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Several scales assessing problematic pornography use (PPU) are available. However, in most previous studies, primarily nonclinical and Western samples were used to validate these scales. Thus, further research is needed to validate scales to assess problematic pornography use across diverse samples, including subclinical populations. The aim of the present study was to examine and compare the psychometric properties of the PPCS-18 in Hungarian and Chinese community samples and in subclinical men. A sample of Chinese community men (N1 = 695), a sample of subclinical men who were screened for PPU using the Brief Pornography Screen (N2 = 4651), and a sample of Hungarian community men (N3= 9395) were recruited to investigate the reliability and validity of the PPCS-18. Item-total score correlation, confirmatory factor analyses, reliability, and measurement invariance tests showed that the PPCS-18 yielded strong psychometric properties among Hungarian and Chinese community men and indicated potential utility in the subclinical men. The network analytic approach also corroborates that the six factors of the PPCS-18 can reflect the characteristic of the participants from different cultural contexts, and participants from community and subclinical populations. In sum, the PPCS-18 demonstrated high generalizability across cultures and community and subclinical men.
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Properties of the Problematic Pornography Consumption Scale (PPCS-18) in
community and subclinical samples in China and Hungary
Lijun Chen, Xiaohui Luo, Beáta Bőthe, Xiaoliu Jiang, Zsolt Demetrovics,
Marc.N. Potenza
PII: S0306-4603(20)30721-8
DOI: https://doi.org/10.1016/j.addbeh.2020.106591
Reference: AB 106591
To appear in: Addictive Behaviors Addictive Behaviors
Received Date: 29 April 2020
Revised Date: 23 July 2020
Accepted Date: 28 July 2020
Please cite this article as: L. Chen, X. Luo, B. Bőthe, X. Jiang, Z. Demetrovics, Marc.N. Potenza, Properties of
the Problematic Pornography Consumption Scale (PPCS-18) in community and subclinical samples in China and
Hungary, Addictive Behaviors Addictive Behaviors (2020), doi: https://doi.org/10.1016/j.addbeh.2020.106591
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Properties of the Problematic Pornography Consumption Scale (PPCS-18) in
community and subclinical samples in China and Hungary
Lijun Chena,b* , Xiaohui Luoa, Beáta Bőthec,d, Xiaoliu Jianga, Zsolt Demetrovicsc
Marc. N. Potenzae,f,g,h*
aDepartment of psychology, School of Humanities and Social Sciences, Fuzhou
University, Fujian, China;
bFaculty of education, Southwest University, Chongqing, China;
cInstitute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary;
dDépartement de Psychologie, Université de Montréal, Montréal, Canada;
eDepartment of Neuroscience, Yale University School of Medicine, New Haven, CT,
USA;
fDepartment of Child Study Center, Yale University School of Medicine, New Haven,
CT, USA;
g Connecticut Mental Health Center, New Haven, CT, USA;
h Connecticut Council on Problem Gambling, Wethersfield, CT, USA;
*Corresponding authors:
Beáta Bőthe, Ph.D., Department of Psychology, Université de Montréal, C.P. 6128,
Succursale Centre-Ville, Montréal, QC, H3C 3J7, Canada
E-mail: beata.bothe@umontreal.ca; bothe.beata@ppk.elte.hu Tel.: +1 438-833-3038
Lijun Chen, Fuzhou University, 2 Wulongjiangbei Avenue, Fuzhou, Fujian Province
350108 China; E-mail: qqkx159@126.com; t05097@fzu.edu.cn
Tel:+86-59122866562
Lijun Chen https://orcid.org/0000-0002-4327-8657
Properties of the Problematic Pornography Consumption Scale (PPCS-18) in
community and subclinical samples in China and Hungary
Abstract
Several scales assessing problematic pornography use (PPU) are available. However,
in most previous studies, primarily nonclinical and Western samples were used to
validate these scales. Thus, further research is needed to validate scales to assess
problematic pornography use across diverse samples, including subclinical
populations. The aim of the present study was to examine and compare the
psychometric properties of the PPCS-18 in Hungarian and Chinese community
samples and in subclinical men. A sample of Chinese community men (N1 = 695), a
sample of subclinical men who were screened for PPU using the Brief Pornography
Screen (N2 = 4651), and a sample of Hungarian community men (N3= 9395) were
recruited to investigate the reliability and validity of the PPCS-18. Item-total score
correlation, confirmatory factor analyses, reliability, and measurement invariance tests
showed that the PPCS-18 yielded strong psychometric properties among Hungarian
and Chinese community men and indicated potential utility in the subclinical men.
The network analytic approach also corroborates that the six factors of the PPCS-18
can reflect the characteristic of the participants from different cultural contexts, and
participants from community and subclinical populations. In sum, the PPCS-18
demonstrated high generalizability across cultures and community and subclinical
men.
Keywords: problematic pornography use; Problematic Pornography Consumption
Scale; screening; validity; cultural context
Properties of the Problematic Pornography Consumption Scale (PPCS-18) in
community and subclinical samples in China and Hungary
Data suggest that increased internet use has been accompanied by increases in
pornography consumption and frequencies of problematic pornography use (PPU),
representing clinically relevant phenomena (Brand, Antons, Wegmann, & Potenza,
2019a; Brand, Blycker, & Potenza, 2019b; de Alarcón, de la Iglesia, Casado, &
Montejo, 2019). Despite an increase in studies on internet-related problems and
disorders, conceptualizations of PPU remain debated (Hertlein & Cravens, 2014;
López-Fernández, 2015; Potenza, Gola, Voon, Kor, & Kraus, 2017; Stark, Klucken,
Potenza, Brand, & Strahler, 2018; Wéry & Billieux, 2017; Young, 2008). Multiple
terms have been used to describe the phenomenon (e.g., internet sex addiction,
problematic online sexual activities, cybersex addiction, and problematic internet
pornography use), and whether subjectively self-perceived addiction to pornography
due to moral incongruence is regarded as PPU has been debated (Brand et al., 2019a;
Vaillancourt‑Morel & Bergeron, 2019). Furthermore, there are no specific diagnostic
criteria for PPU (Brand et al., 2020; Chen & Jiang, 2020; Cooper, Griffin-Shelley,
Delmonico, & Mathy, 2001; Fernandez & Griffiths, 2019; Hertlein & Cravens, 2014;
Wéry & Billieux, 2017). In order to study and treat PPU, researchers have developed
scales that measure different aspects of PPU; however, few have been validated
across cultures and different populations (Chen & Jiang, 2020; Fernandez & Griffiths,
2019; Wéry & Billieux, 2017).
