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  • 1 University of Calgary, Canada
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Background and aims

The phenomenon of Internet pornography (IP) addiction is gainingincreasing attention in the popular media and psychological research.What has not been tested empirically is how frequency and amount ofIP use, along with other individual characteristics, are related tosymptoms of IP addiction.

Methods

105 female and 86 male university students (mean age 21) from Calgary,Canada, were administered measures of IP use, psychosocial functioning(anxiety and depression, life and relationship satisfaction), addictivepropensities, and addictive IP use.

Results

Men reported earlier age of exposure and more frequent currentIP use than women. Individuals not in relationships reported morefrequent use than those in relationships. Frequency of IP use wasnot generally correlated with psychosocial functioning but was significantlypositively correlated with level of IP addiction. Higher level ofIP addiction was associated with poorer psychosocial functioning andproblematic alcohol, cannabis, gambling and, in particular, videogame use. A curvilinear association was found between frequency ofIP use and level of addiction such that daily or greater IP use wasassociated with a sharp rise in addictive IP scores.

Discussion

The failure to find a strong significant relationship between IPuse and general psychosocial functioning suggests that the overalleffect of IP use is not necessarily harmful in and of itself. Addictiveuse of IP, which is associated with poorer psychosocial functioning,emerges when people begin to use IP daily.

Abstract

Background and aims

The phenomenon of Internet pornography (IP) addiction is gainingincreasing attention in the popular media and psychological research.What has not been tested empirically is how frequency and amount ofIP use, along with other individual characteristics, are related tosymptoms of IP addiction.

Methods

105 female and 86 male university students (mean age 21) from Calgary,Canada, were administered measures of IP use, psychosocial functioning(anxiety and depression, life and relationship satisfaction), addictivepropensities, and addictive IP use.

Results

Men reported earlier age of exposure and more frequent currentIP use than women. Individuals not in relationships reported morefrequent use than those in relationships. Frequency of IP use wasnot generally correlated with psychosocial functioning but was significantlypositively correlated with level of IP addiction. Higher level ofIP addiction was associated with poorer psychosocial functioning andproblematic alcohol, cannabis, gambling and, in particular, videogame use. A curvilinear association was found between frequency ofIP use and level of addiction such that daily or greater IP use wasassociated with a sharp rise in addictive IP scores.

Discussion

The failure to find a strong significant relationship between IPuse and general psychosocial functioning suggests that the overalleffect of IP use is not necessarily harmful in and of itself. Addictiveuse of IP, which is associated with poorer psychosocial functioning,emerges when people begin to use IP daily.

Introduction

There exist a growing number of reports ofindividuals who claim their Internet pornography (IP) use has becomeproblematic. The symptoms reported by these individuals, both menand women, include dysfunctions in sexual arousal and achieving orgasm(Schneider, 2000), loss oflibido or sexual interest in a real partner, and loss of interestin one’s romantic partner (Poulsen, Busby, & Galovan, 2013). Symptoms also include a varietyof problems in psychosocial functioning, such as depression, the riskof losing career and relationship opportunities, and a lack of motivation(Philaretou, Malhfouz, & Allen, 2005; Young, 2004).Many individuals describe feeling a strong compulsion to view IP evenat times when it is highly inappropriate to do so, such as at work,in a room where children are present, or on a computer that is nottheir own (Griffiths, 2012).Others also report developing rash misconceptions of sexuality andsexual practice, such as beliefs that certain sexual acts (e.g., analsex) are more socially normative than they actually are. Other misconceptionsmay also reinforce racial and gender stereotypes and potentially increase violencetoward women (Peter & Valkenburg, 2007; Zillmann & Bryant, 1986).

Qualitative research on problematic IP usehas shown that some users have difficulty in attempting to stop orcut down on their use (Delmonico &Miller, 2003; Orzack &Ross, 2000). Other personal and anecdotal accounts from problematicIP users describe positive changes associated with cessation of theirpornography use. These changes include return of libido,a rise in creativity and sense of self-worth, and higher life andrelationship satisfaction (Wilson, 2014). Many of these individuals also indicate in retrospectionthat they had been unaware of how negatively IP use had been affectingtheir lives.

While these reports suggest that IP use is harmful, IP has alsobeen correlated with favorable effects as well. There are reportsof various positive impacts on sexuality, happiness, and reductionsin anxiety and depression, especially for marginalized populations,such as the disabled (Kaufman, Silverberg, &Odette, 2007). The vast majority of IP users regard it positively,claiming that it has improved their personal lives as well as theirintimate sex lives (Hald & Malamuth, 2008). Many individuals report having discovered and assertedaspects of their own sexuality while using IP and the liberating effectthis has had on their sense of identity (Kingston & Malamuth, 2010). Use of IP has allowed formore sexual exploration and validation for homosexual (McLelland, 2002; Correll, 1995), bisexual (Koch & Schockman, 1998), and transgendered people(Broad, 2002). The privacy andanonymity, which the Internet provides, presents less physical andsocial danger than direct personal interaction, allowing support andcommunication about sexuality to flourish. Finally, women who useIP report having better sex lives than those who do not (Poulsen, Busby, & Galovan, 2013).

IP is a relatively recent phenomenon (Leiner, 2009), and therefore, research in this area is limited.Moreover, the topic is extremely sensitive and fraught with many misconceptionsand moral biases. Yet the pervasiveness of IP cannot be understated. Its use has become increasingly widespreadin recent years, not only among adults but also among underage populations (Sabina, Wolak, & Finkelhor, 2008). We are beginning to see the societal effects of IP use as well.The media and other elements of mainstream culture have been describedas undergoing a rapid “pornographication” in recent years(Attwood, 2006; Kinnick, 2007). For such a contemporaryphenomenon to have so large an impact on society and the individualshould be reason enough warrant further research on this topic.

