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  • 1 Department of Clinical Sciences/Psychiatry, Umeå University, Umeå, , Sweden
  • | 2 ANOVA, Karolinska University Hospital, Stockholm, , Sweden
  • | 3 Department of Women’s and Children’s Health, Pediatric Neuropsychiatry Unit, Centre for Neurodevelopmental Disorders at Karolinska Institutet (KIND), Karolinska Institutet, Stockholm, , Sweden
  • | 4 Habilitation & Health, Stockholm Health Care Services, , Region Stockholm, , Sweden
  • | 5 Centre for Psychiatry Research, , Region Stockholm, Stockholm, Sweden
  • | 6 Department of Medicine, Karolinska Institutet, Stockholm, , Sweden
  • | 7 Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, , Sweden
  • | 8 Stockholm Health Care Services, , Region Stockholm, Stockholm, , Sweden
Open access

Abstract

Background and aims

Impulsivity is regarded as a risk factor for sexual crime reoffending, and a suggested core feature in Compulsive Sexual Behavior Disorder. The aim of this study was to explore clinical (e.g. neurodevelopmental disorders), behavioral and neurocognitive dimensions of impulsivity in disorders of problematic sexuality, and the possible correlation between sexual compulsivity and impulsivity.

Methods

Men with Compulsive Sexual Behavior Disorder (n = 20), and Pedophilic Disorder (n = 55), enrolled in two separate drug trials in a specialized Swedish sexual medicine outpatient clinic, as well as healthy male controls (n = 57) were assessed with the Hypersexual Behavior Inventory (HBI) for sexual compulsivity, and with the Barratt Impulsiveness Scale (BIS) and Connors’ Continuous Performance Test-II (CPT-II) for impulsivity. Psychiatric comorbidity information was extracted from interviews and patient case files.

Results

Approximately a quarter of the clinical groups had Attention-Deficit/Hyperactivity Disorder (ADHD) or Autism Spectrum Disorder. Both clinical groups reported more compulsive sexuality (r = 0.73−0.75) and attentional impulsivity (r = 0.36−0.38) than controls (P < 0.05). Based on results on univariate correlation analysis, BIS attentional score, ADHD, and Commissions T-score from CPT-II were entered in a multiple linear regression model, which accounted for 15% of the variance in HBI score (P < 0.0001). BIS attentional score was the only independent positive predictor of HBI (P = 0.001).

Discussion

Self-rated attentional impulsivity is an important associated factor of compulsive sexuality, even after controlling for ADHD. Psychiatric comorbidity and compulsive sexuality are common in Pedophilic Disorder.

Conclusion

Neurodevelopmental disorders and attentional impulsivity – including suitable interventions – should be further investigated in both disorders.

Abstract

Background and aims

Impulsivity is regarded as a risk factor for sexual crime reoffending, and a suggested core feature in Compulsive Sexual Behavior Disorder. The aim of this study was to explore clinical (e.g. neurodevelopmental disorders), behavioral and neurocognitive dimensions of impulsivity in disorders of problematic sexuality, and the possible correlation between sexual compulsivity and impulsivity.

Methods

Men with Compulsive Sexual Behavior Disorder (n = 20), and Pedophilic Disorder (n = 55), enrolled in two separate drug trials in a specialized Swedish sexual medicine outpatient clinic, as well as healthy male controls (n = 57) were assessed with the Hypersexual Behavior Inventory (HBI) for sexual compulsivity, and with the Barratt Impulsiveness Scale (BIS) and Connors’ Continuous Performance Test-II (CPT-II) for impulsivity. Psychiatric comorbidity information was extracted from interviews and patient case files.

Results

Approximately a quarter of the clinical groups had Attention-Deficit/Hyperactivity Disorder (ADHD) or Autism Spectrum Disorder. Both clinical groups reported more compulsive sexuality (r = 0.73−0.75) and attentional impulsivity (r = 0.36−0.38) than controls (P < 0.05). Based on results on univariate correlation analysis, BIS attentional score, ADHD, and Commissions T-score from CPT-II were entered in a multiple linear regression model, which accounted for 15% of the variance in HBI score (P < 0.0001). BIS attentional score was the only independent positive predictor of HBI (P = 0.001).

Discussion

Self-rated attentional impulsivity is an important associated factor of compulsive sexuality, even after controlling for ADHD. Psychiatric comorbidity and compulsive sexuality are common in Pedophilic Disorder.

Conclusion

Neurodevelopmental disorders and attentional impulsivity – including suitable interventions – should be further investigated in both disorders.

Introduction

Compulsive Sexual Behavior Disorder (CSBD) is a diagnosis in the 11th edition of the International Classification of Diseases (ICD-11), section of impulse control disorders (World Health Organization, 2018). It involves a persistent pattern of failure to control intense repetitive sexual impulses or urges, resulting in sexual behaviors with negative consequences affecting different areas of life. There are indications that CSBD and impulsivity importantly relates (Bothe et al., 2019), and that CSBD present similar impulses and reward processing as addictive disorders (Grubbs et al., 2020). However, it is still unclear whether impulsivity is an integrated part of CSBD, is represented in possible subtypes or contexts (e.g. sexual), or is primary related to conditions highly associated with impulsivity e.g. Attention-Deficit/Hyperactivity Disorder (ADHD) or alcohol use. Symptoms of compulsive sexual behavior are common in men primarily seeking treatment for paraphilic disorders, and vice-versa (Sutton, Stratton, Pytyck, Kolla, & Cantor, 2015; Engel et al., 2019). Findings of impulsivity in Pedophilic Disorder (PeD) are inconsistent (Cohen et al., 2002).

Nevertheless, there is limited data on CSBD, PeD, and the link to impulsivity. Remarkable considering that sexual preoccupation, impulsivity and deviant sexual preferences are risk factors for sexual crime reoffending (Hanson & Morton-Bourgon, 2005).

Aims

In this study, we aimed to investigate behavioral and neurocognitive dimensions of impulsivity, and the occurrence of neurodevelopmental disorders likely to be associated with impulsivity in men seeking treatment for CSBD or PeD in the same subspecialized sexual medicine unit, as well as in healthy male controls.

