrapped likelihood ratio test (BLRT) indexes for the a group with only two participants). model (compared with other solutions); b) entropy (measure The final model selected was the three-trajectory solution of the model’s discriminative capacity, that is, its ability to (Fig. 2 shows the line graph with the shapes for the SOGS identify individuals following the different trajectories) above evolution from the pre-therapy measure to the 6-month 0.80; c) high on-diagonal average values (around 0.80) in the follow-up after the CBT). This model yielded lower AIC-BIC matrix containing the probabilities of membership (that is, indexes than the two-trajectory solution (AIC 5 4159.5, high average latent class probabilities for most likely latent BIC 5 4247.4 and adjusted sample-size BIC 5 4161.9), good class membership by latent class); d) no less than 5% of entropy (0.846), very high on-diagonal values in the matrix participants in a class/trajectory (to allow statistical com- with the average latent class probabilities (0.951, 0.898, and parisons); and e) adequate clinical interpretability. The esti- 0.944 for trajectories T1, T2, and T3), and good clinical mation procedure was defined for a linear growth model interpretability. based on the principle of parsimony (other alternative, more Table 2 includes the comparison between trajectories for complex quadratic and cubic components were tested and the variables analyzed in this study (sociodemographic rejected since these other potential solutions did not provide variables are reported in the upper part of the table, baseline substantively better statistical adjustment and/or models with state in the middle portion and the risk of relapse during the better clinical interpretation). CBT in the lower part). Trajectory T1 (n 5 118, 61.5%) Comparison between the empirical latent classes (the included patients with severe GD level at baseline (mean response trajectories in this work) was based on chi-square SOGS 5 12.5) and good evolution to recovery (mean tests for categorical variables (Fisher-exact tests were used SOGS 5 2.6 at post-therapy and 2.4 at the end of the for comparisons with cells with low expected frequencies, follow-up). eij < 5) and analysis of variance (ANOVA) for quantitative Trajectory T2 (n 5 62, 32.3%) represented patients with variables. Variables compared included measures at baseline moderate-high GD affectation at baseline (mean SOGS 5 8.7) (chronological age, age of onset of the gambling, duration of and good evolution to recovery (mean SOGS 5 2.1 at the end the gambling, DSM-5 criteria for GD, SOGS total score, of the therapy and 2.3 at the end of the study). The pro- psychopathological state and personality traits) as well as the gression of the gambling severity for this response trajectory is presence of relapses during the CBT (relapse was defined as quite similar to trajectory T1, and no statistical differences the presence of any gambling episode during which the between T1 and T2 emerged comparing sociodemographics, patients make some kind of bet). The effect size for pairwise chronological age and age of onset of the gambling problems. comparisons was calculated with Cohen’s d for mean However, compared to T1, participants grouped in T2 146 Journal of Behavioral Addictions 9 (2020) 1, 140-152 Table 1. Goodness-of-fit indexes for the LCGA candidate solutions Fit indexes Count-size d Model On-d. e a b c #Traj. Akaike AIC Bayes BIC Adj. BIC LMR-LRT Boost.BLRT Entropy n % post.prob. 1-Tr 4397.8 4446.6 4399.1 – – 1.00 T1 192 100% 1.000 2-Tr 4231.6 4300.0 4233.5 172.7 2183.9 0.954 T1 179 93.2% 0.994 (0.073) (<0.001) T2 13 6.8% 0.935 3-Tr 4159.5 4247.4 4161.9 81.53 2094.8 0.846 T1 118 61.5% 0.951 (0.067) (<0.001) T2 62 32.3% 0.898 T3 12 6.3% 0.944 4-Tr 4063.9 4171.4 4066.8 80.76 2040.2 0.802 T1 117 60.9% 0.931 (0.064) (<0.001) T2 57 29.8% 0.894 T3 16 8.3% 0.872 T4 2 1.0% 0.999 a Sample-size adjusted BIC. b Lo-Mendell-Rubin adjusted likelihood ratio test: test value (significance, P-value). c Bootstrapped likelihood ratio test (BLRT): Log-likelihood value (significance, P-value). d On-diagonal posterior average values in the matrix containing the probability of membership. e Number of trajectories. Figure 2. Response trajectories: from pretreatment to 6-month follow-up after therapy (n 5 192) registered lower values in novelty seeking and harm avoid- gambling episode with bets) during the therapy (33.3% ance, higher scores in persistence, self-directedness and versus 16.1% registered for T1 and 14.5% for T2). cooperativeness, more functional psychopathological state (lower SCL-90R GSI score), lower GD severity at pre-treat- ment and lower evolution of the gambling problems prior to the therapy. DISCUSSION Trajectory T3 (n 5 12, 6.3%) represented patients with severe GD affectation at baseline (mean SOGS 5 11.8) and The main objective of the study was to identify empirical poor evolution after the CBT (mean SOGS 5 6.5 at post- response trajectories for GD severity during the 6-month therapy and 13.0 at 6-month follow-up after the treatment). follow-up after CBT in young and young-adult patients Based on the descriptive estimations, this trajectory included through LCGA. Three trajectories emerged, two of them participants with the worst psychopathological state at the comprising patients with moderate to severe GD affectation beginning of the study (although no significant difference at baseline and good evolution to recovery (T1 and T2 was found between T1 and T3 in the SCL-90R GSI), the included the largest number of patients, n 5 250, 93.7% of highest harm avoidance levels and the lowest self-directed- the whole sample) and one containing patients with severe ness scores. This trajectory also included a high proportion baseline GD severity and poor CBT outcome (T3 included of participants in the low education levels and low socio- n 5 12, 6.3% of the sample). The goodness of fit and the economic status groups, and it registered the highest risk of clinical interpretability of the results constitute evidence relapses (calculated as the probability of occurrence of any about the reliability and validity of the response trajectories. Journal of Behavioral Addictions 9 (2020) 1, 140-152 Table 2. Comparison between empirical response trajectories Total T1 T2 T3 Global comparison Pairwise comparisons N 5 192 n 5 118 n 5 62 n 5 12 (Factor group) T1vsT2 T1vsT3 T2vsT3 a Sociodemographics n % n % n % n % c 2 (df) P P jhj P jhj P jhj Marital status Single 112 58.3% 70 59.3% 34 54.8% 8 66.7% 1.99 (4) 0.738 0.600 0.09 0.537 0.15 0.664 0.24 Married-partner 71 37.0% 44 37.3% 24 38.7% 3 25.0% 0.03 0.27 0.30 Separated-divorce 9 4.7% 4 3.4% 4 6.5% 1 8.3% 0.14 0.21 0.07 Education Primary 83 43.2% 47 39.8% 29 46.8% 7 58.3% 3.39(4) 0.080 0.458 0.14 0.333 0.38 0.621 0.23 Secondary 95 49.5% 60 50.8% 30 48.4% 5 41.7% 0.05 0.18 0.14 University 14 7.3% 11 9.3% 3 4.8% 0 0.0% 0.18 0.51† 0.32 Social Mean-high þ high 17 8.9% 11 9.3% 6 9.7% 0 0.0% 3.94(6) 0.214 0.656 0.01 0.488 0.51† 0.575 0.51† Mean 29 15.1% 21 17.8% 7 11.3% 1 8.3% 0.19 0.28 0.10 Mean-low 78 40.6% 45 38.1% 28 45.2% 5 41.7% 0.14 0.07 0.07 Low 68 35.4% 41 34.7% 21 33.9% 6 50.0% 0.02 0.31 0.33 Laboral status Unemployed 47 24.5% 28 23.7% 16 25.8% 3 25.0% 0.10(2) 0.953 0.758 0.05 0.922 0.03 0.953 0.02 Baseline state Mean SD Mean SD Mean SD Mean SD F(df) P P jdj P jdj P jdj Age (years) 29.68 4.07 29.97 3.85 29.10 4.34 29.83 4.82 0.94(2;189) 0.394 0.175 0.21 0.914 0.03 0.567 0.16 Age onset (years) 21.10 4.70 20.70 4.36 21.77 5.04 21.62 6.05 1.06(2;189) 0.349 0.141 0.23 0.501 0.18 0.937 0.03 Duration (years) 9.78 5.30 10.48 5.23 8.54 5.22 9.18 5.67 2.66(2;189) 0.073 0.024* 0.37 0.436 0.24 0.712 0.12 DSM-5 total criteria 0.75 7.14 1.63 8.04 0.85 5.23 1.14 8.17 0.83 185.3(2;189) <0.001* <0.001* 2.80† 0.667 0.15 <0.001* 2.95† SOGS-total score 0.79 11.27 2.98 12.58 2.41 8.70 2.38 11.67 2.12 52.8(2;189)6 <0.001* <0.001* 1.62† 0.270 0.40 0.001* 1.31† Psychopology SCL-90R: GSI 0.97 0.87 0.55 0.99 0.56 0.57 0.39 1.21 0.66 15.5 <0.001* <0.001* 0.88† 0.219 0.36 0.001* 1.18† Personality (TCI-R) Mean SD Mean SD Mean SD Mean SD F(df) P P jdj P jdj P jdj Novelty seeking 0.72 112.4 13.8 115.1 14.2 106.9 11.6 113.3 12.5 7.56(2;189) 0.001* <0.001* 0.63† 0.658 0.13 0.129 0.53† Harm avoidance 0.83 97.3 16.9 98.2 16.7 93.2 16.4 109.3 15.1 5.20(2;189) 0.006* 0.047* 0.30 0.028* 0.70† 0.002* 1.02† Reward dependence 0.78 98.7 14.3 97.7 14.4 100.9 13.9 97.8 15.6 1.01(2;189) 0.364 0.161 0.23 0.969 0.01 0.503 0.21 Persistence 0.88 109.9 19.7 108.2 20.9 114.1 16.2 105.2 21.9 2.13(2;189) 0.121 0.050* 0.31 0.606 0.14 0.152 0.56† Self-directedness 0.86 128.4 20.5 124.5 19.3 139.5 18.8 111.1 13.4 17.93(2;189) <0.001* <0.001* 0.79† 0.020* 0.80† <0.001* 1.74† Cooperativeness 0.81 130.4 15.5 128.0 15.5 136.4 13.7 123.7 15.9 7.47(2;189) 0.001* 0.001 0.57† 0.341 0.28 0.008* 0.86† Self-transcendence 0.80 59.9 12.9 59.5 12.9 59.6 12.7 65.6 13.5 1.23(2;189) 0.293 0.986 0.00 0.123 0.45 0.142 0.46 During CBT n % n % n % n % c2(df) P P jhj P jhj P jhj a Risk of relapses 32 16.7% 19 16.1% 9 14.5% 4 33.3% 2.63(2) 0.268 0.780 0.04 0.138 0.52† 0.117 0.51† SD5 standard deviation; a5 Cronbach’s alpha in the