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Nicholas C. Borgogna Department of Psychological Sciences, Texas Tech University, Lubbock, TX, United States

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Stephen L. Aita Veterans Affairs Maine Healthcare System, Augusta, ME, United States

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Abstract

Recent debates have evolved regarding the classification/conceptualization of compulsive sexual behavior disorder (CSBD). Conclusions regarding an agreed upon CSBD model are hindered by reliance on the latent disease model. Competing biological-based frameworks are moving forward to replace latent disease classification more broadly but have been met with limited success. We suggest that CSBD researchers move towards developing dimensional, transtheoretical, process-based models. We further suggest additional research, particularly mixed methods and longitudinal studies. Finally, we request that federal funding bodies take a more active role in supporting CSBD research.

Abstract

Recent debates have evolved regarding the classification/conceptualization of compulsive sexual behavior disorder (CSBD). Conclusions regarding an agreed upon CSBD model are hindered by reliance on the latent disease model. Competing biological-based frameworks are moving forward to replace latent disease classification more broadly but have been met with limited success. We suggest that CSBD researchers move towards developing dimensional, transtheoretical, process-based models. We further suggest additional research, particularly mixed methods and longitudinal studies. Finally, we request that federal funding bodies take a more active role in supporting CSBD research.

The recent inclusion of compulsive sexual behavior disorder (CSBD) in the International Classification of Diseases 11th Revision (ICD-11; World Health Organization [WHO], 2022) represents formal recognition of a hypothesized latent disease driving problematic sexual behaviors. The current definition indicates that CSBD is a persistent pattern of failure to control intense, repetitive sexual impulses or urges resulting in repetitive sexual behavior. Symptoms may include repetitive sexual activities becoming a central focus of the person's life to the point of neglecting health and personal care or other interests, activities and responsibilities; numerous unsuccessful efforts to significantly reduce repetitive sexual behavior; and continued repetitive sexual behavior despite adverse consequences or deriving little or no satisfaction from it. The pattern of failure to control intense, sexual impulses or urges and resulting repetitive sexual behavior is manifested over an extended period of time (e.g., 6 months or more), and causes marked distress or significant impairment in personal, family, social, educational, occupational, or other important areas of functioning. Distress that is entirely related to moral judgments and disapproval about sexual impulses, urges, or behaviors is not sufficient to meet this requirement (WHO, 2022).

Recent publications by Brand et al. (2022), Gola et al. (2022), and Sassover and Weinstein (2022) have energized the debate about how to best conceptualize problematic, addictive, impulsive, compulsive, and/or hypersexual behaviors. Additionally, several authors have identified problems with the current CSBD classification. For example, Bőthe et al. (2022) highlighted problems with the classification, such as why a “compulsive” problem is categorized under the “impulse control” category in the ICD-11. Similarly, others have opined that alternative classifications, particularly addiction models, may be more appropriate and should not be ruled out (Castro-Calvo et al., 2022; Lew-Starowicz & Coleman, 2022; Rumpf & Montag, 2022). In short, the essence of the arguments surrounding the characterization of CSBD is whether it is an addiction, impulse control disorder, aspect of a broader syndrome, or perhaps not a disorder at all. In joining this debate, we argue that this issue cannot be solved by virtue of the current state of the literature or our current understanding of mental illness. Indeed, a fundamental problem with this debate is the reliance on a latent disease model for diagnostic classification.

