What Matters: Quantity or Quality of Pornography Use? Psychological
and Behavioral Factors of Seeking Treatment for Problematic
Mateusz Gola, PhD,
Karol Lewczuk, MA,
and Maciej Skorko, MA
Introduction: Pornography has become popular with Internet technology. For most people, pornography use
(PU) is entertainment; for some, it can result in seeking treatment for out-of-control behavior. Previous studies
have suggested that PU can inﬂuence sexual behaviors, but the direct relation between frequency of PU and
treatment-seeking behaviors has not been examined.
Aims: To investigate whether individuals seeking treatment as a consequence of their problematic PU do so
because of their quantity of pornography consumption or because of more complex psychological and behavioral
factors related to PU, such as the severity of negative symptoms associated with PU and/or subjective feeling of
loss of control over one’s behavior.
Methods: A survey study was conducted of 569 heterosexual Caucasian men 18 to 68 years old, including 132
seeking treatment for problematic PU (referred by psychotherapists after their initial visit).
Main Outcomes Measures: The main outcome measures were self-reported PU, its negative symptoms, and
actual treatment-seeking behavior.
Results: We tested models explaining sources of seeking treatment for problematic PU with negative symptoms
associated with PU and additional factors (eg, onset and number of years of PU, religiosity, age, dyadic sexual
activity, and relationship status). Seeking treatment was signiﬁcantly, yet weakly, correlated solely with the
frequency of PU (r ¼0.21, P<.05) and this relation was signiﬁcantly mediated by negative symptoms associated
with PU (strong, nearly full mediation effect size; k
¼0.266). The relation between PU and negative symptoms
was signiﬁcant and mediated by self-reported subjective religiosity (weak, partial mediation; k
¼0.066) in those
not seeking treatment. Onset of PU and age appeared to be insigniﬁcant. Our model was fairly ﬁtted
(comparative ﬁtindex¼0.989; root mean square error of approximation ¼0.06; standardized root mean square
residual ¼0.035) and explained 43% of the variance in treatment-seeking behavior (1% was explained by
frequency of PU and 42% was explained by negative symptoms associated with PU).
Conclusion: Negative symptoms associated with PU more strongly predict seeking treatment than mere quantity
of pornography consumption. Thus, treatment of problematic PU should address qualitative factors, rather than
merely mitigating the frequency of the behavior, because frequency of PU might not be a core issue for all
patients. Future diagnostic criteria for problematic PU should consider the complexity of this issue.
J Sex Med 2016;13:815e824. Copyright 2016, International Society for Sexual Medicine. Published by Elsevier
Inc. All rights reserved.
Key Words: Hypersexual Behavior; Psychotherapy; Treatment Seeking; Pornography; Problematic Sexual
The development of broadband Internet technology has pro-
vided an accessible, affordable, and anonymous access to a wide
range of pornography content.
Analysis of data obtained from a
representative sample of 688 young (18- to 30-year-old) het-
erosexual Danish citizens showed that 67.6% of men and 18.3%
of women use pornography on a regular basis (minimum once
Furthermore, a study of 563 American college
Received October 2, 2015. Accepted February 26, 2016.
Swartz Center for Computational Neuroscience, Institute for Neural Com-
putations, University of CaliforniaeSan Diego, San Diego, CA, USA;
Institute of Psychology, Polish Academy of Science, Warsaw, Poland;
Department of Psychology, University of Warsaw, Warsaw, Poland
Copyright ª2016, International Society for Sexual Medicine. Published by
Elsevier Inc. All rights reserved.
J Sex Med 2016;13:815e824 815
students showed that 93.2% of men and 62.1% of women had
been watching online pornography before 18 years of age.
most users, viewing pornography provides entertainment,
excitement, and inspiration,
but for some, frequent pornog-
raphy use (PU) is a source of suffering (8% of 9177 users
) and a
reason to seek treatment.
PU, accompanied by masturbation,
also is the most common behavior in men, meeting the criteria of
proposed by Kafka
for the Diagnostic
and Statistical Manual of Mental Disorder, Fourth Edition.