We also investigated association between sexual compulsivity and impulsivity measures. Based on the assumption that CSBD is associated with impulsivity, we hypothesized that impulsivity is positively related to the level of compulsive sexual behavior also after adjustment for ADHD and alcohol use. Since trait of compulsive sexual behaviors are common in PeD, we also hypnotized that the PeD group would present more impulsivity than controls, although the literature is inconsistent.

Methods

Participants

Data from two separate drug trials on CSBD and PeD was included in this study (Table 1). The PeD trial only invited men due to the drug properties and no women applied for the CSBD study. Both studies were conducted during overlapping time periods (2016–2019; 2018–2019) at ANOVA, a multidisciplinary center for research, assessment, and treatment in andrology, sexual medicine, and transgender medicine at the Karolinska University Hospital, Stockholm, Sweden.

Table 1.

Sociodemographic Factors, Clinical Characteristics and Assessments of Compulsive Sexual Behavior, Self-rated Impulsivity, and Neurocognitive Impulsivity

VariableGroupStatisticEffect measure: Odds ratio (95% confidence interval)
CSBD (n = 20)PeD (n = 55)HC (n = 57)
Median (range)Mean (SD)Median (range)Mean (SD)Median (range)Mean (SD)
Age, y35.5 (27−60)39 (10)36 (18−66)36 (12)35 (18−64)36 (12)H (2) = 0.99 P = 0.61N/A
Sociodemographicn%n%n%
Highest level of education
Compulsory school (≤9 years) or upper secondary school (12 years)1260325825 4444χ2 = 2.9 (2, n = 132) P = 0.24PeD vs. CSBD: OR = 1.1 (0.4; 3.1)
PeD vs. HC: OR = 0.6 (0.3; 1.2)
CSBD vs. HC: OR = 0.5 (0.2; 1.5)
University84023423256
Employed189032585088χ2 = 15.9 (2, n = 132) P < 0.001 PeD < CSBD = HCPeD vs. CSBD: OR = 0.2 (0.03; 0.7)
PeD vs. HC: OR = 0.2 (0.08; 0.5)
CSBD vs. HC: OR 1.3 (0.2; 6.6)
Cohabitation189021383663χ2 = 17.7 (2, n = 132) P < 0.001 PeD < HC < CSBDPeD vs. CSBD: OR = 0.07 (0.01; 0.3)
CSBD vs. HC: OR = 5.3 (1.1; 24.9)
PeD vs. HC: OR = 0.4 (0.2; 0.8)
Parent115520362646χ2 = 2.3 (2, n = 132) P = 0.31PeD vs. CSBD: OR = 0.5 (0.2; 1.3)
CSBD vs. HC: OR = 1.5 (0.5; 4.1)
PeD vs. HC: OR = 0.7 (0.3; 1.5)
Current affective or anxiety disordera525366624χ2 = 49.5 (2, n = 132) P < 0.001 HC < CSBD < PeDPeD vs. CSBD: OR = 5.7 (1.8; 18.0)
CSBD vs. HC: OR = 9.2 (1.6; 52.0)
PeD vs. HC: OR = 52.1 (11.4; 237.4)
Neurodevelopmental disorder (specified below)525122200χ2 = 15.0 (2, n = 132) P = 0.001 HC < CSBD = PeDCSBD vs PeD: OR = 1.2 (0.4; 4.0)
Autism spectrum disorder005900N/A
ADHD525101800FET, P = 0.53CSBD vs PeD: OR = 1.5 (0.4; 5.1)
Baseline measuresCSBDPeDHCStatisticEffect measure: r
Median (range)Mean (SD)Median (range)Mean (SD)Median (range)Mean (SD)
AUDIT4 (0–11)4.5 (3.4)2 (0–27)4.1 (5.8)5 (0–15)5.0 (3.2)H (2) = 9.42 P = 0.009 PeD < HCPeD vs. HC: r = 0.29
CSBD vs. PeD: r = 0.16
CSBD vs. HC: r = 0.08
DUDIT0 (0–4)0.3 (0.9)0 (0–12)1.3 (2.9)0 (0–8)0.6 (1.5)H (2) = 1.45 P = 0.5CSBD vs. PeD: r = 0.13
CSBD vs. HC: r = 0.08
PeD vs. HC: r = 0.04
HBI total74.5 (42–89)72.8 (13.1)56 (19–93)56.3 (17.0)24 (19–54)26.9 (7.9)H (2) = 81.13, P < 0.001 CSBD > PeD > HCCSBD vs. PeD: r = 0.44
CSBD vs. HC: r = 0.75
PeD vs. HC: r = 0.73
HBI coping27.5 (10–35)24.7 (8.0)20 (7–35)19.6 (7.6)10 (7–23)11.7 (4.3)H (2) = 45.97, P < 0.001 CSBD > PeD > HCCSBD vs. PeD: r = 0.28
CSBD vs. HC: r = 0.62
PeD vs. HC: r = 0.52
HBI control35 (16–40)33.5 (5.8)27 (8–40)27.0 (8.2)9 (8–27)10.0 (3.8)H (2) = 86.03, P < 0.001 CSBD > PeD > HCCSBD vs. PeD: r = 0.40
CSBD vs. HC: r = 0.76
PeD vs. HC: r = 0.78
HBI consequences15 (9–27)14.6 (3.3)10 (4–20)9.9 (3.6)5 (4–11)5.2 (1.6)H (2) = 73. 40, P < 0.001 CSBD > PeD > HCCSBD vs. PeD: r = 0.51
CSBD vs. HC: r = 0.77
PeD vs. HC: r = 0.64
BIS total71 (45–89)68.4 (13.1)64.5 (42–88)66.3 (10.7)63 (46–84)62.3 (8.1)H (2) = 5.76, P = 0.056CSBD vs. HC: r = 0.23
PeD vs. HC: r = 0.19
CSBD vs. PeD: r = 0.08
BIS attention20 (9–27)19.2 (4.5)18 (9–29)18.5 (4.4)15 (10–25)15.5 (3.3)H (2) = 18.65, P < 0.001 CSBD = PeD > HCCSBD vs. HC: r = 0.38
PeD vs. HC: r = 0.36
CSBD vs. PeD: r = 0.10
BIS motor23 (17–31)23.6 (4.7)23 (15–34)23.1 (4.2)22 (15–33)22.9 (3.7)H (2) = 0.15, P = 0.93CSBD vs. PeD: r = 0.04
CSBD vs. HC: r = 0.05
PeD vs. HC: r = 0.006
BIS non-planning27.5 (17–35)25.7 (5.6)25 (14–35)25.0 (4.7)24 (17–31)23.8 (3.4)H (2) = 3.46, P = 0.18CSBD vs. PeD: r = 0.05
CSBD vs. HC: r = 0.17
PeD vs. HC: r = 0.15
CPT-IIb
Commission errors, T-score50.4 (38.0–68.9)50.0 (9.7)50.9 (32.9–73.0)52.1 (10.1)47.5 (34.2–71.3)48.3 (8.2)H (2) = 4.24, P = 0.12CSBD vs. PeD: r = 0.10
CSBD vs. HC: r = 0.07
PeD vs. HC: r = 0.20
HIT RT, T-score54.3 (34.3–66.6)52.1 (9.1)49.5 (29.7–81.1)50.7 (10.3)51.2 (38.3–73.2)52.0 (8.4)H (2) = 1.56, P = 0.46CSBD vs. PeD: r = 0.12
CSBD vs. HC: r = 0.06
PeD vs. HC: r = 0.09
Perseverations, T-score45.8 (42.5–109.2)49.3 (14.9)45.8 (42.5–109.2)53.8 (15.2)45.8 (42.5–70.0)47.1 (5.7)H (2) = 11.59, P = 0.003 PeD > CSBD = HCCSBD vs. PeD: r = 0.26
PeD vs. HC: r = 0.30
CSBD vs. HC: r = 0.03
Perseverations, raw score0 (0–3 (IQR = 0)0.3 (0.8)0 (0–10) (IQR = 0−1)0.9 (1.7)0 (0–4) (IQR = 0)0.3 (0.8)H (2) = 8.63, P = 0.013 PeD > HCPeD vs. HC: r = 0.25
CSBD vs. PeD: r = 0.21
CSBD vs. HC: r = 0.10