Assessment of Problematic Pornography Use
Given debates on the conceptualization of and diagnostic criteria for PPU,
assessment tools have varied across studies and emphasized different characteristics
(Fernandez & Griffiths, 2019). Multiple scales have been based largely on proposed
criteria for hypersexual disorder (e.g., the Hypersexual Behavior Inventory, Reid,
Garos, & Fong, 2012). However, recent studies suggest differences between PPU and
hypersexuality (Bőthe et al., 2019c). Hypersexuality may include high engagement in
various sexual behaviors, including masturbation, cybersex, pornography use,
telephone sex, sexual behavior with consenting adults, strip club visitations, and other
behaviors (Karila et al., 2014). Consistently, the Hypersexual Behavior Inventory
(HBI) assesses hypersexual behaviors more broadly (Brahim, Rothen,
Bianchidemicheli, Courtois, & Khazaal, 2019). Some scales have focused on
compulsive sexual behaviors more generally (e.g., Compulsive Use of Sexually
Explicit Internet Material), with these scales assessing features of compulsive
searching for/viewing of pornography on the internet (Doornwaard, Eijnden, Baams,
Vanwesenbeeck, & Bogt, 2016), rather than those of general compulsive pornography
use, and it did not undergo extensive psychometric evaluation. Some concise scales
exist that aim to measure PPU, but these have, at times, been criticized or debated
regarding their construct validity. For example, the Cyber-Pornography Use
Inventory-9 (CPUI-9, Grubbs, Sessoms, Wheeler, & Volk, 2010) has been used to
assess self-reported addiction and considers moral incongruence, although what it
precisely measures have been questioned (Brand et al., 2019a). Several recent scales
have been developed to assess aspects and domains of PPU more generally including
the Short Internet Addiction Test Adapted to Online Sexual Activities (s-IAT-sex;
Wéry, Burnay, Karila, & Billieux, 2015), the Problematic Pornography Use Scale
(PPUS; Kor et al., 2014), and the Problematic Pornography Consumption Scale
(PPCS-18; Bőthe et al., 2018b). The last two scales were recommended by a recent
systematic review (Fernandez & Griffiths, 2019). More recently, compared with the
PPUS and s-IAT-sex, the PPCS-18 demonstrated higher sensitivity and more
accuracy in screening for PPU (Chen & Jiang, 2020).
The PPCS-18, to our knowledge, is the only instrument that assesses six
specified components of one addiction model: salience, mood modification, conflict,
tolerance, relapse, and withdrawal (Griffiths, 2005). In particular, tolerance and
withdrawal are important dimensions of PPU that are not assessed by the PPUS and
s-IAT-sex (Bőthe et al., 2018b; Fernandez & Griffiths, 2019). Compared with other
measurements of PPU (i.e., the PPUS, s-IAT-sex, CPUI-9), another strength of the
PPCS is that it is one of few instruments to provide a validated cutoff score (≥76,
range 18-126) to differentiate problematic from non-problematic pornography use
(Fernandez & Griffiths, 2019), which adds to its research and clinical utility. Another
recently published screen, the Brief Pornography Screen (BPS, Kraus et al., 2020),
also provides a cutoff (≥4, range 0-10) to screen for PPU. Given its brevity and its
unidimensional structure, the BPS does not assess components such as tolerance.
While cutoffs of usage time per week have been proposed (Cooper, Delmonico, &
Burg, 2000; Mechelmans et al., 2014), usage time is not consistently related to PPU
(Bőthe, Tóth-Király, Potenza, Orosz, & Demetrovics, 2020b; Chen, Ding, Jiang, &
Potenza, 2019; Kühn, & Gallinat, 2014). In addition, convergent and divergent
validity of the PPCS has been supported in studies of sexuality-related (Bőthe,
Tóth-Király, Demetrovics, & Orosz, 2017) and personality-related (Bőthe, Koós,
Tóth-Király, Orosz, & Demetrovics, 2019a; Bőthe et al., 2019c; Bőthe, Tóth-Király,
Potenza, Orosz, & Demetrovics, 2020b) variables.
Despite the previously presented strong psychometric properties of the PPCS-18,
research is needed to further investigate its properties across cultural and
clinical/subclinical contexts (Bőthe, Tóth-Király, Demetrovics & Orosz, 2020a; Bőthe
et al., 2018b), as, for example, cultural characteristics may influence negative
attitudes toward pornography use (Griffiths, 2012; Vaillancourt-Morel & Bergeron,
2019). It has been argued that pornography use may be self-considered as problematic
in one cultural, religious, or moral background and possibly not in another (Grubbs &
Perry, 2019). Prior PPCS-18 studies may have cultural limitations since they have
been mainly conducted in Hungary (Bőthe et al., 2018a; Bőthe et al., 2019b; Bőthe et
al., 2020a; Bőthe, Lonza et al., 2020). This may constitute a significant limitation
since norms, value systems, and experiences of individuals from other cultural
backgrounds may differ from largely Western perspectives in Hungary. Regarding
pornography use and other sexual behaviors, differences in sexual attitudes,
behaviors, and well-being have been reported between Eastern and Western cultures
(Laumann et al., 2006). Thus, research on PPU is needed to ensure that assessments
are both translatable and accurate across cultures (Kraus & Sweeney, 2019). There is
relatively little empirical research on PPU in China and in other Eastern countries, and
only several studies have included participants from Eastern countries (Fernandez &
Griffiths, 2019), and cross-cultural community comparisons have not been examined.
Individuals with PPU may exhibit specific characteristics including strong
cravings, poor self-control, continued engagement despite social or occupational
impairments, and adverse consequences, and using pornography in maladaptive ways
such as to escape from stress or negative mood states (Chen et al., 2018; Cooper et al.,
2004; Kraus, Martino, & Potenza, 2016; Young, Cooper, Griffiths-Shelley, O’Mara,
& Buchanan, 2000). Wéry et al. (2016) reported that 90% of participants with PPU
reported co-occurring psychiatric diagnoses, and only a few scales have been
validated in treatment-seeking samples (Bőthe et al., 2020a; Kraus et al., 2020). Thus,
in addition to the frequency of online sexual activities, craving, compulsive sexual
behaviors, and general mental health were used to examine the criterion validity of the
PPCS. In sum, primarily nonclinical and Western samples have been used in most
studies of PPU assessments like the PPCS-18; therefore, more research is needed to
validate the PPCS-18 across more diverse samples, including clinical or subclinical
population and across cultures.
Network approach in psychopathology
Psychopathological states may exist as complex dynamic systems involving
interacting components (Borsboom, 2017). In contrast to some latent models, network
approaches propose that psychological disorders involve networks of related
symptoms, and individual psychological states may rely more on direct connections
between symptoms rather than on the existence of latent variables (Werner, Stulhofer,
Waldorp, & Jurin, 2018). Network theories and methodologies have been fruitfully
applied to different psychopathological phenomena including alcohol-use disorders
(Anker et al., 2017), anxiety (Beard et al., 2016), depression (Schweren, van Borkulo,
Fried, & Goodyer, 2018), and hypersexuality (Werner et al., 2018). Such network
models may provide important insight into the centrality of specific domains and the
patterns of their relationships. Therefore, in the current study, we used a network
approach to assess PPU network topology and identify symptoms that occupy central
positions in the network, and explored patterns of relationships of symptom domains
in the different populations. This approach will provide insight into how PPU may
interact with symptomatology across cultures and community and subclinical
samples.