sample; df5 degrees of freedom. *Significant comparison (0.05 level). †Bold: effect size in the mild-moderate range (jdj > 0.50 or jhj > 0.50) to high-large range (jdj > 0.80 or jhj > 0.80). a Relapse was considered for the presence of any gambling episode during which the patients make some kind of bet. 147 148 Journal of Behavioral Addictions 9 (2020) 1, 140-152 The second objective of this work was to identify vari- harm avoidance and low self-directedness) are also the ables with the capacity to differentiate between the empirical most predictive of treatment outcomes (the other five trajectories, since this finding also provides evidence about personality traits relate only slightly or not at all to therapy the reliability and validity of the latent classes. Our results results) (Bajraktarov et al., 2017). These results, however, show that during young adulthood, socioeconomic position, must be interpreted with caution, since while self-stigma GD severity at baseline, psychopathological state, and spe- has been widely researched for many mental health con- cific personality traits achieved discriminative capacity to ditions (Livingston & Boyd, 2010), few studies have differentiate between GD response trajectories during the analyzed correlates for self-stigma in the problem next 6 months after the therapy. As a whole, our results are gambling area. Available research suggests that fears consistent with previous studies, which found that worse related to the gambling activity, feelings of shame, guilt, recovery after CBT was related to low education levels, low weakness and embarrassment of being perceived as a socioeconomic status, higher gambling symptom severity, or “problem gambler” could lead to GD patients to keep their emotional distress (Dunn et al., 2012). These variables activity a secret, avoiding disclosure and considering the related to the resistance to the CBT programs have also been results of their behavior as low-efficient (Hing & Russell, previously related to a higher risk of relapses (Challet-Bouju 2017), which together can lead to an increase in self-stigma. et al., 2017; Smith et al., 2015), which was also a variable One would hypothesize that patients with high scores in the with discriminative capacity on the empirical trajectories. temperament trait of harm-avoidance should be characterized In our study, the personality profile defining the worst by excessive worrying, shyness in social contact, fears, and response trajectory to CBT was characterized by high tendency toward pessimism, which can be directly connected harm avoidance and low self-directedness. This profile with a predisposition to psychiatric illness (including GD) would be suggestive of patients with excessive worrying, and the consequent higher levels of stigmatization. Low levels marked tendencies toward pessimism and apprehension, of self-directedness would be characteristic of patients with a drive to react to current circumstances and immediate low ability to regulate and adapt their behavior to the re- needs, clear lack of self-direction in targets and objectives, quirements of the situation and with difficulties in self- ineffectiveness in solving problems, usually with feelings of acceptance, and this profile is also highly vulnerable to general dissatisfaction and low levels of motivation. These developing mental illness and higher self-stigma. characteristics have been typically found in subjects more Finally, the results of our study outlining the predictive prone to developing increased anxiety and depression capacity of high GD and psychopathological state at baseline during their lives (Bajraktarov, Gudeva-Nikovska, Manu- on the worst therapeutic trajectory are also consistent with ševa, & Arsova, 2017; Kampman, Viikki, J€arventausta, & empirical evidence reported in the literature. For example, the Leinonen, 2014). Moreover, this specific personality profile study by Merkouris and colleagues found that low levels of has been described in most dysfunctional impulsivity- gambling problems, accompanied by low depression scores related disorders as well (Claes et al., 2012; del Pino- and low scores in novelty seeking, were the baseline factors Gutierrez et al., 2017), and, in general, these traits have most strongly related to better outcome at post-therapy and been considered as powerful predictors of the maintenance follow-up (Merkouris et al., 2016). The research published by and continuation of dysfunctional behaviors despite Maniaci and colleagues also outlines that gambling severity therapeutic interventions (Ociskova, Prasko, Latalova, and high comorbidity were significant predictors of poor early Kamaradova, & Grambal, 2016). It has been hypothesized therapeutic outcomes (Maniaci et al., 2017). that this persistence in behaviors related to high harm avoidance and low self-directedness is due to the patients’ reluctance to deal with stressful situations and their Limitations and strengths affectation in self-perceived wellness and happiness There are three main research limitations in this study that (C. Robert Cloninger & Zohar, 2011). In other words, it could impact the empirical evidence and results. First, since would be individuals with difficulties in dealing with their data correspond to a short-term follow-up time after the negative emotional states who would self-regulate in a therapy (6 months), the response trajectories could be non- dysfunctional way through strategies of avoidance and representative for a longer period (there is no way of guar- escape, such as gambling. Our results related to the rele- anteeing that the empirical classes will persist over time). vance of personality traits in defining response trajectories Second, all the patients who completed the CBT and fulfilled for GD are in line with those of the few follow-up studies the inclusion criteria were included in the statistical analysis, examining the long-term effects of treatment programs on regardless of the presence of dropouts during the follow-up such patients, which found the relevance of personality (the risk of dropping out was 28.6% in the study, which traits for predicting abstinence at six-month and one-year represents a risk consistent with studies in the gambling area). follow-ups (M€ uller et al., 2017; Ramos-Grille, Goma-i- It must be argued, however, that completers and dropouts did Freixanet, Aragay, Valero, & Valles, 2013). Finally, some not achieve statistical differences in the baseline (sociodemo- studies exploring the association between therapeutic graphic and clinical state) and that the procedure used in this outcomes and personality traits from Cloninger’s bio- study to identify the response trajectories (LCGA in Mplus-8) psychosocial model of personality have concluded that the uses a full information method, which does not replace or two traits most significantly connected to self-stigma (high impute missing data, but which instead handles incomplete Journal of Behavioral Addictions 9 (2020) 1, 140-152 149 information within the analysis using all the available infor- clinical dynamics states. In contrast, person-centered ap- mation in the data set (this procedure has shown good reli- proaches (such as the identification of response trajectories) ability/validity in producing unbiased parameter estimates for start from the grouping of individuals according to their own missing data in these types of modeling [which usually treat responses (in our study, the evolution of gambling problem longitudinal data with a relatively high percentage of missing severity) and focus attention on the intra-individual structure values]). Third, one of the empirical trajectories included only of variables (the individual is conceived as a whole and not as n 5 12 participants, which affects the statistical power to the sum of isolated features). The use of LCGA is common in assess its potential predictive factors. It must be considered, some medical areas, for example, in pediatric studies, which however, that one of the characteristics of the LCGA is its analyze longitudinal data series with the aim of describing capacity to identify even groups of patients who represent courses of children’s functioning based on specific childhood rare/infrequent clinical conditions with adequate reliability/ outcomes (usually named “developmental trajectories”). The validity. In this study, the three-class model achieved adequate results obtained in these studies provide therapists and families goodness of fit, and the emergence of this trajectory should be with robust resources to evaluate the clinical deviation of a considered of high clinical relevance since it grouped patients child’s performance/behavior based on the distance observed in with the worst longitudinal recovery. To allow the identifica- relation to other children of similar ages and/or functional tion of the potential variables explaining the recovery trajec- ability levels. With the increase in the number and scope of tories, this study includes both significance tests and longitudinal research studies, the number of strategies for standardized measures of the effect size that are independent analyzing