ORIGINAL RESEARCH published: 14 December 2021 doi: 10.3389/fpsyg.2021.761802 Does Confinement Affect Treatment Dropout Rates in Patients With Gambling Disorder? A Nine-Month Observational Study Isabel Baenas 1,2, Mikel Etxandi 1, Ester Codina 1, Roser Granero 2,3, Fernando Fernández- Aranda 1,2,4,5, Mónica Gómez-Peña 1, Laura Moragas 1, Sandra Rivas 1, Marc N. Potenza 6,7,8,9, Anders Håkansson 10,11, Amparo del Pino-Gutiérrez 2,12, Bernat Mora-Maltas 1, Eduardo Valenciano-Mendoza 1, José M. Menchón 1,4,5,13 and Susana Jiménez-Murcia 1,2,4,5* 1 Department of Psychiatry, Bellvitge University Hospital-IDIBELL, Barcelona, Spain, 2 Ciber Fisiopatología Obesidad y Nutrición (CIBERObn), Instituto de Salud Carlos III, Madrid, Spain, 3 Department of Psychobiology and Methodology, Autonomous University of Barcelona, Barcelona, Spain, 4 Department of Clinical Sciences, School of Medicine, University of Barcelona, Barcelona, Spain, 5 Psychiatry and Mental Health Group, Neurosciences Programme, Instituto de Investigación Edited by: Biomédica de Bellvitge (IDIBELL), Barcelona, Spain, 6 Department of Psychiatry and Child Study Center, Yale University Tobias Hayer, School of Medicine, New Haven, CT, United States, 7 Connecticut Council on Problem Gambling, Wethersfield, CT, University of Bremen, Germany United States, 8 Connecticut Mental Health Center, New Haven, CT, United States, 9 Department of Neuroscience, Yale Reviewed by: University, New Haven, CT, United States, 10 Department of Clinical Sciences Lund, Psychiatry, Faculty of Medicine, Lund Davinia M. Resurrección, University, Lund, Sweden, 11 Region Skåne, Gambling Disorder Unit, Malmö, Sweden, 12 Department of Public Health, Mental Universidad Loyola Andalucía, Spain Health and Perinatal Nursing, School of Nursing, University of Barcelona, Barcelona, Spain, 13 Ciber Salut Mental Juan Francisco Rodríguez-Testal, (CIBERSAM), Instituto de Salud Carlos III, Madrid, Spain Sevilla University, Spain *Correspondence: Susana Jiménez-Murcia Background and Aims: COVID-19 pandemic and confinement have represented a sjimenez@bellvitgehospital.cat challenge for patients with gambling disorder (GD). Regarding treatment outcome, dropout may have been influenced by these adverse circumstances. The aims of this study were: Specialty section: This article was submitted to (a) to analyze treatment dropout rates in patients with GD throughout two periods: during Psychology for Clinical Settings, and after the lockdown and (b) to assess clinical features that could represent vulnerability a section of the journal factors for treatment dropout. Frontiers in Psychology Received: 20 August 2021 Methods: The sample consisted of n = 86 adults, mostly men (n = 79, 91.9%) and with Accepted: 11 November 2021 a mean age of 45 years old (SD = 16.85). Patients were diagnosed with GD according to Published: 14 December 2021 DSM-5 criteria and were undergoing therapy at a Behavioral Addiction Unit when Citation: Baenas I, Etxandi M, Codina E, confinement started. Clinical data were collected through a semi-structured interview and Granero R, Fernández-Aranda F, protocolized psychometric assessment. A brief telephone survey related to COVID-19 Gómez-Peña M, Moragas L, Rivas S, Potenza MN, Håkansson A, concerns was also administered at the beginning of the lockdown. Dropout data were del Pino-Gutiérrez A, Mora-Maltas B, evaluated at two moments throughout a nine-month observational period (T1: during the Valenciano-Mendoza E, lockdown, and T2: after the lockdown). Menchón JM and Jiménez-Murcia S (2021) Does Results: The risk of dropout during the complete observational period was R = 32/86 = 0.372 Confinement Affect Treatment Dropout Rates in Patients With (37.2%), the Incidence Density Rate (IDR) ratio T2/T1 being equal to 0.052/0.033 = 1.60 Gambling Disorder? A Nine-Month (p = 0.252). Shorter treatment duration (p = 0.007), lower anxiety (p = 0.025), depressive Observational Study. Front. Psychol. 12:761802. symptoms (p = 0.045) and lower use of adaptive coping strategies (p = 0.046) characterized doi: 10.3389/fpsyg.2021.761802 patients who abandoned treatment during the lockdown. Briefer duration of treatment Frontiers in Psychology | www.frontiersin.org 1 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout (p = 0.001) and higher employment concerns (p = 0.044) were highlighted in the individuals who dropped out after the lockdown. Treatment duration was a predictor of dropout in both periods (p = 0.005 and p < 0.001, respectively). Conclusion: The present results suggest an impact of the COVID-19 pandemic on treatment dropout among patients with GD during and after the lockdown, being treatment duration a predictor of dropout. Assessing vulnerability features in GD may help clinicians identify high-risk individuals and enhance prevention and treatment approaches in future similar situations. Keywords: COVID-19, confinement, gambling disorder, dropout, coping INTRODUCTION activity, could be used to cope with psychological distress (Asmundson and Taylor, 2020; Rajkumar, 2020; Fernández- The COVID-19 pandemic, declared as a public health emergency Aranda et al., 2020a; Avena et al., 2021), specifically in individuals by the World Health Organization [World Health Organization with higher vulnerability (e.g., those with a mental illness; (WHO), 2020], has affected more than 200 countries around Fernández-Aranda et al., 2020a; Baenas et al., 2020). the world since the first case appeared in Wuhan (China) in During confinement, the use of technologies has extended December 2019 (Yuki et al., 2020). Spain has been considered to more aspects of daily life. Hence, excessive engagement in one of the most affected countries by this pandemic since the specific online activities, such as gambling, may lead to severe early stages. Its first case of infection was reported within the problems and increases the risk of a disordered or addictive first months of 2021, and since then, the number of cases use (King et al., 2020; Mestre-Bach et al., 2020). These maladaptive has continued to increase. Along with other European countries, behaviors are usually presented in combination with social such as Italy and France, Spain has presented one of the highest isolation and boredom, factors which have been also linked mortality rates due to the pandemic (Ceylan, 2020). to confinement and previously associated with the pathogenesis To control pandemic spread, confinement and other restrictive of GD (Ledgerwood and Petry, 2006; Mercer and Eastwood, measures have been stated everywhere (Hale et al., 2020), being 2010). On the other hand, the use of gambling has been also social distancing, disruption of daily routines, and economic stated as a mechanism to deal with adverse economic and employment uncertainty reported as some of the most circumstances in prior financial crises (Olason et al., 2015; frequent COVID-19-related concerns (Chew et al., 2020). This Economou et al., 2019). Similarly, economic difficulties due context alongside with health worries due to the pandemic to pandemic and confinement might represent a risk factor has led to an increase in anxiety and depressive symptoms that could favor gambling activity. Moreover, some works have among general population (Islam et al., 2020; Wang et al., described a risk profile for engaging