Notes: Test statistics: H = Kruskal-Wallis test with r as effect measure; χ2 = Chi-square test; FET = Fisher's exact Test; Odds ratios (OR) and confidence intervals are only calculated in 2 x 2 table when at least one cell ≥1.

Abbreviations and symbols: a = According to Mini International Neuropsychiatric Interview; b = Population norm T-score = 50 (SD = 10). ADHD = Attention-Deficit/Hyperactivity Disorder; CSBD = Compulsive Sexual Behavior Disorder; HC = Healthy Controls; N/A = Not applicable; PeD = Pedophilic Disorder.

Variables: AUDIT = Alcohol Use Disorders Identification Test (Missing data: PeD = 2); DUDIT = The Drug Use Disorders Identification Test (Missing data: PeD = 2); HBI = Hypersexual Behavior Inventory (Missing data HBI total: PeD = 3; control PeD = 3; coping and consequences PeD = 2); BIS = Barratt Impulsiveness Scale (Missing data BIS total: PeD = 5, HC = 1; attentional and non-planning PeD = 4; motor PeD = 5, HC = 1); CPT-II = Conners' Continuous Performance Test (Missing data: CSBD = 1).

CSBD: Thirty-two men were evaluated on-site, of which 20 were included in a pilot study of the opioid antagonist naltrexone for CSBD (Savard et al., 2020). Two independent interviews with a board-certified psychiatrist and a psychologist confirmed the diagnosis of CSBD according to ICD–11 and the conceptualization of Hypersexual Disorder (Kafka, 2010) (not meeting criteria, n = 7). Exclusion criteria included severe physical illness or mental disorder such as current psychotic episode, a substance use disorder during the past month (n = 3), participation in another study (n = 1) or ongoing psychotherapy (n = 1). No participant met criteria for PeD.

PeD: Sixty-five men were screened by phone for eligibility by a board-certified psychiatrist. Exclusion criteria included severe psychosis, severe ongoing substance-related disorders, and the use of hormonal therapy. Three participants did not meet criteria for PeD, six declined participation and one had hormonal therapy. Hence, fifty-five men were evaluated on-site by a psychiatrist for PeD according to the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) (American Psychiatric Association, 2013) and included for participation in a double-blind, randomized, controlled trial of a testosterone-suppressing agent (Landgren et al., 2020).

Healthy controls: Fifty-seven men age-matched to the PeD cohort were recruited from the Karolinska Trial Alliance database, and by advertisement on the Karolinska Institutet website. They were included after a telephone interview as part of the PeD study. Subjects did not meet criteria for PeD or any of the exclusion criteria in the PeD study. Neither the PeD group, nor the healthy controls were formally interviewed for a diagnosis of CSBD.

Measures

A full list of measures with psychometric properties are presented in Supplementary Table 1.

Psychiatric comorbidity

The Mini International Neuropsychiatric Interview (MINI) version 6.0 (PeD; controls) and 7.0 (CSBD), a validated diagnostic structured interview, was used to assess for mental disorders (Sheehan et al., 1998).

The Alcohol Use Disorders Identification Test (AUDIT) (Saunders, Aasland, Babor, de la Fuente, & Grant, 1993), and the Drug Use Disorders Identification Test (DUDIT) (Berman, Bergman, Palmstierna, & Schlyter, 2005) were used for eligibility assessments.

Compulsive sexual behavior

The Hypersexual Behavior Inventory (HBI) is a scale designed to reflect the proposed DSM-5 criteria of Hypersexual Disorder. HBI consists of three subscales, which measure sex as a coping mechanism, the experience of loss of control, and negative consequences (Reid, Garos, & Carpenter, 2011).