Because the concept of hypersexual disorder was not accepted
by the American Psychiatric Association owing to insufﬁcient
currently, there are no universally
recognized diagnostic criteria for various out-of-control sexual
behaviors (eg, problematic PU, excessive masturbation, use of
paid sexual services, frequent risky casual sex, etc). Researchers
studying these behaviors use many different norms for discrim-
ination of so-called clinical and control subjects. By analyzing
studies on out-of-control sexual behaviors,
one can see an
attempt to deﬁne these behaviors based on quantity (ie, amount
or number of sexual partners
) or through the role
and consequences of sexual behavior (ie, “quality”of PU).
Quantitative norms for human sexual behaviors are very
difﬁcult (if possible) to deﬁne. Problematic PU also might be
difﬁcult to deﬁne through quantitative aspects. Our clinical
experience shows that subjects seeking treatment for problematic
PU exhibit high variability of PU quantity. This variability also is
visible in recent experimental studies. Voon et al
Mechelman et al
reported 1.75 hours per week (SD ¼3.36) of
PU for the control group and 13.21 hours per week (SD ¼9.85;
information presented by Voon et al during the American Psy-
chological Science conference in 2015) for subjects meeting
hypersexual disorder criteria.
However, Prause et al
0.6 hour per week of PU (SD ¼1.5) for control subjects and 3.8
hours per week (SD ¼1.3) for subjects labeled “hypersexual”
(subjects were not examined for hypersexual disorder criteria but
for self-reported problematic PU). Kühn and Gallinat
that individuals using pornography for 0 to 19.5 hours per week
(mean ¼4.09 hours per week, SD ¼3.9) do not meet the
problematic PU criteria set by the Internet Sex Screening Test.
In our opinion, these data suggest that the mere frequency of PU
might be only weakly associated with self-perceived problems
and treatment-seeking behaviors.
During the long-lasting debates on the nature of out-of-control
sexual behaviors (for reviews, see Kor et al
and Ley et al
Short et al
speciﬁcally about pornography), most deﬁnitions
have focused on the subjective experience of the individual, such as
impact on everyday life, negative consequences, role of the
behavior in mood regulation,
or perceived lack of control
Recent studies have shown that frequent PU is
negatively related to the enjoyment of sexually intimate behaviors
with a partner
and positively associated with frequent distraction
by sexual thoughts,
frequency of masturbation, and sexual
boredom in the relationship.
Some data have shown that such
boredom can be compensated by the increase in different sexual
behaviors, with their contents related directly to the scripts
watched in pornographic videos.
Although we need to be
careful about causal interpretations, because these studies show
only correlations, each of such negative symptoms related to PU
could play a crucial role in seeking treatment.
These observations bring up the question of whether individuals
seeking treatment for problematic PU do so because of excessive
consumption of pornography (quantity) or because of more
complex psychological and behavioral factors related to PU,
such as associated habits, their functions, negative conse-
quences, and/or subjective feelings of loss of control over one’s
behavior. To address this question, we propose a theoretical
mediation model (Figure 1). This simple model assumes that
high frequency of PU can lead to treatment-seeking behaviors
(path A) or negative symptoms (mediator) that consequently
lead to treatment-seeking behavior (path B). To analyze the
pattern of mutual relations between measured variables, one can
use path analysis.
This statistical procedure tests whether a
gathered set of data ﬁts well with a created a priori complex
theoretical model of causal relations between particular vari-
ables. The analysis is done by conducting simultaneous mul-
tiple linear regressions and presented graphically using path
diagrams (Figures 2 and 3).
Taking advantage of path analysis methodology, we explored
the roles of other variables suggested in the literature as poten-
tially important for problematic PU. Studies on addictive
behaviors, such as substance abuse
and pathologic gambling,
have indicated that the age of onset of the behavior is related to
the severity of symptoms and places individuals at higher risk of
comorbid disorders. Similar correlations have been found for the
duration of such an addictive behavior.
For these reasons, we
ﬁnd it important to verify what role symptom severity and
behavior duration play in problematic PU.
Recent publications on PU have suggested religiosity as
having an important role for self-perceiving problematic PU.