in gambling behavior 2020). In this vein, people with a mental illness, such as during confinement (being young male regular gambler with gambling disorder (GD), have been considered at particularly high alcohol use prior to confinement; Håkansson, 2020a; high risk of suffering the psychological impact of the COVID-19 Emond et al., 2021; Hodgins and Stevens, 2021). In the pandemic (González-Sanguino et al., 2020; Özdin and Bayrak non-clinical study by Price (2020), online gambling modality Özdin, 2020; Rajkumar, 2020). was associated with the subgroup of gamblers at a higher risk GD is defined as engaging in a repeated compulsive gambling of developing GD, characterized by greater psychological impact behavior, accompanied by unsuccessful efforts to stop the behavior due to pandemic and substance use while gambling. In this and uncontrollable urges to keep gambling, which leads to line, gambling behavior prior to the pandemic predicted gambling considerable distress and impairment. This gambling behavior activity during confinement, mainly at the expense of online tends to persist over time despite negative consequences on the gambling (Gainsbury et al., 2020; Håkansson, 2020b; Emond person’s physical, mental, social, or financial well-being [American et al., 2021; Hodgins and Stevens, 2021). Psychiatry Association (APA), 2013]. GD was included within With reference to the potential of the pandemic worsening the “substance-related and addictive disorders” category in the gambling problems (King et al., 2020; Marsden et al., 2020), fifth edition of the Diagnostic and Statistical Manual of Mental legal measures have been adopted by governments in an attempt Disorders [DSM-5; American Psychiatry Association (APA), to minimize these consequences. For instance, in Spain, 2013]. It has been considered the most prevalent behavioral advertising related to gambling has been limited (SBC News, addiction, with a lifetime prevalence ranging from 1.1 to 10.6% 2020). Among other useful tools, a consensus guidance on (Calado and Griffiths, 2016). In Europe, epidemiological studies how to avoid problematic use of the internet during the have shown that gambling problems range from 0.3 to 3.3% pandemic has been also published (Király et al., 2020). In this (Dirección General de Ordenación del Juego (DGOJ) 2015). guidance, healthy general practices, such as those related to In the face of environmental changes, maladaptive coping exercise or sleep hygiene were recommended, as well as specific strategies and behaviors, such as those related to gambling tips regarding Internet use. Monitoring and regulating screen Frontiers in Psychology | www.frontiersin.org 2 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout time exposure in children and adults, using digital well-being 2015; Mallorquí-Bagué et al., 2018, 2019; Mestre-Bach apps and analogue technical tools, keeping social contact with et al., 2019). relatives and friends, or seeking professional help when needed So far, most published studies concerning gambling activity were highly advised (Király et al., 2020). during confinement focused on non-clinical populations (Auer Among people with GD, the challenges represented by the et al., 2020; Brown and Hickman, 2020; Gunstone et al., 2020; pandemic and confinement (Håkansson et al., 2020; King et al., Lindner et al., 2020; Zamboni et al., 2021). Scarce research 2020) were based on different vulnerability aspects (Allami on the effects of pandemic on GD treatment outcome and et al., 2021; Hodgins and Stevens, 2021). For instance, higher possible associated factors has been reported (Price, 2020; levels of anxiety, depressive symptoms and hostility have been Donati et al., 2021). Furthermore, information related to initial described in subjects with GD during confinement, in comparison stages of confinement provided a limited knowledge not only with the general population (Salerno and Pallanti, 2021). In regarding its longer-term impact, but also in distinguishing this context, gambling behavior could be conducted (and its effects during time periods characterized by different levels reinforced) to regulate emotions (Barrault et al., 2019), being of restrictive measures, such as the lockdown and the a trigger for relapse in those patients who remained abstinent following months. (Campbell, 2020). However, restrictive strategies and some To the best of our knowledge, this is the first observational policies adopted during confinement seemed to reduce gambling clinical study regarding the effect of the pandemic on GD opportunities, specifically at offline locations, promoting treatment outcome related to dropout rates among clinical abstinence (Donati et al., 2021). In this line, patients already population. The longitudinal nature of the present work favors in treatment for GD reported a positive attitude about restrictions reporting data comparing two well-established periods of time due to pandemic and related to gambling activity, with improved across confinement (i.e., during and after the lockdown). Finally, social and familiar environments. This positive social the already existing involvement of these patients with the reinforcement also contributed to maintain abstinence. treatment Unit and a suitable observational period allow for Interestingly, large-scale migration from offline to online gambling evaluating clinical features possibly associated with dropout. has not been observed so far among patients with GD during Thus, the main aims of this study were to analyze treatment confinement (Donati et al., 2021). dropout rates in patients with GD in the two established Works regarding GD treatment during confinement did not periods, and assess clinical features that would be linked to report an increase in treatment-seeking for GD, at least in treatment dropout in both periods. the short term (Gunstone et al., 2020; Donati et al., 2021; Håkansson et al., 2021). When talking about GD treatment, cognitive-behavioral therapy (CBT) and group-based modalities MATERIALS AND METHODS have been widely demonstrated as effective options for the management of this disorder (Gooding and Tarrier, 2009; Participants Cowlishaw et al., 2012; Jiménez-Murcia et al., 2015). Besides, The sample consisted of n = 86 adults, mostly men (n = 79, internet-based treatments for GD demonstrated similar efficacy 91.9%) and with a mean age of 45 years old (SD = 16.85). to traditional treatments (Hedman et al., 2012; Chakrabarti, Participants had been diagnosed according to DSM-5 criteria 2015). Trying more flexible approaches to patient care in the [American Psychiatry Association (APA), 2013] and were face of pandemic situation (Marsden et al., 2020), tele-psychiatry voluntarily recruited in the region of Catalonia (Spain), specifically has shown to be helpful (Hollander and Carr, 2020) and at the Behavioral Addiction Unit within the Psychiatry internet-based tools for GD have been used in some treatment Department of a Public University Hospital in Barcelona (Spain). facilities during confinement (Columb et al., 2020). All the patients recruited in the present study were already Within the treatment outcome in GD, dropout has been enrolled in the outpatient treatment program when confinement defined as leaving before the completion of a predetermined started. The