History and popularity of Internet pornography

A vast amount of pornography exists on the World Wide Web. It isestimated that 12% of the Internet is composed of pornography, whichequates to roughly 24.6 million websites (Twohig, Crosby, & Cox, 2009) or 156 billion gigabytes.Twenty-five percent of all searches on the Web are for pornography (Ropelato, 2006). As of 2007,annual income for all pornographic websites was estimated at 20 billiondollars, but the Free Speech Coalition has estimated a 50% reductionin pornography revenues between 2007 and 2011 due to the amount offree pornography available online (Barrett, 2012). It should also be noted that numerous individualshave reported having accidently accessed pornographic material onthe Internet despite efforts to avoid doing so (Mitchell, Finkelhor, & Wolak, 2003).

Cooper (1998) describesthe popularity of IP as driven by the effect of three characteristics,which he labels as the Triple-A engine: access, affordability, andanonymity. Prior to the creation of the World Wide Web in 1991, transferof pornography via computer networks or peer-to-peer file sharingwas quite limited. Almost all pornography was disseminated among thepublic in print and video format. Acquisition of pornography requiredphysically purchasing it from an adult store or theatre, and thesebusinesses often carried negative stigma and reputation. Since theinception of the World Wide Web, and the subsequent creation of pornographicwebsites, public usage of pornography has exploded. Access to pornographyhas never been easier, and this is especially true due to the creationof mobile smartphones that ostensibly allow access to the Internetanywhere on the globe (Silver, 2012). The vast majority of pornography on the Internet may also be accessedat no additional cost to the user, and the user may view this pornographywithout ever having to identify themselves or leave their homes.

Expanding on Cooper, there is a fourth characteristic of IP thatis particularly salient to understanding how its use can become problematic:the characteristic of “novelty.” Novelty here refers tothe immense amount and diversity of erotic imagery available on theInternet. Individuals who identify as having problematic IP use reporthaving spent hours at a time searching for hundreds of different imagesand videos but never feeling satisfied (Orzack & Ross, 2000). Others have also admitted to collectingthousands of pornographic files but never revisiting any of them (Delmonico & Miller, 2003). Thisbehavior shows similarities to the tolerance and habituation effectsof substance addictions, as well as the obsessive “search andacquire” behaviors and procrastinatory behaviors of Internetaddiction disorder (Davis, Flett, & Besser, 2002).

Can we become addicted to Internet pornography?

Sexual desire in the brain begins with the arrival of sexuallystimulating sensory signals at the medial preoptic area, which isthe hub of the telodiencephalic reproductive complex (Kim et al., 2013). This complexalso incorporates the neural network of the mesolimbic reward center,the network most involved in addiction (Roxo, Franceschini, Zubaran, Kleber, & Sander, 2011).Neuroimaging has demonstrated that viewing images of sexually availablepartners (i.e., pornography) has the same effect on the medial preopticarea as viewing actual sexual partners. Upon viewing either stimuli,subjects become aroused and tend to desire more of it (Hilton & Watts, 2011; Voon et al., 2014). What isdifferent is that the Internet provides access to a vast surplus oferotic imagery, and the novelty of this imagery is practically unending.The preference for novelty in sexual partners has been well documentedin animal and human test subjects: a phenomenon often referred toas the Coolidge effect (Fiorino, Coury, & Phillips, 1997; Wilson, 1997). It has been suggested that the unbridled access to a large quantityof novel sexual images on the Internet has an effect on the mesolimbicreward center that is similar to the effect of addictive substances(Pitchers et al., 2013; Barrett, 2010).

A recent study using fMRI imaging found a common neural networkbetween drug-cue reactivity in subjects with drug addictions and sexual-cuereactivity in subjects with problematic pornography use (Voon et al., 2014). Problematicpornography users displayed a similar neural responsivity to cuesof pornography that drug addicts display for drug cues. These participants also reported cravings to viewmore pornography when not viewing it, but then reported not enjoyingthe experience when they were viewing it. This disparity found between “liking”and “wanting” is consistent with theories of incentivemotivation in addiction research (Robinson & Berridge 1993; Voon et al., 2014).

It is also possible that the biological structure of the brainitself can be altered due to frequent IP use (Kühn & Gallinat, 2014). Magnetic resonance imagingscans have shown that gray matter volume of the right caudate of thestriatum is negatively associated with reported IP use. Functionalactivation of left putamen, as well as functional connectivity ofthe right caudate to the left dorsolateral prefontal cortex, was alsonegatively associated. This suggests that frequent exposure to IPcauses downregulation and “wearing” of the underlyingbrain structure. The individual must then seek out a stronger externalstimulation leading to a search for novel and more extreme pornographicmaterial. This behavior shows strong similarities to the toleranceand habituation effects of addiction. However, Kühn and Gallinat (2014) note that this associationwith IP and gray matter volume and functional connectivity may indicatea precondition already present in the brain, rather than a consequenceof frequent IP use.

Despite these findings, classification of problematic IP use asan addiction has been controversial. Historically, it has been labeledeither as a type of impulse control disorder (Morahan-Martin, 2005), as a subtype of hypersexualityand sex disorders (Kafka, 2010), or as a subtype of Internet addiction disorder (Young, 2004). As of yet, no formal diagnostic criteriafor problematic IP use exist, which limits research considerably.Of the few scales that assess pornography use, only two target IPdirectly: the Internet Sex Screening Test (Delmonico & Miller, 2003) and the Cyber-PornographyUse Inventory (CPUI) (Grubbs, Sessoms,Wheeler, & Volk, 2010). Both of these scales have demonstratedpromising psychometric properties in assessing the addictive natureof IP.