The aims of the current study
Considering that men relative to women typically show stronger cravings for
pornography and more frequent use (Weinstein, Zolek, Babkin, Cohen, & Lejoyeux,
2015), more frequent PPU (Kafka, 2010; Kraus et al., 2016; Kraus, Potenza, Martino,
& Grant, 2015), and more treatment-seeking for PPU (Bőthe et al., 2020a), the aims
of the present study were (1) to examine the reliability, structure and convergent
validity of the PPCS-18 both in community and subclinical samples of Chinese men;
and (2) to examine and compare the factor structure of PPCS-18 across Hungarian
and Chinese samples, and across community and subclinical samples; and, (3) to
explore the extent to which the PPCS-18 reflects characteristics related to the different
populations in network typology analyses.
Method
Participants and Procedure
This study was conducted in accordance with the Declaration of Helsinki, and
the protocol was approved by the Ethics Committee of the Department of Psychology,
Fuzhou University, and by the Eötvös Loránd University. Data collection was
conducted via online surveys. Participants were informed about the aims of the study.
Only individuals aged 18 years or older were allowed to participate.
Sample 1: A community sample of Chinese men. This online study was
conducted through a popular Chinese survey website, namely, Wenjuanxing
(www.sojump.com, a website like Survey monkey). A total of 695 adult men (aged 18
to 48 years, Mage = 25.39, SD = 7.18) were recruited from participants from 110 cities
in 28 of the 34 provinces/regions in China (i.e., identified using the internet protocol
addresses). In May 2019, emails with a link that redirected them to the survey website
and a brief introduction to our survey were sent to potential participants, and
individuals were invited to participate in the survey if they were interested. In this
sample, the most common sexual orientations reported were heterosexual (94.4%,
656), bisexual (4.2%, 29), and homosexual (1.4%, 9). Reported relationship status
including being single (50.5%, 351), having committed sexual partners (48.0%, 334),
and having casual sexual partners (1.4%, 14).
Sample 2: A subclinical sample of Chinese men. We invited 5536 men (Mage =
22.70 years, SD = 4.33) who felt they had experienced PPU and sought help on a
website (www.ryeboy.org/, a nonprofit website focusing on interventions for PPU).
These participants were newly registered users and were screened for potential PPU
using the BPS (Kraus et al., 2020). Kraus et al. (2020) suggested a BPS cutoff score
of 4 to indicate PPU, and 4651 individuals met this criterion. In this sample,
reported sexual orientations were heterosexual (93.1%, 4330), bisexual (3.1%, 144),
and homosexual (3.8%, 177). Reported relationship status included being single
(81.6%, 3795), having committed sexual partners (16.9%,786), and having casual
sexual partners (1.5%, 70).
Sample 3: A community sample of Hungarian men. The survey in Hungary
was part of a larger project
(https://osf.io/dzxrw/?view_only=7139da46cef44c4a9177f711a249a7a4; Bőthe et al.,
2019b). Respondents were invited to participate via advertisements on one of the
largest Hungarian news portals in January 2017. A total of 10,582 men participated in
this survey; however, in order to match the ages to the Chinese sample, we only
selected the participants between 18 to 48 years old, resulting in a sample of 9395
Hungarian men (Mage = 23.35 years, SD = 3.34). The PPCS was developed in a
different Hungarian sample (Bőthe et al., 2018b), and reliability and structural validity
have been reported previously in a Hungarian cultural context (Bőthe et al., 2018b;
Bőthe et al., 2019b; Bőthe et al., 2020b). As for relationship status, 30.3% (2847)
were single, 68.5% (6436) were in any kind of romantic relationship (i.e., being in a
relationship, engaged, or married), and 1.2% (113) indicated the “other” option.
Measures
Brief Pornography Screen (BPS, Kraus et al., 2020)1. The BPS is a
screening tool for PPU (Efrati & Gola, 2018; Gola et al., 2017). It is a five-item
assessment and uses a three-point rating scale for each item (0 = never, 1 =
occasionally, 2 = always). The Cronbach’s alpha of the BPS was .89 in the Chinese
community sample and .74 in the Chinese subclinical sample.
Problematic Pornography Consumption Scale (PPCS-18, Bőthe et al.,
2018b). The PPCS translation followed guidelines for the process of cross-cultural
adaptation of self-report measures (Beaton, Bombardier, Guillemin, & Ferraz, 2000).
The initial PPCS was translated into Chinese by two graduate students, one majoring
in psychology, the other one majoring in Chinese. The PPCS includes 18-item and six
core elements: salience, mood modification, conflict, tolerance, relapse, and
withdrawal, and each factor included three items. Responses were recorded on the
following 7-point scale: 1 = never, 2 = rarely, 3 = occasionally, 4 = sometimes, 5 =
often, 6 = very often, 7 = all the time. The Cronbach’s alpha of the PPCS-18 was .95
in the Chinese community sample, .94 in the Hungarian sample, and .94 in the
Chinese subclinical sample.
Pornography Craving questionnaire (PCQ, Kraus & Rosenberg, 2014). This
12-item questionnaire is a unidimensional assessment (Kraus & Rosenberg, 2014;
1The BPS was translated into Chinese based on a preestablished translation-back-translation protocol
(Beaton et al., 2000). Confirmatory factor analysis (CFA) was conducted to examine its factor structure
in the Chinese community and subclinical samples. According to the CFA results, the scale showed
excellent structural validity in the community sample (CFI =.999, TLI =.997, RMSEA =.042 [90% CI
.000-.045]), and acceptable structural validity in the subclinical sample (CFI =.982, TLI =.964,
RMSEA =.072 [90% CI .069-.080]).
Rosenberg & Kraus, 2014). The respondents were required to indicate how strongly
they agreed with each item using the following seven response options (presented
without numerals): “completely disagree,” “somewhat disagree,” “disagree a little,”
“neither agree nor disagree,” “agree a little,” “somewhat agree” and “completely
agree.” Higher scores are indicative of a greater craving for pornography. The
Chinese version of the PCQ has been used in a previous study (Chen et al., 2019). The
Cronbach’s alpha of this scale was .92 in the Chinese community sample and .91 in
the Chinese subclinical sample.
Sexual Compulsivity Scale (SCS, Kalichman & Rompa, 1995). The extent to
which participants exhibit characteristics of sexual compulsivity was assessed using
the ten-item SCS. Responses were recorded on a four-point rating scale (1 = not at all
like me, 2 = slightly like me, 3 = mainly like me, 4 = very much like me). The
Chinese version of the SCS has been previously described (Chen & Jiang, 2020). The
SCS demonstrated excellent reliability in the present study (α was .91 in community
men and .90 in subclinical men).
Questionnaire of online sexual activities Chinese version (OSAs, Zheng &
Zheng, 2014). Thirteen items were used to measure participants’ use of the internet
for the following purposes: (1) viewing sexually explicit material (SEM), (2) seeking
sexual partners, (3) cybersex, and (4) flirting and sexual relationship maintenance.
The Cronbach’s alpha of the entire scale was .84 in the Chinese community men
and .81 in subclinical men. Higher scores were indicative of more frequent
engagement in OSAs.
12-item General Health Questionnaire (GHQ-12, Goldberg & Hillier, 1979).
