Emotional regulation in eating disorders and gambling disorder: A transdiagnostic approach LUCERO MUNGUIA1,2, SUSANA JIMENEZ-MURCIA  1,2,3p , 3,4 1,3 ROSER GRANERO , ISABEL BAENAS , ZAIDA AGUERA , € 1,2,5 Journal of Behavioral  ISABEL SANCHEZ 1,3 , ESTER CODINA1, Addictions  AMPARO DEL PINO-GUTIERREZ 1,3,5 , GIULIA TESTA1,3, 10 (2021) 3, 508–523 JANET TREASURE6 and  FERNANDO FERNANDEZ-ARANDA 1,2,3p Special Section on Overweight, obesity and 1 eating disorders in Department of Psychiatry, Bellvitge University Hospital-IDIBELL, 08907 Barcelona, Spain 2 relation to addiction Department of Clinical Sciences, School of Medicine, University of Barcelona, 08907 Barcelona, Spain 3 DOI: Ciber Physiopathology, Obesity and Nutrition (CIBERObn), Instituto de Salud Carlos III, 08907 10.1556/2006.2021.00017 Barcelona, Spain © 2021 The Author(s) 4 Department of Psychobiology and Methodology of Health Sciences, Universitat Aut onoma de Barcelona, 08193 Barcelona, Spain 5 Department of Public Health, Mental Health and Maternal-Child Nursing, School of Nursing, University of Barcelona, 08907 Barcelona, Spain 6 Section of Eating Disorders, Department of Psychological Medicine, Institute of Psychiatry, FULL-LENGTH REPORT Psychology and Neuroscience, King’s College London, London, UK Received: November 6, 2020 • Revised manuscript received: January 4, 2021; February 5, 2021 • Accepted: February 22, 2021 Published online: March 13, 2021 ABSTRACT Background and aims: Difficulties in Emotion Regulation (ER) are related to the etiology and main- tenance of several psychological disorders, including Eating Disorders (ED) and Gambling Disorder (GD). This study explored the existence of latent empirical groups between both disorders, based on ER difficulties and considering a set of indicators of personality traits, the severity of the disorder, and psychopathological distress. Methods: The sample included 1,288 female and male participants, diag- nosed with ED (n 5 906) and GD (n 5 382). Two-step clustering was used for the empirical classi- fication, while analysis of variance and chi-square tests were used for the comparison between the latent groups. Results: Three empirical groups were identified, from the most disturbed ER profile (Subgroup 1) to the most functional (Subgroup 3). The ER state showed a linear relationship with the severity of each disorder and the psychopathological state. Different personality traits were found to be related to the level of emotion dysregulation. Discussion and conclusion: In this study, three distinct empirical groups based on ER were identified across ED and GD, suggesting that ER is a transdiagnostic construct. These findings may lead to the development of common treatment strategies and more tailored approaches. KEYWORDS eating disorders, gambling disorders, emotion regulation, transdiagnostic p Corresponding authors. E-mail: ffernandez@bellvitgehospital. cat E-mail: sjimenez@bellvitgehospital.cat INTRODUCTION Over the years, the study of mental and behavioral disorders has evolved from a categorical diagnostic approach to a dimensional one. For it organization, The International Classifi- cation of Diseases 11th Revision (ICD-11) has deepened in shared etiological and Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 509 phenomenological factors among disorders (Reed et al., et al., 2012; Del Pino-Gutierrez et al., 2017; Jimenez-Murcia 2019). Incorporating the description of clinical features that et al., 2015; Kim, von Ranson, Hodgins, McGrath, & are not diagnostically determinative but are frequently Tavares, 2018; Lesieur & Blume, 1993). However, no associated with the disorders helps to recognize their vari- research has directly addressed the hypothesis of whether ER ations across disorders (First, Reed, Hyman, & Saxena, could be a transdiagnostic construct between these condi- 2015). This has reopened the discussion regarding whether tions, considering jointly clinical samples of both disorders. large clusters of diagnoses can be identified by shared GD is considered to be a mental disorder characterized external validating factors rather than by symptom pictures by recurrent gambling behaviors that become persistent over alone (Andrews et al., 2009). time, despite their negative consequences (American Psy- Emotion Regulation (ER) has been defined as a set of chiatric Association, 2013). Gambling activities may be strategies that are used to manage and modulate an affective divided into Strategic, where the gambler can use knowledge experience (Gratz, Weiss, & Tull, 2015; Gross, 2015), of the game to influence or predict the outcome, and Non- including awareness, acceptance and clarity of emotions, and Strategic, which implies little or no possibility of influencing access to effective goal-directed behaviors (Gratz & Roemer, the outcome (Potenza et al., 2001; Potenza, Steinberg, 2004). Conversely, emotion dysregulation includes the McLaughlin, Rounsaville, & O'Malley, 2000). Among ED, frequent use of maladaptive strategies, such as avoidance anorexia nervosa (AN) and bulimia nervosa (BN) are and suppression (Sloan et al., 2017). characterized by the overvaluation of weight and shape and ER and dysfunctional emotional processing are related to extreme weight control behaviors (e.g., self-starvation in AN the etiology and maintenance of several psychological dis- and a cycle of binge eating and purging in BN). Binge Eating orders, including eating disorders (ED) (Brockmeyer et al., Disorder (BED) implies recurrent binge eating without 2014; Henderson, Fox, Trayner, & Wittkowski, 2019; compensatory weight loss behaviors. Patients whose prob- Kanakam, Krug, Raoult, Collier, & Treasure, 2013; Wolz lems are less well conceptualized receive the diagnosis of et al., 2015), gambling disorder (GD) (Estevez et al., 2020; Other Specified Feeding or Eating Disorder (OSFED) Granero et al., 2018; Sancho et al., 2019; Williams, Grisham, (American Psychiatric Association, 2013). Erskine, & Cassedy, 2012), borderline personality disorder Dysfunctional emotional processing in AN includes (Cackowski et al., 2014; Van Zutphen et al., 2018), anxiety rumination and avoidance and lack of emotional awareness (Cisler & Olatunji, 2012), depression (Joormann & Stanton, (Aldao et al., 2010; Monell, Clinton, & Birgeg ard, 2018; 2016), compulsive buying disorder (Estevez et al., 2020), and Kolar et al., 2019). In contrast, in patients with externalizing other behavioral addictions (Estevez, Jauregui, Sanchez- disorders such as BN or BED, compulsive binge episodes or Marcos, L opez-Gonzalez, & Griffiths, 2017). Improvements excessive exercise are frequently adopted as maladaptive in ER are associated with a reduction in psychopathological strategies to cope with negative emotions (Engel et al., 2013). symptoms (Axelrod et al., 2011; Gratz et al., 2015; Khakpoor In a similar way, pathological gamblers often report using et al., 2019; Mallorquı-Bague et al., 2018; Neacsiu et al., 2014; gambling to escape from negative mood states (Blaszczynski Sloan et al., 2017) and a better therapy outcome (Oldershaw & McConaghy, 1989; Getty, Watson, & Frisch, 2000). et al., 2018; Mallorquı-Bague et al., 2018; Norton & Paulus, Dysfunctional ER is associated with a higher severity of 2016). eating disorders (Claes et al., 2012; Rodrıguez-Cano, Beato- These studies suggest that ER could be an underlying Fernandez, Rojo-Moreno, & Vaz-Leal, 2014; Wolz et al., transdiagnostic trait and behavioral endophenotype across 2015) and a poor response to therapy in patients with GD or different disorders (Kanakam et al., 2013; Sloan et al., 2017). ED (Bodell et al., 2019; Mallorquı-Bague et al., 2018; Steward However, to date, no studies have jointly evaluated a clinical et al., 2020). population of different entities with the aim of finding The neural networks involved in dysfunctional possible sub-empirical groups based on ER difficulties in emotional processing have been extensively described order to clarify whether emotional regulation can be regar- (Brandl, Le Houcq Corbi, Mulej Bratec, & Sorg, 2019; Liu, ded as a transdiagnostic construct. Peeters, Fernandez, & Kohn, 2020; Raschle et al., 2019; Emotion dysregulation has been hypothesized to be a Kucharska et al., 2019), with increasing evidence showing common risk trait for externalizing disorders such as ED, similar neurobiological features (Mallorquı-Bague et al., Substance Use Disorders (SUD), and addictive behaviors 2020; Navas et al., 2017; Steward et al., 2019, 2020) and such as GD, being suggested that the performance of the reward processing (Balodis et al., 2012, 2013) between ED disorder-related behaviors could be used to cope with and GD although, there are no studies directly comparing negative emotional states (Aldao, Nolen-Hoeksema, & the two populations. Schweizer, 2010; Estevez et al., 2017; Kassel, Veilleux, Heinz, Similar personality traits are related to problems in ER in Braun, & Conrad, 2013; Leehr et al., 2015). both disorders. In ED high harm avoidance, impulsivity, and Among these conditions, ED and GD have been studied low self-directedness are common (Ag€ uera et al., 2019; together due to the prevalence of comorbidity between them Atiye, Miettunen, & Raevuori-Helkamaa, 2015; Mikhail & (Jimenez-Murcia et al., 2013; Von Ranson, Wallace, Holub, Kring, 2019; Wolz et al., 2015). High novelty seeking and a & Hodgins, 2013) and their commonalities, considering lack of emotional control and planning are associated with psychological and neurobiological characteristics, personal- maladaptive emotion expression (e.g., anger expression and  ity traits, and ER processes (Alvarez-Moya et al., 2007; Claes lack of anger control) in GD and ED, particularly the binge- Unauthenticated | Downloaded 11/25/22 04:08 PM UTC 510 Journal of Behavioral Addictions 10 (2021) 3, 508–523 purging subtypes of ED (e.g., BN or BED) (Aymamı et al., consists of six subscales: Non-acceptance of emotional re- 2014; Maniaci et al., 2017; Tarrega et al., 