Present study

Evidence has accumulated to suggest that one’s IP use maybecome addictive. Addiction to IP has been associated with symptomsof poor psychosocial functioning, including depression, anxiety, anddissatisfaction with one’s life and relationships, as well asthe urge to use more IP despite negative consequences. The goal ofthe present study is to explore these correlates of problematic IPuse and, more specifically, discern how different patterns of behaviorand IP use are associated with addiction and psychosocial functioning.Assessment of these relationships may allow us to pinpoint a generalthreshold at which frequency and volume of use coincides with theemergence of negative effects. Moreover, determining whether frequencyand volume of IP use are related to harmful effects could help makedistinctions between recreational users of IP and problematic IP users.This understanding could allow users of IP to gauge their use andcurtail it to a less harmful level. As stated earlier, some problematicusers have indicated they did not know that their use was causingthem difficulties until they had stopped. Additionally, assessingindividual factors that are highly correlated with problematic oraddictive IP use (e.g., demographics, addictive propensities, etc.)may help to identify at-risk populations.

The hypothesis of the present study is that high frequency andvolume of IP use will correlate negatively with measures of psychosocialfunctioning and positively with degree of addiction. We will explorethe linearity of these relationships to assess whether levels of useare associated with the emergence of symptoms of addiction. Finally,we will explore the association of IP addiction with problematic useof alcohol, cannabis, video gaming, and gambling, which are relativelycommon among university students.

Methods

Participants

The sample (N = 191) wasrecruited through the University of Calgary Research ParticipationSystem, whereby students enrolled in psychology courses receive bonuscredit in exchange for their research participation.Potential participants were informed that the studywould entail inquiry into their IP use, masturbatory behaviors, andmeasurements of addiction and behavioral functioning, by completinga battery of questionnaires.

Procedure

The questionnaire was administered online through Qualtrics andwas completed by each participant on a private personal computer insmall groups. Before beginning the questionnaires, participants werebriefed as to the nature of the study, the potential of personal orsensitive questions being asked, and then assured of their anonymityin the experiment. Measures assessing psychosocial functioning wereadministered first, as to avoid the issue of priming the participantswith questions addressing IP and masturbation, should they experienceany initial distress from these questions.

Measures

Demographics questionnaire

A brief demographic survey was administered, assessing informationof age, gender, area of residence, relationship status, sexual orientation,education, employment status, household income, ethnicity, and religiousaffiliation.

Brief Symptom Inventory 18

The abbreviated version of the Brief Symptom Inventory (BSI-18)was used to measure psychological symptoms of distress: somatization,depression, and anxiety (Derogatis, 2001). Reported internal consistency estimates for the totalscore of the BSI-18 are very good (α = .89).

Satisfaction with life scale

Overall life satisfaction was assessed with the five-item satisfactionwith life scale (SWLS) (Diener et al., 1985). This scale is used to narrowly measure global life satisfactionand has favorable psychometric properties including good internalconsistency (α = .79)and temporal reliability (r = .80).The scale also correlates highly with other measures of subjectivewell being, including the BSI-18.

Relationship assessment scale

Participants currently in relationships completed the seven-itemrelationship assessment scale (Hendrick, Dicke, & Hendrick, 1998), to measure their general levelof satisfaction with their current relationship. This scale was chosendue to its high correlation with feelings of boredom in relationships,a commonly reported occurrence with high IP use (Poulsen, Busby, & Galovan, 2013). Higher scoresrepresent a greater satisfaction with one’s partner. Temporalreliability for the relationship assessment scale (RAS) is very good(r = .85) and the internal consistencyis acceptable (α = .73).

Problematic gambling, alcohol, and cannabisuse

The alcohol use disorders identification test (AUDIT; Babor, Higgins-Biddle, Saunders, & Monteiro, 2001), the cannabis use disorders identification test –revised (CUDIT-R; Adamson et al., 2010), and the problemgambling severity index (PGSI; Wynne, 2003) were included as alcohol, cannabis, and gambling, whichare three common addictive entities present in student life. The AUDITshows good internal consistency (α = .80),the CUDIT-R shows excellent internal consistency (α = .94),and the PGSI shows good internal consistency (α = .84).Any correlations between these measures and the addictive measuresof IP (see below) may show that problematic IP use may belong to acluster of addictive tendencies and practices. Scores of 8 or higheron the AUDIT are considered an indication of hazardous and harmfulalcohol use. Hazardous cannabis use is indicative of a score of 13or higher on the CUDIT-R. Scores of 5+ on the PGSI are consideredmoderate, whereas scores of 8+ are considered indicative of problemgambling (Currie, Hodgins, & Casey, 2013).

Game Addiction Inventory for Adults

Included with the addiction measures was the Game Addiction Inventoryfor Adults (GAIA), a scale developed to assess addictive propensitiesto video games (Wong & Hodgins, 2013). The overall addiction score of the GAIA has excellentinternal reliability (α = .94). Scoresof 30+ are considered mild-moderate and scores of 40+ aresignificant level of problem. Both problematic IP use and problematicvideo game use are disorders that involve the use of computers andthe Internet. We predict a moderate correlation between these twodisorders, and inclusion of this measure allows for additional explorationof the association of computer- and Internet-based disorders.

Frequency/volume of Internet pornography questionnaire

Participants answered an 11-item researcher compiled questionnairethat assessed IP use. Questions included the participant’s frequencyof IP use (number of sessions per month), the time spent per IP session(in minutes), and the number of pictures/videos/files/documents usedwithin each session. Participants were also asked to indicate theage of their first exposure to IP and to briefly describe the natureof that experience in words. Finally, participants were asked whethertheir frequency of IP use, the time spent per IP session, and/or theamount of IP per session had increased or decreased within the previousyear. Total IP exposure was calculated by subtracting the first ageof exposure from the participant’s current age. Participantswho did not use IP were omitted from this measure.