However, the nature of this relation remains unclear. Grubbs
demonstrated that in college students and adults
(not seeking treatment), self-perceived addiction to Internet
pornography was positively associated with religiosity, but
religiosity was unrelated to the actual amount of PU. Martyniuk
presented contradictory results, showing a negative relation
to the amount of PU in female students and a positive relation
in male students. According to our understanding, the factor of
religiosity could mediate a relation between PU and perceived
negative symptoms (Figure 3). Usually, religious norms depict
PU and extramarital sexual activity as morally reprehensible;
therefore, people who are more religious might perceive their
PU as having more morally troubling consequences. In other
words, we propose that religiosity can amplify the experienced
consequences of PU (Figure 3).
Moreover, we argue that age should be considered because
studies have shown decreasing sexual desire and activity with
J Sex Med 2016;13:815e824
816 Gola et al
Changes in the frequency of PU across an
individual’s lifespan remain mostly unknown. Baumgartner et al
showed a comparable, and stable, rate of risky sexual online
behaviors across a group of 18- to 88-year-old men, but they did
not report on overall PU. Even if the age factor is not correlated
directly with PU, it is associated with decreased dyadic sexual
which indicates a possible link to a higher frequency of
PU as a form of compensatory behavior. Furthermore, dyadic
sexual activity might be related to the availability of a sexual
partner, because those in a partnership probably have greater
sexual activity than those not in a partnership. For this reason,
dyadic activity also should be controlled. To address our research
question, we tested our a priori deﬁned model (Figures 1 and 2)
and then extended it with additional, potentially signiﬁcant vari-
ables (Figure 3).
Data were collected from March 2014 through March 2015
fromasampleofPolishcitizens through an online-based sur-
vey. It took 1 year to acquire a sufﬁcient number (N ¼132)
of subjects seeking treatment for problematic PU. To do this,
we asked 23 professional therapists (17 psychologists and psy-
chotherapists, 4 psychiatrists, and 2 sexologists) to refer their
most recent patients declaring problematic PU to the survey.
Subjects not looking for treatment were recruited through
social media advertisements. Upon entering the survey,
respondents received informed consent information. The study
materials and protocol were approved by the ethical committee
of the Institute of Psychology, Polish Academy of Sciences
Data reported in this publication were gathered from a sample
569 heterosexual Caucasian white men (mean age ¼28.71 years;
SD ¼6.36). Sexual orientation was controlled by the Polish
adaptation of the Kinsey Sexual Orientation Scale.
who obtained values of 0 (exclusively heterosexual) or 1 (pre-
dominantly heterosexual, only incidentally homosexual) of 7 on
the scale were classiﬁed as heterosexual. The sample included 132
subjects identiﬁed as seeking treatment for problematic PU.
Collaborating therapists referred 119 treatment seekers, and 13
individuals who reported previously seeking treatment for
extensive PU were acquired during the recruitment for the
nonetreatment-seeking cohort. Pairwise observations with
missing data were excluded (overall response rate ¼89%),
providing a slightly different ﬁnal number of participants for each
variable (Table 1).
MAIN OUTCOME MEASURES
Seeking treatment for problematic PU was the main mea-
surement (contact with psychologist, psychiatrist, or sexologist
who directed a patient to the survey). For control purposes,
within the survey for non-treatment seekers, we asked whether
the subject had ever used any kind of help because of sexual
behavior. If the subject responded “yes,”we asked additional
questions regarding the type of, and reason for, help. Frequency
of PU was measured as the declared average number of minutes
per week spent on PU during the past month. Negative symp-
toms were assessed by a Polish adaptation of the Sexual Addic-
tion Screening TesteRevised (SAST-R
), which measures (i)
preoccupation, (ii) affect, (iii) relationship disturbance by sexual
behaviors, and (iv) the feeling of losing control over sexual
behavior. The questionnaire consists of 20 items with yes-or-no
response options. It is important to note that, except for
measuring the four factors mentioned earlier, some items of the
SAST-R refer to suffering from one’s sexual behavior (ie, Do you
ever feel bad about your sexual behavior? Have you felt degraded
Figure 2. Path analysis model showing standardized path
coefﬁcients tested with 95% biased-corrected conﬁdence intervals
(**P.001; *P<.05). The standardized coefﬁcient (within pa-
rentheses) represents the direct effect of frequency of pornography
use on seeking treatment before accounting for mediation through
negative symptoms associated with pornography use.