2015), as well as sponses, difficulties engaging in goal-directed behavior when with emotional dysregulation (Pettorruso et al., 2020). having strong emotions, impulse-control difficulties, lack of Despite what has been mentioned above, there is a lack emotional awareness, limited access to emotional regulation of research directly investigating a transdiagnostic approach strategies, and lack of emotional clarity. Participants are regarding ER in both disorders. Transdiagnostic approaches asked to respond to each item using a five-point Likert scale in mental health that include the identification of different ranging from 1 (almost never) to 5 (almost always). Higher phenomenological constructs, such as ER, in order to scores indicate greater problems with ER. The internal identify clinical phenotypes could complement and deepen consistency of the DERS total score in our sample was diagnosis, prediction, and treatment research (Nelson, excellent (a 5 0.94) and, for the first-order subscales, it McGorry, & Fernandez, 2020; Shah et al., 2020). ranged between a 5 0.76 (for limited access to emotional Therefore, the aim of the present study was to explore in regulation strategies) to a 5 0.91 (impulse-control diffi- a large clinical sample of patients with ED and GD to culties). determine whether specific clusters based on ER difficulties, Temperament and Character Inventory–Revised (TCI-R). personality traits, disorder severity, and general psychopa- (Cloninger, 1999), which is a 240-item questionnaire with a thology could be identified. From the pre-existing literature five-point Likert scale format. It measures four tempera- (Kanakam et al., 2013; Sloan et al., 2017), we hypothesized ments (harm avoidance, novelty seeking, reward depen- that it would be possible to identify different clinical groups dence, and persistence) and three character dimensions defined by the degree of ER difficulties, and that these would (self-directedness, cooperativeness, and self-transcendence). be related to the severity of the disorder symptomatology, This questionnaire has been validated in a Spanish adult general psychopathology, and personality traits. Identifica- population (Gutierrez-Zotes et al., 2004). The Cronbach’s tion of similar specific phenotypes in two related disorders alpha for the different scales in the current sample ranged would validate a transdiagnostic construct that might have from a 5 0.79 (for novelty seeking) to a 5 0.90 (for harm implications for common treatment approaches in both avoidance). disorders. To the best of our knowledge, this is the first study Symptom Checklist-90 Items-Revised (SCL-90-R). (Dero- to investigate if ER is a transdiagnostic construct across gatis, 1994), which is a 90-item questionnaire used for these disorders, considering the joint evaluation of different assessing self-reported psychological distress and psycho- clinical samples, which may fill a gap in the pre-existing pathology. It evaluates nine primary symptom dimensions: literature. Somatization, obsessive-compulsive, interpersonal sensi- tivity, depression, anxiety, hostility, phobic anxiety, paranoid ideation, and psychoticism, as well as three global indices: MATERIALS AND METHODS Global Severity Index (GSI), Positive Symptom Total (PST), and Positive Symptom Distress Index (PSDI). This instru- Participants ment has been validated in a Spanish population (Derogatis, 2002). The internal consistency of the subscales in our The sample consisted of 1,288 participants with ED (n 5 sample ranged from a 5 0.78 (for paranoid) to a 5 0.98 (for 906) and GD (n 5 382) diagnoses, 584 females (n 5 44 with the global indexes). GD and n 5 810 with ED) and 434 males (n 5 338 with GD Eating Disorder Inventory-2 (EDI-2), which is a 91-item and n 5 96 with ED). The diagnostic distribution for ED multidimensional self-report questionnaire that assesses was 172 participants with AN, 280 with BN, 129 with BED, psychological and behavioral characteristics relevant to and 325 with OSFED; meanwhile, the distribution for GD eating disorders. The questionnaire consists of 11 subscales, was 212 participants with Non-Strategic gambling only answered on a six-point Likert scale: Drive for thinness, (Non-Strategic), 93 with Strategic gambling only (Strategic), body dissatisfaction, bulimia, ineffectiveness, perfectionism, and 77 participants with both Non-Strategic and Strategic interpersonal distrust, interoceptive awareness, maturity gambling (Both). All participants included in the study were fears, asceticism, impulse regulation, and social insecurity. diagnosed according to the Diagnostic and Statistical This instrument have been validated in a Spanish population Manual of Mental Disorders, Fifth Edition (DSM-5) criteria (Garner, 1998). The internal consistency of the EDI-2 total (American Psychiatric Association, 2013), and consecutively score in our sample was a 5 0.95. referred for assessment and treatment between April 2014 South Oaks Gambling Severity Screen (SOGS-GD). and July 2019. (Lesieur & Blume, 1987), which is a 20-item self-report scale for screening current problem gambling severity during the Assessment last 12 months, and has been validated for a Spanish pop- The assessment included a specific sociodemographic ulation (Echebur ua, Baez, Fernandez, & Paez, 1994). The questionnaire and the following instruments. scale’s internal consistency in our study sample was a 5 Difficulties in Emotion Regulation Strategies (DERS). 0.74. (Gratz & Roemer, 2004), which is a 36-item scale used for Diagnostic Questionnaire for Pathological Gambling the evaluation of emotion dysregulation that has been vali- (According to the DSM Criteria). (Stinchfield, 2003), which is dated in a Spanish population (Wolz et al., 2015). The DERS a self-report questionnaire that identifies the presence of GD Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 511 through 19 items that measure the DSM criteria for the Procedure and ethics DSM-IV-TR (American Psychiatric Association, 2010) and the DSM-5 (American Psychiatric Association, 2013) ver- All participants in our sample voluntarily sought treatment sions. The questionnaire has been validated in a Spanish for GD and ED and were diagnosed according to the DSM-5 population (Jimenez-Murcia et al., 2009). The internal criteria (American Psychiatric Association, 2013) by clinical consistency for this scale in our study sample was a 5 0.78. psychologists and psychiatrists with more than 15 years of Other socioeconomic measures. Additional information experience in the field of behavioral addictions and eating was collected through a semi-structured interview with the disorders. They conducted two face-to-face clinical in- clinicians. This interview included sex, age, and education terviews, before and after a psychometric evaluation. The level. The Hollingshead survey was also completed to first appointment consisted of a clinical interview, and in the calculate the socioeconomic position index, based on the subsequent visit, the results of the tests and information retired/employed status, educational attainment, and occu- about the treatment according to their clinical profile were pational position (Hollingshead, 2011). shared. The psychometric evaluation was based on specific pencil and paper tests and self-reports. The patients included in this study did not receive any kind of compensation for their participation. STATISTICAL ANALYSIS According to the Declaration of Helsinki, the present study was approved by the appropriate research committee. The analysis was carried out using SPSS24 for windows Written and signed informed consent was obtained from all (IBM Corp., 2016). The clustering two-step analysis proce- participants. dure, an exploratory method to identify natural latent groupings within a dataset of continuous and categorical Ethics features, based on the agglomerative hierarchical clustering According to the Declaration of Helsinki, the present study method and assuming a joint multinomial-normal distri- was approved by the Clinical Research Ethics Committee bution was used. This analysis produces an automatic (CEIC) of Bellvitge University Hospital, and written and determination of the optimal number of latent groups, and signed informed consent was obtained from all participants. in this study, the log-likelihood distance and the Schwarz Bayesian Information Criterion (BIC) was used. The set of indicator variables for the clustering procedure carried out included the emotional regulation profile (DERS scores), the RESULTS severity of the disorder (measured with the EDI-2 total for ED and the number of DSM-5 criteria for GD), personality Characteristics of the sample traits (TCI-R scores), and global psychological distress (SCL- Within the GD subsample, most participants were men (n 5 90R GSI). The cluster quality for the final model was esti- 338, 88.5%), whereas in ED most were women (n 5 810, mated with the Silhouette index, which constitutes a global 89.4%). The mean age of the GD patients was higher than consistency measure of the cohesion/separation (Rousseeuw, that of the ED patients [40.5 years (SD 5 13.4) for GD and 1987). Silhouette values fall within the range of 1 to þ1: 30.7 years (SD 5 12.1) for ED]. The age of onset of gambling High values are interpreted as adequate matching in one’s activity [24.8 years (SD 5 10.4)], was later compared to the own cluster (that is, individuals within a latent cluster are age of onset of eating problems [20.2 years (SD 5 8.8)]. similar) and as poor matching in other clusters (individuals The GD patients were predominantly single (n 5 177, within a latent cluster are different compared to the other 46.3%) or married (n 5 169, 44.2%), while most of the ED clusters). Values lower than 0.30 are interpreted as having a participants were single (n 5 647, 71.4%). The social posi- poor fit, between 0.30 and 0.50 as fair, and higher than 0.50 tion index was low for both disorders (n 5 192, 50.3% for as