Internet pornography addiction criterion questions

The Diagnostic and Statistical Manual of Mental Disorders (5th ed.; DSM-5;American Psychiatric Association, 2013) includes a preliminary set of criteria for diagnosing Internet GamingDisorder. An international group has proposed a set of correspondingassessment questions (Petry et al., 2014), which have been adapted by the researchers to assessfor IP addiction criteria (see Appendix). Adapting these items required minimal rephrasing. Some items wereexpanded into more distinct questions to assess each of their partsseparately. Three additional questions were added to assess issuesof sexual dysfunction with arousal, orgasm, and pain. A likert scale(Not at all [0], Rarely [1], Sometimes [2], Often [3]) was adoptedto allow for a richer dataset. As with the Internet Gaming Disordercriterion questions, each question was in reference to the last 12months. A high internal consistency was found among items within thesample of the present study (α = .90).Corrected total item correlations ranged from .55 to .76.

Cyber-pornography use inventory – compulsionmeasure

Finally, the CPUI (Grubbs et al., 2010) was included to assessconvergent validity with an inventory that has demonstrated acceptablereliability (α > .80) and some evidence of construct validity. The compulsive subscaleis 11-item scale meant to assess an individual’s lack of self-regulatorybehaviors, despite the desire to quit using IP.

Data analysis

Relationships between IP use (frequency, time, and amount) andpsychosocial functioning, addiction measures, and IP addiction wereassessed using bivariate Pearson correlations and independent sample t-tests. Sequential polynomial regression analysis (Wuensch, 2014) was used to assesswhether relationships between IP use and psychosocial functioningare linear, quadratic, or cubic. The shape of this relationship wasexamined to identify a potential thresholdof harmful IP use. Descriptive thematic analysis (Braun & Clarke, 2006) was used to analyze participantresponses to experiences of first exposure to IP. Finally, multipleregression analysis was computed to assess at-risk factors that predictproblematic and addictive IP use. Statistical outliers were adjustedin the IP frequency, time, and amount measures. For frequency, theoutlier responses of 60, 50, and 40 times per month were adjustedto 34, 33, and 32 times per month. For time spent per IP session,the outlier responses of 120, 100, and 95 minutes were adjusted to63, 62, and 61 min. For amount of IP/session, the outlier responseof use of 100 pornographic items/session was adjusted to 61 items.

Ethics

Ethical review was provided by the University’s ConjointFaculties Research Ethics Board. All subjects were informed aboutthe study and all provided informed consent. Upon completionof the questionnaires, participants were debriefedand given information on where to seek counseling if any part of thestudy had caused them distress.

Results

Description of the sample

The responses of 191 undergraduate students, 86 male and 105 female,were analyzed. Mean age was 21.05 years (SD = 2.96,range = 17 to 38) and ethnicity was mostly Caucasian(n = 97), followed by Chinese(n = 23), South Asian (n = 20), Latin American (n = 12), Southeast Asian (n = 8), Black (n = 6), Arab (n = 5),Other (n = 5), Filipino (n = 4), West Asian (n = 4), Korean (n = 4), Aboriginal (n = 2),and French Canadian (n = 1).Total annual household income was bimodally distributed, with 27%of students reporting $100,000 and over (n = 52),and 21% reporting under $10,000 (n = 40).Current relationship status was 50% single (n = 96),17% dating (n = 32), and 33%in a serious relationship (n = 63).Participants were predominantly heterosexual (n = 162),with 6% of participants identifying as homosexual (n = 12), 6% as bisexual (n = 11),and 3% identifying as asexual (n = 6).Participants were predominantly atheist/agnostic (n = 85), followed by Catholic (n = 31), Christian (n = 22),Muslim (n = 15), Protestant(n = 12), Other (n = 10), Buddhist (n = 6),Sikh (n = 6), Hindu (n = 2), and Jewish (n = 2). Participant religiosity and spiritualitywas recorded, with a rating of 1 being of no importance and 4 beingof high importance. Mean ratings for importance of religion in one’slife was low (M = 1.15, SD = 1.12) with the majority of participantsstating that they did not find religion important at all (n = 74). Spiritualitywas rated slightly higher in importance (M = 1.49, SD = 1.04) with the majority of participantsrating spirituality as somewhat important (n = 65).

Table 1 provides themeans, standard deviations, and ranges for measures of psychosocialfunctioning, addiction measures, and measures of addictive and IPuse. Participant mean score on the BSI-18 was 12.45 (SD = 9.00). Mean score on the BSI-18 for studentpopulations has been previously recorded at 8.41 (SD = 7.83, n = 266)(Meijer, de Vries, & van Bruggen, 2011), which is significantlylower than the present study, t(455) = 5.11, p < 0.001. Participant mean scores on theSWLS (M = 24.17, SD = 4.52) were in the average range of 20 to24, typical of individuals, who live in economically developed regions(Diener et al., 1985).Percentage of participants who scored below this range was 22%. Meanparticipant scores for the RAS (M = 29.91, SD = 4.52) are indicative of aboveaverage range scores (M = 28.00),the highest being a score of 35 (Hendricket al., 1998). Only 6% of participants scored in the rangeof greater relationship distress and dissatisfaction.

Table 1.