Figure 1. Model used to explain the role of quantity and quality of
pornography use in individuals seeking treatment for problematic
pornography use. Path A indicates a simple correlation of the
amount of pornography use and seeking treatment. Path B
describes the scenario in which pornography use can lead to
negative consequences and then seeking treatment.
J Sex Med 2016;13:815e824
Seeking Treatment for Problematic Use of Pornography 817
by your sexual behaviors? When you have sex, do you feel
depressed afterward?). The overall score for each participant was
calculated by aggregating the score from all items. Internal
consistency of the questionnaire in our study was very high
(Cronbach a¼0.90). Because analysis of the latent structure of
pornography addiction symptoms was not the direct aim, the
overall score in the SAST-R questionnaire was treated as an
Age of respondents was expressed in years, onset of PU was
measured as the declared age at which respondents started viewing
explicit sexual pictures or videos, and number of years of PU was
calculated from the onset of PU and the current age of the
respondent. Subjective religiosity was measured on a Likert-type
scale with anchors at 0 (deﬁnitely no) and 4 (deﬁnitely yes)
using the following question: Do you consider yourself a religious
person? People who had values higher than 0 on this scale were
asked additional questions about their religious practices,
measured by the declared average amount of time spent (minutes
per week) on religious or spiritual practices such as prayers,
participation in services and rituals, spiritual reading, mediations,
etc. We also asked for time elapsed since the last dyadic sexual
activity using an ordinal scale from 0 to 7 (0 ¼today; 1 ¼
yesterday; 2 ¼past 3 days; 3 ¼past 7 days; 4 ¼past 30 days; 5 ¼
past 3 months; 6 ¼>90 days ago; 7 ¼I have never had sex with
other person). Subjects were asked to select the most accurate
response. Relationship status was measured as a declaration of
being in a relationship (formal or informal; yes ¼1, no ¼0).
Using path analysis, we tested the signiﬁcance of all indirect
and direct relations within the models, estimating the effect of
each speciﬁc mediator, and simultaneously controlling for the
Figure 3. Path analysis of the extended model showing standardized path coefﬁcients tested with 95% biased-corrected conﬁdence
intervals (**P.001; *P<.05). Standardized coefﬁcients (within parentheses) represent direct effects before accounting for indirect
pathways. Bold arrows represent the relation between frequency of PU and seeking treatment and its mediation through negative
symptoms associated with PU (from the basic model presented in Figures 1 and 2). The remaining paths represent effects introduced in our
extended model. Dashed lines indicate paths that were deleted from the ﬁnal model and solid lines represent paths that remained in the
ﬁnal model. Relationship status is a dummy variable (1 ¼in relationship, 0 ¼not in relationship). PU ¼pornography use.
J Sex Med 2016;13:815e824
818 Gola et al
inﬂuence of other mediators. Moreover, this approach provided
the “big picture”of analyzed relations instead of presenting the
results in a fragmented manner. Analyses were performed with
IBM SPSS AMOS
using maximum likelihood estimation, with
correlation matrix as the input.
To take into account
non-normal distribution of some variables, we estimated the
signiﬁcance of standardized coefﬁcients using 5,000 bootstrap
iterations. The signiﬁcance of the indirect effects also was tested
with 95% biased-corrected bootstrapped conﬁdence intervals, as
proposed by MacKinnon.
Goodness of ﬁt of a particular
model was tested and a good ﬁt was indicated when there was a
non-signiﬁcant test result within the c
test, a comparative ﬁt
index (CFI) value greater than 0.95, a root mean square error of
approximation (RMSEA) lower than 0.06, and a standardized
root mean square residual (SRMR) lower than 0.08.
full-information maximum likelihood analysis to verify relations
with missing data, because this method provides more reliable
results than pairwise deletion in such cases.
By default, we were
not using full-information maximum likelihood because it does
not allow for bootstrapping.