The latent disease model suggests that a psychiatric diagnosis is best understood as a “syndrome characterized by clinically significant disturbance in an individual's cognition, emotion regulation, or behavior that reflects a dysfunction in the psychological, biological, or developmental processes underlying mental functioning” (American Psychiatric Association, 2013; p. 20). This is the model espoused by the United States via the Diagnostic and Statistical Manual (DSM), and internationally via the ICD-11. This model assumes that all presentations are reflective of underlying latent diseases. Much the same way a fever is a symptom of underlying COVID-19, chronic pornography use could be a symptom of underlying CSBD. The problem, however, occurs when trying to determine the etiology. In the former example, COVID-19 can be easily detected via an antibody test (among other validated methods). When a positive test is observed, the probability of the symptoms being attributable to a disease with similar symptoms (e.g., influenza) drops to almost zero (excepting rare cases of comorbidity). Medical professionals, governing bodies, and the public have a general trust in such methodologies as there is robust scientific documentation of reliable and valid biological markers associated with COVID-19 and other pathogenic diseases.

The problem is such strict biomedical models do not work, or at a minimum are not easily translatable, to psychiatric illnesses. Few psychiatric illnesses share robust biological markers, with almost none of them being easily measurable. Currently, the accepted diagnostic approach is to conduct in-depth assessments via clinical interview and/or test administration to identify which cluster of symptoms match a preferred definition. In theory, this approach should lead to reliable and valid psychiatric diagnoses. However, after decades of research, this approach is only reliable at best (Insel et al., 2010). Indeed, the validity of psychiatric diagnoses, particularly discriminant validity, is almost always unsatisfactory. When a diagnosis of CSBD is determined, the probability of also being diagnosed with a separate psychiatric disorder does not drop to near zero – it increases. In other words, comorbidity is the rule not the exception. While this problem exists for virtually all psychiatric diagnoses (Jakovljević & Crnčević, 2012; van Loo, Romeijn, de Jonge, & Schoevers, 2013), it is particularly problematic for CSBD. For instance, Ballester-Arnal, Castro-Calvo, Giménez-García, Gil-Juliá, and Gil-Llario (2020) found that 91.2% of participants diagnosed with CSBD also met criteria for a comorbid axis 1 disorder. As such, new classification approaches are needed. By extension, it is a moot question whether CSBD is an addiction or impulse control disorder (or something else).

In all likelihood, there is a confluence of etiologies resulting in various CSBD presentations, some best fitting under an addiction framework and others an impulse control framework. Many presentations might be explainable from multiple frameworks simultaneously. For instance, how many clients struggling with impulsive aspects of sexual behavior (e.g., trying to resist morally incongruent urges to masturbate) also deal with addictive aspects of sexual behavior (e.g., viewing increasing amounts of harder content pornography)? Trying to parse out which model is preferable using mid-level terminology is equivalent to pathologists discussing a “Fever model of COVID-19” versus a “Cough model of COVID-19”. The COVID-19 nosology does not devolve into such debates because the etiology behind any COVID-19 presentation is easily identifiable via biological marker. Embarrassingly, this is what the argument looks like when we debate addiction versus impulse control models for CSBD. Until a better understanding of the underlying etiology (or etiologies) is developed, no agreed upon answer to the CSBD classification issue will be available.

Competing classification system: RDoC

Recognition of the problems associated with the latent disease model are not new. In the words of Hoffman and Hayes (2019), release of the DSM-5 in 2013 was met with “a notable lack of enthusiasm in almost every corner of the field” (p. 39). The same can easily be said for the current DSM-5-TR, as well as the ICD-11. In partial recognition of this problem, in the United States, the National Institute of Mental Health (NIMH) has largely moved away from a latent disease model as a program of research. In 2010, NIMH ushered in the era of the Research Domain Criteria or RDoC (Insel et al., 2010). The primary aim of the RDoC is to provide data on the basic biological processes related to mental health by developing psychiatric nosologies anchored in neuroscience instead of descriptive phenomenology (Cuthbert, 2014). By focusing on identifiable biological indicators of specific behavioral phenomena, valid diagnostic entities may become a reality. Extended to CSBD, if specific biological markers could be identified then research, treatment, and prevention would improve substantially.