good. GD n 5 492, 54.3% for ED), and employment status was Chi-square tests (c2) were used to compare the cate- similar between groups (n 5 231, 60.5% for GD and n 5 gorical variables between the identified latent empirical 511, 56.4% for ED), as well as the education level (primary groups, while the quantitative measures were compared by studies, n 5 257, 67.3% for GD and primary or secondary analysis of variance (ANOVA). To estimate the effect size education levels, n 5 744, 82.2% for ED). for the proportion differences, Cohen’s h was obtained as the Table S1 (in the Supplementary Materials) includes the difference between the arcsine transformation for the descriptive data for all of the variables analyzed in the study, probabilities calculated in each group (poor–low effect size as well as a comparison between both subsamples. was considered for |h| > 0.20, moderate–medium for |h| > 0.5, and large–high for |h| > 0.80) (Cohen, 1988). Since Clustering outcomes multiple statistical tests were performed, a possible increase in Type-I error was controlled for using Finner’s method, a The solution selected as the optimal in the two-step cluster stepwise familywise error rate characterized by providing procedure was for three latent empirical groups. This ach- more powerful capacity than the classical Bonferroni ieved the highest ratio distance measure (2.587) and a correction (Finner, 1993). cohesion/separation index into the fair range (silhouette 5 Unauthenticated | Downloaded 11/25/22 04:08 PM UTC 512 Journal of Behavioral Addictions 10 (2021) 3, 508–523 Fig. 1 Summary for the clustering Note. Sg1: Subgroup 1. Sg2: Subgroup 2. Sg3: Subgroup 3. DERS: Difficulties in Emotion Regulation Strategies. SCL-90: Symptom Checklist- 90 Items-Revised. TCI-R: Temperament and Character Inventory–Revised. 0.40). This three-group model was selected as the most in the two-step procedure, as well as a statistical comparison favorable in this work, since it achieved reliable interpreta- between the groups. These results provide a quantitative tion of the results in clinical terms. Table S2 (in the Sup- summary of the phenotypes associated with each empirical plementary Materials) includes the complete results of the group. Patients in subgroup 1 (Sg1; n 5 455, 35.3%) were auto-clustering. young with a shorter duration of the problematic behavior, The first panel of Fig. 1 displays the ordered bar chart as well as an earlier age of onset, a higher severity of the with the relative relevance for each measure used in the disorder, the poorest emotion regulation profile, and more clustering. These weights were in the range 0 to þ1, and they extreme personality traits of harm avoidance and self-tran- were interpreted as a measure of the discriminative capacity scendence. This subgroup included a higher proportion of of each variable within the classification (greater values are single women, with secondary education. related to a lower likelihood that changes between clusters Subgroup 2 (Sg2; n 5 478, 37.1%) was in the middle are attributable to chance). The measure with the greatest range of clinical features and personality traits. Two thirds of discriminative relevance (plotted with the darkest bar) was this group were women, mostly single, employed, with low the DERS subscale “limited access to emotional regulation education levels and low social indexes. strategies,” closely followed by psychopathological distress, On the contrary, subgroup 3 (Sg3; n 5 355, 27.6%) impulse control difficulties (DERS), self-directedness (TCI- comprised older men, with a later onset of the disorder, R), and difficulties engaging in goal-directed behaviors which was protracted but with low severity. This subgroup (DERS). The lowest discriminative relevance was for the lack had a more functional emotion regulation profile and higher of emotional awareness (DERS), followed by four TCI-R personality traits of reward dependence, persistence, self- scales (self-transcendence, persistence, reward dependence, directedness, and cooperativeness, as well as the lowest mean and novelty seeking). in self-transcendence. Participants in this group were not in The second and third panels of Fig. 1 show graphical relationships (single or divorced), employed, and had the images of the cluster quality (silhouette measure) and the highest education levels and social indexes. cluster distribution in the three empirical latent groups (the Figure 2 displays a radar plot of the distribution of the ratio of the largest versus the smallest sizes was 478/355 5 mean scores of the variables distinguished in the empirical 1.35), respectively. groups (z-standardized values are shown). Figure 3 contains line charts, when considering normative scores, with the prevalence of the participants within the clinical range, in Comparison between empirical groups terms of severity level of the disorder, emotion regulation Table 1 displays the distribution of the variables analyzed in (DERS), psychopathological state (SCL-90R), and personal- the study within the three latent empirical groups identified ity traits (TCI-R). These graphics represents a visual Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 Table 1. Comparison between the empirical groups in sociodemographical and clinical variables, psychopathology, personality traits and emotional disregulation Sg1 (n 5 455) Sg2 (n 5 478) Sg3 (n 5 355) Group Sg1 vs Sg2 Sg1 vs Sg3 Sg2 vs Sg3 n % n % n % P P |d| P |d| P |d| Sex Women 365 80.2% 313 65.5% 176 49.6% <0.001* <0.001* 0.33 <0.001* 0.66y <0.001* 0.32 Men 90 19.8% 165 34.5% 179 50.4% Marital Single 330 72.5% 295 61.7% 199 56.1% <0.001* 0.002* 0.23 <0.001* 0.35 0.253 0.12 Married/Partner 96 21.1% 139 29.1% 120 33.8% 0.18 0.29 0.10 Divorced/Separated 29 6.4% 44 9.2% 36 10.1% 0.11 0.14 0.03 Education Primary 210 46.2% 261 54.6% 168 47.3% 0.089 0.035* 0.17 0.790 0.02 0.108 0.15 Secondary 173 38.0% 151 31.6% 127 35.8% 0.14 0.05 0.09 University 72 15.8% 66 13.8% 60 16.9% 0.06 0.03 0.09 Social index High 8 1.8% 6 1.3% 6 1.7% 0.040* 0.821 0.04 0.037* 0.01 0.010* 0.04 Mean-high 34 7.5% 44 9.2% 30 8.5% 0.06 0.04 0.03 Mean 58 12.7% 56 11.7% 52 14.6% 0.03 0.06 0.09 Mean-low 101 22.2% 102 21.3% 107 30.1% 0.02 0.18 0.20 Low 254 55.8% 270 56.5% 160 45.1% 0.01 0.22 0.23 Employ. Unem./student 209 45.9% 201 42.1% 136 38.3% 0.092 0.232 0.08 0.029* 0.15 0.277 0.08 Employed 246 54.1% 277 57.9% 219 61.7% Mean SD Mean SD Mean SD LT QT P |d| P |d| P |d| Age (yrs) 31.3 12.7 33.8 12.8 36.2 14.3 <0.001* 0.922 0.003* 0.20 <0.001* 0.37 0.009* 0.18 Onset disorder (yrs) 19.9 8.5 22.0 9.8 23.1 10.1 <0.001* 0.388 0.001* 0.23 <0.001* 0.34 0.091 0.11 Duration disorder (yrs) 11.3 10.7 11.8 10.6 13.1 11.8 0.026* 0.534 0.498 0.05 0.023* 0.16 0.097 0.11 Severity of disorder (EDI-2 for ED and 96.9 6.4 88.1 13.6 77.3 21.6 <0.001* 0.255 <0.001* 0.83y <0.001* 1.23y <0.001* 0.59y Unauthenticated | Downloaded 11/25/22 04:08 PM UTC SOGS and DSM criteria for GD) DERS Non-accept-em 23.9 4.9 18.1 5.5 12.1 5.1 <0.001* 0.744 <0.001* 1.12y <0.001* 2.37y <0.001* 1.14y DERS Diff-direct-beh 20.8 3.0 15.9 3.8 11.0 3.6 <0.001* 0.844 <0.001* 1.43y <0.001* 2.95y <0.001* 1.31y DERS Limit-emot-reg 17.6 5.2 18.6 4.6 15.7 4.6 <0.001* <0.001* 0.001* 0.21 <0.001* 0.39 <0.001* 0.64y DERS Lack-emot-awar 31.5 4.8 22.4 5.1 13.7 4.1 <0.001* 0.411 <0.001* 1.86y <0.001* 4.02y <0.001* 1.89y DERS Impulse-cont-dif 21.7 4.8 14.1 4.0 9.8 2.8 <0.001* <0.001* <0.001* 1.72y <0.001* 3.03y <0.001* 1.24y DERS Lack-emot-clar 17.0 4.3 13.8 3.9 9.1 3.0 <0.001* 0.001* <0.001* 0.78y <0.001* 2.11y <0.001* 1.34y DERS Total score 132.5 13.9 102.8 12.9 71.5 12.7 <0.001* 0.285 <0.001* 2.21y <0.001* 4.57y <0.001* 2.45y SCL-90R Somatic 2.24 0.83 1.47 0.80 0.82 0.72 <0.001* 0.211 <0.001* 0.94y <0.001* 1.83y <0.001* 0.86y SCL-90R Obss-com 2.42 0.66 1.60 0.68 0.77 0.55 <0.001* 0.919 <0.001* 1.22y <0.001* 2.70y <0.001* 1.34y SCL-90R Int.sens. 2.60 0.69 1.60 0.71 0.67 0.61 <0.001* 0.320 <0.001* 1.43y <0.001* 2.96y <0.001* 1.40y SCL-90R Depress. 2.89 0.61 1.99 0.69 0.97 0.65 <0.001* 0.079 <0.001* 1.37y <0.001* 3.04y <0.001* 1.53y SCL-90R Anx 2.25 0.76 1.33 0.65 0.63 0.52 <0.001* .003* <0.001* 1.30y <0.001* 2.48y <0.001* 1.18y 513 (continued) 514 Table 1. Continued Sg1 (n 5 455) Sg2 (n 5 478) Sg3 (n 5 355) Group Sg1 vs Sg2 Sg1 vs Sg3 Sg2 vs Sg3 n % n % n % P P |d| P |d| P |d| y y SCL-90R Hostility 1.83 0.93 1.05 0.71 0.54 0.58 <0.001* 0.003* <0.001* 0.94 <0.001* 1.66 <0.001* 0.79y SCL-90R Pho.Anx 1.46 0.94 0.70 0.67 0.22 0.35 <0.001* 0.001* <0.001* 0.93y <0.001* 1.74y <0.001* 0.90y SCL-90R Paranoia 1.95 0.76 1.18 0.67 0.58 0.54 <0.001* 0.022* <0.001* 1.08y <0.001* 2.09y <0.001* 0.98y SCL-90R Psychotic 1.84 0.65 1.08 0.56 0.44 0.38 <0.001* 0.067 <0.001* 1.25y <0.001* 2.62y <0.001* 1.34y SCL-90R GSI 2.27 0.54 1.44 0.50 0.70 0.45 <0.001* 0.150 <0.001* 1.59y <0.001* 3.16y <0.001* 1.57y SCL-90R PST 73.5 11.4 60.0 15.0 36.1 17.6 <0.001* <0.001* <0.001* 1.02y <0.001* 2.52y <0.001* 1.46y SCL-90R PSDI 2.74 0.43 2.13 0.47 1.65 0.43 <0.001* 0.009* <0.001* 1.36y <0.001* 2.52y <0.001* 1.06y TCI-R Novelty seeking 104.3 17.9 102.3 16.9 103.1 13.2 0.252 0.142 0.064 0.11 0.302 0.08 0.489 0.05 TCI-R Harm avoidance 125.7 17.9 111.6 17.1 92.4 14.8 <0.001* 0.008* <0.001* 0.80y <0.001* 2.03y <0.001* 1.20y TCI-R Reward depend. 98.1 16.5 98.0 15.2 103.9 14.0 <0.001* 0.001* 0.911 0.01 <0.001* 0.38 <0.001* 0.41 TCI-R Persistence 105.2 21.4 107.0 19.2 115.1 18.9 <0.001* 0.007* 0.166 0.09 <0.001* 0.51y <0.001* 0.42 TCI-R Self-directedness 103.5 14.8 120.2 13.9 145.3 15.9 <0.001* <0.001* <0.001* 1.17y <0.001* 2.72y <0.001* 1.68y TCI-R Cooperativeness 127.3 17.2 132.9 14.6 139.4 13.4 <0.001* 0.625 <0.001* 0.35 <0.001* 0.79y <0.001* 0.46 TCI-R Self-transcend. 