mean duration of treatment at this point, considering program (Milton et al., 2002; Robson et al., 2002). Despite therapy phase and follow-up was 14.3 months (SD = 9.2 months) a broad dropout range (14–50%) reported by previous national and around 10.5% (n = 9) were not abstinent before the lockdown. and international studies (Melville et al., 2007; Smith et al., The outpatient treatment program offered in the Unit 2010; Jimenez-Murcia et al., 2012), an average of around was based on a standardized protocol (Jiménez-Murcia et al., 26% has been agreed (Melville et al., 2007). Prior to 2006). It has shown adequate effectiveness for GD in both confinement, a recent national study (Jiménez-Murcia et al., short- and medium-terms, and has been widely described 2019) reported dropout rates of 32.4% among patients with in previous Unit’s studies related to treatment of GD (Jiménez- GD regarding clinical trajectories based on GD severity Murcia et al., 2006, 2007, 2019; Jimenez-Murcia et al., 2012). among patients following a 12 months manualized CBT It comprised (a) two initial baseline assessment visits, (b) program. Features such as patients’ medical or family issues, CBT group therapy phase, and (c) a post-therapy follow-up. length of therapy, personality traits (e.g., perseverance, reward In the sessions prior to the treatment phase, a semi-structured sensitivity, sensation-seeking), younger age, lower educational clinical interview was conducted by expert psychologists level, and neurocognitive variables, among others, have been and psychiatrists of our Unit with high experience in the studied as potential predictors of treatment dropout (Melville field of behavioral addictions (SCID-5; First et al., 2015). et al., 2007; Álvarez-Moya et al., 2011; Jiménez-Murcia et al., Moreover, a protocolized psychometric assessment was also Frontiers in Psychology | www.frontiersin.org 3 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout completed in a second session lasting about 90 min (Jiménez- Assessments Murcia et al., 2006). The treatment phase was composed At Baseline of 16 weekly sessions with a mean duration of 90 min per South Oaks Gambling Screen (SOGS; Lesieur and Blume, 1987): session, conducted by an experienced clinical psychologist. a 20-item instrument for screening for past-year gambling The main treatment objective was training patients to put problems and related negative consequences. The total score into practice CBT strategies to achieve full and definitive obtained as the sum of the scored items has been used as a abstinence from gambling. Among other techniques, measure of problem-gambling severity, with a score of 5 or psychoeducation, stimulus control, response prevention, more suggestive of “probable pathological gambling.” The Spanish cognitive restructuring, reinforcement and self-reinforcement, validation of the scale achieved very good psychometric results skills training, and relapse-prevention techniques were used. (test–retest reliability R = 0.98, internal consistency α = 0.94 and Once completed, a post-treatment evaluation was performed, convergent validity R = 0.92; Echeburúa et al., 1994). The internal and a 24-month follow-up was initiated before being discharged consistency for this scale in the study sample was good (α = 0.74). from the Unit. The therapists recorded dropouts and relapses Diagnostic Questionnaire for Pathological Gambling According based on patients’ oral reports and written diaries and to DSM criteria (Stinchfield, 2003): a self-report questionnaire relatives’ collateral information. The presence of a co-therapist with 19 items coded in a binary scale (yes-no), used for (e.g., partner, family member, and close friend) was diagnosing GD according to the DSM-IV-TR [American highly recommended. Psychiatry Association (APA), 2000] and DSM-5 [American Psychiatry Association (APA), 2013] criteria. The Spanish Contextual Setting Due to the Pandemic adaptation of the questionnaire obtained satisfactory psychometric The officially established COVID-19 lockdown period in the properties (Cronbach’s alpha α = 0.81 for a population-based region of Catalonia (Spain) extended from March 14 to May sample and α = 0.77 for a clinical sample; Jiménez-Murcia et al., 11, 2020. This period was characterized by a stay-at-home 2009). The internal consistency for this scale in the study policy with measures such as the interruption of all non-essential sample was good (α = 0.83). work, academic, social and leisure activities outside. The coverage Symptom Checklist-90-Revised (SCL-90-R; Derogatis, 1990): of basic products was guaranteed, as well as emergency a 90-item self-report questionnaire measured on an ordinal medical assistance. 3-point scale. It evaluates a broad range of psychological During the nine-month observational period of the present problems and psychopathology, based on nine primary symptom study, the described treatment schedule was maintained in dimensions (Somatization, Obsession-Compulsion, Interpersonal each case. However, specific modifications were carried out Sensitivity, Depression, Anxiety, Hostility, Phobic Anxiety, due to the pandemic situation and restrictive measures. During Paranoid Ideation, and Psychoticism). It includes three global the lockdown (i.e., March 14, 2020–May 11, 2020), face-to-face indices (global severity index, positive symptom distress index, treatment was adapted to virtual modality using internet-based and total positive symptom). The validation of the scale in a tools. Tutorial information was provided to guarantee accessibility Spanish population (Derogatis, 2002) obtained a mean internal and a proper use. Eventually, the presence of the co-therapist consistency of α = 0.75. The internal consistency in the study was also ensured. After the lockdown, usual face-to-face treatment was between good (α = 0.77 for paranoid ideation) to excellent was resumed (i.e., after May 11, 2020). (α = 0.98 for global indexes). Temperament and Character Inventory-Revised (TCI-R; Procedure Cloninger, 1999): a questionnaire with 240-items scored on a All the assessments apart from the Brief Telephone Survey 5-point Likert scale and measuring personality derived from related to COVID-19 (Behavioral Addictions Unit, Psychiatry three character dimensions (Self-Directedness, Cooperativeness, Department, University Hospital, Barcelona, Spain, 2020) were and Self-Transcendence) and four temperament dimensions part of the standardized assessment within the Unit’s treatment (Harm Avoidance, Novelty Seeking, Reward Dependence, and program previously described (Jiménez-Murcia et al., 2006), Persistence). Evaluation of the Spanish revised version (Gutiérrez- and contemplated in other studies related to treatment of GD Zotes et al., 2004) had an internal consistency of α = 0.87. (Jiménez-Murcia et al., 2006, 2007, 2019; Jimenez-Murcia We obtained verbal consent from the author for using the et al., 2012). TCI-R questionnaire in a public non-profit hospital and The Brief Telephone Survey related to COVID-19 was obtained exclusively linked to the field of research. This questionnaire in the first therapeutic contact with each patient within the was administered in its Spanish adaptation, in which the original first 2 months of confinement in Spain (i.e., lockdown period), author participated (Gutiérrez-Zotes et al., 2004). The internal mostly at the beginning of the lockdown. Over the nine-month consistency in the study was between good (α = 0.72 for novelty observational period of this study, information regarding dropout seeking) to excellent (α = 0.90 for persistence). (bivariant dropout/non-dropout) was collected by reviewing Other variables: Additional data (e.g., socio-demographic, therapists’ clinical reports. Two dropout periods were and socio-economic) were measured. They were collected in distinguished: (T1) between March 14 and May 11 (i.e., during a semi-structured face-to-face clinical interview as described the lockdown), and (T2) between May 12 and December 31, elsewhere (Jiménez-Murcia et al., 2006). Disorder-related 2020 (i.e., after the lockdown). variables such as the age of onset and duration of GD were Frontiers in Psychology | www.frontiersin.org 4 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout also assessed. Some variables were updated during the lockdown is the product of the person-time of the at-risk sample, and period as part of the Brief Telephone Survey, as it was therefore this measurement is not dependent on the duration described below. of the observational period. Next, chi-square tests (χ2) were evaluated comparisons between At Lockdown groups for categorical variables, and T-TEST for quantitative Brief Telephone Survey (Behavioral Addictions Unit, Psychiatry measures. For these analyses, Cohen’s h coefficients measured Department, University Hospital, Barcelona, Spain, 2020). A effect sizes for proportion comparisons and Cohen’s d for mean binary qualitative scale (yes/no) was employed to answer most comparisons (null effect size was considered for values |h| < 0.20 of the points although some questions were open-ended. The or |d| < 0.20, low-poor for |h| > 0.20 or |d| > 0.20, moderate- different sections of the survey are described as follows: medium for |h| > 0.50 or |d| > 0.50, and large-high for |h| > 0.80 a. Socio-demographics in the lockdown situation: (1) or |d| > 0.80; Cohen, 1988; Kelley and Preacher, 2012). In employment status, (2) working during confinement, (3) addition, the Finner’s-method (a family-wise error rate stepwise being confined and since when with reference to the beginning procedure, a less stringent approach than a conservative of the lockdown period, (4) affected close people by COVID- Bonferroni correction) was used to control Type-I error related 19, and (5) the presence of social support. to multiple comparisons (Finner and Roters, 2001). b. GD behaviors in the lockdown situation: (1) increased, Third, logistic regressions explored significant contributors reduced, or maintained GD symptoms versus abstinence for the risk of dropout during the observational period, state and (2) the presence of new symptoms related to GD considering as potential predictors socio-demographic not referred before the lockdown (e.g., different type of variables (sex, age, marital status, education, employment, gambling modality). and social position index), contextual variables during c. COVID-19-related concerns in the lockdown situation: (1) COVID-19-related confinement, GD-related measures at fear of infection, (2) uncertain future, (3) worries about baseline/prior to the confinement (age of onset and duration employment, and (4) difficulties in accessing to treatment. of gambling problems, and problem-gambling severity), d. Psychological state due to the pandemic (1) pandemic-related personality measures (TCI-R scores) and psychological distress anxiety at psychic, emotional, motor, and cognitive dimensions at baseline (SCL-90R GSI). These analyses used a stepwise (e.g., headaches, tachycardia, dizziness, nervousness, avoidance method to automatically select significant statistical predictors behaviors, recurrent thoughts, intrusions, and anticipation) separately for the risk of dropout during the lockdown (i.e., and (2) the presence of depressive-symptoms in the lockdown T1) and after the lockdown (i.e., T2). situation (e.g., presence of hopelessness, pessimism, discouragement, sleepiness, indifference, lack of illusion, crying, social/communicative isolation, and passive thoughts of death). RESULTS e. Questions about other items, such as (1) boredom, (2) frequent arguments with cohabitants, family, friends, and Characteristics of the Sample (3) receiving and looking for continuous information on Most participants were men (91.9%), employed (53.5%) and COVID-19 were also included. within mean-low to low social position indexes (75.5%). Many f. Finally, coping strategies during confinement were evaluated were single (44.4%) or married (43.0%), with primary (45.3%) in two ways: (1) as the presence or absence of both adaptive or secondary (40.7%) education levels. The mean age was and maladaptive mechanisms (yes/no) and (2) the kind of 45.0 years (SD = 16.9), mean age of onset of GD was 31.8 years strategies used, categorizing the coping mechanisms in five (SD = 12.7) and mean duration of GD was 6.2 years (SD = 7.8). dimensions for adaptive strategies (i.e., social contact, leisure, The most frequently acknowledged preferred gambling form sporting activities, daily routines, and academic/work activity) was non-strategic [46.5%, followed by strategic (33.7%), and and three related to maladaptive ones (i.e., obtaining too mixed (19.8%)], and preferred gambling locations was through much COVID-19-related information; behaviors related to offline platforms (66.3%). Table 1 includes the complete GD and other maladaptive behaviors, such as substance use). description for the variables of the study measured at baseline, prior to the COVID-19-related confinement. Statistical Analysis Statistical analysis was conducted with Stata17 for Windows Environmental Contextual Factors During (StateCorp, 2021). First, the incidence density rate (IDR, also COVID-19-Related Confinement called the person-time incidence rate) of dropout and relapse Table 2 includes the frequency distribution of the variables was estimated, and comparison between the periods T1 (i.e., assessing contextual environment and personal measures during during the lockdown) and T2 (i.e., after the lockdown) were the COVID-19-related confinement. The percentage of performed. IDR is the measure of the frequency with which participants reporting working was 25.6%, while 89.5% lived the event occurs (in the study dropout and gambling-episodes) with other people, and 5.8% indicated an affected close people over a specified period. The denominator of this estimation by COVID-19. Frontiers in Psychology | www.frontiersin.org 5 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout TABLE 1 | Socio-demographics and clinical features (n = 86). Socio-demographics n % Clinical features Mean SD Gender Male 79 91.9% Onset of GD (yrs.) 31.77 12.67 Female 7 8.1% Duration of GD (yrs.) 6.21 7.78 Marital status Single 38 44.2% Duration of treatment and 14.29 9.19 follow-up (months) Married - in a couple 37 43.0% 1 SOGS total score 10.73 3.23 Divorced - separated 11 12.8% 1 DSM-5 total criteria 7.05 2.11 Education Primary/less 39 45.3% SCL-90R: Somatization 0.95 0.82 Secondary 35 40.7% SCL-90R: Obsess. / 1.21 0.81 Compulsive University 12 14.0% SCL-90R: Interpersonal 1.05 0.85 sensitivity Social position High / mean-high 12 