While the RDoC represents a welcome alternative to the latent disease model as an advancement of CSBD research, it is not without criticism. The RDoC has been viewed as biologically reductionistic (Parnas, 2014), with others arguing that the fundamental approach to mental illness is flawed (Ross & Margolis, 2019). Concerningly, despite more than 10 years of RDoC funded programs, relatively few fundamental changes in the way we understand psychiatric illnesses have been identified.

Most concerning for CSBD, many presentations may not actually have any biological markers that are invariant/replicable on quantitative scales. The Moral Incongruence Model of problematic pornography use (Grubbs, Perry, Wilt, & Reid, 2019) exemplifies one potential issue. Religious individuals, particularly those who are “scrupulously” religious, indicate experiencing significant perceptions that their pornography use is problematic (Borgogna, Isacco, & McDermott, 2020) or even addictive (Grubbs, Exline, Pargament, Hook, & Carlisle, 2015). Yet, in many of these cases, they do not actually consume abnormal amounts of pornography, certainly not enough to be considered “addictive” in the same way as tobacco, narcotics, and alcohol (hence the term “perceived addiction” to pornography; Grubbs et al., 2015). As such, if a person describes their experience as “addictive” but does not demonstrate behavior that is consistent with the current conceptualization of addiction, it is unlikely that underlying biomarkers would be consistent between perceived addiction and actual addiction cases. In the same vein, Jennings, Gleason, and Kraus (2022) noted concern for how professionals conceptualize CSBD when considering individuals from minoritized sexual identity backgrounds. Indeed, pornography use and other sexual behaviors may be more frequent in sexually diverse people, yet this may not mean that it is necessarily associated with additional distress (Bőthe, Vaillancourt-Morel, Bergeron, & Demetrovics, 2019). Accordingly, identifying invariant biomarkers correlated with behavior would be difficult if the subjective distress associated with the behavior is non-invariant. Cultural factors influence the way behavior is perceived and experienced; in this context, it is unlikely that a purely biological explanation will be possible for all CSBD presentations.

So where do we go?

Finding a balance between valid biological indicators, culture, and subjective experience is no easy task. At this time, no definitive answer can be identified. However, some suggestions are offered in the spirit of leading us to a valid model of CSBD. First, in echoing the statements of Jennings et al. (2022), theoretical models of CSBD need to be tested against one another. It is hoped that researchers will put forth new/updated transtheoretical, dimensional (as opposed to categorical classification), and biopsychosocial frameworks of CSBD and then test them against existing models. Rigor and parsimony should be favored, and measurement should be examined with more scrutiny than is currently being employed (c.f., Fernandez & Griffiths, 2021; Kohut et al., 2020; Marshall & Miller, 2019). Researchers are also encouraged to take a process-based approach to hopefully avoid the “addiction” vs “impulse control” debates in model development. Scholars adopting process-based research in other areas may provide useful examples of the direction CSBD researchers want to go (see Hayes, Hofmann, & Ciarrochi, 2020; Hong & Cheung, 2015; Mendelson, Gates, & Lerner, 2016 for examples).

Second, a more fundamental understanding of the basic phenomenology of CSBD is needed. The current body of work is overwhelmingly cross-sectional and non-representative (Grubbs et al., 2020; Kowalewska, Gola, Kraus, & Lew-Starowicz, 2020). As such, more longitudinal, qualitative, mixed methods, and experimental designs are necessary. Advances in technology and statistical packages have made intensive longitudinal research, such as ecological momentary assessment studies, much easier today than in past times. These should be better utilized by CSBD researchers. More basic neuroscientific studies are also cautiously recommended. While the neuroscience of CSBD is burgeoning (Draps, Kowalczyk-Grębska, Marchewka, Shi, & Gola, 2021; Golec, Draps, Stark, Pluta, & Gola, 2021; Kowalewska et al., 2018, 2020), and will likely be aided by RDoC, funding for imaging studies should not necessarily be prioritized over well designed longitudinal and mixed methods approaches, at least until imaging technologies improve. This “cautious” recommendation is a direct result of the current methodological/reproducibility crisis ongoing within the neuroimaging community (Eklund, Nichols, & Knutsson, 2016; Marek et al., 2022; Mueller, Lepsien, Möller, & Lohmann, 2017; Turner, Paul, Miller, & Barbey, 2018). Altogether, a better understanding of the basic phenomenology will aid in the construction/revision of theoretical models to be tested.