Impulsivity

The Barratt Impulsiveness Scale (BIS) consists of three subscales measuring motor, non-planning, and attentional impulsivity (Patton, Stanford, & Barratt, 1995). Conners’ Continuous Performance Test (CPT-II) is a computerized measure with suggested impulsivity variables: Commission errors, Hit RT, and Perseverations (Conners & MHS Staff, 2000).

Procedure

Study participants were screened for inclusion when calling the national helpline PrevenTell for individuals with self-identified compulsive sexual behavior and/or paraphilia. Assessments were performed in face-to-face interviews including information of previous diagnosis of Autism Spectrum Disorder or ADHD including all subtypes. In Sweden, an extensive clinical assessment of neurodevelopmental disorders includes psychiatric and psychological interviews and neurocognitive testing.

Statistical analysis

All analyses were carried out using IBM SPSS Statistics 25.0. The Kruskal-Wallis test and Mann-Whitney U test were used for group comparisons as the Shapiro-Wilk test as well as skewness ranging from -1.7−4.0 and kurtosis from -1.3−16.9 indicated non-normal distributions. Effect sizes were calculated using r and interpreted according to Cohen (J. Cohen, 1988; Pallant, 2016). For dichotomous data, a χ 2-test was used, or Fisher’s exact test if expected frequencies were less than five. Odds ratios (OR) are reported for significant tests where at least one cell ≥1. Based on results of univariate correlation analyses of all study participants, variables likely to influence sexual compulsivity were integrated simultaneously in a standard multiple linear regression model (assumptions for the analysis were met, all analyses α < 0.05). The sample size was regarded a priori large enough for the regression analysis (Tabachnick & Fidell, 2006, p. 123).

Ethics

The study procedures were carried out in accordance with the Declaration of Helsinki. All subjects were informed about the study and all provided written informed consent. The Swedish Ethical Review Authority approved both studies and that data were analyzed together (Ref. no. 2020-01258 and 2019-06092).

Results

Sociodemographic factors and psychiatric comorbidity

Group differences among the 132 men are presented in Table 1. Men with PeD were less likely to be employed (OR = 0.2, 95% CI 0.03; 0.7) or cohabit (OR = 0.07, 95% CI 0.01; 0.3) in comparison to the CSBD group as well as in controls (employment OR = 0.2, 95% CI 0.08; 0.5; cohabitant OR = 0.4, 95% CI 0.2; 0.8). The rate of current affective and anxiety comorbidities was higher in the PeD group (66%) in comparison to the CSBD group (25%; OR = 5.7, 95% CI 1.8; 18.0).

Approximately a quarter of the clinical groups had a previous neurodevelopmental disorder diagnosis (Table 1).

Assessment of compulsive sexual behavior and impulsivity

Table 1 shows mean scores on HBI, BIS, and CPT-II. Thirty-three among PeD and one among heathy controls met the suggested cut-off ≥53 on HBI. The clinical groups had higher HBI scores than the controls (all P-values <0.001). The CSBD group reported higher scores on all HBI scales and subscales compared to PeD group with medium-large effect sizes for the total score (r = 0.44), control and consequences subscales (r = 0.40; r = 0.51), and low-medium for the coping subscale (r = 0.28).

The clinical groups scored higher on the BIS attentional subscale (CSBD vs. controls r = 0.38; PeD vs. controls r = 0.36). There were no significant differences between the three groups on motor and non-planning subscales.

Results from the CPT-II revealed no group differences in T-scores of Commission errors or Hit RT. The PeD group recorded higher Perseveration T-scores than the CSBD group and controls. However, the data was remarkably skewed and therefore the Perseveration raw scores were also analyzed, hence the difference remained only between PeD and controls (r = 0.25).

The correlation between impulsivity and compulsive sexual behavior

Commission errors T-score (r = 0.20) and ADHD diagnosis (r = 0.29) were positively associated with HBI in all participants, as was BIS total (r = 0.30), non-planning (r = 0.23) and attentional score (r = 0.40. Supplementary Figure 1). Based on these results, a multiple regression analysis was performed using HBI total score as a dependent variable and BIS attentional score, ADHD diagnosis, and Commission errors T-score were simultaneously entered as independent variables. The overall model was significant (F = 8.39, P < 0.0001) with R = 0.41, R 2 = 0.17 and adjusted R2 = 0.15, which implies that the model accounted for 15% of the variance in HBI score. Only BIS attentional score was an independent predictor of HBI, with B = = 1.62, β = 0.31 (P = 0.001) indicating a positive relationship with the two measures (Table 2).

Table 2.

Correlation Matrix and Results of the Multiple Linear Regression Analysis for Impulsivity Factors and the Dependent Variable Hypersexual Behavior Inventory (HBI)

VariablenMSD1234
1. HBI total12945.8422.02
2. BIS attentional12817.274.27r = 0.40 P <0.001
3. ADHD132r = 0.29 P = 0.001r = 0.45 P <0.001
4. CPT commissions T-score13150.159.34r = 0.20 P = 0.026r = 0.24 P = 0.007r = 0.18 P = 0.041
EffectBSE95% CIβtP
LLUP
Intercept6.0711.66−17.0129.160.60
BIS attentional1.620.480.662.570.313.360.001
ADHD9.906.74−3.4523.260.131.470.15
CPT commissions, T-score0.210.20−0.180.610.091.060.29
R = 0.41, R2 = 0.17 (adjusted R2 = 0.15)

Notes: HBI = The Hypersexual Behavior Inventory; BIS = Barratt Impulsiveness Scale; ADHD = Attention-Deficit/Hyperactivity Disorder; CPT = Conners' Continuous Performance Test; CI = confidence interval; LL = lower limit; UL = upper limit; β = Standardized Coefficients Beta.

Finally, to control for the known association between alcohol use disorders and impulsivity, a sensitivity analysis was conducted with AUDIT scores entered as an independent variable in the regression model; this was found not to be a significant independent predictor, nor lead to enhancement of the adjusted R2.

Discussion

This study explored associations between dimensions of impulsivity and compulsive sexuality, remarkably understudied despite of indication of importance in CSBD and PeD.