14.0% SCL-90R: Depressive 1.53 0.95 Mean 9 10.5% SCL-90R: Anxiety 0.98 0.79 Mean-low 31 36.0% SCL-90R: Hostility 0.96 0.88 Low 34 39.5% SCL-90R: Phobic anxiety 0.45 0.75 Employment Unemployed 40 46.5% SCL-90R: Paranoid 0.91 0.76 Ideation Employed 46 53.5% SCL-90R: Psychotic 0.98 0.81 Age (yrs.); mean-SD 45.00 16.85 SCL-90R: PST score 1.07 0.71 n % SCL-90R: GSI score 46.27 21.59 Gambling-related variables Gambling type Non-strategic 40 46.5% SCL-90R: PSDI score 1.91 0.64 Strategic 29 33.7% TCI-R: Novelty seeking 111.72 11.96 Mixed 17 19.8% TCI-R: Harm avoidance 98.72 14.01 Modality Offline 57 66.3% TCI-R: Reward 97.09 13.50 dependence Online 12 14.0% TCI-R: Persistence 107.87 18.69 Mixed 17 19.8% TCI-R: Self-directedness 129.92 19.65 Treatment Individual 27 31.4% TCI-R: Cooperativeness 128.98 15.36 Group 59 68.6% TCI-R: Self- 59.94 11.77 Transcendence SD: standard deviation. GD: gambling disorder. The percentage of participants reporting COVID-19-related (dash-line) the inverse 1-cumulative survival function. The concerns was 67.4%. Most patients employed adaptive reactions cumulate survival function estimates the proportion of patients (74.4%), while 22.1% reported maladaptive reactions. The surviving in treatment (without dropout) for certain amounts presence of anxiety symptoms was reported by 25.6% of the of time. The inverse curve (1-cumulative survival function) participants, and depressive symptoms by 19.8%. Family conflicts plots the cumulate proportion of dropouts during the due to confinement were reported by 9.3% of participants. observational period. The shape of the cumulate survival function, in the form of regular jumps/rectangles during the period March–July suggested that most dropouts were observed during Factors Contributing to Dropout During this period, (concretely, 31.4% of participants had abandoned the Observational Period during these months). The remaining 5.8% of dropouts were The risk of dropout during the complete observational period registered during the following months (August–December). was R = 32/86 = 0.372 (37.2%), and the IDR was 0.045 per person The frequency of relapses was very low during the complete month (4.5 patients dropped out per 100 participants-month). observational period. Figure 3 contains the bar-chart with the Considering separately the two periods of time of the IDR of gambling episodes in the study. The lowest IDR was observational period (Figure 1), IDR increased from 0.033 registered during the lockdown period (1.2 patients reported (3.3 individuals dropped out per 100 participants-month) at relapses per 100 participants-month), followed by the post- T1 to 0.052 (5.2 dropped out per 100 participants-month) at lockdown stage (1.3 patients reported relapses per 100 T2, the IDR ratio being equal to 0.052/0.033 = 1.60 (p = 0.252). participants-month). Compared with the period prior to when Figure 2 shows the survival functions (Kaplan–Meier product- confinement started (IDR = 0.037 at baseline, 3.7 relapses per limit estimator) for dropouts, considering the period from the 100 participants-month), the probability of relapses during the regional COVID-19-related the lockdown and the end of the lockdown was 3.11 times lower (p = 0.049), and after the observational period (March 2020–December 2020). The curve lockdown the probability of relapses was 2.87 times lower in the upper part of the figure (continuous-line) represents (p = 0.041). No statistical differences was observed comparing the cumulative survival function, and the lower curve the IDR during and after the lockdown (p = 0.941). Frontiers in Psychology | www.frontiersin.org 6 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout TABLE 2 | Descriptive variables related to confinement during the COVID-19 Table 3 shows the bivariate comparisons between the groups pandemic. defined based on the dropouts (non-dropout versus dropout) n % n % for the variables of the study (socio-demographics, gambling related measures, clinical profile, and those variables collected Working 22 25.6% Non-adaptive 19 22.1% via the Brief Telephone Survey). Separate analyses were performed reactions for the T1 and T2 stages. Variables related to the increase in With company 77 89.5% Non-adaptive 11 12.8% the risk of dropout during T1 were male sex, higher education reactions: COVID Affected close people 5 5.8% Non-adaptive 1 1.2% levels, higher social position indexes, lower SCL-90R anxiety by COVID reactions: GD and psychotic scores, lower use of adaptive and non-adaptive COVID-related 58 67.4% Non-adaptive 7 8.1% reactions, and lower level of anxiety and depression symptoms concerns reactions: Other due to pandemic. Online gambling was a protective factor for Concerns: infection 35 40.7% Anxiety (any type) 22 25.6% dropout during T1. Variables contributing to increase the risk risk Concerns: uncertain 34 39.5% Anxiety: physic 10 11.6% of dropout during T2 were shorter duration of treatment and future more concerns related to employment status during the lockdown. Concerns: 19 22.1% Anxiety: emotional 17 19.8% Table 4 contains the final models obtained in the stepwise employment logistic regression models, considering the risk of dropout as Concerns: medical 2 2.3% Anxiety: motor 6 7.0% treatments criterion and as potential predictors the socio-demographic Concerns: other 5 5.8% Anxiety: cognitive 16 18.6% variables, the gambling related measures at baseline, clinical Adaptive reactions 64 74.4% Depression 17 19.8% state at baseline and during the lockdown, as well as the Adaptive reactions: 21 24.4% Family conflicts 8 9.3% contextual factors during the lockdown. The three final models social obtained considering separately the stages T1 and T2, and the Adaptive reactions: 30 34.9% leisure entire observational period, retained as the only significant Adaptive reactions: 10 11.6% predictor the duration of the GD treatment: the shorter the sport duration of treatment, the higher the likelihood of dropout. Adaptive reactions: 25 29.1% routine Adaptive reactions: 5 5.8% work-studies DISCUSSION SD: standard deviation. The present study was designed to explore the impact of the COVID-19 pandemic and confinement on treatment adherence among patients with GD. For this purpose, we evaluated dropout rates both during and after the lockdown. The relationship between clinical variables and dropout was also explored in both periods. Most patients of the sample were male and employed, and their main gambling problem involved offline gambling. This socio-demographic and clinical profile is similar to the characterization reported in previous studies of our Unit (Jiménez-Murcia et al., 2007, 2015). Regarding treatment outcome, the risk of dropout over the nine-month observational period reached similar values to those mentioned in the literature (Melville et al., 2007) and described before confinement started (Jiménez-Murcia et al., 2019). A slightly lower mean incidence of dropout was found during the lockdown in comparison with the following months although without reaching statistical significance. The restrictive characteristics of the lockdown has allowed for greater stimulus control, especially related to offline gambling activity. Consequently, the reduction of gambling opportunities, improved social/familiar environments (Donati et al., 2021), and the maintenance