Means and standard deviation for scores on psychosocial functioning,addiction inventories, IP addiction measures, and exposure to IP.Gender differences shown in t values

Total (N = 191)Males (n = 86)Females (n = 105)t(189)MinMax
BSI-1812.45 (9.00)11.66 (10.70)13.09 (11.70)0.8690.0046.00
SWLS24.17 (4.52)23.07 (6.76)25.08 (5.56)0.2258.0035.00
RAS129.92 (4.52)30.05a (6.00)29.83b (3.34)0.19913.0035.00
AUDIT4.90 (4.78)5.45 (5.54)4.44 (4.02)1.4650.0027.00
CUDIT-R2.13 (3.76)3.02 (4.65)1.39 (2.64)2.798*0.0023.00
PGSI0.34 (0.89)0.53 (1.10)0.18 (0.62)3.050*0.005.00
GAIA14.14 (17.39)23.95 (19.05)6.10 (10.53)8.200**0.0082.00
IP-CRIT7.41 (8.04)11.60 (8.76)3.98 (5.39)7.376**0.0032.00
CPUI-COMP11.28 (8.64)16.35 (9.28)7.12 (5.21)8.658**0.0039.00
Age of first exposure13.95 (3.00)12.78 (1.92)15.10 (3.42)5.457**7.0032.00
Total years of exposure7.24 (3.67)8.60 (3.42)5.90 (3.42)5.144**0.0019.00
Frequency of IP use (times/month)7.68 (9.82)14.73 (10.66)1.90 (2.92)11.819**0.0034.00
Time spent per IP session (in min)14.97 (15.87)17.31 (13.05)13.05 (16.19)1.8560.0063.00
Amount of IP (files per session)4.72 (8.72)6.78 (9.43)3.03 (7.73)3.016*0.0061.00

Note. BSI-18 = Brief SymptomInventory; SWLS = Satisfaction With Life Scale;RAS = Relationship Assessment Scale; AUDIT = AlcoholUse Disorders Identification Test; CUDIT-R = CannabisUse Disorders Identification Test – Revised; PGSI = ProblematicGambling Severity Index; GAIA = Game AddictionInventory for Adults; IP-CRIT = adapted DSM-5Internet pornography addiction criteria; CPUI-COMP = Cyber-Pornography Use Inventory –Compulsion Measure.

1 n = 67. an = 26. bn = 41.

*p < .01. **p < .001.

Table 1 provides meansand standard deviations for scores on addiction measures. Mean participantscores for the AUDIT was M = 4.90(SD = 4.78) and the percentageof participants in the problematic range was 25%. For the CUDIT-R(M = 2.13, SD = 3.76), only 2% of participants met criteriafor problematic cannabis use. Scores on the PGSI (M = 0.34, SD = 0.89)were particularly low, as very few participants indicated they gambledat all (9%). No participants met criteria for problematic gambling,and only 3% of participants met criteria for moderate gambling severity.GAIA mean score was 14.14 (SD = 17.39),with 13% falling in the mild-moderate range and 20% in the significantrange of problems.

Pornography use

Mean age of first exposure to IP was 12.78 yearsfor males (SD = 1.92), and 15.10years (SD = 3.42) for females.In terms of frequency of IP use, males and females differed significantly, χ2(6) = 8.87, p < 0.001.For females, 46% (n = 48) didnot use IP for masturbation whatsoever, 23% (n = 24)used it less than monthly, 11% (n = 12)once a month, 11% (n = 11) morethan once a week, and 10% (n = 10)once a week. For males, 5% (n = 4)indicated that they did not use IP for masturbation at all, 6% (n = 5) of males used IP less than monthly,8% (n = 7) used IP once a month,12% (n = 11) used IP once aweek, 36% (n = 31)used IP for masturbation more than once a week, 27% (n = 24) used IP daily, and 5% (n = 4) indicated that they were using IP formasturbation twice a day or more.

Qualitative analysis of first exposure to Internetpornography

Descriptive thematic analysis was used to analyze the written descriptionsof first exposure to IP of 84 male and 86 female participants. Themajority of responses (57%) described having been first exposed toIP by intentionally searching for IP on a personal computer whilein private. The five most common themes found in participant descriptionsof their first exposure were feelings of curiosity (34%), followedby feelings of awkwardness/confusion (24%), excitement (15%), guilt/immorality(14%), and finally arousal (11%).

Coding for quality of experience was based on language of positiveor negative connotation. Language such as “enjoyed” or “pleasure”was coded as positive, and language such as “uncomfortable”or “gross” was coded as negative. Responses were codedas mixed if equal amounts of positive and negative language were usedor if no clear connotation to the language used could be identified.Males predominantly rated their first exposure to IP as being a positiveexperience (35% of male responses) with 11% of male responses describinga negative experience, and 24% describing a mixed experience. Femaleshad more negative experiences than males (34% of responses), with20% of female responses describing a positive experience, and 26%of responses describing a mixed experience. The differences betweenpositive and negative experiences for males and females were significant, χ2(2) = 13.04, p < 0.005,with males being more likely than females to rate their first exposureas being a positive experience. Six female participants describedhaving first been exposed to IP via a significant other, the majorityof which were negative experiences. Many females who had positiveexperiences did not find the experience sexually arousing and describedthe experience as one of amusement or humor (41% of female’spositive experiences). Finally, most males intentionally sought outIP for their first exposure (73%), as opposed to accidentally viewingit (19%). Many female participants described having stumbled uponIP unintentionallyor being introduced to it without their discretion (37% of responses).Quality of experience of first exposure was neither found to be associatedwith later IP frequency and volume of use nor was quality of firstexposure associated with higher scores on IP addiction measures.

Demographics and Internet pornography exposure

The t tests for participant demographics and IPuse found that the frequency of IP use per month for single participants(M = 9.07, SD = 10.50) was significantly higher than thefrequency of IP use for participants in relationships (M = 6.27, SD = 8.92), t(189) = 1.99, p = 0.05.The t tests also confirmed the likelihood of higherscores on addictive IP criteria for participants, who were single(M = 9.16, SD = 8.50) than for participants in relationships(M = 5.65, SD = 7.18), t(189) = 3.08, p = 0.002.