The GHQ-12 is a widely used screening instrument for common mental disorders and
is recommended as a case detector since it is considered brief, effective and robust
and works as well as its longer versions (Goldberg et al.,1997; Petkovska, Bojadziev,
& Stefanovska, 2015). The GHQ-12 has been translated into many languages,
including Chinese, and its psychometric properties have been studied among many
different populations (Pan & Goldberg, 1990; Petkovska et al., 2015). The GHQ-12
includes 12 items total (six positive and six negative), each scored on a four-point
Likert scale, with higher scores reflecting worse psychological health. The
Cronbach’s alpha of the scale was .89 in Chinese community men and .93 in
subclinical men.
Statistical Analyses
First, CFA was conducted on the Hungarian men, then on Sample 1 and
Sample 2 to cross-validate the results in the community and subclinical samples of
Chinese men. The mean- and variance-adjusted weighted least squares estimator
(WLSMV) was used for parameter estimation. Model fit indices were determined by
Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), and the Root Mean Square
Error of Approximation (RMSEA) and standardized root mean square residual
(SRMR). CFI and TLI values greater than .95 were considered as excellent fit (≥.90
for acceptable fit). RMSEA values of less than .06 were considered excellent (≤ .08
for adequate fit, and .10 for acceptable fit with its 90% confidence interval)
(Browne & Cudeck, 1993; Schermelleh-Engel et al., 2003). SRMR values less than
0.08 (≤.06 for a good fit) were considered indicative of an acceptable model (Hu &
Bentler, 1999). Additionally, to test measurement invariance among different cultural
contexts (Hungarian and Chinese), and community and subclinical populations,
multi-group CFAs were conducted on the three samples. Six levels of invariance were
tested and compared in each case: configural, metric, scalar, residual, latent variance,
and latent mean. When comparing the increasingly constrained models, relative
changes in fit indices were observed, with a recommended acceptable range as
follows: ΔCFI .010; ΔTLI .010; and ΔRMSEA .015 (Meade, Johnson, &
Braddy, 2008).
Cronbach’s alpha and Composite Reliability (CR) values were also calculated.
Associations between the sexual compulsivity scale (SCS), pornography craving
questionnaire (PCQ), general health questionnaire (GHQ-12), frequency of OSAs,
BPS, and PPCS-18 were assessed to corroborate the validity of the PPCS-18.
Correlations between variables were examined using Pearson correlation coefficients
after controlling for age, sexual orientation, and relationship status.
We estimated and analyzed the PPCS-18 networks in two steps. The first step
was to establish a regularized network, also known as a markov random field. LASSO
regression was adopted for adjustment to reduce the appearance of false connections.
As described previously (Epskamp & Fried, 2017), the EBIC hyperparameter was set
at .5. Second, we assessed the relative position of nodes using centrality statistics and
tested three common centrality metrics: node strength, closeness, and betweenness
centrality. Among them, betweenness centrality refers to the number of times that a
node stays on the shortest path between other nodes. Closeness centrality is the
inverse of the sum of the shortest paths from one node to all other nodes. In addition,
we compared the global strength of connectivity for each network (i.e., the sum of all
the associated strengths) using the Network Comparison Test. All network analyses
were performed using the qgraph, dplyr, NetworkComparisonTest, and bootnet
packages in R. (Version 3.6.2).
Results
Validity and reliability of the PPCS-18 in Chinese community and
subclinical men
Findings relating to item-total correlations, CFAs, reliability, and convergent
validity are shown in Table 1. The correlation coefficients of the items and their
corresponding total scores were calculated to demonstrate adequate fit of item
analysis: the PPCS-18 had strong correlations between items in the subclinical
Chinese men, and the PPCS-18 demonstrated good or acceptable fit indices using
CFA among the two community samples. Although the RMSEA was slightly higher
than the threshold in the subclinical men, the CFI, SRMR were good, and the TLI was
acceptable. Based on the correlation analyses, the PPCS-18 had positive associations
with qualitative indicators of sexual compulsivity, pornography craving, and general
mental health, followed by quantitative indicators, including frequency of OSAs.
--------- Table 1---------
--------- Table 2---------
Measurement invariance test of the PPCS-18 across cultures and in
community and subclinical men
The results of measurement invariance are shown in table 3. For configural
invariance, RMSEA was slightly higher than the recommended threshold value
(i.e., .10), but the model demonstrated acceptable fit indices on the CFI, TLI, and
SRMR. Thus, we retained this model for the further steps of invariance testing. In the
metric model, the fit indices were more suitable compared to the preceding model.
Then, scalar and residual invariance were achieved, but latent mean invariance was
not, suggesting the presence of latent mean differences between the community and
subclinical men (see Table 3). When the subclinical men’s latent mean differences
were constrained to zero for the purpose of model identification, individuals’ latent
means in the community men were substantially lower than participants’ latent means
in the subclinical men (Sample 1: -0.88 to -1.81 SD in the six factors, p < .001;
Sample 3: -0.39 to -2.46 SD in the six factors, p < .01), indicating that subclinical
individuals demonstrated significantly higher scores on the PPCS than those in the
Chinese and Hungarian community samples. In sum, the PPCS-18 had similar
meanings and latent structure in Chinese and Hungarian community men, and it may
be used in comparisons of Chinese and Hungarian men.
--------- Table 3--------
Interaction of the six factors of the PPCS-18 in each sample
Results of Markov random fields showed that there was a significant
difference between the Hungarian and Chinese men (p < .01). Among the Chinese
community and subclinical men, conflict was negatively related to salience;
otherwise, conflict did not relate to salience directly, and had positive correlations
with other factors among Hungarian men (see Figure 1). Schematic diagrams of
Chinese community and subclinical men were similar, and no significant difference in
the global strength of connectivity was observed (p = 0.6). Centrality estimates are
presented in Figure 2 (centrality plots). In the three samples’ networks, withdrawal
was the most central node, while tolerance was also a central node in the subclinical
individuals’ network. In support of these estimates, withdrawal was characterized by
high predictability in all networks (Chinese community men:76.8%, Chinese
subclinical men: 68.8%, and Hungarian community men: 64.2%).
--------- Figure 1 ----------
--------- Figure 2 ----------
Discussion
Although several scales for assessing PPU are available to researchers and
clinicians, few have been subsequently revalidated across different cultures, and the
psychometric properties of scales in subclinical men have rarely been examined.
Additionally, how symptom domains related to PPU relate (i.e., interrelationships
between salience, withdrawal, tolerance, mood modification, conflict, and relapse) in
such samples is poorly understood (Bőthe, Lonza, et al., 2020). Therefore, we
examined the reliability and validity of the PPCS-18 in Chinese contexts and
demonstrated support for its use in Chinese community and subclinical men. The
Chinese version of the PPCS-18 demonstrated high internal consistency, composite
reliability, and convergent validity in both Chinese community and subclinical men.
Measurement invariance testing suggested that the scale was similarly applicable to
the Hungarian community, the Chinese community, and the Chinese subclinical
populations, supporting the scale’s potential cross-cultural and clinical utility.
Network analysis showed that the interaction between the six factors of the PPCS-18
was significantly different in Hungarian and Chinese men. Centrality estimates
indicated that the subclinical sample’s core symptoms were withdrawal and tolerance,
but only the withdrawal domain was a central node in both community samples.