of an active treatment adapted to the context might be considered as protective factors (e.g., reassessing the situation and seeking alternative methods of treatment and prevention; Lee and Rovers, 2008; Côté et al., 2020). Lower levels of anxiety and depressive symptoms due to pandemic and higher socio-economic positions at baseline were FIGURE 1 | Incidence Density Rate (IDR) of Dropout during the nine-month stated among the individuals who dropped out during the observational period (n = 86). lockdown. These findings possibly suggest that those patients Frontiers in Psychology | www.frontiersin.org 7 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout FIGURE 2 | Kaplan–Meier survival function to dropout (n = 86). FIGURE 3 | Incidence Density Rate (IDR) of relapse rates during the nine-month observational period (n = 86). with better socio-economic background prior to confinement stages of confinement. Also, a lower use of adaptive coping and lower referred psychological impact due to pandemic (in strategies during the lockdown was also described in patients terms of anxiety and depressive symptoms) may have been who dropped out in comparison to those who remained in more likely to discontinue treatment, already from the initial treatment. In contrast, patients with greater insight about their Frontiers in Psychology | www.frontiersin.org 8 December 2021 | Volume 12 | Article 761802 Frontiers in Psychology | www.frontiersin.org Baenas et al. TABLE 3 | Association between socio-demographics and dropout during two periods of the COVID-19 pandemic: during (T1) and after (T2) the lockdown. T1 T2 Non-dropout Dropout Non-dropout Dropout n = 78 n=8 n = 54 n = 24 Socio-demographics n % n % p |h| n % n % p |h| Gender (female) 7 9.0% 0 0.0% 0.377 0.61† 5 9.3% 2 8.3% 0.895 0.03 Marital status (non-married) 46 59.0% 3 37.5% 0.243 0.43 30 55.6% 16 66.7% 0.357 0.23 Education (low levels) 37 47.4% 2 25.0% 0.225 0.51† 26 48.1% 11 45.8% 0.850 0.05 Social status (low levels) 33 42.3% 1 12.5% 0.043* 0.69† 22 40.7% 11 45.8% 0.674 0.10 Employment (unemployed) 38 48.7% 2 25.0% 0.200 0.48 26 48.1% 12 50.0% 0.880 0.04 Gambling activity n % n % p |h| n % n % p |h| Type Non- 36 46.2% 4 50.0% 0.842 0.08 26 48.1% 10 41.7% 0.328 0.13 strategic Strategic 27 34.6% 2 25.0% 0.21 16 29.6% 11 45.8% 0.34 Mixed 15 19.2% 2 25.0% 0.14 12 22.2% 3 12.5% 0.26 Modality Offline 52 66.7% 5 62.5% 0.265 0.09 37 68.5% 15 62.5% 0.538 0.13 Online 12 15.4% 0 0.0% 0.81† 9 16.7% 3 12.5% 0.12 Mixed 14 17.9% 3 37.5% 0.44 8 14.8% 6 25.0% 0.26 Clinical profile Mean SD Mean SD p |d| Mean SD Mean SD p |d| Age (yrs) 44.74 16.67 47.50 19.61 0.662 0.15 45.74 16.59 42.50 16.97 0.432 0.19 9 Onset of GD (yrs) 31.96 12.90 29.94 10.70 0.669 0.17 32.81 12.98 30.06 12.76 0.387 0.21 Duration of GD (yrs) 6.47 8.04 3.63 3.89 0.327 0.45 6.80 8.22 5.75 7.76 0.599 0.13 Duration of treatment 15.14 9.17 6.00 3.59 0.007 1.31† 18.09 9.16 8.50 4.66 0.001 1.32† (months) 1 SOGS total score 10.78 3.29 10.25 2.66 0.660 0.18 10.63 3.29 11.13 3.34 0.543 0.15 1 DSM-5 total criteria 7.04 2.18 7.13 1.25 0.913 0.05 7.17 2.25 6.75 2.03 0.440 0.19 SCL-90R: Somatization 0.96 0.83 0.83 0.69 0.675 0.17 0.91 0.81 1.07 0.88 0.434 0.19 SCL-90R: Obsess. /comp. 1.24 0.79 0.90 0.97 0.263 0.38 1.25 0.76 1.20 0.87 0.808 0.06 SCL-90R: Interp.sens. 1.08 0.85 0.74 0.84 0.274 0.41 1.06 0.79 1.14 0.97 0.691 0.09 SCL-90R: Depressive 1.56 0.94 1.17 1.06 0.271 0.39 1.58 0.90 1.53 1.05 0.812 0.06 SCL-90R: Anxiety 1.02 0.80 0.61 0.58 0.167 0.58† 1.06 0.76 0.92 0.89 0.473 0.17 SCL-90R: Hostility 0.99 0.88 0.73 0.87 0.433 0.29 0.97 0.80 1.03 1.07 0.753 0.07 SCL-90R: Phobic anx. 0.47 0.78 0.21 0.24 0.358 0.45 0.51 0.83 0.39 0.65 0.529 0.16 SCL-90R: Paranoid 0.93 0.77 0.69 0.66 0.393 0.34 0.89 0.71 1.03 0.92 0.469 0.17 December 2021 | Volume 12 | Article 761802 SCL-90R: Psychotic 1.02 0.82 0.59 0.59 0.152 0.60† 0.98 0.73 1.10 1.00 0.578 0.13 Lockdown and GD: Treatment Dropout SCL-90R: PST score 1.10 0.72 0.79 0.67 0.242 0.45 1.10 0.66 1.11 0.84 0.954 0.01 SCL-90R: GSI score 47.27 21.06 36.50 25.67 0.181 0.46 47.50 19.16 46.75 25.27 0.886 0.03 SCL-90R: PSDI score 1.94 0.65 1.69 0.57 0.304 0.40 1.97 0.62 1.86 0.72 0.492 0.16 TCI-R: Novelty seeking 111.82 12.40 110.75 6.71 0.811 0.11 111.33 12.55 112.92 12.25 0.606 0.13 TCI-R: Harm avoidance 98.77 13.65 98.25 18.29 0.921 0.03 99.39 13.23 97.38 14.74 0.551 0.14 TCI-R: Reward depend. 96.92 13.32 98.75 16.02 0.718 0.12 98.30 13.57 93.83 12.46 0.174 0.34 TCI-R: Persistence 107.82 18.11 108.38 25.21 0.937 0.03 108.17 19.54 107.04 14.72 0.802 0.07 TCI-R: Self-directedness 129.15 19.79 137.38 17.68 0.262 0.44 128.89 18.08 129.75 23.60 0.861 0.04 TCI-R: Cooperativeness 128.53 15.66 133.38 12.07 0.398 0.35 129.54 15.48 126.25 16.15 0.396 0.21 TCI-R: Self-Transcend. 59.91 12.24 60.25 6.02 0.939 0.04 59.89 11.33 59.96 14.34 0.982 0.01 (Continued) Frontiers in Psychology | www.frontiersin.org Baenas et al. TABLE 3 | Continued T1 T2 Non-dropout Dropout Non-dropout Dropout n = 78 n=8 n = 54 n = 24 Confinement measures n % n % p |h| n % n % p |h| Working 20 25.6% 2 25.0% 0.968 0.01 14 25.9% 6 25.0% 0.931 0.02 With company 71 91.0% 6 75.0% 0.158 0.44 48 88.9% 23 95.8% 0.322 0.27 Affected family environment 4 5.1% 1 12.5% 0.396 0.27 2 3.7% 2 8.3% 0.392 0.20 COVID-related concerns 53 67.9% 5 62.5% 0.754 0.11 37 68.5% 16 66.7% 0.872 0.04 10 Concerns: infection risk 31 39.7% 4 50.0% 0.574 0.21 21 38.9% 10 41.7% 0.909 0.06 Concerns: uncertain future 32 41.0% 2 25.0% 0.377 0.34 23 42.6% 9 37.5% 0.673 0.10 Concerns: employment 18 23.1% 1 12.5% 0.492 0.28 9 16.7% 9 37.5% 0.044 0.51† Adaptive reactions 60 76.9% 4 50.0% 0.046 0.57† 42 77.8% 18 75.0% 0.788 0.07 Adaptive reactions: social 19 24.4% 2 25.0% 0.968 0.01 14 25.9% 5 20.8% 0.629 0.12 Adaptive reactions: leisure 27 34.6% 3 37.5% 0.870 0.06 20 37.0% 7 29.2% 0.500 0.17 Adaptive reactions: routines 24 30.8% 1 12.5% 0.278 0.51† 15 27.8% 9 37.5% 0.391 0.21 Non-adaptive reactions 19 24.4% 0 0.0% 0.040 1.03† 14 25.9% 5 20.8% 0.629 0.12 Anxiety 22 28.2% 0 0.0% 0.025 1.12† 15 27.8% 7 29.2% 0.900 0.03 Depression 17 21.8% 0 0.0% 0.045 0.97† 14 25.9% 3 12.5% 0.185 0.35 SD: standard deviation. †Bold: effect size into the range mild–moderate (|d| > 0.50 or |h| > 0.50) to high-large (|d| > 0.80 or |h| > 0.80). December 2021 | Volume 12 | Article 761802 Lockdown and GD: Treatment Dropout Baenas et al. Lockdown and GD: Treatment Dropout TABLE 4 | Predictive models for the risk of dropout: stepwise logistic regression (n = 86). B SE p OR 95%CI (OR) Dropout during T1 −0.341 0.120 0.005 0.711 0.561 0.900 Duration of treatment (months) Dropout during T2 Duration of treatment (months) −0.349 0.090 <0.001 0.706 0.592 0.841 Dropout (during T1 or T2) Duration of treatment (months) −0.382 0.090 <0.001 0.682 0.572 0.814 List of predictors: socio-demographics, variables at baseline and variables related to the confinement by COVID-19. gambling problem and more urgent needs for professional help associated with more employment concerns due to the may have been more likely to remain in treatment, even if pandemic. In this line, the financial pressure of job insecurity the need was not directly related to gambling behavior (i.e., and unemployment could motivate individuals to use gambling social support, anxiety, and depressive symptoms). Several as a mechanism to earn money and manage