Despite similar education levels across the three groups, the PeD group presented lower psychosocial functioning as well as higher rates of autism spectrum disorder and current affective and anxiety disorders, compared to the CSBD group and controls. Additionally, ADHD was more common in both clinical groups than in the general population (Polyzoi, Ahnemark, Medin, & Ginsberg, 2018). Attentional impulsivity was higher in both clinical groups, but did not differ between men with PeD and CSBD. Symptoms of compulsive sexuality were common in PeD; the routine assessment should evaluate whether such symptoms are a result of distress and negative consequences linked to their sexuality or comorbid CSBD.

Our results suggest self-rated attentional impulsivity, rather than motor or non-planning impulsivity, to be an associated factor with compulsive sexual behavior. As hypothesized (attentional) impulsivity was positively associated to the level of compulsive sexual behavior also after adjustment for ADHD, though a large proportion of variance in compulsive sexuality is explained by other factors than the measures used in this study. For example, affective disorders has been suggested to predict compulsive sexuality (Scanavino et al., 2013).

One strength of this study compared to previous studies is the relatively large number of formally diagnosed participants in both the PeD and CSBD groups enrolled during overlapping time periods, thus making the study unique in its use of DSM-5 and ICD-11 diagnostic criteria, respectively.

Further, we were able to investigate behavioral and neurocognitive dimensions of impulsivity in relation to compulsive sexual behavior. Nonetheless, the ecological validity of continuous performance tests has been questioned (Hall et al., 2016). Some additional limitations should be pointed out. Firstly, this study used data from two separate studies with different research questions, yielding only a few comparable assessments. Secondly, the diagnostic procedures for PeD and CSBD differ, and the PeD cohort was not formally evaluated for CSBD, although compulsive sexual behavior in the PeD cohort was assessed using a well-established measurement. Thirdly, the cross-sectional format prevents interpretation of causation. Furthermore, the controls were recruited to age-match the PeD group and not the CSBD group. On the other hand, the groups did not differ in terms of background factors such as age and educational level. Finally, the error rate for multiple comparisons was not corrected for and some analyses were underpowered – as can be seen by the large confidence intervals. Overall, the results should therefore only be considered preliminary until replicated.

Conclusion

Participants with CSBD and PeD reported more impulsivity and had more often comorbid ADHD than healthy controls. ADHD did not predict the level of compulsive sexuality, whereas self-rated attentional impulsivity did. Screening for neurodevelopmental disorder should nevertheless be part of routine assessment in disorders of problematic sexuality, since treatment of ADHD can improve attentional impulsivity. Clinicians should be aware of low psychosocial functioning, high psychiatric comorbidity and compulsive sexuality in PeD.

CSBD is categorized as an impulse control disorder in ICD-11, however, a large proportion of variance in compulsive sexuality may be explained by other factors than the impulsivity measures used in this study. Future studies should not only investigate other aspects of impulsivity such as sensation seeking or impulsivity in specific contexts (e.g. presence of sexual cues) but also further explore the suggested shared neurobiological mechanisms with substance use disorders (Gola et al., 2017).

Funding sources

This study was supported by the Swedish Society for Medicine (SLS-501421 and SLS-886481), the Swedish Society for Medical Research (P14-0136), the Söderström König Foundation; the Fredrik and Ingrid Thuring Foundation (FITS-2015-00157), the Center for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institutet (CPF-99/2016), and by the ALF agreement between the Swedish government and the county councils (SLL20150518, SLL20160555, SLL 20190015 and RV747701, RV929554, RV864171). The supporters had no role in the design, analysis, interpretation, or publication of this study.

Authors’ contribution

Study concept and design: J.S., T.H., K.G.Ö., C.D. C.R and J.J; analysis and interpretation of data: J.S., T.H., K.G.Ö., C.D., C.R and J.J.; statistical analysis: J.S., T.H., and J.J.; funding acquisition: J.J., and C.R.; writing – original draft: J.S.; writing – review & editing: J.S., T.H., K.G.Ö., C.D., C.R and J.J.; study supervision: K.G.Ö., C.D., C.R and J.J. All authors had full access to all data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis.

Conflicts of interests

Jussi Jokinen has participated in Advisory Board of Janssen concerning esketamine for MDD with current suicidal ideation.

Supplementary Material

Supplementary data to this article can be found online at https://doi.org/10.1556/2006.2021.00044.

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  • Engel, J. , Veit, M. , Sinke, C. , Heitland, I. , Kneer, J. , Hillemacher, T. , … Kruger, T. H. C. (2019). Same same but different: A clinical characterization of men with hypersexual disorder in the Sex@Brain study. J Clin Med, 8(2). https://doi.org/10.3390/jcm8020157.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gola, M. , Wordecha, M. , Sescousse, G. , Lew-Starowicz, M. , Kossowski, B. , Wypych, M. , … Marchewka, A. (2017). Can pornography be addictive? An fMRI study of men seeking treatment for problematic pornography use. Neuropsychopharmacology, 42(10), 20212031. https://doi.org/10.1038/npp.2017.78.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grubbs, J. B. , Hoagland, K. C. , Lee, B. N. , Grant, J. T. , Davison, P. , Reid, R. C. , & Kraus, S. W. (2020). Sexual addiction 25 years on: A systematic and methodological review of empirical literature and an agenda for future research. Clinical Psychology Review, 82, 101925. https://doi.org/10.1016/j.cpr.2020.101925.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hall, C. L. , Valentine, A. Z. , Groom, M. J. , Walker, G. M. , Sayal, K. , Daley, D. , & Hollis, C. (2016). The clinical utility of the continuous performance test and objective measures of activity for diagnosing and monitoring ADHD in children: A systematic review. European Child & Adolescent Psychiatry, 25(7), 677699. https://doi.org/10.1007/s00787-015-0798-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hanson, R. K. , & Morton-Bourgon, K. E. (2005). The characteristics of persistent sexual offenders: A meta-analysis of recidivism studies. Journal of Consulting and Clinical Psychology, 73(6), 11541163. https://doi.org/10.1037/0022-006x.73.6.1154.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kafka, M. P. (2010). Hypersexual disorder: A proposed diagnosis for DSM-V. Archives of Sexual Behavior, 39(2), 377400. https://doi.org/10.1007/s10508-009-9574-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landgren, V. , Malki, K. , Bottai, M. , Arver, S. , & Rahm, C. (2020). Effect of gonadotropin-releasing hormone antagonist on risk of committing child sexual abuse in men with pedophilic disorder: A randomized clinical trial. JAMA Psychiatry, 77(9), 897905. https://doi.org/10.1001/jamapsychiatry.2020.0440. .