68.3 15.0 64.2 14.7 60.2 15.4 <0.001* 0.960 <0.001* 0.27 <0.001* 0.53y <0.001* 0.26 Note. SD: standard deviation. LT: linear trend. QT: quadratic trend. Sg1: Subgroup 1. Sg2: Subgroup 2. Sg3: Subgroup 3. EDI-2: Eating disorder inventory-2. ED: Eating disorder. SOGS: South oaks gambling severity screen. DSM: Diagnostic Questionnaire for Pathological Gambling. GD: Gambling disorder. DERS: Difficulties in Emotion Regulation Strategies. SCL-90: Symptom Checklist-90 Items-Revised. TCI-R: Temperament and Character Inventory–Revised. *Bold: significant comparison (0.05). y Bold: effect size into the mild-moderate (|d|>0.50) to the high-large range (|d|>0.80). Journal of Behavioral Addictions 10 (2021) 3, 508–523 Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 515 Fig. 2 Radar-chart displaying the main differences between empirical groups Note. Sg1: Subgroup 1. Sg2: Subgroup 2. Sg3: Subgroup 3. DERS: Difficulties in Emotion Regulation Strategies. SCL-90: Symptom Checklist- 90 Items-Revised. TCI-R: Temperament and Character Inventory–Revised. Fig. 3 Line-chart displaying the prevalence of participants into the non-normative groups Note. Sg1: Subgroup 1. Sg2: Subgroup 2. Sg3: Subgroup 3. DERS: Difficulties in Emotion Regulation Strategies. SCL-90: Symptom Checklist- 90 Items-Revised. TCI-R: Temperament and Character Inventory–Revised. GSI: Global severity index. PST: Positive symptom total. PSDI: Positive symptom distress index. summary of the composition of the empirical latent groups indicates that GD patients were mostly included within in the study. Based on the set of results in this study, Sg1 was subgroups Sg2 and Sg3 (39.8% in each latent group), while labeled “severe profile,” Sg2 as “moderate profile,” and Sg3 as ED patients were mostly included within latent subgroups “low profile.” Sg1 (41.6%) and Sg2 (36.0%). Considering the ED subtype (second panel), AN was similarly distributed across the three clusters, while BN and BED were mainly distributed across Diagnostic subtypes within the empirical latent groups Sg1 and Sg2; the distribution for the OSFED patients was Figure 4 displays 100% stacked bar charts with the distri- more similar to AN than to BN and BED. Regarding the GD bution of the diagnostic subtypes in the latent empirical subtypes (third panel): (a) Non-Strategic gambling was groups. The first panel obtained for the total sample mostly included in Sg3 (48.4%) and Sg2 (39.8%); (b) Unauthenticated | Downloaded 11/25/22 04:08 PM UTC 516 Journal of Behavioral Addictions 10 (2021) 3, 508–523 Fig. 4. Distribution of the diagnostic subtype into the empirical groups Note. Sg1: Subgroup 1. Sg2: Subgroup 2. Sg3: Subgroup 3. AN: Anorexia nervosa. BN: Bulimia nervosa. BED: Binge eating disorder. OSFED: other specified feeding eating disorder. GD: gambling disorder. Total sample: n 5 1,288. Gambling disorder subsample: n 5 382. Eating disorder subsample: n 5 906. Strategic gambling was also mostly within Sg2 (40.6%) and Even though ER difficulties have already been described Sg3 (37.7%), but with a higher percentage in Sg1 (21.7%) in ED (Brockmeyer et al., 2014; Mallorquı-Bague et al., compared with Non-Strategic gambling in the same sub- 2018) and GD (Granero et al., 2018; Sancho et al., 2019; group; (c) people with mixed gambling subtypes were Williams et al., 2012), a characterization of clusters based on similarly distributed across the three empirical groups: Sg1 ER has not been explored in previous literature. To the best (27.3%), Sg2 (37.7%), and Sg3 (35.1%). of our knowledge, this is the first study to confirm a trans- diagnostic approach of ER in well-defined phenotypically clinical samples. DISCUSSION Participants with BN, followed by BED, were categorized into the severe profile (Sg1), and the mixed group of GD The aim of the present study was to explore the existence of (Non-Strategic and Strategic gambling activities) were also latent empirical groups among ED and GD, based on categorized into this profile. In addition to greater difficulties emotional regulation difficulties and considering personality in ER, this group had more difficulties in the other variables traits, general psychopathology, and severity of the disorder. that were measured. The presence of higher ER difficulties in As we hypothesized, the phenotypes were defined by the the purgative bulimic subtypes of ED has already been degree of ER difficulties, in particular the DERS subscale described in the literature (Aloi, Rania, Caroleo, De Fazio, & limited access to emotional regulation strategies. There was a Segura-Garcıa, 2017; Mallorquı-Bague et al., 2018; Wolz linear relationship between the ER profile and the severity et al., 2015). Likewise, in the case of GD, it has been reported and general psychopathological state within the disorder. that patients with both, Non-Strategic and Strategic gambling The three clusters were labeled as Sg1 “severe profile,” Sg2 activities showed higher severity of the disorder (Susana “moderate profile,” and Sg3 “low profile.” Jimenez-Murcia, Granero, Fernandez-Aranda, & Mench on, The transdiagnostic approach is presented as a proposal 2020). This aligns with the profile of the participants in Sg1. that different mental disorders could share some core un- These results suggest that the behaviors related to the dis- derlying clinical dimensions, which may have important order (i.e., binge eating and gambling activities) may be used implications in treatment (Norton & Paulus, 2016; Reinholt to avoid or suppress negative emotional states (Kassel et al., & Krogh, 2014). In the case of ER, it was already hypothe- 2013; Lavender et al., 2014). sized, at the theoretical level, that it could be a trans- Harm avoidance was the personality trait that was diagnostic construct among several conditions (Kanakam et increased within Sg1. Higher ER difficulties and lower self- al., 2013; Sloan et al., 2017), especially in anxiety and mood directedness (both found in this subgroup) are associated disorders (Faustino, 2020). However, there is a lack of with a poorer adherence to treatment and a poorer prog- studies aimed at identifying the phenotypes defined by ER, nosis (Claes et al., 2012; Del Pino-Gutierrez et al., 2017; evaluating jointly different clinical samples. Fernandez-Aranda et al., 2006; Wolz et al., 2015). Moreover, The findings of the present research were confirmatory these personality traits are associated with a worse psycho- of the transdiagnostic role of ER in the studied disorders, pathological state and severity of the disorder (Ag€ uera et al., being the determinant factor that grouped both conditions 2017; Greenberg & Schoen, 2008). beyond diagnostic criteria. ED and GD were represented Participants with BED and Strategic gamblers were within the three empirical groups. mainly categorized into the moderate profile group (Sg2), Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 517 which presented a middle ER difficulty profile that followed It is possible that those in Sg1 may benefit from treat- linearity with the other studied variables. This aligns with ments augmented by emotion regulation therapy, such as clinical experience in which a negative mood frequently emotion regulation skill training (Adamson, Leppanen, precedes binge eating episodes (Gianini, White, & Masheb, Murin, & Tchanturia, 2018; Berking et al., 2008; Fresco, 2013; Nicholls, Devonport, & Blake, 2016). The important Mennin, Heimberg, & Ritter, 2013; Gratz et al., 2015; presence of alexithymia has been described in Strategic Tchanturia, Doris, Mountford, & Fleming, 2015) and gamblers (Bonnaire et al., 2017) and they may use gambling mindfulness-based strategies (Hermann, Kress, & Stark, to regulate internal undifferentiated emotional states (Di 2017; Lutz et al., 2013; Opialla et al., 2014). In addition, Trani, Renzi, Vari, Zavattini, & Solano, 2017). This is specific strategies may be needed to address the personality consistent with the high scores in the lack of emotional traits of this subgroup, such as high harm avoidance and low awareness DERS subscale in these participants. Nevertheless, self-directedness, which are associated with low adherence to the Sg2 cluster showed fewer dysfunctional personality traits, treatment. In order to target these difficulties, the use of which may contribute to a better outcome than those in Sg1. non-conventional treatments, such as those based on new ER difficulties were lower in Sg3. This does not mean technologies, could be considered. In this line, different that AN or Non-Strategic gamblers (the participants with a approaches have been adopted in ED and GD with the aim higher presence in Sg3) do not present ER difficulties, but of improving ER, such as the use of serious videogames that they are not as determinant in this empirical group as in (Fernandez-Aranda et al., 2015; Lorenzetti et al., 2018; Sg1. Passive gambling (Non-Strategic) is considered to be an Mena-Moreno et al., 2019; Tarrega et al., 2015), mobile avoidance strategy when facing negative emotional states, applications (Beck, 2017), or mindfulness (Plaza, Demarzo, rather than a search for stimulation (Sancho et al., 2019). Herrera-Mercadal, & Garcıa-Campayo, 2013; Sala et al., Similarly, excessive exercise or eating restriction in AN are 2018). thought to be part of an avoidant strategy in response to Those in Sg2 showed ER difficulties within the normative difficult emotion recognition and regulation (Engel et al., range, but they had higher levels of disorder-related severity 2013; Harrison, Sullivan, Tchanturia, & Treasure, 2009). and general psychopathology. For instance, Cognitive Moreover, Sg3 displayed several factors associated with a Behavioral Therapy (Mallorquı-Bague, Mena-Moreno et al., better adherence to and outcome of treatment (reduced 2018), Dialectical Behavior Therapy (DBT) (Linehan, 1993), psychological distress, lowest severity of the disorder, and or Acceptance-Based Behavioral Therapy (Roemer, Orsillo, higher levels of functional personality traits, i.e., high & Salters-Pedneault, 2008) might be more appropriate. persistence and self-directedness). Finally, it is important to mention the role of gender in There was a wide variation in the age and duration of these phenotypes. A higher percentage of women and pa- disorder within subgroups. The