We begin with presenting the results of the analysis of the
basic model related to our a priori formulated hypothesis
(Figures 1 and 2). Descriptive statistics and correlation matrices
for all variables used in the analyses are presented in Table 1.We
used a point-biserial correlation coefﬁcient in the dummy-coded
variable (seeking treatment and relationship status).
The basic model (Figure 1) was used to test whether negative
symptoms mediate (path B in Figure 1) a direct effect (path A) of
frequency of PU on seeking treatment. Results showed that
frequency of PU was directly related to seeking treatment
(estimate ¼0.21, P<.001). This relation became negative,
weak, and only marginally signiﬁcant (estimate ¼0.07 [95%
bias corrected interval ¼0.14 to 0.01], P¼.046) after
accounting for the mediation effect of negative symptoms. Full-
information maximum likelihood analysis showed that after,
accounting for the mediation effect, this relation did not reach a
signiﬁcant level (estimate ¼0.04, P¼.292).
The indirect pathway from frequency of PU to seeking treat-
ment for negative symptoms was signiﬁcant (0.28 [0.23e0.34]).
The mediation effect was strong, with a large effect size
, as proposed by Preacher and Kelley
Because our basic model is a saturated model (all potential paths
between variables have been speciﬁed and all degrees of freedom
have been exhausted), its goodness of ﬁtbydeﬁnition is ideal.
In the second step, we extended our basic model and introduced
four parallel mediators of a relation between PU and negative
symptoms (onset and number of years of PU, subjective religiosity,
and religious practices; Figure 3). We estimated the signiﬁcance of
each mediation path with user-deﬁned estimates. Neither onset nor
number of years of PU was signiﬁcant (0.000 [0.000 to 0.000]
for the two comparisons). Instead, this effect was mediated by
subjective religiosity (0.001 [0.000e0.002]), but not by religious
practices (0.000 [0.000e0.000]). Mediation through subjective
religiosity was signiﬁcant but rather weak (effect size k
Moreover, the relation between subjective religiosity and negative
symptoms was signiﬁcant only for the nonetreatment-seeking
group (estimate ¼0.27, P<.001); we did not ﬁnd such a relation
among treatment-seekers (estimate ¼0.00).
Table 1. Descriptive statistics and correlation coefﬁcients for all variables included in the analysis
Variable n Mean SD 1 2 3 4 5 6 7 8 9
1. Negative symptoms (0e20) 561 7.28 5.25 1
2. Frequency of pornography
428 229.86 252.46 0.41
3. Subjective religiosity (0e4) 476 1.53 1.50 0.40
4. Religious practices (min/wk)
280 140.09 192.99 0.20
5. Years of pornography
531 13.40 6.13 0.03 0.03 0.11* 0.02 1
6. Age at onset of pornography
528 15.42 3.46 0.08 0.01 0.01 0.04 0.19
7. Age (y) 568 28.71 6.36 0.00 0.01 0.11* 0.04 0.81
8. Time elapsed since last dyadic
sexual activity (0e7)
536 3.22 2.25 0.42
9. Seeking treatment
(1 ¼yes, 0 ¼no)
569 132 yes 437 no 0.65
0.14* 0.08 0.07 0.05 0.29
10. Relationship status
(1 ¼in relationship, 0 ¼not
559 329 yes 231 no 0.27
0.12* 0.10* 0.07 0.20* 0.11* 0.25
‡Question about religious practices was asked only to those participants who stated that they are religious in the previous question (subjective
J Sex Med 2016;13:815e824
Seeking Treatment for Problematic Use of Pornography 819
The direct relation between subjects’age and frequency of PU
was insigniﬁcant. Although the indirect pathway through the
time elapsed from last dyadic sexual activity was signiﬁcant
(0.03 [0.03 to 0.01]), this effect disappeared after the
inclusion of relationship status in the model (0.01 [0.02 to
0.00], P¼.239). Older subjects were in relationships more often
(r ¼0.25) and being in a relationship was predictive of a shorter
time since the last dyadic sexual activity (estimate ¼0.58).