Validity and reliability of the PPCS-18 in Chinese populations
The construct validity and reliability of the PPCS-18 were cross-validated on
these three independent and distinct samples. Not only was the construct validity of
the PPCS-18 supported, but also its convergent validity was established by reporting
its associations with pornography craving, compulsive sexual behaviors, frequencies
of OSAs, and participants’ general psychological health levels. Similar to a prior
study (Bőthe et al., 2020b), the frequency of OSAs did not appear as reliable an
indicator of PPU, due to the correlation coefficients between four sub-types of OSAs
and PPCS-18 ranging from small to large, which suggests that the PPCS-18 may also
be sensitive to quantitative aspects of PPU in Chinese contexts, although this
possibility warrants additional study.
Besides the frequency of consumption, qualitative aspects such as content that
may elicit pornography craving should be considered (Kraus & Rosenberg, 2014).
The subjective experience of craving is a common element of addictions (Kraus &
Rosenberg, 2014), and is relevant in predicting the occurrence, maintenance and
relapse of addictive behaviors after withdrawal (Drummond, Litten, Lowman, & Hunt,
2000). Consistent with previous studies (Gola & Potenza, 2016; Young et al., 2000),
worse mental health scores and more compulsive sexual behaviors correlated with
higher PPCS scores. These results suggest it may be advisable to consider craving,
mental health factors, and compulsive use in screening and diagnosing PPU (Brand,
Rumpf et al., 2020).
The PPCS-18 demonstrated scale invariance in Hungarian and Chinese
community men, which indicated that it might be reliably used in both two cultures.
Additionally, measurement invariance testing indicated that the latent mean of
PPCS-18 scores was higher among subclinical men than in those in the community,
corroborating previous findings (Bőthe et al., 2020a; Bőthe, Lonza, et al., 2020).
Subclinical men reported higher scores on all six factors of the PPCS-18 compared to
community men (see Table 2), further supporting its validity and also demonstrating
the scale’s potential clinical utility. Consistent with current findings, individuals with
PPU often exhibit craving, poor self-control, worse mental health (Chen et al., 2018;
Cooper et al., 2004). In addition, excessive use and poor control (i.e., difficulty
controlling urges/craving) are shared among various definitions of and scales
assessing PPU (Bőthe et al., 2017; Goodman, 1998; Kafka, 2013; Kraus et al., 2016;
Wéry & Billieux, 2017). Our data support that the PPCS-18 shows similar
characteristics in China as in other jurisdictions and among subclinical men.
Networks of PPU symptoms in community and subclinical men
Similar to the application of a network approach in hypersexuality (Werner et
al., 2018), we applied this approach to PPU in order to examine whether the PPCS-18
demonstrates similar or distinct relationships across different samples. The overall
network topologies of the three samples suggest that the relationships between
domains of the PPCS-18 may have culture-related differences. In Chinese men, the
conflict factor was negatively associated with salience, while in Hungarian men,
salience did not relate to conflict. In parallel with massive socio-economic changes
over past decades in China, increasingly more Chinese people are criticizing
conservative sexual attitudes, especially those who define sex as immoral, and
instead, they have begun to highlight the importance of sexual pleasure (Lin, 2018;
Wong, 2014). In the current study, participants were men. In predominating sexual
scripts in China, men are encouraged to pursue sexual expression and exhibit more
permissive sexual attitudes (Zheng et al., 2011). Therefore, when men’s thoughts may
be focused on pornography, they may not experience conflict. On the other hand, the
assessment of the “conflict” component on the PPCS is limited to its inclusion of
more peripheral aspects of conflict (e.g., negative effects on sexual life) and exclusion
of more central aspects of conflict (e.g., interpersonal conflict) (Fernandez &
Griffiths, 2019). However, the precise reasons for underlying differences in
relationships between Chinese and Hungarian men in relationships between conflict
and salience warrant additional study, particularly given that factors like social
acceptance and governmental regulation of pornography use may differ across
jurisdictions.
Additionally, centrality estimates in the six factors of the PPCS-18 displayed
withdrawal as the most crucial factor in all three samples. According to the strength,
closeness, and betweenness centrality results among subclinical participants, tolerance
also contributed importantly, being second only to withdrawal. These findings suggest
that withdrawal and tolerance are particularly important in subclinical individuals.
Tolerance and withdrawal are considered as physiological criteria relating to
addictions (Himmelsbach, 1941). Concepts like tolerance and withdrawal should
constitute a crucial part of future research in PPU (de Alarcón et al., 2019; Fernandez
& Griffiths, 2019). Griffiths (2005) postulated that tolerance and withdrawal
symptoms should be present for any behavior to be considered addictive. Our
analyses support the notion that withdrawal and tolerance domains are important
clinically for PPU. Consistent with Reid’s view (Reid, 2016), evidence of tolerance
and withdrawal in patients with compulsive sexual behaviors may be an important
consideration in characterizing dysfunctional sexual behaviors as addictive.
Limitations and future studies
The present study is not without limitations. First, temporal stability was not
tested. Second, data were collected using self-report measures; therefore, the
reliability of the results depends on respondents’ honesty and accuracy and their
comprehension of items. Third, the RMSEA value was slightly higher in the
subclinical samples, warranting further research. Participants included only men aged
18-48 years; thus, the applicability of the PPCS-18 in older populations and women
should be further examined. It still unclear whether gender-related differences may be
influenced by cultural or jurisdictional factors. Hence, more research is needed to
validate the PPCS-18 across more diverse samples, including women, diverse age
groups, and other cultures and jurisdictions. Additionally, the subclinical group
studied was derived from an online forum. The extent to which the findings may
extend to other settings (e.g., those providing face-to-face treatment) warrants further
study.
Conclusions
The PPCS-18 had strong psychometric properties in community men from
Hungary and China, and subclinical men from China who reported poorly controlled
pornography use. Thus, the PPCS-18 appears to be a valid and reliable measure to
assess PPU across specific Western and Eastern jurisdictions and may be used among
subclinical individuals. Furthermore, relationships between the PPCS-18 domains also
can reflect distinct characteristics of different populations, and the current findings
suggest that withdrawal and tolerance are important to consider in PPU. The findings
advance understanding by reporting subclinical and community samples in China,
expanding the generalizability of the PPCS-18, and exploring relationships between
different symptom domains across cultures.
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Statement of authorship:
Conceptualization: Lijun Chen
Methodology: Lijun Chen, Xiaohui Luo
Formal analysis: Beáta Bőthe, Xiaohui Luo, Lijun Chen
Investigation: Xiaoliu Jiang, Xiaohui Luo
Resources: Marc. N. Potenza, Lijun Chen, Zsolt Demetrovics
Data curation: Lijun Chen, Beáta Bőthe
Writing—original draft preparation: Lijun Chen
Writing—review and editing: Lijun Chen, Beáta Bőthe, Marc. N. Potenza
Visualization: Beáta Bőthe, Xiaoliu Jiang, Xiaohui Luo
Supervision: Marc. N. Potenza, Zsolt Demetrovics
Project administration: Lijun Chen, Marc. N. Potenza, Zsolt Demetrovics.