youngest participants and tients with ED were found in Sg1, whereas Sg3 was char- those with the earliest age of onset and the lowest duration acterized by a higher presence of men and patients with GD. of the disorder were found in Sg1, while the older partici- This is in concordance with the gender prevalence in each pants with a longer duration of illness were located in Sg3. It disorder (Jimenez-Murcia et al., 2020; Treasure, Duarte, & is therefore possible that developmental factors might ac- Schmidt, 2020), but it does not imply that gender itself de- count for the ER problems in the younger group (Zimmer- termines the level of ER difficulties. Gembeck & Skinner, 2011), while the use of better ER In ED, ER difficulties may be a predictor of abnormal strategies has been reported in older population (Kessler & eating behaviors in both males and females from adoles- Staudinger, 2009; Phillips, Henry, Hosie, & Milne, 2008). cence (Hayaki & Free, 2016). Although no differences have In addition to the results explained above, the clinical found in the ER difficulties between females and males with relevance of the variables that explained the three phenotypes ED, personality traits have been described as a mediator was studied. In Sg1, the scores in the measured variables were between ER and gender in the ED population (Ag€ uera et al., higher than the normative ranges (Derogatis, 2002; Gutier- 2019; Ambwani, Slane, Thomas, Hopwood, & Grilo, 2014). rez-Zotes et al., 2004; Wolz et al., 2015), followed by Sg2 Similarly, in GD, difficulties in ER have been found in both (except in ER difficulties), while Sg3 presented the closest genders, but are related to different choices in gambling percentages to the sub-clinic range in all of the variables. subtypes. Higher rates of arousal-seeking behavior have been There are several clinical implications that may follow described as a reason why men prefer Strategic games, which from these findings. For example treatment that focuses on might also be applied to substance-abusing recreational emotional regulation would be most appropriate for those in gamblers (Liu, Maciejewski, & Potenza, 2009). In contrast, Sg1, while those in Sg3 might respond well to guided self- emotional issues may underlie women’s choice for Non- help (the first stage of a stepped care model advocated by Strategic games (Ledgerwood & Petry, 2006). NICE) or, given the high presence of AN patients in this group, a new therapy named “Radically Open Dialectical Behavior Therapy (RO DBT)” directed to increase emotional LIMITATIONS AND STRENGTHS expressiveness, receptivity, flexibility, and inhibition of emotions (Gilbert, Hall, & Codd, 2020; Lynch, Hempel, & The following limitations of this study need to be consid- Dunkley, 2015), as in AN patients (Hempel, Vanderbleek, & ered. The transdiagnostic approach was only studied in two Lynch, 2018), could be useful. associated disorders; for future studies, related impulse Unauthenticated | Downloaded 11/25/22 04:08 PM UTC 518 Journal of Behavioral Addictions 10 (2021) 3, 508–523 control disorders, such as other behavioral addictions or of the Mexican Institution Consejo Nacional de Ciencia y substance use disorders, and other conditions associated Tecnologıa-CONACYT (Science and Technology National with difficulties in emotional regulation would be of interest Counsel). IB was partially supported by a Post-Residency (Aldao et al., 2010; Estevez et al., 2017; Kassel et al., 2013). Grant from Research Committee of the University Hospital Unfortunately, the demographics of the participants differed of Bellvitge (HUB; Barcelona, Spain) 2019–2020. Additional in terms of gender, age, and incidence, which added funding was received from EU-H2020 (Eat2beNICE-Ref complexity to the interpretation of the results. 728018 and PRIME-Ref. 847879). This study also has several strengths. First, the large sample size provided high external validity. A second Conflicts of interest: The authors declare no conflict of in- strength was the use of multiple measures in the clustering terest. The funders had no role in the design of the study; in process. The clustering clinical data depends on the rele- the collection, analyses, or interpretation of data; in the vance of the indicator variables. It is essential that all key writing of the manuscript, or in the decision to publish the variables related to the constructs under study are included results. in the grouping process (Torgo & da Costa, 2000). In addition to the scores of the measures of emotional dysre- Authors’ contribution: LM, SJM and FFA contributed to the gulation, we included key features of the clinical individuals’ development of the study concept and design. RG performed profiles (disorder severity, global psychopathological the statistical analysis. LM, IB, EC, APG aided with data distress, and personality traits). Two-step cluster analysis is a collection. LM, SJM, FFA, IB and GT aided with interpre- powerful and robust technique that can be used with tation of data and the writing of the manuscript. JT, ZA and dimensional data in large datasets, and this system provides IS revised the manuscript and provided substantial com- the weight/relevance of each predictor in the clustering ments. process. SUPPLEMENTARY MATERIAL CONCLUSIONS Supplementary data to this article can be found online at We found a three-cluster structure between ED and GD, https://doi.org/10.1556/2006.2021.00017. with emotional regulation as a transdiagnostic construct ranging from “severe” to “low” profile, with variations be- tween clusters in the severity of the disorder, psychopatho- logical distress, and associated personality traits. Both the REFERENCES identification of the clusters and their characterization ac- cording to the other relevant clinical variables offer the Adamson, J., Leppanen, J., Murin, M., & Tchanturia, K. (2018). possibility of designing a more precise treatment approach Effectiveness of emotional skills training for patients with between ED and GD. This is an important implication, anorexia nervosa with autistic symptoms in group and indi- considering that in other psychiatric conditions, such as vidual format. European Eating Disorders Review, 26(4), 367– anxiety and mood disorders, transdiagnostic treatments 375. http://doi.org/10.1002/erv.2594. have proven to obtain positive results focusing on “core” uera, Z., Paslakis, G., Munguıa, L., Sanchez, I., Granero, R., Ag€ pathological processes (Barlow et al., 2017). To the best of Sanchez-Gonzalez, J., et al. (2019). Gender-related patterns of our knowledge, this is the first study that has confirmed the emotion regulation among patients with eating disorders. transdiagnostic approach of ER in a clinical population with Journal of Clinical Medicine, 8(2), 161. http://doi.org/10.3390/ a phenotype approximation in two related disorders. jcm8020161. uera, Z., Sanchez, I., Granero, R., Riesco, N., Steward, T., Martın- Ag€ Romera, V., et al. (2017). Short-term treatment outcomes and Funding and acknowledgment: We thank CERCA Pro- dropout risk in men and women with eating disorders. Euro- gramme/Generalitat de Catalunya for institutional support. pean Eating Disorders Review, 25(4), 293–301. http://doi.org/10. This manuscript and research was supported by grants from 1002/erv.2519. the Ministerio de Economıa y Competitividad (PSI2015- Aldao, A., Nolen-Hoeksema, S., & Schweizer, S. (2010). Emotion- 68701-R), by the Delegaci on del Gobierno para el Plan regulation strategies across psychopathology: A meta-analytic Nacional sobre Drogas (2017I067 and 2019I47), by the review. Clinical Psychology Review, 30(2), 217–237. http://doi. Instituto de Salud Carlos III (ISCIII) (FIS PI17/01167 and org/10.1016/j.cpr.2009.11.004. PI20/132), by the SLT006/17/00246 grant, funded by the Aloi, M., Rania, M., Caroleo, M., De Fazio, P., & Segura-Garcıa, C. Department of Health of the Generalitat de Catalunya by the (2017). Social cognition and emotional functioning in patients call “Accio instrumental de programes de recerca orientats with binge eating disorder. European Eating Disorders Review, en l’ambit de la recerca i la innovacio en salut”, and co- 25(3), 172–178. http://doi.org/10.1002/erv.2504. funded by FEDER funds/European Regional Development  Alvarez-Moya, E. M., Jimenez-Murcia, S., Granero, R., Vallejo, J., Fund (ERDF), a way to build Europe. CIBERObn is an Krug, I., Bulik, C. M., et al. (2007). Comparison of personality initiative of ISCIII. LM is supported by a postdoctoral Grant risk factors in bulimia nervosa and pathological gambling. Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 519 Comprehensive Psychiatry, 48(5), 452–457. http://doi.org/10. Bodell, L. P., Pearson, C. M., Smith, K. E., Cao, L., Crosby, R. D., 1016/j.comppsych.2007.03.008. Peterson, C. B., et al. (2019). Longitudinal associations between Ambwani, S., Slane, J. D., Thomas, K. M., Hopwood, C. J., & Grilo, C. emotion regulation skills, negative affect, and eating disorder M. (2014). Interpersonal dysfunction and affect-regulation diffi- symptoms in a clinical sample of individuals with binge eating. culties in disordered eating among men and women. Eating Be- Eating Behaviors, 32, 69–73. http://doi.org/10.1016/j.eatbeh. haviors, 15(4), 550–554. http://doi.org/10.1016/j.eatbeh.2014.08.005. 2018.12.005. American Psychiatric Association. (2010). Diagnostic and statistical Bonnaire, C., Barrault, S., Aı€te, A., Cassotti, M., Moutier, S., & manual of mental disorders (4th ed.). Washington, DC: Varescon, I. (2017). Relationship between pathological American Psychiatric Association. gambling, alexithymia, and gambling type. American Journal on American Psychiatric Association. (2013). Diagnostic and statistical Addictions, 26(2), 152–160. http://doi.org/10.1111/ajad.12506. manual of mental disorders (5th ed.). Washington DC: Amer- Brandl, F., Le Houcq Corbi, Z., Mulej Bratec, S., & Sorg, C. (2019). ican Psychiatric Association. Cognitive reward control recruits medial and lateral frontal Andrews, G., Goldberg, D. P., Krueger, R. F., Carpenter, W. T., cortices, which are also involved in cognitive emotion regula- Hyman, S. E., Sachdev, P., et al. (2009). Exploring the feasibility of tion: A coordinate-based meta-analysis of fMRI studies. Neu- a meta-structure for DSM-V and ICD-11: Could it improve utility roImage, 200, 659–673. http://doi.org/10.1016/j.neuroimage. and validity? Psychological Medicine. Psychol Med, 39(12), 1993– 2019.07.008. 