Furthermore, subjects reporting a longer time since the last
dyadic sexual activity were using pornography more frequently
In the next analysis, we compared two nested models: (i)
unconstrained, which consisted of all analyzed paths (all regres-
sion paths shown in Figure 3), and (ii) constrained, in which
insigniﬁcant paths were constrained to 0. This procedure enabled
us to check whether insigniﬁcant paths (such as onset of PU,
number of years of PU, path between religious practices and
negative symptoms, direct effect of age on frequency of PU, and
time since last sexual activity) added any informative value to the
model (if yes, then analyzed models should differ signiﬁcantly).
Fit indices for the unconstrained model (c
P<.001, CFI ¼0.293, RMSEA ¼0.33, SRMR ¼0.168)
and the constrained model (c
CFI ¼0.292, RMSEA ¼0.30, SRMR ¼0.170) at this stage of
analysis did not differ signiﬁcantly (c
¼9.31, P¼.231), so we
removed the insigniﬁcant paths from the ﬁnal version of the
extended model. We also deleted a signiﬁcant path from fre-
quency of PU to religious practices. This path was part of an
insigniﬁcant mediation between frequency of PU and negative
symptoms, with no rationale for leaving it in the model. Deleted
paths are shown with dashed arrows in Figure 3. Goodness of
ﬁt of our model at this stage was reﬂected by the indices
(CFI ¼868; RMSEA ¼0.016, SRMR ¼0.13). We added three
covariances to the model: (i) between residual error terms of
negative symptoms and time elapsed since the last dyadic sexual
activity (r ¼0.23); (ii) between error terms of negative symptoms
and relationship status (r ¼0.23); and (iii) between error terms
of subjective religiosity and time elapsed since the last dyadic
sexual activity (r ¼0.28). These relations are in line with pre-
vious studies but because they were not central to any of our
main hypotheses, we did not include them in our earlier analysis.
The conceptual justiﬁcation for including those relations in our
model (along with corresponding literature review) is elaborated
in the Discussion. Predictors of seeking treatment in our ﬁnal
model (negative symptoms and frequency of PU) explained 43%
of its variance. However, the strength of the two predictors in our
model was drastically different: 42% of variance in seeking
treatment was explained by negative symptoms and only 1% was
explained by frequency of PU. Fit indices for the ﬁnal model
indicated overall good ﬁt(c
¼14.96, P¼0.01, CFI ¼0.989,
RMSEA ¼0.06, SRMR ¼0.035).
Because the main purpose of our study was to determine the
predictive strength of problematic PU (quantity of PU or nega-
tive symptoms associated with PU) for seeking treatment, ana-
lyses were performed on the entire group of subjects (seeking and
not seeking treatment). We also compared the two groups
(Table 2). These groups differed in all variables except number of
years of PU and age.
According to our a priori predictions, PU can lead to negative
symptoms and the severity of these symptoms can lead to seeking
treatment (Figure 1, path B). The frequency of PU alone was not a
signiﬁcant predictor of seeking treatment for problematic PU
when controlling for negative symptoms associated with PU
(Figure 2). Such a weak relation had been indirectly suggested
by previous studies on pornography users. Cooper et al
Table 2. Descriptive statistics and mean comparison of variables used in models depending on seeking treatment (yes or no)*
N Mean SD Minimum Maximum
Yes No Yes No Yes No Yes No Yes No
1. Negative symptoms (0e20) 129 432 13.55 5.41
3.96 3,99 1 0 19 19
2. Frequency of pornography
89 339 333.08 202.76
300.13 231.35 2 2 1,680 1,833
3. Subjective religiosity (0e4) 112 364 2.48 1.23
1.39 1.42 0 0 4 4
4. Religious practices (min/wk) 109 171 172.70 119.31
189.95 192.59 1 1 1,200 1,200
5. Years of pornography consumption 130 401 14.29 13.11 7.13 5.74 3 0 39 40
6. Age of onset of pornography
128 400 14.98 15.56
3.51 3.43 7 5 29 29
7. Age (y) 131 437 29.24 28.55 7.71 5.89 19 17 68 52
8. Time elapsed since last dyadic
sexual activity (0e7)
125 411 4.96 3.42
2.20 2.13 0 0 7 7
P<.001; signiﬁcant difference in mean score between groups as assessed by Mann-Whitney U-test.