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Pallant, J. (2016). SPSS survival manual. McGraw-Hill Education.

  • Patton, J. H. , Stanford, M. S. , & Barratt, E. S. (1995). Factor structure of the Barratt impulsiveness scale. Journal of Clinical Psychology, 51(6), 768774. https://doi.org/10.1002/1097-4679(199511)51:6<768::aid-jclp2270510607>3.0.co;2-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polyzoi, M. , Ahnemark, E. , Medin, E. , & Ginsberg, Y. (2018). Estimated prevalence and incidence of diagnosed ADHD and Health care utilization in adults in Sweden - a longitudinal population-based register study. Neuropsychiatric Disease and Treatment, 14, 11491161. https://doi.org/10.2147/NDT.S155838.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reid, R. C. , Garos, S. , & Carpenter, B. N. (2011). Reliability, validity, and psychometric development of the hypersexual behavior inventory in an outpatient sample of men. Sexual Addiction & Compulsivity, 18(1), 3051. https.//doi.org/10.1080/10720162.2011.555709.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, J. B. , Aasland, O. G. , Babor, T. F. , de la Fuente, J. R. , & Grant, M. (1993). Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption--II. Addiction, 88(6), 791804. https://doi.org/10.1111/j.1360-0443.1993.tb02093.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Savard, J. , Öberg, K. G. , Chatzittofis, A. , Dhejne, C. , Arver, S. , & Jokinen, J. (2020). Naltrexone in compulsive sexual behavior disorder: A feasibility study of twenty men. The Journal of Sexual Medicine, 17(8), 15441552. https://doi.org/10.1016/j.jsxm.2020.04.318. .

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Scanavino, M. D. T. , Ventuneac, A. , Abdo, C. H. N. , Tavares, H. , Amaral, M. L. S. D. , Messina, B. , … Parsons, J. T. (2013). Compulsive sexual behavior and psychopathology among treatment-seeking men in São Paulo, Brazil. Psychiatry Research, 209(3), 518524. https://doi.org/10.1016/j.psychres.2013.01.021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sheehan, D. V. , Lecrubier, Y. , Sheehan, K. H. , Amorim, P. , Janavs, J. , Weiller, E. , … Dunbar, G. C. (1998). The mini-international neuropsychiatric interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry, 59 Suppl 20, 2233, quiz 34-57.

    • Search Google Scholar
    • Export Citation
  • Sutton, K. S. , Stratton, N. , Pytyck, J. , Kolla, N. J. , & Cantor, J. M. (2015). Patient characteristics by type of hypersexuality referral: A quantitative chart review of 115 consecutive male cases. Journal of Sex & Marital Therapy, 41(6), 563580. https://doi.org/10.1080/0092623x.2014.935539.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tabachnick, B. G. , & Fidell, L. S. (2006). Using multivariate statistics, 5th ed., (pp. 123). Pearson.

  • World Health Organization. (2018). ICD-11 - mortality and morbidity statistics. Retrieved February 9, 2020, from https://icd.who.int/browse11/l-m/en#/http%3a%2f%2fid.who.int%2ficd%2fentity%2f274880002.

    • Search Google Scholar
    • Export Citation

Supplementary Materials

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  • Bothe, B. , Tóth-Király, I. , Potenza, M. , Griffiths, M. , Orosz, G. , & Demetrovics, Z. (2019). Revisiting the role of impulsivity and compulsivity in problematic sexual behaviors. The Journal of Sex Research, 56, 166179. https://doi.org/10.1080/00224499.2018.1480744.

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  • Cohen, L. J. , Gans, S. W. , McGeoch, P. G. , Poznansky, O. , Itskovich, Y. , Murphy, S. , …, Galynker, II. (2002). Impulsive personality traits in male pedophiles versus healthy controls: Is pedophilia an impulsive-aggressive disorder? Comprehensive Psychiatry, 43(2), 127134. https://doi.org/10.1053/comp.2002.30796.

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  • Conners, C. , & MHS Staff. (2000). Conners’ continuous performance test (CPT II): Technical guide and software manual, Multi-Health Systems.

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  • Engel, J. , Veit, M. , Sinke, C. , Heitland, I. , Kneer, J. , Hillemacher, T. , … Kruger, T. H. C. (2019). Same same but different: A clinical characterization of men with hypersexual disorder in the Sex@Brain study. J Clin Med, 8(2). https://doi.org/10.3390/jcm8020157.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Gola, M. , Wordecha, M. , Sescousse, G. , Lew-Starowicz, M. , Kossowski, B. , Wypych, M. , … Marchewka, A. (2017). Can pornography be addictive? An fMRI study of men seeking treatment for problematic pornography use. Neuropsychopharmacology, 42(10), 20212031. https://doi.org/10.1038/npp.2017.78.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Grubbs, J. B. , Hoagland, K. C. , Lee, B. N. , Grant, J. T. , Davison, P. , Reid, R. C. , & Kraus, S. W. (2020). Sexual addiction 25 years on: A systematic and methodological review of empirical literature and an agenda for future research. Clinical Psychology Review, 82, 101925. https://doi.org/10.1016/j.cpr.2020.101925.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hall, C. L. , Valentine, A. Z. , Groom, M. J. , Walker, G. M. , Sayal, K. , Daley, D. , & Hollis, C. (2016). The clinical utility of the continuous performance test and objective measures of activity for diagnosing and monitoring ADHD in children: A systematic review. European Child & Adolescent Psychiatry, 25(7), 677699. https://doi.org/10.1007/s00787-015-0798-x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Hanson, R. K. , & Morton-Bourgon, K. E. (2005). The characteristics of persistent sexual offenders: A meta-analysis of recidivism studies. Journal of Consulting and Clinical Psychology, 73(6), 11541163. https://doi.org/10.1037/0022-006x.73.6.1154.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Kafka, M. P. (2010). Hypersexual disorder: A proposed diagnosis for DSM-V. Archives of Sexual Behavior, 39(2), 377400. https://doi.org/10.1007/s10508-009-9574-7.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Landgren, V. , Malki, K. , Bottai, M. , Arver, S. , & Rahm, C. (2020). Effect of gonadotropin-releasing hormone antagonist on risk of committing child sexual abuse in men with pedophilic disorder: A randomized clinical trial. JAMA Psychiatry, 77(9), 897905. https://doi.org/10.1001/jamapsychiatry.2020.0440. .