Third, in echoing the sentiments of Borgogna, Garos, Meyer, Trussell, and Kraus (2022), more funding is necessary for CSBD projects. Particularly, federal funding mechanisms across the developed world are needed to advance the programs of research necessary to identify valid CSBD models. Even if the classification is imperfect, the current ICD-11 recognition of CSBD justifies the need for funding from federal bodies. With substantial financial support, improved models can be developed and then tested against one another. It is hoped that funders will better acknowledge this need in the service of improving the prevention, treatment, and understanding of CSBD.

In conclusion, it is our hope that the current classification debates evolve into empirical contests with data being the metric of evaluation. As with all sciences, the growing pains of developing scientific paradigms requires constant reevaluation. The current debates are indicative of a scientific developmental milestone. CSBD researchers have an opportunity to move beyond the fringes and into mainstream psychiatric illness research should they rise to the opportunity.

Funding sources

Nothing declared.

Authors' contribution

Dr. Borgogna is responsible for the conceptualization and writing of this manuscript. Dr. Aita provided additional comments, review, and editing of the final work.

Conflict of interest

Dr. Borgogna and Dr. Aita declare no conflicts of interest.

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    • Search Google Scholar
    • Export Citation
  • Bőthe, B. , Vaillancourt-Morel, M. P. , Bergeron, S. , & Demetrovics, Z. (2019). Problematic and non-problematic pornography use among LGBTQ adolescents: A systematic literature review. Current Addiction Reports, 6, 478494. https://doi.org/10.1007/S40429-019-00289-5/TABLES/1.

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    • PubMed
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The author instruction is available in PDF.
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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2021  
Web of Science  
Total Cites
WoS
5223
Journal Impact Factor 7,772
Rank by Impact Factor Psychiatry SCIE 26/155
Psychiatry SSCI 19/142
Impact Factor
without
Journal Self Cites
7,130
5 Year
Impact Factor
9,026
Journal Citation Indicator 1,39
Rank by Journal Citation Indicator

Psychiatry 34/257

Scimago  
Scimago
H-index
56
Scimago
Journal Rank
1,951
Scimago Quartile Score Clinical Psychology (Q1)
Medicine (miscellaneous) (Q1)
Psychiatry and Mental Health (Q1)
Scopus  
Scopus
Cite Score
11,5
Scopus
CIte Score Rank
Clinical Psychology 5/292 (D1)
Psychiatry and Mental Health 20/529 (D1)
Medicine (miscellaneous) 17/276 (D1)
Scopus
SNIP
2,184

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

Journal of Behavioral Addictions
Language English
Size A4
Year of
Foundation
2011
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

  • Joel BILLIEUX (University of Lausanne, Switzerland)
  • Beáta BŐTHE (University of Montreal, Canada)
  • Matthias BRAND (University of Duisburg-Essen, Germany)
  • Luke CLARK (University of British Columbia, Canada)
  • Daniel KING (Flinders University, Australia)
  • Ludwig KRAUS (IFT Institute for Therapy Research, Germany)
  • H. N. Alexander LOGEMANN (ELTE Eötvös Loránd University, Hungary)
  • 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)
  • Judit BALÁZS (ELTE Eötvös Loránd University, Hungary)
  • Kenneth BLUM (University of Florida, USA)
  • Henrietta BOWDEN-JONES (Imperial College, United Kingdom)
  • 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)
  • Anneke GOUDRIAAN (University of Amsterdam, The Netherlands)
  • 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 (Humboldt-Universität zu Berlin, Germany)
  • 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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