*Relationship status (0 ¼not in relationship, 1 ¼in relationship) differed depending on the seeking of treatment (yes or no) as assessed by c
¼14.67, P<.001). Of treatment seekers, 57 subjects were in a relationship and 72 were not in a relationship. Of those not seeking treatment, 272
were in a relationship and 159 were currently not engaged in any kind of intimate relationship.
J Sex Med 2016;13:815e824
820 Gola et al
showed that, among subjects engaging in online sexual activities
(not only PU, but also sex chats), 22.6% of 4,278 light users
(<1 hour per week) reported an interference of their online sexual
activity in many areas of their everyday lives, whereas 49% of 764
heavy users (>11 hours per week) never experienced such
In the second step of data analysis, we extended our model by
testing four parallel mediators of a relation between PU and
negative symptoms (onset and number of years of PU, subjective
religiosity, and religious practices; Figure 3). Effects of onset and
numbers of years of use reported in studies on substance abuse
and pathologic gambling
appeared insigniﬁcant in our dataset.
Lack of such ﬁndings could suggest a potentially lower longitu-
dinal impact of PU on functioning than substance abuse or
pathologic gambling. This result also could be related to the
methodologic limitations of our study. We calculated number of
years of PU as the difference between onset of PU and the
subjects’current age. It is possible that some subjects were using
pornography for only a limited time from their onset; thus, this
measurement presented in our analyses could be inaccurate.
Future studies should investigate the number of years of regular
PU. Another possible limitation is that, for negative symptoms,
we used the SAST-R because it was the only questionnaire for
hypersexual behavior assessment available in the Polish lan-
This questionnaire was designed to measure a wide
spectrum of negative consequences related not only to PU but
also to other sexual behaviors. The obtained signiﬁcant relation
between frequency of PU and SAST-R scores shows that, among
other sexual behaviors, it measures the negative symptoms
related to PU. However, the SAST-R is not speciﬁc to only
solitary sexual activity. For future research, we predict that the
application of more speciﬁc and sensitive measurement tools
could help uncover signiﬁcant mediating effects of onset and
duration of PU.
We expected greater religiosity to amplify self-perceived
problematic PU as reported in previous studies.
assumption appeared to be true for subjective religiosity
measured as a declaration of the level of importance of religion in
an individual’s life (Figure 3). Interestingly, careful examination
showed that this effect was signiﬁcant only in those not seeking
treatment. In those seeking treatment, religiosity was not related
to negative symptoms. Religious practices were insigniﬁcant
mediators (Figure 3), which was surprising because actual reli-
gious practice could be a better measurement of religiosity then
mere declaration. These results emphasize the previously
mentioned role of religiosity in sexual behaviors and indicate the
need for further studies on this topic. The relation between
religiosity and PU and between religiosity and self-perceived
addiction had been investigated only in nonetreatment-seeking
Thus, our novel ﬁnding of no such relation in
treatment-seeking subjects is very interesting but needs to be
replicated in future studies in subjects in treatment for prob-
We also examined the role of respondents’age and time
elapsed since the last dyadic sexual activity in the context of PU.
Age was an insigniﬁcant predictor of frequency of PU, as was the
time elapsed since the last dyadic sexual activity. The latter
variable was related to the subjects’relationship status. Subjects
in relationships (formal or informal) were characterized by
shorter time since the last dyadic sexual activity, and this variable
was negatively related to frequency of PU. Between-group
comparison (Table 2) clearly showed that subjects seeking
treatment for problematic PU in general were less likely to be in a
relationship, declare a longer time since their last dyadic sexual
activity, use pornography more frequently, and experience more
severe negative symptoms. The direction of those relations
needs further investigations. On the one hand, difﬁculties within
relationships can be a cause of lower availability of dyadic sexual
activity, which could lead to more frequent PU and solitary
sexual activities, causing negative symptoms. On the other hand,
frequent PU and negative symptoms could be the cause of dif-
ﬁculties in relationships and dyadic sexual activity, as suggested
by Carvalheira et al
and Sun et al.
Analysis of the extended version of our model showed three
relations (correlations of error terms) that we did not include in
our a priori formulated hypothesis, although we mentioned them
in the Introduction. First, severity of negative symptoms asso-
ciated with PU was related to a lower probability of having an
intimate relationship. This result agrees with previous research
indicating that excessive PU could be related to social isolation,
difﬁculties with ﬁnding an intimate partner, and
maintaining a relationship.