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Pallant, J. (2016). SPSS survival manual. McGraw-Hill Education.

  • Patton, J. H. , Stanford, M. S. , & Barratt, E. S. (1995). Factor structure of the Barratt impulsiveness scale. Journal of Clinical Psychology, 51(6), 768774. https://doi.org/10.1002/1097-4679(199511)51:6<768::aid-jclp2270510607>3.0.co;2-1.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Polyzoi, M. , Ahnemark, E. , Medin, E. , & Ginsberg, Y. (2018). Estimated prevalence and incidence of diagnosed ADHD and Health care utilization in adults in Sweden - a longitudinal population-based register study. Neuropsychiatric Disease and Treatment, 14, 11491161. https://doi.org/10.2147/NDT.S155838.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Reid, R. C. , Garos, S. , & Carpenter, B. N. (2011). Reliability, validity, and psychometric development of the hypersexual behavior inventory in an outpatient sample of men. Sexual Addiction & Compulsivity, 18(1), 3051. https.//doi.org/10.1080/10720162.2011.555709.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Saunders, J. B. , Aasland, O. G. , Babor, T. F. , de la Fuente, J. R. , & Grant, M. (1993). Development of the alcohol use disorders identification test (AUDIT): WHO collaborative project on early detection of persons with harmful alcohol consumption--II. Addiction, 88(6), 791804. https://doi.org/10.1111/j.1360-0443.1993.tb02093.x.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Savard, J. , Öberg, K. G. , Chatzittofis, A. , Dhejne, C. , Arver, S. , & Jokinen, J. (2020). Naltrexone in compulsive sexual behavior disorder: A feasibility study of twenty men. The Journal of Sexual Medicine, 17(8), 15441552. https://doi.org/10.1016/j.jsxm.2020.04.318. .

    • Crossref
    • PubMed
    • Search Google Scholar
    • Export Citation
  • Scanavino, M. D. T. , Ventuneac, A. , Abdo, C. H. N. , Tavares, H. , Amaral, M. L. S. D. , Messina, B. , … Parsons, J. T. (2013). Compulsive sexual behavior and psychopathology among treatment-seeking men in São Paulo, Brazil. Psychiatry Research, 209(3), 518524. https://doi.org/10.1016/j.psychres.2013.01.021.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Sheehan, D. V. , Lecrubier, Y. , Sheehan, K. H. , Amorim, P. , Janavs, J. , Weiller, E. , … Dunbar, G. C. (1998). The mini-international neuropsychiatric interview (M.I.N.I.): The development and validation of a structured diagnostic psychiatric interview for DSM-IV and ICD-10. Journal of Clinical Psychiatry, 59 Suppl 20, 2233, quiz 34-57.

    • Search Google Scholar
    • Export Citation
  • Sutton, K. S. , Stratton, N. , Pytyck, J. , Kolla, N. J. , & Cantor, J. M. (2015). Patient characteristics by type of hypersexuality referral: A quantitative chart review of 115 consecutive male cases. Journal of Sex & Marital Therapy, 41(6), 563580. https://doi.org/10.1080/0092623x.2014.935539.

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Tabachnick, B. G. , & Fidell, L. S. (2006). Using multivariate statistics, 5th ed., (pp. 123). Pearson.

  • World Health Organization. (2018). ICD-11 - mortality and morbidity statistics. Retrieved February 9, 2020, from https://icd.who.int/browse11/l-m/en#/http%3a%2f%2fid.who.int%2ficd%2fentity%2f274880002.

    • Search Google Scholar
    • Export Citation
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Please, download the file from HERE

Dr. Zsolt Demetrovics
Institute of Psychology, ELTE Eötvös Loránd University
Address: Izabella u. 46. H-1064 Budapest, Hungary
Phone: +36-1-461-2681
E-mail: jba@ppk.elte.hu

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2020  
Total Cites 4024
WoS
Journal
Impact Factor
6,756
Rank by Psychiatry (SSCI) 12/143 (Q1)
Impact Factor Psychiatry 19/156 (Q1)
Impact Factor 6,052
without
Journal Self Cites
5 Year 8,735
Impact Factor
Journal  1,48
Citation Indicator  
Rank by Journal  Psychiatry 24/250 (Q1)
Citation Indicator   
Citable 86
Items
Total 74
Articles
Total 12
Reviews
Scimago 47
H-index
Scimago 2,265
Journal Rank
Scimago Clinical Psychology Q1
Quartile Score Psychiatry and Mental Health Q1
  Medicine (miscellaneous) Q1
Scopus 3593/367=9,8
Scite Score  
Scopus Clinical Psychology 7/283 (Q1)
Scite Score Rank Psychiatry and Mental Health 22/502 (Q1)
Scopus 2,026
SNIP  
Days from  38
submission  
to 1st decision  
Days from  37
acceptance  
to publication  
Acceptance 31%
Rate  