Funding: The research was supported by the National Social Science Foundation of
China (Grant No. 19BSH117 and CEA150173) and the Education Reform Project of
Fujian province (FBJG20170038). BB was funded by a postdoctoral fellowship award
by Team SCOUP – Sexuality and Couples – Fonds de recherche du Québec, Société et
Culture. ZD was supported by the Hungarian National Research, Development and
Innovation Office (Grant numbers: KKP126835, NKFIH-1157-8/2019-DT). MNP’s
involvement was supported by the National Center for Responsible Gaming through a
Center of Excellence grant. The funding agencies did not have input into the content of
the manuscript and the views described in the manuscript reflect those of the authors
and not necessarily those of the funding agencies.
Funding: The research was supported by the National Social Science Foundation of
China (Grant No. 19BSH117 and CEA150173) and the Education Reform Project of
Fujian province (FBJG20170038). BB was funded by a postdoctoral fellowship award
by Team SCOUP – Sexuality and Couples – Fonds de recherche du Québec, Société et
Culture. ZD was supported by the Hungarian National Research, Development and
Innovation Office (Grant numbers: KKP126835, NKFIH-1157-8/2019-DT). MNP’s
involvement was supported by the National Center for Responsible Gaming through a
Center of Excellence grant. The funding agencies did not have input into the content of
the manuscript and the views described in the manuscript reflect those of the authors
and not necessarily those of the funding agencies.
Contributors:
Lijun Chena,b* , Xiaohui Luoa, Beáta Bőthec,d, Xiaoliu Jianga, Zsolt Demetrovicsc
Marc. N. Potenzae,f,g,h*
aDepartment of psychology, School of Humanities and Social Sciences, Fuzhou
University, Fujian, China;
bFaculty of education, Southwest University, Chongqing, China;
cInstitute of Psychology, ELTE Eötvös Loránd University, Budapest, Hungary;
dDépartement de Psychologie, Université de Montréal, Montréal, Canada;
eDepartment of Neuroscience, Yale University School of Medicine, New Haven, CT,
USA;
fDepartment of Child Study Center, Yale University School of Medicine, New Haven,
CT, USA;
g Connecticut Mental Health Center, New Haven, CT, USA;
h Connecticut Council on Problem Gambling, Wethersfield, CT, USA;
Conflict of interest: The authors declare no conflict of interest with respect to the
content of this manuscript.
Acknowledgments: We would like to acknowledge Bin Wu and Yan Zhao (the
founders of the “Reyboys”, a non-governmental organization focusing on helping the
problematic internet pornography users) for their help to recruit participants who
sought help for their pornography use on “Reyboys” website , and pay tribute to them
for their effort in helping the problematic users.
Highlights
PPCS-18 yielded strong psychometric properties among Chinese men.
The network analytic approach corroborated the six factors of the PPCS-18.
PPCS-18 demonstrated high generalizability across cultures.
PPCS-18 demonstrated high generalizability across community and
subclinical men.
PPCS-18 may be reliably used in subclinical samples.
Figure 1. Network schematic diagram in three groups of men.
Notes. The Chinese community men’s network is presented on the left and the
Hungarian community men’s network on the right. The middle is the network of
Chinese subclinical sample men. Solid edges indicate positive and dashed edges
indicate negative relationships.
Figure 2. Node centrality plot in the three groups of men
Table 1. Reliability and validity of the PPCS-18 in the three groups of men
Confirmatory Factor Analysis
Samples
rs
(Item-
Total
Correl
ation)
WLSM
2/df
TL
I
RMSE
A
[90%
CI]
SR
MR
α
C
R
Hungarian
community men
(.58-.73
) ***
7155.75
8/120
.96
5
.079[.07
7, .081]
.029
.9
4
.97
Chinese
community men
(.61-.83
) ***
723.926
/120
.97
4
.085[.07
9, .091]
.026
.9
5
.97
Table 2. Descriptive analysis and associations between the PPCS-18 scores with
other measures in Chinese community and subclinical men
Chinese community men (N = 695)
Chinese subclinical men (N = 4651)
Scales
Ra
ng
e
Skewne
ss (SE)
Kurtosi
s (SE)
M(SD
)
PPC
S-18
Skewnes
sSE)
Kurtosis
(SE)
M(SD)
PPC
S-18
1. PPCS-18
1-7
.76 (.09)
-0.15
(.19)
2.58
(1.31)
_
0.10
(.04)
-0.63
(.07)
4.36
(1.33)*
**
_
1.1Salience
1-7
1.01
(.09)
0.72
(.19)
2.22
(1.20)
.78**
*
0.50
(.04)
-0.88
(.07)
3.39
(1.65)*
**
.82**
*
1.2 mood
modification
1-7
0.85
(.09)
-0.06
(.19)
2.48
(1.44)
.82**
*
0.22
(.04)
-0.47
(.07)
3.76
(1.74)*
**
.82**
*
1.3 conflict
1-7
0.79
(.09)
-0.36
(.19)
2.82
(1.73)
.81**
*
-0.50
(.04)
-0.99
(.07)
5.09
(1.49)*
**
.75**
*
Chinese
help-seeking
men
(.53-.79
) ***
6381.47
9/120
.93
8
.106[.10
4, .108]
.035
.9
4
.96
Notes. CFI = comparative fit index, TLI = Tucker-Lewis index, RMSEA =
root mean square error of approximation, CI = confidence interval,
SRMR=Standardized Root Mean Square Residual; α = Cronbach’s alpha;
CR= composite reliability *** p < .001.
1.4 tolerance
1-7
1.24
(.09)
0.83
(.19)
2.34
(1.52)
.90**
*
-0.07
(.04)
-0.60
(.07)
4.34
(1.73)*
**
.88**
*
1.5 relapse
1-7
0.71
(.09)
-0.61
(.19)
2.95
(1.80)
.89**
*
-0.60
(.04)
-0.45
(.07)
5.30
(1.47)*
**
.77**
*
1.6
withdrawal
1-7
0.92
(.09)
0.13
(.19)
2.53
(1.48)
.91**
*
0.01
(.04)
-0.89
(.07)
4.31
(1.65)*
**
.88**
*
2. SCS
1-4
0.76
(.09)
0.10
(.19)
1.99
(0.71)
.75
***
-0.29
(.04)
-0.49
(.07)
2.90
(0.68)*
**
.57
***
3. PCQ
1-7
0.57
(.09)
-0.36
(.19)
2.94
(1.30)
.74
***
0.26
(.04)
-0.67
(.07)
4.23
(1.37)*
**
.65
***
4. BPS
0-2
0.40
(.09)
-0.96
(.19)
0.75
(0.61)
.81
***
-0.43
(.04)
-1.15
(.07)
1.55
(0.39)*
**
.61
***
5. GHQ
0-3
1.10
(.09)
1.37
(.19)
0.93
(0.55)
.43
***
0.18
(.04)
-0.68
(.07)
1.57
(0.69)*
**
.38
***
6. OSAs
1-9
1.39
(.09)
2.32
(.19)
2.20
(1.01)
.56
***
1.68
(.04)
4.03
(.07)
2.90
(1.15)*
**
.39
***
6.1Viewing
SEM
1-9
0.83
(.09)
0.29
(.19)
2.91
(1.44)
.63
***
0.32
(.04)
-0.07
(.07)
4.49
(1.55)*
**
.48
***
6.2Flirt and
relationship
1-9
1.62
(.09)
2.03
(.19)
2.10
(1.56)
.14
***
2.12
(.04)
4.29
(.07)
1.95
(1.58)*
**
.08
***
6.3 Partner
seeking
1-9
2.35
(.09)
5.36
(.19)
1.63
(1.24)
.26
***
2.87
(.04)
8.75
(.07)
1.64
(1.43)
.15
***
6.4 Cybersex
1-9
2.27
(.09)
6.08
(.19)
1.65
(1.13)
.41
***
1.98
(.04)
3.88
(.07)
2.02
(1.61)*
**
.22
***
Notes. PPCS-18 was developed in the Hungarian sample, so external and convergent in Hungarian
sample was not measured. SCS = Sexual Compulsivity Scale, PCQ = Pornography Craving
Questionnaire, OSAs = online sexual activities, BPS= the brief pornography screen, GHQ=general
health questionnaire, SEM = sexually explicit material. ***above the M (SD) of subclinical men
indicates a significant difference from the community men.