Age of first exposure to IP (M = 13.95, SD = 3.00) was found to be significantlycorrelated with frequent and addictive IP use (see Table 2). Participants who were exposedto IP at an earlier age were more likely to use IP more frequently(r = −.27, p < 0.001), have longer IP sessions (r = −.16, p = 0.033),and more likely to score higher on Adapted DSM-5 Internet PornographyAddiction Criteria (IP-CRIT; r = −.28, p < 0.001) and CPUI-COMP measures (r = −.29, p < 0.001).Finally, total IP exposure was found to be significantly correlatedwith higher frequency of IP use. Participants who had longer totalexposure to IP were also more likely to have more IP sessions permonth (r = .25, p = 0.003).

Table 2.

Measures of psychosocial functioning, addiction, and exposure toIP correlated with IP use and measures of IP addiction

Frequency of IP useTime spent per sessionAmount per sessionIP-CRITCPUI-COMP
BSI-180.0600.0860.1120.255***0.250***
SWLS−0.137−0.063−0.155*−0.318***−0.362***
RAS (n = 67)0.038−0.153−0.179−0.263*−0.316**
AUDIT0.190**0.150*−0.0260.0490.033
CUDIT-R0.203**0.0890.0190.1250.060
PGSI0.180*0.0300.0710.217**0.242**
GAIA0.459***0.189**0.281***0.403***0.435***
Age of first IP exposure−0.267***−0.163*−0.033−0.282***−0.292***
Total exposure to IP0.281***0.161*0.1430.168*0.204**

Note. BSI-18 = Brief SymptomInventory; SWLS = satisfaction with life scale;RAS = relationship assessment scale; AUDIT = alcoholuse disorders identification test; CUDIT-R = cannabisuse disorders identification test – revised; PGSI = problematicgambling severity index; GAIA = Game AddictionInventory for Adults; IP-CRIT = adapted DSM-5Internet pornography addiction criteria; CPUI-COMP = cyber-pornographyuse inventory – compulsion measure.

p < .05. **p < .01. ***p < .001.

Internet pornography use and psychosocial functioning

Table 2 provides Pearsoncorrelations between BSI-18, SWLS, and RAS scores and IP use. Overall,there was minimal to no association found between IP use and reportsof poor psychosocial functioning. There was a small but significantnegative correlation found between life satisfaction and amount ofIP use (r = −.15, p = 0.04). Participants who used highervolume of IP/session were more likely to rate their life satisfactionlower than others.

Reports on psychosocial functioning were also compared to IP addictivecriteria (see Table 2).Significant correlations were found between IP-CRIT and BSI-18 scores(r = .26, p < 0.001) and LSSscores (r = −.32, p < 0.001). Participants were more likelyto have higher general anxiety and distress, as well as lower lifesatisfaction, if they reported symptoms of addictive IP use. AddictiveIP use also had a small but significantnegative correlation with RAS (r = −.26, p = 0.03).CPUI measure of compulsive use of IP was also significantly correlatedwith higher scores on the BSI-18 (r = .25, p < 0.001), a lower score on the SWLS (r = −.36, p < 0.001)and slightly more likely to have lower RAS scores (r = −.32, p = 0.009).Participants who identified as having addictive propensities to IPshowed higher general levels of distress and lower levels of lifesatisfaction and relationship satisfaction.

Internet pornography use and addictive propensities

Pearson correlations were computed to compare IP use and IP addictionwith other measures of addiction: alcohol (AUDIT), cannabis (CUDIT-R),problematic gambling (PGSI), and video games (GAIA). Significant correlationswere found between frequency of IP use and all four addiction measures(see Table 2).

Threshold of harmful Internet pornography use

To assess whether a threshold of harmful IP use exists, sequentialpolynomial regression analysis was used to investigate the natureof the relationship between IP use and psychosocial functioning, andto identify a curvilinear relationship, as per Wuensch (2014). As shown in Table 3, no significant relationships werefound with the BSI-18, the SWLS, or the RAS. The relationship betweenIP use and psychosocial functioning does not appear to be curvilinear,and therefore, no threshold of harmful IP use could be identified.However, there were significant curvilinear relationships found withIP-CRIT (r = .39, p < 0.001) and CPUI-COMP (r = .40, p < 0.001) IP use (see Figures 1 and 2). Initially, scores on both IPmeasures rise from zero, but then plateau.Addictive IP use criteria scores appear to plateau at 15 IP sessions/month,and at a score of ∼14.00. Scores on the CPUI-compulsion(COMP) scale plateau at 13 IP sessions/month and at a score of ∼18.00.However, these scores sharply rise again in a positively acceleratingcurve when sessions occur more than once a day. At daily or greateruse of IP, there is a noticeable increase in the scores of IP addictionmeasures.

Figure 1.
Figure 1.

Curvilinear relationship between frequency of IP use and addictiveIP criteria adapted from DSM-5. Line of best fit suggests that addictiveuse of IP plateaus at a use of 15 sessions/month but increases onceparticipants begin using IP once a day

Citation: Journal of Behavioral Addictions 5, 2; 10.1556/2006.5.2016.022

Figure 2.
Figure 2.

Curvilinear relationship between frequency of IP use and the CPUImeasure of compulsive IP use. Note the similarity with the line ofbest fit in Figure 1.CPUI-COMP plateaus at 13 sessions/month but then increases when participantsuse IP once or more a day

Citation: Journal of Behavioral Addictions 5, 2; 10.1556/2006.5.2016.022

Table 3.