2000. http://doi.org/10.1017/S0033291709990250. Brockmeyer, T., Skunde, M., Wu, M., Bresslein, E., Rudofsky, G., Atiye, M., Miettunen, J., & Raevuori-Helkamaa, A. (2015). A meta- Herzog, W., et al. (2014). Difficulties in emotion regulation analysis of temperament in eating disorders. European Eating across the spectrum of eating disorders. Comprehensive Psy- Disorders Review, 23(2), 139–146. http://doi.org/10.1002/erv.2342. chiatry, 55(3), 565–571. http://doi.org/10.1016/j.comppsych. Axelrod, S. R., Perepletchikova, F., Holtzman, K., & Sinha, R. 2013.12.001. (2011). Emotion regulation and substance use frequency in Cackowski, S., Reitz, A. C., Ende, G., Kleindienst, N., Bohus, M., women with substance dependence and borderline personality Schmahl, C., et al. (2014). Impact of stress on different com- disorder receiving dialectical behavior therapy. The American ponents of impulsivity in borderline personality disorder. Psy- Journal of Drug and Alcohol Abuse, 37(1), 37–42. http://doi.org/ chological Medicine, 44(15), 3329–3340. http://doi.org/10.1017/ 10.3109/00952990.2010.535582. S0033291714000427. Aymamı, N., Granero, R., Penelo, E., Fernandez-Aranda, F., Krug, Cisler, J. M., & Olatunji, B. O. (2012). Emotion regulation and I., Gunnard, K., et al. (2014). Anger in pathological gambling: anxiety disorders. Current Psychiatry Reports, 14(3), 182–187. Clinical, psychopathological, and personality correlates. http://doi.org/10.1007/s11920-012-0262-2. Spanish Journal of Psychology, 17(2). http://doi.org/10.1017/ Claes, L., Jimenez-Murcia, S., Ag€ uera, Z., Castro, R., Sanchez, I., sjp.2014.40. Mench~ on, J. M., et al. (2012). Male eating disorder patients with Balodis, I. M., Kober, H., Worhunsky, P. D., Stevens, M. C., and without non-suicidal self-injury: A comparison of psycho- Pearlson, G. D., & Potenza, M. N. (2012). Diminished fron- pathological and personality features. European Eating Disorders tostriatal activity during processing of monetary rewards and Review, 20(4), 335–338. http://doi.org/10.1002/erv.1161. losses in pathological gambling. Biological Psychiatry, 71(8), Cloninger, C. R. (1999). The temperament and character in- 749–757. http://doi.org/10.1016/j.biopsych.2012.01.006. ventory—Revised. St Louis, MO, USA: Center for Psychobiology Balodis, I. M., Kober, H., Worhunsky, P. D., White, M. A., Stevens, of Personality, Washington University. M. C., Pearlson, G. D., et al. (2013). Monetary reward pro- Cohen, J. (1988). Statistical power analysis for the behavioral sci- cessing in obese individuals with and without binge eating ences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, disorder. Biological Psychiatry, 73(9), 877–886. http://doi.org/ Publishers. 10.1016/j.biopsych.2013.01.014. Del Pino-Gutierrez, A., Jimenez-Murcia, S., Fernandez-Aranda, F., Barlow, D. H., Farchione, T. J., Bullis, J. R., Gallagher, M. W., Ag€ uera, Z., Granero, R., Hakansson, A., et al. (2017). The Murray-Latin, H., Sauer-Zavala, S., et al. (2017). The unified relevance of personality traits in impulsivity-related disorders: protocol for transdiagnostic treatment of emotional disor- From substance use disorders and gambling disorder to bulimia ders compared with diagnosis-specific protocols for anxiety nervosa. Journal of Behavioral Addictions, 6(3), 396–405. http:// disorders: A randomized clinical trial. JAMA Psychiatry, doi.org/10.1556/2006.6.2017.051. 74(9), 875–884. http://doi.org/10.1001/jamapsychiatry.2017. Derogatis, L. R. (1994). SCL-90-R: Symptom checklist-90-R. Admin- 2164. istration, scoring and procedures manuall—II for the Revised Beck, N. A. (2017). Mobile apps for cognitive restructuring: A review version. Towson, MD, USA,: Clinical Psychometric Research. and comparative analysis. Pepperdine University. Derogatis, L. R. (2002). SCL-90-R. Cuestionario de 90 Sıntomas- Berking, M., Wupperman, P., Reichardt, A., Pejic, T., Dippel, A., & Manual. (TEA, Ed.). Madrid, Spain. Znoj, H. (2008). Emotion-regulation skills as a treatment target Di Trani, M., Renzi, A., Vari, C., Zavattini, G. C., & Solano, L. in psychotherapy. Behaviour Research and Therapy, 46(11), (2017). Gambling disorder and affect regulation: The role of 1230–1237. http://doi.org/10.1016/j.brat.2008.08.005. alexithymia and attachment style. Journal of Gambling Studies, Blaszczynski, A. P., & McConaghy, N. (1989). The medical model 33(2), 649–659. http://doi.org/10.1007/s10899-016-9637-3. of pathological gambling: Current shortcomings. Journal of Echebur ua, E., Baez, C., Fernandez, J., & Paez, D. (1994). Cues- Gambling Behavior, 5(1), 42–52. http://doi.org/10.1007/ tionario de Juego Patol ogico de South Oaks (SOGS): validaci on BF01022136. espa~nola. Analisis de Modificacion de Conducta, 20, 769–791. Unauthenticated | Downloaded 11/25/22 04:08 PM UTC 520 Journal of Behavioral Addictions 10 (2021) 3, 508–523 Engel, S. G., Wonderlich, S. A., Crosby, R. D., Mitchell, J. E., Crow, adults with binge eating disorder. Eating Behaviors, 14(3), 309– S., Peterson, C. B., et al. (2013). The role of affect in the 313. http://doi.org/10.1016/j.eatbeh.2013.05.008. maintenance of anorexia nervosa: Evidence from a naturalistic Gilbert, K., Hall, K., & Codd, R. T. (2020). Radically open dialectical assessment of momentary behaviors and emotion. Journal of behavior therapy: Social signaling, transdiagnostic utility and Abnormal Psychology, 122(3), 709–719. http://doi.org/10.1037/ current evidence. Psychology Research and Behavior Manage- a0034010. ment, 13, 19–28. http://doi.org/10.2147/PRBM.S201848. Estevez, A., Jauregui, P., Granero, R., Munguıa, L., Lopez-Gonzalez, Granero, R., Fernandez-Aranda, F., Mestre-Bach, G., Steward, T., H., Macıa, L., et al. (2020). Buying-shopping disorder, emotion Garcıa-Caro, B., Prever, F., et al. (2018). Clustering of treat- dysregulation, coping and materialism: A comparative ment-seeking women with gambling disorder. Journal of approach with gambling patients and young people and ado- Behavioral Addictions, 7(3), 770–780. http://doi.org/10.1556/ lescents. International Journal of Psychiatry in Clinical Practice, 2006.7.2018.93. 24(4), 407–415. http://doi.org/10.1080/13651501.2020.1780616. Gratz, K. L., & Roemer, L. (2004). Multidimensional assessment Estevez, A., Jauregui, P., Lopez-Gonzalez, H., Mena-Moreno, T., of emotion regulation and dysregulation: Development, Lozano-Madrid, M., Macia, L., et al. (2020) (In press). The factor structure, and initial validation of the difficulties in severity of gambling and gambling related cognitions as pre- emotion regulation scale. Journal of Psychopathology and dictors of emotional regulation and coping strategies in ado- Behavioral Assessment, 26, 41–54. http://doi.org/10.1007/ lescents. Journal of Gambling Studies. http://doi.org/10.1007/ s10862-008-9102-4. s10899-020-09953-2. Gratz, K. L., Weiss, N. H., & Tull, M. T. (2015). Examining emotion Estevez, A., Jauregui, P., Sanchez-Marcos, I., Lopez-Gonzalez, H., & regulation as an outcome, mechanism, or target of psycholog- Griffiths, M. D. (2017). Attachment and emotion regulation in ical treatments. Current Opinion in Psychology, 3, 85–90. http:// substance addictions and behavioral addictions. Journal of doi.org/10.1016/j.copsyc.2015.02.010. Behavioral Addictions, 6(4), 534–544. http://doi.org/10.1556/ Greenberg, S. T., & Schoen, E. G. (2008). Males and eating disor- 2006.6.2017.086. ders: Gender-based therapy for eating disorder recovery. Pro- Faustino, B. (2020). Transdiagnostic perspective on psychological fessional Psychology: Research and Practice, 39(4), 464–471. inflexibility and emotional dysregulation. Behavioural and http://doi.org/10.1037/0735-7028.39.4.464. Cognitive Psychotherapy, Sep 8, 1–14. http://doi.org/10.1017/ Gross, J. J. (2015). Emotion regulation: Current status and future S1352465820000600. prospects. Psychological Inquiry, 26(1), 1–26. http://doi.org/10.  Fernandez-Aranda, F., Jimenez-Murcia, S., Alvarez-Moya, E. M., 1080/1047840X.2014.940781. Granero, R., Vallejo, J., & Bulik, C. M. (2006). Impulse control Gutierrez-Zotes, J. A., Bay on, C., Montserrat, C., Valero, J., Labad, disorders in eating disorders: Clinical and therapeutic impli- A., Cloninger, C. R., et al. (2004). Temperament and Character cations. Comprehensive Psychiatry, 47(6), 482–488. http://doi. Inventory Revised (TCI-R). Standardization and normative org/10.1016/j.comppsych.2006.03.002. data in a general population sample. Actas Espanolas de Psi- Fernandez-Aranda, F., Jimenez-Murcia, S., Santamarıa, J. J., Giner- quiatria, 32(1), 8–15. Retrieved from http://www.ncbi.nlm.nih. Bartolome, C., Mestre-Bach, G., Granero, R., et al. (2015). The gov/pubmed/14963776. use of videogames as complementary therapeutic tool for Harrison, A., Sullivan, S., Tchanturia, K., & Treasure, J. (2009). cognitive behavioral therapy in bulimia nervosa patients. Emotion recognition and regulation in anorexia nervosa. Cyberpsychology, Behavior, and Social Networking, 18(12), 744– Clinical Psychology & Psychotherapy, 16(4), 348–356. http://doi. 751. http://doi.org/10.1089/cyber.2015.0265. org/10.1002/cpp.628. Finner, H. (1993). On A monotonicity problem in step-down Hayaki, J., & Free, S. (2016). Positive and negative eating expec- multiple test procedures. Journal of the American tancies in disordered eating among women and men. Eating Statistical Association, 88(423), 920–923. http://doi.org/10. Behaviors, 22, 22–26. http://doi.org/10.1016/j.eatbeh.2016.03.025. 