debts (van individuals who remained in treatment reported using Schalkwyk et al., 2020; Salerno and Pallanti, 2021). Also, non-adaptive strategies during the lockdown (such as concerns previous financial crises have shown the possibility of engaging related to COVID-19 and gambling behavior). In this sense, in gambling behaviors to attempt economic restitution (Olason we hypothesize that treatment attendance may represent an et al., 2015; Economou et al., 2019). One plausible explanation adaptive mechanism to deal with emotional distress. Hence, for our results could be that those patients reporting work treatment should focus on coping with emotions as a helpful instability and difficult financial situations due to the lockdown approach to tackle gambling problems in the face of similar could have relapsed and abandoned treatment. Another future adverse circumstances (Estévez et al., 2021). possible rationale could be that, coinciding with the easing During the lockdown, a more flexible approach to treatment of restrictions after the lockdown, some patients may find was employed (Marsden et al., 2020), using Internet-based it difficult to juggle work and treatment, prioritizing the tools therapeutic strategies (Columb et al., 2020). This search and maintenance of a job over treatment. While approach may have influenced treatment adherence in patients many of these notions are currently speculative, they warrant who were already in treatment for GD, from two different direct examination in future studies. perspectives. On the one hand, online therapy was more The survival analysis showed that most dropouts were accessible to people who had previously found it difficult concentrated in the first months of this period, especially to attend (American Psychological Association, 2015). between May and July 2020. These months in Spain could Moreover, the relationship between therapist and patient in be considered as a transition period between the measures the case of virtual therapy has been described as good as taken during the lockdown and the beginning of the gradual for in-person therapy (Bergman and Kelly, 2021), allowing phasing out of these measures. It was characterized by an the therapeutic alliance to be preserved in these exceptional increased uncertainty about the return to daily routines (e.g., circumstances. On the other hand, the absence of in-person work routines), the ubiquity of social contact and health activities, a lack of peer-to-peer social and emotional concerns related to COVID-19. The general instability of connections, inequities in Internet access, and online this phase, along with the reopening of the gambling distractions could represent challenges for adapting to shifting establishments, made these first months after lockdown a from face-to-face to online therapy. These issues have been particular period of high vulnerability for relapse and for previously reported in virtual therapeutic approaches in other treatment dropout. Furthermore, some of the patients who mental disorders during confinement, such as in substance abandoned treatment during the first months of confinement use disorders and eating disorders (Fernández-Aranda et al., were in the early stages of the treatment phase. These results 2020b; Bergman and Kelly, 2021). In the present study, are in line with previous studies which described a although changes in the treatment approach did not seem predominant tendency to dropout at the start of the treatment to have detrimental effects on treatment adherence, some or after the first few sessions (Jiménez-Murcia et al., 2015). of the patients who dropped out may have presented some Going one step further, mean incidence of relapse for of the described difficulties. Pandemic situation highlights gambling behavior was significantly decreased during and the need to efficiently adapt the available treatment strategies after lockdown in comparison with mean rates prior to the to these exceptional circumstances to ensure therapeutic confinement started. However, there were not differences continuity. In this vein, customizing proven treatment in relapse rates between during and after the lockdown. strategies to virtual formats has been a useful tool, preserving Most patients reported mainly gambling offline and living the initial therapeutic objectives. with others during the nine-month observational period. A After the lockdown, restrictive measures were progressively high abstinence from gambling of around 75% has previously reduced (e.g., related to “stay-at-home” measures, social been described in patients who were already in CBT treatment distancing, and diminished mobility) and the treatment and/or in the follow-up phase (Jiménez-Murcia et al., 2007; program in its original format was reinstated. Dropout was Cowlishaw et al., 2012). In the context of pandemic, our Frontiers in Psychology | www.frontiersin.org 11 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout results also agreed with recent literature that pointed out DATA AVAILABILITY STATEMENT higher abstinence rate during confinement (Avanzi et al., 2020). In line with Donati et al. (2021), restrictive measures Individuals may inquire with Dr. Jiménez-Murcia regarding due to pandemic, social support and some policies related availability of the data as there is ongoing studies using the to gambling activity adopted during confinement, have data. To avoid overlapping research efforts, Dr. Jiménez-Murcia promoted gambling abstinence by reducing offline will consider a request on a case-by-case basis. gambling opportunities. Finally, an association between treatment duration and dropout was found during and after lockdown. Specifically, ETHICS STATEMENT the shorter the duration of treatment, the higher the risk of dropout during and after the lockdown. Furthermore, and The present study was conducted in accordance with the latest according to the predictive analysis model, the duration of version of the Declaration of Helsinki. The Clinical Research the treatment would be a predictive factor of dropout. Length Ethics Committee of the first author’s Public University Hospital of therapy has been positively related to treatment outcome gave approval before confinement, as most of the data used in previous studies (Orlinsky et al., 1994). In this sense, achieving in this study was part of the baseline 308 assessment protocol a strong therapeutic alliance with the patient early in treatment prior to the start of treatment and previously used in the Unit’s is important for improving adherence to therapy (Gómez-Peña studies related to treatment (Ref: PR329/19). We added the et al., 2012). Therefore, patients with weaker therapeutic links brief telephone survey to this protocol at the beginning of and lower durations of treatment may have found it more confinement. Signed informed consent was obtained from challenging to preserve treatment adherence in the face of all participants. similar adverse situations. AUTHOR CONTRIBUTIONS STRENGTHS AND LIMITATIONS IB, EC, ME, and SJ-M contributed to the development of the The strengths of the study included a clinical sample of study concept and design and aided with interpretation of patients already engaged with our treatment Unit. Moreover, data and the writing of the manuscript. RG performed the we