Sequential polynomial regression analysis of IP use, psychosocialfunctioning, and measures of addictive IP use

Pearson correlationsBSI-18SWLSRASaIP-CRITCPUI-COMP
Frequency of IP useLinear0.060−0.137−0.0380.536***0.528***
Quadratic0.057−0.0890.1380.445***0.455***
Cubic0.053−0.0600.1850.385***0.401***
Time spent per IP sessionLinear0.086−0.063−0.1530.389***0.302***
Quadratic0.075−0.025−0.1280.262***0.188**
Cubic0.063−0.003−0.1040.203**0.133
Amount of IP per sessionLinear0.112−0.155*−0.1790.333***0.325***
Quadratic0.115−0.119−01380.166*0.176*
Cubic0.112−0.105−0.1200.1150.124

Note. IP = Internet pornography;SWLS = satisfaction with life scale; RAS = relationshipassessment scale; IP-CRIT = adapted DSM-5 Internetpornography addiction criteria; CPUI-COMP = cyber-pornographyuse inventory – compulsion measure.

n = 67.

p < .05. **p < .01. ***p < .001.

Discussion

Higher scores on addictive measures of IP use were correlated withdaily or more frequent use of IP. However, the results indicate thatthere was no direct link between the amount and frequency of an individual’spornography use and struggles withanxiety, depression, and life and relationshipsatisfaction. Significant correlations to high IP addiction scoresincluded an early first exposure to IP, addiction to video games,and being male. While some positive effects ofIP use have been documented in previous literature (Broad, 2002; Correll, 1995; Hald & Malamuth, 2008; Kaufman et al., 2007; Kingston & Malamuth, 2010; Koch & Schockman, 1998; McLelland, 2002; Poulsen, Busby, & Galovan, 2013), our results do not indicatethat psychosocial functioning improves with moderate or casual useof IP.

Threshold of harmful Internet pornography use

The failure to find a strong significant relationship between IPuse and poor psychosocial functioning (general anxiety and distress,life satisfaction, relationship satisfaction) suggests that the overalleffect of IP use is not necessarily harmful in and of itself. However,higher IP addiction scores were associated with poor psychosocialfunctioning. The scores on addictive IP measures increased once participantsindicated IP use of at least once a year, but these scores eventuallyplateaued once participants were using it every second day. Whilethis could be interpreted as evidence that IP is inherently addictive,what is more likely is that these scores of ~14.00 for IP-CRIT and~18.00 for the CPUI-COMP measure are the scores of recreational IPusers. Naturally, there would be some observable score on either measurewhen a participant is using IP, even if this use does not qualifyas addictive.

We did see a dramatic shift in addictive IP use when participantswere using IP once a day or more. Above this frequency, there is anincrease in scores of addiction. This pattern would suggest that addictiveuse of IP, which is associated with poorer psychosocial functioning,emerges only when people begin to use IP daily. However, as the datafrom the addictive measures of IP use were based on self-report, thisalso suggests that poor psychosocial functioning may coincide withfrequent IP use only when the individual feels that their use is problematicor addictive. Whether the individuals’ distress is caused bydaily use of IP or is reflective of the individuals’ reactionto their suspicion of being addicted is unclear.

A similar distinction between level of use and addiction has beenreported in the video gambling addiction literature (Charlton & Danforth, 2007, 2010; Wong & Hodgins, 2013). Although strong engagement is anecessary condition for addiction or problematic play, strong engagementis not synonymous with addiction.

At-risk populations

The results of the present study suggest that populations thatare the most at-risk for problematic IP use are single males who wereexposed to IP at an early age. Early first exposure to IP is frequentlycited in research as being related to poorer psychosocial functioning.These problems may include increased delinquent behavior and substanceuse in later years (Ybarra & Mitchell, 2005), risky sexual behaviors in adolescence (Sinković, Štulhofer, &Božić, 2013), and increased propensity for sexualaggression (Flood, 2009). UsingIP as an addendum, or perhaps even a substitute, for sexual educationcreates the potential for youths to develop misconceptions about sexand sexuality. Further study of this early onset age group would providemore information on this idea.

Gender

Males were the predominant IPusers in this study and the most likely to identify as having addictiveIP use. The finding is consistent with the existing literature. Thisis not to say that women are not at risk for developing addictiveuse of IP, but males appear to be a much more prone population. Asto why males find pornography so enticing, some have pointed to evolutionfor an explanation (Vasey & Abild2013; Wilson, 1997, 2014). The prevalent (often intuited)opinion is that males evolved to be “hard-wired” to preferlarge numbers of novel sexual partners, as this is apparently themost efficient way to pass on their genetics. While this explanationhas its merits, it makes the assumption that males are preordainedby their evolutionary past to exhibit this preference. This and manyother assumptions housed in evolutionary psychology have their limitationsand can create misunderstandings about human behavior (Confer et al., 2010). What ismore likely is that modern public attitudes and accepted norms ofmale sexual behavior perpetuate this preference for IP, whereasthe modern attitudes and norms of female sexual behavior do not (Malamuth, 1996). Research has shownthat both sexes who use IP enjoy it equally, depending on the content(Ciclitira, 2004; Poulsen, Busby, & Galovan, 2013). Male use of IP may be simply more socially acceptable than itis for females in Western culture.

IP and video games

Addictive use of IP appears to be moderately correlated with videogame addiction. This should not be necessarily surprising, as thereare strong similarities between these two addictions. Both utilizecomputers and the Internet, and the way that either medium is accessedand interacted with is virtually the same. Moreover, many adult anderotic video games have been created in recent years (e.g., BoneCraft,Leisure Suit Larry) and their popularity is steadily increasing. Evencommercial video games are beginning to show increasing levels ofsexual content (e.g., God of War, The Witcher, Grand Theft Auto).