2019  
Total Cites
WoS
2 184
Impact Factor 5,143
Impact Factor
without
Journal Self Cites
4,346
5 Year
Impact Factor
5,758
Immediacy
Index
0,587
Citable
Items
75
Total
Articles
67
Total
Reviews
8
Cited
Half-Life
3,3
Citing
Half-Life
6,8
Eigenfactor
Score
0,00597
Article Influence
Score
1,447
% Articles
in
Citable Items
89,33
Normalized
Eigenfactor
0,7294
Average
IF
Percentile
87,923
Scimago
H-index
37
Scimago
Journal Rank
1,767
Scopus
Scite Score
2540/376=6,8
Scopus
Scite Score Rank
Cllinical Psychology 16/275 (Q1)
Medicine (miscellenous) 31/219 (Q1)
Psychiatry and Mental Health 47/506 (Q1)
Scopus
SNIP
1,441
Acceptance
Rate
32%

 

Journal of Behavioral Addictions
Publication Model Gold Open Access
Submission Fee none
Article Processing Charge 850 EUR/article
Printed Color Illustrations 40 EUR (or 10 000 HUF) + VAT / piece
Regional discounts on country of the funding agency World Bank Lower-middle-income economies: 50%
World Bank Low-income economies: 100%
Further Discounts Editorial Board / Advisory Board members: 50%
Corresponding authors, affiliated to an EISZ member institution subscribing to the journal package of Akadémiai Kiadó: 100%
Subscription Information Gold Open Access
Purchase per Title  

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
Publication
Programme
2021 Volume 10
Volumes
per Year
1
Issues
per Year
4
Founder Eötvös Loránd Tudományegyetem
Founder's
Address
H-1053 Budapest, Hungary Egyetem tér 1-3.
Publisher Akadémiai Kiadó
Publisher's
Address
H-1117 Budapest, Hungary 1516 Budapest, PO Box 245.
Responsible
Publisher
Chief Executive Officer, Akadémiai Kiadó
ISSN 2062-5871 (Print)
ISSN 2063-5303 (Online)

Senior editors

Editor(s)-in-Chief: Zsolt DEMETROVICS

Assistant Editor(s): Csilla ÁGOSTON

Associate Editors

  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • Daniel KING (Flinders University, Australia)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • H. N. Alexander LOGEMANN (ELTE Eötvös Loránd University, Hungary)
  • Anikó MARÁZ (Humboldt University of Berlin, Germany)
  • Astrid MÜLLER (Hannover Medical School, Germany)
  • Marc N. POTENZA (Yale University, USA)
  • Hans-Jurgen RUMPF (University of Lübeck, Germany)
  • Attila SZABÓ (ELTE Eötvös Loránd University, Hungary)
  • Róbert URBÁN (ELTE Eötvös Loránd University, Hungary)
  • Aviv M. WEINSTEIN (Ariel University, Israel)

Editorial Board

  • Max W. ABBOTT (Auckland University of Technology, New Zealand)
  • Elias N. ABOUJAOUDE (Stanford University School of Medicine, USA)
  • Hojjat ADELI (Ohio State University, USA)
  • Alex BALDACCHINO (University of Dundee, United Kingdom)
  • Alex BLASZCZYNSKI (University of Sidney, Australia)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • Beáta BÖTHE (University of Montreal, Canada)
  • Wim VAN DEN BRINK (University of Amsterdam, The Netherlands)
  • Gerhard BÜHRINGER (Technische Universität Dresden, Germany)
  • Sam-Wook CHOI (Eulji University, Republic of Korea)
  • Damiaan DENYS (University of Amsterdam, The Netherlands)
  • Jeffrey L. DEREVENSKY (McGill University, Canada)
  • Naomi FINEBERG (University of Hertfordshire, United Kingdom)
  • Marie GRALL-BRONNEC (University Hospital of Nantes, France)
  • Jon E. GRANT (University of Minnesota, USA)
  • Mark GRIFFITHS (Nottingham Trent University, United Kingdom)
  • Heather HAUSENBLAS (Jacksonville University, USA)
  • Tobias HAYER (University of Bremen, Germany)
  • Susumu HIGUCHI (National Hospital Organization Kurihama Medical and Addiction Center, Japan)
  • David HODGINS (University of Calgary, Canada)
  • Eric HOLLANDER (Albert Einstein College of Medicine, USA)
  • Jaeseung JEONG (Korea Advanced Institute of Science and Technology, Republic of Korea)
  • Yasser KHAZAAL (Geneva University Hospital, Switzerland)
  • Orsolya KIRÁLY (Eötvös Loránd University, Hungary)
  • Emmanuel KUNTSCHE (La Trobe University, Australia)
  • Hae Kook LEE (The Catholic University of Korea, Republic of Korea)
  • Michel LEJOXEUX (Paris University, France)
  • Anikó MARÁZ (Eötvös Loránd University, Hungary)
  • Giovanni MARTINOTTI (‘Gabriele d’Annunzio’ University of Chieti-Pescara, Italy)
  • Frederick GERARD MOELLER (University of Texas, USA)
  • Daniel Thor OLASON (University of Iceland, Iceland)
  • Nancy PETRY (University of Connecticut, USA)
  • Bettina PIKÓ (University of Szeged, Hungary)
  • Afarin RAHIMI-MOVAGHAR (Teheran University of Medical Sciences, Iran)
  • József RÁCZ (Hungarian Academy of Sciences, Hungary)
  • Rory C. REID (University of California Los Angeles, USA)
  • Marcantanio M. SPADA (London South Bank University, United Kingdom)
  • Daniel SPRITZER (Study Group on Technological Addictions, Brazil)
  • Dan J. STEIN (University of Cape Town, South Africa)
  • Sherry H. STEWART (Dalhousie University, Canada)
  • Attila SZABÓ (Eötvös Loránd University, Hungary)
  • Ferenc TÚRY (Semmelweis University, Hungary)
  • Alfred UHL (Austrian Federal Health Institute, Austria)
  • Johan VANDERLINDEN (University Psychiatric Center K.U.Leuven, Belgium)
  • Alexander E. VOISKOUNSKY (Moscow State University, Russia)
  • Kimberly YOUNG (Center for Internet Addiction, USA)

 

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