prospective data has also expanded, and various of the sample sizes (Cohen’s-d and Cohen’s-h coefficients). medical areas now employ longitudinal analytical techniques Fourth, the results can be generalized only to GD men: women such as LCGA. Nonetheless, to our knowledge, few studies have were not considered in this study because the low sample size addressed the study of GD based on the identification of of gambling disordered females in our treatment unit and the response/course trajectories, and the published research differences in the CBT programs (depending on the patients’ employing these techniques has examined the natural history of sex) could become a source of bias leading to incorrect results untreated problem gamblers, largely at young ages. Therefore, and conclusions. Fifth, the lack of a control group in this work gambling severity trajectories obtained in this study should be does not allow attributing the empirical trajectories of the considered as being well suited for addressing questions that LCGA to reliable phenotypes/responses to the CBT program. concern individual differences in clinical profiles, their Control groups are needed for discriminating between treat- response trajectories and their correlates. These results also put ment outcomes from other factors, such as the natural history forward future lines of research on gambling progression after of a disease or even the researchers’ or patients’ expectations. It therapeutic clinical interventions and about the risk factors for must be stated that a no-treatment group was not ethically poor response to therapy in young and young-adult gambling reasonable in our work because adequate care for GD has been samples. well clinically established for CBT and potential alternatives (such as waiting-lists) were not possible in our treatment unit. Finally, the comparison between the empirical trajectories was CONCLUSIONS performed for a limited number of measures. Although this study includes all the variables available in the complete Our results have implications in both the measurement and sample, considering more characteristics informing on other the intervention areas. The patient profile most strongly gambling related variables (such as the neuropsychological related to poor treatment trajectory in our study includes functioning and additional features of gambling beyond gambling severity and higher general psychopathology at severity) would have been relevant to provide a complete baseline, as well as harm avoidance and self-directedness picture of the empirical classes. traits. Effectiveness measurement and managing of these Strengths of this study include the analysis of longitudinal features could prevent therapy resistance and thereby help data (from baseline to 6-month follow-up after therapy) in a prevent individuals from entering the vicious circle of large sample of young and young-adult GD patients. Strength of chronic gambling, suffering, and disability. this work is its statistical methodological approach, which combines person-centered and variable-level techniques. Traditionally, the study of the effectiveness of the therapeutic Funding: We thank the CERCA Programme/Generalitat de plans to treat GD has been focused on variable-centered Catalunya for institutional support. This manuscript and methods, focused on exploring and describing the relationships research were supported by grants from the Ministerio between the potential predictors and the therapeutic outcomes, de Economía y Competitividad (PSI2015-68701-R). The and which have the distinctive feature of considering the pa- research was funded by the Delegacion del Gobierno para el tients as a group, isolating the significant clinical features in Plan Nacional sobre Drogas (2017I067 and 2019I47), Insti- which individuals differ (these methods operate based on the tuto de Salud Carlos III (ISCIII) (FIS PI14/00290 and PI17/ analysis of the potential correlational structure of the variables, 01167) and co-funded by FEDER funds/European Regional their stability over time, and their predictive capacity for pre- Development Fund (ERDF), a way to build Europe. determined criteria). Therefore, variable-level approaches do CIBERobn and CIBERSAM are both initiatives of ISCIII. The not provide information on person-specific (intra-individual) study received the support of the Secretariat for Universities 150 Journal of Behavioral Addictions 9 (2020) 1, 140-152 and Research of the Ministry of Business and Knowledge of Blaszczynski, A., & Nower, L. 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