2307/2290782. Hempel, R., Vanderbleek, E., & Lynch, T. R. (2018). Radically open First, M. B., Reed, G. M., Hyman, S. E., & Saxena, S. (2015). The DBT: Targeting emotional loneliness in anorexia nervosa. development of the ICD-11 clinical descriptions and diagnostic Eating Disorders, 26(1), 92–104. http://doi.org/10.1080/ guidelines for mental and behavioural disorders. World Psy- 10640266.2018.1418268. chiatry, 14(1), 82–90. http://doi.org/10.1002/wps.20189. Henderson, Z. B., Fox, J. R. E., Trayner, P., & Wittkowski, A. Fresco, D. M., Mennin, D. S., Heimberg, R. G., & Ritter, M. (2013). (2019). Emotional development in eating disorders: A qualita- Emotion regulation therapy for generalized anxiety disorder. tive metasynthesis. Clinical Psychology & Psychotherapy, 264, Cognitive and Behavioral Practice, 20(3), 282–300. http://doi. 440–457. http://doi.org/10.1002/cpp.2365. org/10.1016/j.cbpra.2013.02.001. Hermann, A., Kress, L., & Stark, R. (2017). Neural correlates of im- Garner, D. M. (1998). Inventario de Trastornos de la Conducta mediate and prolonged effects of cognitive reappraisal and Alimentaria (EDI-2)—Manual. Madrid, Spain: TEA. distraction on emotional experience. Brain Imaging and Behavior, Getty, H. A., Watson, J., & Frisch, G. R. (2000). A comparison of 11(5), 1227–1237. http://doi.org/10.1007/s11682-016-9603-9. depression and styles of coping in male and female GA mem- Hollingshead, A. B. (2011). Four factor index of social status. Yale bers and controls. Journal of Gambling Studies, 16(4), 377–391. Journal of Sociology, 8, 21–51. Retrieved from http://www.yale. http://doi.org/10.1023/A:1009480106531. edu/sociology/yjs/yjs_fall_2011.pdf. Gianini, L. M., White, M. A., & Masheb, R. M. (2013). Eating pa- IBM Corp. (2016). IBM SPSS statistics for windows, version 24.0. thology, emotion regulation, and emotional overeating in obese Arkmonk, NY: IBM Corp. Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 521 Jimenez-Murcia, S., Granero, R., Fernandez-Aranda, F., & ecological momentary assessment. Eur Eat Disorders Rev, 28(2), Menchon, J. M. (2020). Comparison of gambling profiles based 170–183. on strategic versus non-strategic preferences. Current Opinion Kucharska, K., Kot, E., Biernacka, K., Zimowski, J., Rogoza, R., in Behavioral Sciences, 31, 13–20. http://doi.org/10.1016/j. Rybakowski, F., et al. (2019). Interaction between poly- cobeha.2019.09.001. morphisms of the oxytocinergic system genes and emotion Jimenez-Murcia, S., Granero, R., Gimenez, M., del Pino-Gutierrez, perception in inpatients with anorexia nervosa. Eur Eat Dis- A., Mestre-Bach, G., Mena-Moreno, T., et al. (2020). Moderator orders Rev. effect of sex in the clustering of treatment-seeking patients with Lavender, J. M., Wonderlich, S. A., Peterson, C. B., Crosby, R. D., gambling problems. Neuropsychiatrie, 34(3), 116–129. http:// Engel, S. G., Mitchell, J. E., et al. (2014). Dimensions of doi.org/10.1007/s40211-020-00341-1. emotion dysregulation in bulimia Nervosa. European Eating Jimenez-Murcia, S., Granero, R., Moragas, L., Steiger, H., Israel, M., Disorders Review, 22(3), 212–216. http://doi.org/10.1002/erv. Aymamı, N., et al. (2015). Differences and similarities between 2288. bulimia nervosa, compulsive buying and gambling disorder. Ledgerwood, D. M., & Petry, N. M. (2006). Psychological experi- European Eating Disorders Review, 23(2), 126–132. http://doi. ence of gambling and subtypes of pathological gamblers. Psy- org/10.1002/erv.2340. chiatry Research, 144(1), 17–27. http://doi.org/10.1016/j. Jimenez-Murcia, S., Steiger, H., Isr€ael, M., Granero, R., Prat, R., psychres.2005.08.017. Santamarıa, J. J., et al. (2013). Pathological gambling in eating Leehr, E. J., Krohmer, K., Schag, K., Dresler, T., Zipfel, S., & Giel, K. disorders: Prevalence and clinical implications. Comprehensive E. (2015). Emotion regulation model in binge eating disorder Psychiatry, 54(7), 1053– 1060. http://doi.org/10.1016/j. and obesity - a systematic review. Neuroscience & Biobehavioral comppsych.2013.04.014. Reviews, 49, 125–134. http://doi.org/10.1016/j.neubiorev.2014.  Jimenez-Murcia, S., Stinchfield, R., Alvarez-Moya, E., Jaurrieta, N., 12.008. Bueno, B., Granero, R., et al. (2009). Reliability, validity, and Lesieur, H. R., & Blume, S. B. (1987). The south oaks gambling classification accuracy of a Spanish translation of a measure of screen (SOGS): A new instrument for the identification of DSM-IV diagnostic criteria for pathological gambling. Journal pathological gamblers. American Journal of Psychiatry, 144(9), of Gambling Studies, 25, 93–104. http://doi.org/10.1007/s10899- 1184–1188. http://doi.org/10.1176/ajp.144.9.1184. 008-9104-x. Lesieur, H. R., & Blume, S. (1993). Pathological gambling, eating Joormann, J., & Stanton, C. H. (2016). Examining emotion regu- disorders, and the psychoactive substance use disorders. Journal lation in depression: A review and future directions. Behaviour of Addictive Diseases, 12(3), 89–102. http://doi.org/10.1300/ Research and Therapy, 86, 35–49. http://doi.org/10.1016/j.brat. J069v12n03_08. 2016.07.007. Linehan, M. (1993). Cognitive behavioral treatment of borderline Kanakam, N., Krug, I., Raoult, C., Collier, D., & Treasure, J. (2013). personality disorder. New York, NY: Guilford Press. Social and emotional processing as a behavioural endopheno- Liu, T., Maciejewski, P. K., & Potenza, M. N. (2009). The rela- type in eating disorders: A pilot investigation in twins. Euro- tionship between recreational gambling and substance abuse/ pean Eating Disorders Review, 21(4), 294–307. http://doi.org/10. dependence: Data from a nationally representative sample. 1002/erv.2232. Drug and Alcohol Dependence, 100(1–2), 164–168. http://doi. Kassel, J. D., Veilleux, J. C., Heinz, A. J., Braun, A. R., & Conrad, M. org/10.1016/j.drugalcdep.2008.09.011. (2013). Emotions and addictive processes. In P. Miller (Ed.), Liu, W., Peeters, N., Fernandez, G., & Kohn, N. (2020). Common Principles of addiction (1st ed., vol 1, pp. 213–222). San Diego; neural and transcriptional correlates of inhibitory control un- London; Walthan: Elseiver. derlie emotion regulation and memory control. Social Cognitive Kessler, E. M., & Staudinger, U. M. (2009). Affective experience in and Affective Neuroscience, 15(5), 523–536. http://doi.org/10. adulthood and old age: The role of affective arousal and 1093/scan/nsaa073. perceived affect regulation. Psychology and Aging, 24(2), 349– Lorenzetti, V., Melo, B., Basılio, R., Suo, C., Y€ ucel, M., Tierra- 362. http://doi.org/10.1037/a0015352. Criollo, C. J., et al. (2018). Emotion regulation using virtual Khakpoor, S., Saed, O., & Armani Kian, A. (2019). Emotion environments and real-time fMRI neurofeedback. Frontiers in regulation as the mediator of reductions in anxiety and Neurology, 9(JUL), 390. http://doi.org/10.3389/fneur.2018. depression in the Unified Protocol (UP) for transdiagnostic 00390. treatment of emotional disorders: Double-blind randomized Lutz, J., Herwig, U., Opialla, S., Hittmeyer, A., J€ancke, L., Rufer, M., clinical trial. Trends in Psychiatry and Psychotherapy, 41(3), et al. (2013). Mindfulness and emotion regulation-an fMRI 227–236. http://doi.org/10.1590/2237-6089-2018-0074. study. Social Cognitive and Affective Neuroscience, 9(6), 776– Kim, H. S., von Ranson, K. M., Hodgins, D. C., McGrath, D. S., & 785. http://doi.org/10.1093/scan/nst043. Tavares, H. (2018). Demographic, psychiatric, and personality Lynch, T. R., Hempel, R. J., & Dunkley, C. (2015). Radically open- correlates of adults seeking treatment for disordered gambling dialectical behavior therapy for disorders of over-control: with a comorbid binge/purge type eating disorder. European Signaling matters. American Journal of Psychotherapy, 692, Eating Disorders Review, 26(5), 508–518. http://doi.org/10. 141–162. http://doi.org/10.1176/appi.psychotherapy.2015.69.2. 1002/erv.2606. 141. Kolar, D. R., Neumayr, C., Roth, M., Voderholzer, U., Perthes, K., & Mallorquı-Bague, N., Mena-Moreno, T., Granero, R., Vintr o- Schlegl, S. (2019). Testing an emotion regulation model of Alcaraz, C., Sanchez-Gonzalez, J., Fernandez-Aranda, F., et al. physical activity in adolescents with anorexia nervosa: A pilot (2018). Suicidal ideation and history of suicide attempts in Unauthenticated | Downloaded 11/25/22 04:08 PM UTC 522 Journal of Behavioral Addictions 10 (2021) 3, 508–523 treatment-seeking patients with gambling disorder: The role of therapeutic outcomes for adults with anorexia nervosa? Eur Eat emotion dysregulation and high trait impulsivity. Journal of Disorders Rev, 26(4), 346–359. Behavioral Addictions, 7(4), 1112–1121. http://doi.org/10.1556/ Opialla, S., Lutz, J., Scherpiet, S., Hittmeyer, A., J€ancke, L., Rufer, 2006.7.2018.132. M., et al. (2014). Neural circuits of emotion regulation: A Mallorquı-Bague, N., Testa, G., Lozano-Madrid, M., Vintr o- comparison of mindfulness-based and cognitive reappraisal Alcaraz, C., Sanchez, I., Riesco, N., et al. (2020). Emotional and strategies. European Archives of Psychiatry and Clinical non-emotional facets of impulsivity in eating disorders: From Neuroscience, 265(1), 45–55. http://doi.org/10.1007/s00406- anorexia nervosa to bulimic spectrum disorders. European 014-0510-z. Eating Disorders Review, 28(4), 410–422. http://doi.org/10. Pettorruso, M., Valle, S., Cavic, E., Martinotti, G., di Giannantonio, 1002/erv.2734. M., & Grant, J. E. (2020). Problematic Internet use (PIU), Mallorquı-Bague, N., Vintro-Alcaraz, C., Sanchez, I., Riesco, N., personality profiles and emotion dysregulation in a cohort of Ag€uera, Z., Granero, R., et al. (2018). Emotion regulation as a young adults: Trajectories from risky behaviors to addiction. transdiagnostic feature among eating disorders: Cross-sectional Psychiatry Research, 289. http://doi.org/10.1016/j.psychres. and longitudinal approach. European Eating Disorders Review, 2020.113036. 