*** p < .001.
Table 3. Indices of the measurement invariance test for the PPCS-18 across cultural contexts and community/subclinical men
Model
WLSMVχ2(df)
CFI
TLI
RMSEA
90% CI
SRMR
χ2(df)
CFI
TLI
RMSEA
(A) Configural
25622.135*(360)
.935
.917
.120
.118-.121
.035
——
——
——
——
(B) Metric
15057.070*(384)
.962
.955
.088
.087-.089
.031
-12490.935*(24)
.007
.038
-.032
(C) Scalar
16788.044*(552)
.958
.965
.077
.076-.078
.034
1730.974*(168)
-.004
.010
-.011
(D) Residual
17521.081*(588)
.956
.966
.077
.076-.078
.038
733.037*(36)
-.002
.001
.000
(E) Latent variance
8649.892*(630)
.981
.986
.049
.048-.050
.050
-8871.189*(42)
.025
.020
-.028
(F) Latent means
74078.612*(642)
.811
.865
.153
.152-.154
.082
65428.72*(12)
-.170
-.121
.104
Notes. WLSMV = weighted least squares mean- and variance-adjusted estimator; χ2 = Chi-square; df = degrees of freedom; TLI is the TLI
difference of the row model and the previous model; CFI is the CFI difference of the row model and the previous model. RMSEA is
RMSEA change of the row model and the previous model. Bold letters indicate the final levels of invariance that were achieved. *p < .01
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Background: Previously, variable-centered analytic approaches showed positive, weak-to-moderate associations between frequency of pornography use (FPU) and problematic pornography use (PPU). However, person-centered studies are sparse in the literature, and these could provide insight into whether there are individuals who use pornography frequently and do not experience problems or whether there are individuals with comparable high-frequency use who differ on reported experiencing of negative consequences. Aim: The aims of the present study were (i) to identify profiles of pornography use based on FPU and PPU by applying a person-centered analytic approach and (ii) to examine whether the identified profiles could be distinguished based on theoretically relevant demographic and psychological constructs. Methods: Latent profile analyses were conducted on 3 nonclinical samples recruited from general websites and a pornography site (study 1: N = 14,006; study 2: N = 483; study 3: N = 672). Results: Results were consistent across all studies. 3 distinct pornography-use profiles emerged: nonproblematic low-frequency pornography use (68-73% of individuals), nonproblematic high-frequency pornography use (19-29% of individuals), and problematic high-frequency use (3-8% of individuals). Nonproblematic and problematic high-frequency-use groups showed differences in several constructs (ie, hypersexuality, depressive symptoms, boredom susceptibility, self-esteem, uncomfortable feelings regarding pornography, and basic psychological needs). Clinical translation: FPU should not be considered as a sufficient or reliable indicator of PPU because the number of people with nonproblematic high-frequency use was 3-6 times higher than that with problematic high-frequency use. These results suggest that individuals with PPU use pornography frequently; however, FPU may not always be problematic. Strengths & limitations: Self-report cross-sectional methods have possible biases that should be considered when interpreting findings (eg, underreporting or overreporting). However, the present research included 3 studies and involved large community samples and visitors of a pornography website. The present study is the first that empirically investigated pornography-use profiles with a wide range of correlates using both severity of PPU and FPU as profile indicators on specific and general samples. Conclusion: The present study is a first step in the differentiated examination of pornography-use profiles, taking into consideration both PPU and FPU, and it provides a foundation for further clinical and large-scale studies. Different psychological mechanisms may underlie the development and maintenance of FPU with or without PPU, suggesting different treatment approaches. Therefore, the present results may guide clinical work when considering reasons for seeking treatment for PPU. Bőthe B, Tóth-Király I, Potenza MN, et al. High-Frequency Pornography Use May Not Always Be Problematic. J Sex Med 2020;XX:XXX-XXX.
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The primary aim of this study was to compare different screening tools for problematic internet pornography use (IPU) and identify the most accurate measure. The reliability and validity of three scales, namely, the Problematic Pornography Consumption Scale (PPCS), Problematic Pornography Use Scale (PPUS), and Short Internet Addiction Test Adapted to Online Sexual Activities(s-IAT-sex), were examined using three homogeneous groups, respectively. A total of 972 adults (mean age = 24.8) from 28 provinces/regions in China participated in the quantitative part (QUAN). The Brief Pornography Screener served as the reference standard. The PPCS demonstrated stronger reliability and validity, including criterion validity, as well as greater sensitivity and acceptable specificity; therefore, it was considered to be the more accurate screening instrument. In the qualitative part (QUAL), we interviewed 22 volunteers and 11 therapists (who had worked with individuals with problematic IPU) to examine their perspectives on the core features of problematic IPU and dimensions of the PPCS. Almost all the interviewees endorsed the structure of the PPCS. These findings encourage the use of the PPCS in future research studies and underscore its screening applications because of its ability to classify IPU as problematic or nonproblematic.
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To date, no short scale existed that could assess problematic pornography use (PPU) having a solid theoretical background and strong psychometric properties. Having such a short scale may be advantageous when scarce resources are available and/or when respondents’ attention spans are limited. The aim of the present investigation was to develop a short scale that can be utilized to screen for PPU. The Problematic Pornography Consumption Scale (PPCS-18) was used as a basis for the development of a short measure of PPU (PPCS-6). A community sample (N1=15,051), a sample of pornography site visitors (N2=760), and a sample of treatment-seeking individuals (N3=266) were recruited to investigate the reliability and validity of the PPCS-6. Also, its association was tested to theoretically-relevant correlates (e.g., hypersexuality, frequency of masturbation), and a cut-off score was determined. The PPCS-6 yielded strong psychometric properties in terms of factor structure, measurement invariance, reliability, correlated reasonably with the assessed variables, and an optimal cut-off was identified that could reliably distinguish between PPU and non-problematic pornography use. PPCS-6 can be considered as a short, reliable, and valid scale to assess PPU in studies when the length of a questionnaire is essential or when a brief screening for PPU is necessary.
