Marlene Werner1, Aleksandar Štulhofer2, Lourens Waldorp3, Tanja Jurin4. 1. Department of Psychology, Faculty of Social and Behavioral Sciences, University of Amsterdam, Amsterdam, The Netherlands. Electronic address: ma.al.werner@gmail.com. 2. Department of Sociology, Faculty of Humanities and Social Sciences, University of Zagreb, Croatia. 3. Department of Psychology, Faculty of Social and Behavioral Sciences, University of Amsterdam, Amsterdam, The Netherlands; Program Group: Psychological Methods, University of Amsterdam, Amsterdam, The Netherlands. 4. Department of Psychology, Faculty of Humanities and Social Sciences, University of Zagreb, Croatia.
Abstract
BACKGROUND: In spite of a growing interest in research on hypersexuality, consensus about its etiology and best treatment strategy has not been achieved. AIM: To further the empirical and clinical understanding of hypersexuality by exploring the structure of its symptoms using a network analytic approach. METHODS: In 2014, an online survey advertised as focusing on Internet pornography, sexual health, and relationships was carried out among Croatian men and women aged 18-60 years (Mage = 31.1 years, SD = 9.67). In a sample of 3,028 participants, we applied a network analytic approach to explore the structure of hypersexuality symptoms. In the network, nodes represented hypersexuality symptoms and associated sexual behaviors, while their connections were operationalized as partial correlations. 4 Research questions were addressed: (1) does the hypersexuality network differ between genders; (2) which symptoms are centrally positioned; (3) what is the topological location of pornography use; and (4) are there distinct clusters ("communities") of symptoms in the network? OUTCOMES: We estimated and plotted hypersexuality networks by gender using items from the Hypersexual Disorder Screening Inventory and the Hypersexual Behavioral Consequences Scale, as well as indicators of sexual desire, pornography use, sexual intercourse, and masturbation frequency. RESULTS: The structure of the hypersexuality network was surprisingly similar in women and men, both in terms of symptom centrality and the clustering of symptoms. Psychological distress and negative emotions triggered by sexual fantasies and/or behaviors, together with a loss of control over sexual feelings, occupied central positions in the networks. Pornography use was located peripherally in both the men's and women's hypersexuality networks. CLINICAL TRANSLATION: Psychological distress and negative emotions triggered by sexual fantasies and/or behaviors constituted the core of the hypersexuality network, which makes them potential prime targets for clinical intervention and calls for normalization of (presumably self-stigmatized) sexual expression through affirmative therapy and interventions that enhance self-care, self-compassion, and adaptive coping mechanisms. STRENGTHS & LIMITATIONS: This is the first network analytic approach to hypersexuality. Apart from its novel insights about the structure of hypersexuality, the study employed several methods to assure reliability and robustness of findings. Considering that networks were estimated in a convenience-based community sample, the findings might not generalize to clinically distressed individuals. CONCLUSION: Our results demonstrate the usefulness of network analytics to hypersexuality in a non-clinical sample and we encourage future clinical and longitudinal explorations of hypersexuality using this novel approach. Werner M, Štulhofer A, Waldorp L, et al. A Network Approach to Hypersexuality: Insights and Clinical Implications. J Sex Med 2018;15:373-386.
BACKGROUND: In spite of a growing interest in research on hypersexuality, consensus about its etiology and best treatment strategy has not been achieved. AIM: To further the empirical and clinical understanding of hypersexuality by exploring the structure of its symptoms using a network analytic approach. METHODS: In 2014, an online survey advertised as focusing on Internet pornography, sexual health, and relationships was carried out among Croatian men and women aged 18-60 years (Mage = 31.1 years, SD = 9.67). In a sample of 3,028 participants, we applied a network analytic approach to explore the structure of hypersexuality symptoms. In the network, nodes represented hypersexuality symptoms and associated sexual behaviors, while their connections were operationalized as partial correlations. 4 Research questions were addressed: (1) does the hypersexuality network differ between genders; (2) which symptoms are centrally positioned; (3) what is the topological location of pornography use; and (4) are there distinct clusters ("communities") of symptoms in the network? OUTCOMES: We estimated and plotted hypersexuality networks by gender using items from the Hypersexual Disorder Screening Inventory and the Hypersexual Behavioral Consequences Scale, as well as indicators of sexual desire, pornography use, sexual intercourse, and masturbation frequency. RESULTS: The structure of the hypersexuality network was surprisingly similar in women and men, both in terms of symptom centrality and the clustering of symptoms. Psychological distress and negative emotions triggered by sexual fantasies and/or behaviors, together with a loss of control over sexual feelings, occupied central positions in the networks. Pornography use was located peripherally in both the men's and women's hypersexuality networks. CLINICAL TRANSLATION: Psychological distress and negative emotions triggered by sexual fantasies and/or behaviors constituted the core of the hypersexuality network, which makes them potential prime targets for clinical intervention and calls for normalization of (presumably self-stigmatized) sexual expression through affirmative therapy and interventions that enhance self-care, self-compassion, and adaptive coping mechanisms. STRENGTHS & LIMITATIONS: This is the first network analytic approach to hypersexuality. Apart from its novel insights about the structure of hypersexuality, the study employed several methods to assure reliability and robustness of findings. Considering that networks were estimated in a convenience-based community sample, the findings might not generalize to clinically distressed individuals. CONCLUSION: Our results demonstrate the usefulness of network analytics to hypersexuality in a non-clinical sample and we encourage future clinical and longitudinal explorations of hypersexuality using this novel approach. Werner M, Štulhofer A, Waldorp L, et al. A Network Approach to Hypersexuality: Insights and Clinical Implications. J Sex Med 2018;15:373-386.
Authors: Xiaoliu Jiang; Yingfei Lu; Youjuan Hong; Ying Zhang; Lijun Chen Journal: Int J Environ Res Public Health Date: 2022-05-12 Impact factor: 4.614
Authors: Beáta Bőthe; Christian Baumgartner; Michael P Schaub; Zsolt Demetrovics; Gábor Orosz Journal: J Behav Addict Date: 2021-10-29 Impact factor: 6.756
Authors: J Castro-Calvo; M D Gil-Llario; C Giménez-García; B Gil-Juliá; R Ballester-Arnal Journal: J Behav Addict Date: 2020-06-16 Impact factor: 6.756