used clinical records and assessments to evaluate patients statistical analysis. IB, MG-P, LM, SR, AP-G, BM-M, EV-M, rather than just self-report measures. The longitudinal nature and SJ-M aided with data collection. FF-A, SJ-M, MP, AH, of this work allowed reporting treatment outcomes related and JM revised the manuscript and provided substantial to data over the course of 9 months. Limitations included comments. FF-A and SJ-M obtained funding. All authors the modest sample size, limited geographic location, and contributed to the article and approved the submitted version. the absence of a control group for comparison and multiple qualitative assessments. Some clinical and socio-demographic variables were collected prior to the onset of the lockdown FUNDING (i.e., at the baseline evaluation prior to treatment) and their possible changes due to the pandemic were updated in the CERCA Programme/Generalitat de Catalunya gave institutional short-term during confinement. However, the influence of support. This work was additionally supported by a grant new changes in these variables in the middle-long term from the Ministerio de Ciencia, Innovación y Universidades should be contemplated in future research. Moreover, (grant RTI2018-101837-B-100). The research was funded by upcoming studies would benefit from including quantitative the Delegación del Gobierno para el Plan Nacional sobre validated scales and evaluating changes over longer time Drogas (2017I067 and 2019I47), Instituto de Salud Carlos periods in GD symptomatology and associated factors, III (ISCIII) (PI17/01167) and co-funded by FEDER funds/ throughout different stages of the COVID-19 pandemic in European Regional Development Fund (ERDF), a way to build multiple jurisdictions and cultures. Europe. CIBEROBN and CIBERSAM are both initiatives of ISCIII. IB was partially supported by a Post-Residency Grant from Research Committee of the University Hospital of Bellvitge CONCLUSION (HUB; Barcelona, Spain) 2020–2021. The funders had no role in the study design, data collection and analysis, decision to In conclusion, the present findings provide data on the treatment publish or preparation of the manuscript. dropout in clinical population diagnosed with GD and potential contributing factors during confinement. In this line, duration of treatment could be a possible predictor of dropout in the ACKNOWLEDGMENTS face of adverse external situations. These results have relevance for identifying potentially high-risk subjects and optimizing We thank CERCA Programme/Generalitat de Catalunya, Instituto individualized early interventions in the setting of future similar de Salud Carlos III (ICSIII) and Instituto de Investigación adverse circumstances. Biomédica de Bellvitge (IDIBELL). Frontiers in Psychology | www.frontiersin.org 12 December 2021 | Volume 12 | Article 761802 Baenas et al. Lockdown and GD: Treatment Dropout Côté, M., Tremblay, J., Jiménez-Murcia, S., Fernàndez-Aranda, F., and Brunelle, N. 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(2010). consulted for and advised Game Day Data, the Addiction Policy Forum, AXA, Treatment outcomes and predictors of drop out for problem gamblers in Idorsia, and Opiant/Lakelight Therapeutics; received research support from the South Australia: A cohort study. Aust. N. Z. J. Psychiatry 44, 911–920. doi: Veteran’s Administration, Mohegan Sun Casino, and the National Center for 10.3109/00048674.2010.493502 Responsible Gaming (on the International Center for Responsible Gambling); StataCorp (2021). Stata Statistical Software: Release 17. Station, TX: StataCorp LLC. participated in surveys, mailings, or telephone consultations related to addictions, Stinchfield, R. (2003). Reliability, validity, and classification accuracy of a measure impulse-control disorders or other health topics; consulted for law offices and of DSM-IV diagnostic criteria for pathological gambling. Am. J. Psychiatry the federal public defender’s office in issues related to impulse-control and 160, 180–182. doi: 10.1176/appi.ajp.160.1.180 addictive disorders; provided clinical care in the Connecticut Department of van Schalkwyk, M.C.I., Heetham, D., Reeves, A., and Petticreew, M. (2020). Mental Health and Addiction Services Problem Gambling Services Program; We must take urgent action to avoid an increase in problem gambling and performed grant reviews for the National Institutes of Health and other agencies; gambling related harms. BMJ. Available at: https://blogs.bmj.com/ edited journals and journal sections; given academic lectures in grand rounds, bmj/2020/04/06/covid-19-we-must-take-urgent-action-to-avoid-an-increase-in- CME events and other clinical/scientific venues; and generated books or chapters problem-gambling-and-gambling-related-harms for publishers of mental health texts. Wang, C., Pan, R., Wan, X., Tan, Y., Xu, L., Ho, C. S., et al. (2020). Immediate psychological responses and associated factors during the initial stage of The remaining authors declare that the research was conducted in the absence the 2019 coronavirus disease (COVID-19) epidemic among the general of any commercial or financial relationships that could be construed as a potential population in China. Int. J. Environ. Res. Public Health 17. doi: 10.3390/ conflict of interest. ijerph17051729 World Health Organization (WHO). (2020). #HealthyAtHome – Mental Health. Publisher’s Note: All claims expressed in this article are solely those of the Available at: https://www.who.int/news-room/campaigns/connecting-the-world- authors and do not necessarily represent those of their affiliated organizations, to-combat-coronavirus/healthyathome/healthyathome—mental-health or those of the publisher, the editors and the reviewers. Any product that may Yuki, K., Fujiogi, M., and Koutsogiannaki, S. (2020). COVID-19 pathophysiology: be evaluated in this article, or claim that may be made by its manufacturer, is A review. Clin. Immunol. 215:108427. doi: 10.1016/j.clim.2020.108427 not guaranteed or endorsed by the publisher. Zamboni, L., Carli, S., Belleri, M., Giordano, R., Saretta, G., and Lugoboni, F. (2021). Covid-19 lockdown: impact on online gambling, online shopping, Copyright © 2021 Baenas, Etxandi, Codina, Granero, Fernández-Aranda, Gómez- web navigation and online pornography. J. Public Health Res. 10, 1–6. doi: Peña, Moragas, Rivas, Potenza, Håkansson, del Pino-Gutiérrez, Mora-Maltas, 10.4081/jphr.2021.1959 Valenciano-Mendoza, Menchón and Jiménez-Murcia. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). Conflict of Interest: AH holds a position at Lund University, Sweden, sponsored The use, distribution or reproduction in other forums is permitted, provided the by the state-owned Swedish gambling operator AB Svenska Spel and has funding original author(s) and the copyright owner(s) are credited and that the original from the research council of the same organization and from the research publication in this journal is cited, in accordance with accepted academic practice. councils of the Swedish state-owned alcohol monopoly Systembolaget AB and No use, distribution or reproduction is permitted which does not comply with the Swedish sports federation. MP notes the following disclosures. He has: these terms. Frontiers in Psychology | www.frontiersin.org 15 December 2021 | Volume 12 | Article 761802