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Background and aims: Cybersex is increasingly associated with concerns about compulsive use. The aim of this study was to assess the roles of motives and sexual desire in the compulsive use of cybersex. Methods: The sample consisted of 306 cybersex users (150 men and 156 women). The participants were assessed using the Compulsive Internet Use Scale (CIUS) adapted for cybersex, the Cybersex Motives Questionnaire (enhancement, coping, and social motives), and the Sexual Desire Inventory-2 (dyadic and solitary sexual desire). Results: For both genders, coping motive was associated with CIUS score. For women, an additional association with social motives was found whereas an association with sexual desire was found for men. Conclusion: The study showed gender differences in the contributors to sex-related CIUS scores.
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Introduction: Attention deficit hyperactivity disorder (ADHD) is one of the most prevalent comorbid disorders in hypersexuality; however, previous studies only examined the associations of ADHD and hypersexuality among men seeking treatment. Although problematic pornography use (PPU) might be considered the most frequent manifestation of hypersexuality, no previous research examined its association with ADHD symptoms. Aim: To (i) examine ADHD symptoms in relation to hypersexuality and PPU and (ii) identify possible similarities and differences in relationship with hypersexuality and PPU in a large, non-clinical sample between both sexes. Methods: Multi-group structural equation modeling was conducted to investigate the hypothesized associations among adult ADHD symptoms, hypersexuality, and PPU between men and women (N = 14,043 participants; women = 4,237; mean age = 33.5 years, SD = 10.9). Main Outcome Measures: Adult ADHD symptoms were assessed in relation to hypersexuality and PPU via self-reported measures. Results: Results indicated that hypersexuality had positive and moderate association with problematic pornography use among women (r[14041] = .50, p < .01) and positive and strong association among men (r[14041] = .70, p < .01). ADHD symptoms had positive and moderate associations with hypersexuality in both men and women (β = .50, p < .01; β = .43; p < .01; respectively). Regarding men, ADHD symptoms had a positive, moderate association with PPU (β = .45, p < .01), whereas ADHD symptoms had a positive, but weak, association with PPU in the case of women (β = .26, p < .01). Clinical Implications: When men have high levels of hypersexuality or PPU, ADHD should be assessed as a potential comorbid disorder. With regard to women, ADHD should be assessed as a potential comorbid disorder only in the case of hypersexuality. Strength & Limitations: Applying self-report methods have possible biases that should be taken into account when interpreting the present findings. However, the present study was conducted on a large community sample and examined the differentiated role of ADHD symptoms in hypersexuality and PPU, not only in men but also in women, that has never been addressed in the literature. Conclusion: ADHD symptoms might play an important role in the severity of hypersexuality between both sexes, whereas ADHD symptoms might only play a stronger role in PPU among men but not women. The findings corroborate previous results that PPU may not be unambiguously considered as a subcategory of hypersexuality. In addition, potential background mechanisms behind problematic pornography use should be examined separately between men and women.
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Questions remain regarding how best to define problematic online sexual activities (OSAs) and about paths that may lead to problematic use of OSAs and their consequences. Although frequency and duration of use and motivational drive, as expressed through craving, to view pornography have been implicated in problematic OSAs, their inter-relationships warrant direct examination. We propose and test a model by which pornography craving may promote more frequent engagement in OSAs and more time spent engaging in OSAs, and this may lead to problematic OSAs and subsequent negative consequences like negative emotions. Data from 1070 college students suggested that 20.63% of students were at risk of problematic OSAs use, and this group had greater frequency of OSAs, more usage time, higher pornography craving and more negative academic emotions. Our proposed path model was partially supported. Pornography craving was associated with problematic OSAs use more, so through frequency than quantity of OSAs, and OSAs were related to negative academic emotions. Future studies of problematic OSAs use should consider the complexity of relationships between craving, use of OSAs and negative health measures in college students and other groups.
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Background Pornography use may become problematic for 1–6% of the people and may be associated with adverse consequences leading to treatment-seeking behavior. Although the identification of the central symptoms of problematic pornography use (PPU) may inform treatment strategies, no prior study has applied the network approach to examine the symptoms of PPU. Aim To explore the network structure of PPU symptoms, identify the topological location of pornography use frequency in this network, and examine whether the structure of this network of symptoms differs between participants who considered and those who did not consider treatment. Methods A large-scale online sample of 4,253 men (Mage = 38.33 years, SD = 12.40) was used to explore the structure of PPU symptoms in 2 distinct groups: considered treatment group (n = 509) and not-considered treatment group (n = 3,684). Outcomes Participants completed a self-report questionnaire about their past-year pornography use frequency and PPU measured by the short version of the Problematic Pornography Consumption Scale. Results The global structure of symptoms did not differ significantly between the considered treatment and the not-considered treatment groups. 2 clusters of symptoms were identified in both groups, with the first cluster including salience, mood modification, and pornography use frequency and the second cluster including conflict, withdrawal, relapse, and tolerance. In the networks of both groups, salience, tolerance, withdrawal, and conflict appeared as central symptoms, whereas pornography use frequency was the most peripheral symptom. However, mood modification had a more central place in the considered treatment group’s network and a more peripheral position in the not-considered treatment group’s network. Clinical Implications Based on the results of the centrality analysis in the considered treatment group, targeting salience, mood modification, and withdrawal symptoms first in the treatment may be an effective way of reducing PPU. Strengths & Limitations The present study appears to be the first to analyze the symptoms of PPU using a network analytic approach. Self-reported measures of PPU and pornography use frequency might have introduced some biases. Conclusion The network of PPU symptoms was similar in participants who did and those who did not consider treatment because of their pornography use, with the exception of the mood modification symptom. Targeting the central symptoms in the treatments of PPU seems to be more effective than focusing on reducing pornography use. Bőthe B, Lonza A, Štulhofer A, et al. Symptoms of Problematic Pornography Use in a Sample of Treatment Considering and Treatment Non-Considering Men: A Network Approach. J Sex Med 2020;XX:XXX–XXX.
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Despite a lack of consensus in the field about how best to conceptualize problematic pornography use, psychometric instruments have nonetheless been developed to assess the construct. The present systematic review aimed to (i) identify psychometric tools that have been developed to assess problematic pornography use; (ii) summarize key characteristics, psychometric properties, and strengths and limitations of instruments for problematic pornography use; (iii) compare the instruments’ theoretical conceptualizations of problematic pornography use; and (iv) evaluate each instrument on their ability to assess various core components of addiction. In this article, 22 instruments assessing problematic pornography use were reviewed. Results indicated that while the instruments had different conceptualizations of problematic pornography use, addiction still emerged as the most common theoretical framework used by the instruments. Five of the most commonly assessed addiction components across the different instruments were (1) impaired control, (2) salience, (3) mood modification, (4) interpersonal conflict, and (5) general life conflict. Contextual factors that may potentially affect the assessment of problematic pornography use and recommendations for researchers and clinicians are discussed.