Because we showed a signiﬁcant
correlation between frequency of PU and negative symptoms
associated with PU (Figure 2), those negative consequences
probably contribute to the difﬁculties in creating long-lasting
The causality of this relation is
unclear, but it can be hypothesized that problematic PU and
difﬁculties with intimate relationships have a bidirectional rela-
tion and reinforce each other. Second, we found a related positive
relation between negative symptoms and time elapsed since the
last dyadic sexual activity. Compared with those not seeking
treatment (Table 2), problematic pornography users were char-
acterized by greater severity of negative symptoms associated with
PU and lower chances of having intimate relationships and
dyadic sexual activity (Table 2 and Figure 3). Recent studies have
shown that frequent PU is negatively related to the enjoyment of
sexually intimate behaviors with a partner
associated with frequency of masturbation and sexual boredom in
The causality of relations between frequency
of dyadic sexual activity and negative symptoms has to be
Third, our study found a positive relation between subjective
religiosity and time elapsed since the last sexual activity.
Although the results of some previous studies that focused on
relations between religiosity and sexual activity are not entirely
with our results, most studies have suggested that
J Sex Med 2016;13:815e824
Seeking Treatment for Problematic Use of Pornography 821
non-religious individuals report having more sexual experi-
and earlier onset of sexual activity.
are observable especially in individuals who see religious and
conservative values as central to their life
and therefore can be
more apparent in relatively conservative societies with strong
religious traditions, such as Poland, where the sample was
recruited (see also Martyniuk et al
). The discussed relations
deﬁnitely deserve systematic investigation for their contribution
to sexual addiction in future studies.
To the best of our knowledge, this study is the ﬁrst direct
examination of associations between the frequency of PU and
actual seeking of treatment for problematic PU (measured as
visiting the psychologist, psychiatrist, or sexologist for this pur-
pose). Our results indicate that future studies, and treatment, in
this ﬁeld should focus more on the impact of PU on the life of an
individual (quality) rather than its mere frequency (quantity),
because the negative symptoms associated with PU (rather than
PU frequency ) are the most signiﬁcant predictors of treatment-
seeking behavior. From the perspective of the obtained results,
we postulate that factors such as negative behavioral consequences
associated with PU should be considered in deﬁning, and recog-
nizing, problematic PU (and perhaps other out-of-control sexual
behaviors). We also suggest further investigation of the role of
quality of sexual life in intimate relationships in patients with
problematic PU and possible factors causing difﬁculties in creating
We are grateful to all psychotherapists, sexologists, and psy-
chiatrists who directed their patients to our internet surveys and
the team of www.onanizm.pl for promoting our studies. We are
also grateful to Bradly Stone for signiﬁcant language improve-
ment of this manuscript.
Corresponding Author: Mateusz Gola, PhD, Swartz Center for
Computational Neuroscience, Institute for Neural Computa-
tions, University of CaliforniaeSan Diego, 9500 Gilman Drive,
San Diego, CA 92093-0559, USA. Tel: þ1-858-500-2554;
ofﬁce tel: þ1-858-822-7543; E-mail: firstname.lastname@example.org
Conﬂict of Interest: The authors report no conﬂicts of interest.
Funding: This study was supported by the National Science
Centre of Poland OPUS grant, 2014/15/B/HS6/03792
(M. Gola). Dr Mateusz Gola is also supported by the Polish
Ministry of Science grant Mobility Plus (1057/MOB/2013/0).
STATEMENT OF AUTHORSHIP
(a) Conception and Design
(b) Acquisition of Data
Mateusz Gola; Maciej Skorko
(c) Analysis and Interpretation of Data
Mateusz Gola; Karol Lewczuk
(a) Drafting the Article
Mateusz Gola; Karol Lewczuk; Maciej Skorko
(b) Revising It for Intellectual Content
Mateusz Gola; Karol Lewczuk
(a) Final Approval of the Completed Article
Mateusz Gola; Karol Lewczuk; Maciej Skorko
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