26(1), 53–61. http://doi.org/10.1002/erv.2570. Phillips, L. H., Henry, J. D., Hosie, J. A., & Milne, A. B. (2008). Maniaci, G., Picone, F., van Holst, R. J., Bolloni, C., Scardina, S., & Effective regulation of the experience and expression of nega- Cannizzaro, C. (2017). Alterations in the emotional regulation tive affect in old age. Journals of Gerontology: Series B, 63(3), process in gambling addiction: The role of anger and alex- 138–145. ithymia. Journal of Gambling Studies, 33(2), 633–647. http:// Plaza, I., Demarzo, M. M. P., Herrera-Mercadal, P., & Garcıa- doi.org/10.1007/s10899-016-9636-4. Campayo, J. (2013). Mindfulness-based mobile applications: Mena-Moreno, T., Mestre-Bach, G., Munguıa, L., Ag€ uera, Z., Literature review and analysis of current features. JMIR Fernandez-Aranda, F., & Jimenez-Murcia, S. (2019). O Jogo mHealth and uHealth, 1(2), e24. http://doi.org/10.2196/ online como recurso psicoterap^eutico nas depend^encias. In I. mhealth.2733. Patr~ao & I. Leal (Eds.), Intervenç~ao em Ciberpsicologia (pp. Potenza, M. N., Steinberg, M. A., McLaughlin, S. D., Rounsaville, B. 251–266). Lisboa: Pactor. J., & O’Malley, S. S. (2000). Illegal behaviors in problem Mikhail, M. E., & Kring, A. M. (2019). Emotion regulation strategy gambling: Analysis of data from a gambling helpline. Journal of use and eating disorder symptoms in daily life. Eating Behav- the American Academy of Psychiatry and the Law, 28(4), 389– iors, 34. http://doi.org/10.1016/j.eatbeh.2019.101315. 403. Monell, E., Clinton, D., & Birgeg ard, A. (2018). Emotion dys- Potenza, M. N., Steinberg, M. A., McLaughlin, S. D., Wu, R., regulation and eating disorders—Associations with diag- Rounsaville, B. J., & O’Malley, S. S. (2001). Gender-related dif- nostic presentation and key symptoms. International Journal ferences in the characteristics of problem gamblers using a of Eating Disorders, 51(8), 921–930. http://doi.org/10.1002/ gambling helpline. American Journal of Psychiatry, 158(9), 1500– eat.22925. 1505. http://doi.org/https://doi.org/10.1176/appi.ajp.158.9.1500. Navas, J. F., Contreras-Rodrıguez, O., Verdejo-Roman, J., Raschle, N. M., Fehlbaum, L. V., Menks, W. M., Martinelli, A., Perandres-Gomez, A., Albein-Urios, N., Verdejo-Garcıa, A., Pr€atzlich, M., Bernhard, A., et al. (2019). Atypical dorsolateral et al. (2017). Trait and neurobiological underpinnings of prefrontal activity in female adolescents with conduct disorder negative emotion regulation in gambling disorder. Addiction, during effortful emotion regulation. Biological Psychiatry: 112(6), 1086–1094. http://doi.org/10.1111/add.13751. Cognitive Neuroscience and Neuroimaging, 4(11), 984–994. Neacsiu, A. D., Eberle, J. W., Kramer, R., Wiesmann, T., & Linehan, http://doi.org/10.1016/j.bpsc.2019.05.003. M. M. (2014). Dialectical behavior therapy skills for trans- Reed, G. M., First, M. B., Kogan, C. S., Hyman, S. E., Gureje, O., diagnostic emotion dysregulation: A pilot randomized Gaebel, W., et al. (2019). Innovations and changes in the ICD- controlled trial. Behaviour Research and Therapy, 59, 40–51. 11 classification of mental, behavioural and neuro- http://doi.org/10.1016/j.brat.2014.05.005. developmental disorders. World Psychiatry, 18(1), 3–19. http:// Nelson, B., McGorry, P. D., & Fernandez, A. V. (2020). Integrating doi.org/10.1002/wps.20611. clinical staging and phenomenological psychopathology to add Reinholt, N., & Krogh, J. (2014). Efficacy of transdiagnostic depth, nuance, and utility to clinical phenotyping: A heuristic cognitive behaviour therapy for anxiety disorders: A systematic challenge. The Lancet Psychiatry, 8(2), 162–168. http://doi.org/ review and meta-analysis of published outcome studies. 10.1016/s2215-0366(20)30316-3. Cognitive Behaviour Therapy, 43(3), 171–184. Nicholls, W., Devonport, T. J., & Blake, M. (2016). The association Rodrıguez-Cano, T., Beato-Fernandez, L., Rojo-Moreno, L., & Vaz- between emotions and eating behaviour in an obese population Leal, F. J. (2014). The role of temperament and character in the with binge eating disorder. Obesity Reviews, 17(1), 30–42. outcome of depressive mood in eating disorders. Comprehen- http://doi.org/10.1111/obr.12329. sive Psychiatry, 55(5), 1130–1136. http://doi.org/10.1016/j. Norton, P. J., & Paulus, D. J. (2016). Toward a unified treatment for comppsych.2014.02.009. emotional disorders: Update on the science and practice. Roemer, L., Orsillo, S. M., & Salters-Pedneault, K. (2008). Efficacy Behavior Therapy, 476, 854–868. http://doi.org/10.1016/j.beth. of an acceptance-based behavior therapy for generalized anxiety 2015.07.002. disorder: Evaluation in a randomized controlled trial. Journal of Oldershaw, A., Lavender, T., & Schmidt, U. (2018). Are socio- Consulting and Clinical Psychology, 76(6), 1083–1089. http:// emotional and neurocognitive functioning predictors of doi.org/10.1037/a0012720. Unauthenticated | Downloaded 11/25/22 04:08 PM UTC Journal of Behavioral Addictions 10 (2021) 3, 508–523 523 Rousseeuw, P. J. (1987). Silhouettes: A graphical aid to the inter- Frontiers in Psychology, 6, 1721. http://doi.org/10.3389/fpsyg. pretation and validation of cluster analysis. Journal of 2015.01721. Computational and Applied Mathematics, 20, 53–65. http://doi. Tchanturia, K., Doris, E., Mountford, V., & Fleming, C. (2015). org/10.1016/0377-0427(87)90125-7. Cognitive remediation and emotion skills training (CREST) for Sala, M., Vanzhula, I. A., & Levinson, C. A. (2018). A longitudinal anorexia nervosa in individual format: Self-reported outcomes. study on the association between facets of mindfulness and BMC Psychiatry, 15(53). http://doi.org/10.1186/s12888-015- eating disorder symptoms in individuals diagnosed with eating 0434-9. disorders. Eur. Eat. Disorders Rev., 27(3), 295–305. Torgo, L., & da Costa, J. P. (2000). Clustered multiple regression. In Sancho, M., de Gracia, M., Granero, R., Gonzalez-Simarro, S., H. A. L. Kiers, J. Rasson, P. J. F. Groenen, & M. Schader (Eds.), Sanchez, I., Fernandez-Aranda, F., et al. (2019). Differences in Data analysis, classification, and related methods. Studies in emotion regulation considering gender, age, and gambling classification, data analysis, and knowledge organization (pp. preferences in a sample of gambling disorder patients. Frontiers 217–222). Berlin, Heidelberg: Springer. http://doi.org/10.1007/ in Psychiatry, 10. http://doi.org/10.3389/fpsyt.2019.00625. 978-3-642-59789-3_35. Shah, J. L., Scott, J., McGorry, P. D., Cross, S. P. M., Keshavan, M. S., Treasure, J., Duarte, T. A., & Schmidt, U. (2020). Eating disorders. Nelson, B., et al. (2020). Transdiagnostic clinical staging in youth The lancet. Lancet Publishing Group. http://doi.org/10.1016/ mental health: A first international consensus statement. World S0140-6736(20)30059-3. Psychiatry, 19(2), 233–242. http://doi.org/10.1002/wps.20745. Van Zutphen, L., Siep, N., Jacob, G. A., Domes, G., Sprenger, A., Sloan, E., Hall, K., Moulding, R., Bryce, S., Mildred, H., & Staiger, P. Willenborg, B., . . . Arntz, A. (2018). Always on guard: Emotion K. (2017). Emotion regulation as a transdiagnostic treatment regulation in women with borderline personality disorder construct across anxiety, depression, substance, eating and compared to nonpatient controls and patients with cluster-C borderline personality disorders: A systematic review. Clinical personality disorder. Journal of Psychiatry & Neuroscience, Psychology Review, 57, 141–163. http://doi.org/10.1016/j.cpr. 43(1), 37–47. http://doi.org/10.1503/jpn.170008. 2017.09.002. Von Ranson, K. M., Wallace, L. M., Holub, A., & Hodgins, D. C. Steward, T., Martınez-Zalacaın, I., Mestre-Bach, G., Sanchez, I., (2013). Eating disorders, substance use disorders, and impul- Riesco, N., Jimenez-Murcia, S., et al. (2020) (In press). Dorso- siveness among disordered gamblers in a community sample. lateral prefrontal cortex and amygdala function during cogni- European Eating Disorders Review, 21(2), 148–154. http://doi. tive reappraisal predicts weight restoration and emotion org/10.1002/erv.2207. regulation impairment in anorexia nervosa. Psychological Williams, A. D., Grisham, J. R., Erskine, A., & Cassedy, E. (2012). Medicine, 1–9. http://doi.org/10.1017/s0033291720002457. Deficits in emotion regulation associated with pathological Steward, T., Pico-Perez, M., Mestre-Bach, G., Martınez-Zalacaın, I., gambling. British Journal of Clinical Psychology, 51(2), 223–238. Su~nol, M., Jimenez-Murcia, S., et al. (2019). A multimodal MRI http://doi.org/10.1111/j.2044-8260.2011.02022.x. study of the neural mechanisms of emotion regulation impair- Wolz, I., Ag€uera, Z., Granero, R., Jimenez-Murcia, S., Gratz, K. L., ment in women with obesity. Translational Psychiatry, 9(1), 194. Mench on, J. M., et al. (2015). Emotion regulation in disordered http://doi.org/10.1038/s41398-019-0533-3. eating: Psychometric properties of the difficulties in emotion Stinchfield, R. (2003). Reliability, validity, and classification accu- regulation scale among Spanish adults and its interrelations racy of a measure of DSM-IV diagnostic criteria for patholog- with personality and clinical severity. Frontiers in Psychology, 6. ical gambling. American Journal of Psychiatry, 160, 180–182. http://doi.org/10.3389/fpsyg.2015.00907. http://doi.org/10.1176/appi.ajp.160.1.180. Zimmer-Gembeck, M. J., & Skinner, E. A. (2011). Review: The Tarrega, S., Castro-Carreras, L., Fernandez-Aranda, F., Granero, R., development of coping across childhood and adolescence: An Giner-Bartolome, C., Aymamı, N., et al. (2015). A serious integrative review and critique of research. International Jour- videogame as an additional therapy tool for training emotional nal of Behavioral Development, 35(1), 1–17. http://doi.org/10. regulation and impulsivity control in severe gambling disorder. 1177/0165025410384923. Open Access. This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (https:// creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted use, distribution, and reproduction in any medium for non-commercial purposes, provided the original author and source are credited, a link to the CC License is provided, and changes – if any – are indicated. Unauthenticated | Downloaded 11/25/22 04:08 PM UTC