Given the similarities of these two mediums, it is possible thataddiction to video games and IP could reinforce each other. ProblematicIP use and problematic video game use are both moderately correlatedwith reports of isolation and loneliness, as both mediums are oftenused as substitutions for social contact (Ng & Wiemer-Hastings, 2005; Yoder, Virden, & Amin, 2005). This may create a harmfulcycle in which the individual does not receive regular social contact,and then substitutes the lack of social contact with video games andIP. Adolescent males would be particularly prone to this cycle (Jansz, 2005; Sabina et al., 2008), and further research intothe connection between these two addictions may elucidate causes andat-risk factors during adolescent development.

Limitations

All participant responses were based on self-report. It is possiblethat some participants may have lied due to the sensitive nature ofthe questions. It is also possible that some participants exaggeratedwhen responding (e.g., reporting their IP use was greater than itwas), or incorrectly estimated their behavior. Social desirabilitymay also have played a large role in how participants answered thequestionnaire. Although participants were provided with private computerswhen completing the measures, some may have been too embarrassed togive accurate responses. Others may have had prior knowledge of thetheory of IP addiction and wanted to prove ordisprove this theory. Additionally, recruitment of students takingpsychology courses may have affected responses. Some participantsmay have had prior exposure to or knowledge of the scales included.Recruitment of other student populations, or certainly populationsoutside of academia, could be more representative of the general population.

The scales used to assess IP addiction in this study, the CPUI-COMPmeasure, the GAIA, and the additive IP criteria, which were adaptedfrom the DSM-5, lack validated cutpoints to indicate clinically relevantelevations. Therefore, it is not clear what constitutes as averageuse versus harmful use of IP or video games based on these measures.

Finally, as this study utilizes a correlation design, no definitiveclaims can be made about a threshold of harmful IP use or at-riskfactors. However, the results generated by this study do stand inopposition to many popular claims and conceptions about IP use.

Future directions

Revisions of this study should include recruitment of a largernumber of male participants, and perhaps even a version of the studyentirely composed of male participants. A caveat to this, however,will be the difficulty in finding a control group, as it is very uncommonfor males to have never used IP.

There should be further examination into the combinedeffect of problematic video games and IP use. The present study collectedthe responses of a large number of adult gamers, but it would be beneficialto also look at younger ages closerto the mean age of first exposure. The effect of video games and IPon the minds of adolescents is a very sensitive topic,and obtaining ethics would present an issue. However, designing astudy for an adolescent age range couldvastly increase our understanding of how problematic IP and videogame use develop and potentially reinforce one another.

Summary

Our results show that daily IP use has no direct correlation withpoor psychosocial functioning. Poor psychosocial functioning emergedonly when an individual identified as having addictive IP use. Thissuggests that identifying oneself as an IP addict may be what causesdistress and poor psychosocial functioning, not the IP itself. However,there is potential for daily IP use to lead to addictive behavior.There may also be a relationship with addictive use of IP and videogame addiction, as these two mediums are sometimes used as a substitutefor healthy social contact. This substitution may cause a compoundingeffect of poorer psychosocial functioning over time. Additionally,earlier exposure to IP may lead to higher risk of problematic IP use.Adolescent males are likely to be an at-risk group, and future studywith this population could confirm this and elucidate more detailedat-risk factors.

Authors’contribution

CH and DH made study concept and design, analysis of data, statisticalanalysis.

Conflict of interest

The authors report no financial or other relationship relevantto the subject of this article.

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  • Vasey, P. L., & Abild, M. (2013). A billion wicked thoughts: What the Internet tells us about sexualrelationships. Archives of Sexual Behavior, 42(6), 11011103. doi:10.1007/s10508-013-0170-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voon, V., Mole, T. B., Banca, P., Porter, L., Morris, L., Mitchell, S., Lapa, T. R., Karr, J., Harrison, N. A., Potenza, M. N., & Irvine, M. (2014). Neural correlates of sexual cue reactivity in individuals with andwithout compulsive sexual behaviours. PloSOne, 9(7), e102419. doi:10.1371/journal.pone.0102419

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilson, G. (2014). Your brain on porn: Internet pornography and the emerging scienceof addiction. Margate, Kent: Commonwealth Publishing.

    • Search Google Scholar
    • Export Citation
  • Wilson, G. D. (1997). Gender differences in sexual fantasy: An evolutionaryanalysis. Personality and Individual Differences, 22(1), 2731. doi:10.1016/S0191-8869(96)00180-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wong, U., & Hodgins, D. C. (2013). Development ofthe Game Addiction Inventory for Adults (GAIA). Addiction Research & Theory, 22(3), 195209.doi:10.3109/16066359.2013.824565

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wuensch, K. L. (2014). Curvilinear bivariate regression. In East Carolina University Department of Psychology. Retrieved from http://core.ecu.edu/psyc/wuenschk/MV/multReg/Curvi.docx

    • Search Google Scholar
    • Export Citation
  • Wynne, H. (2003). Introducing the Canadian Problem Gambling Index. Edmonton, AB: Wynne Resources.

  • Ybarra, M. L., & Mitchell, K. J. (2005). Exposure to Internet pornography among children and adolescents:A national survey. CyberPsychology & Behavior, 8(5), 473486. doi:10.1089/cpb.2005.8.473

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yoder, V. C., Virden, T. B., III, & Amin, K. (2005). Internet pornography and loneliness:An association? Sexual Addiction & Compulsivity, 12(1), 1944. doi:10.1080/10720160590933653

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Young, K. S. (2004). Internet addiction a new clinical phenomenon andits consequences. American Behavioral Scientist, 48(4), 402415. doi:10.1177/0002764204270278

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zillmann, D., & Bryant, J. (1986). Shifting preferencesin pornography consumption. CommunicationResearch, 13(4), 560578. doi:10.1177/009365086013004003

    • Search Google Scholar
    • Export Citation

Appendix: Internet pornography addiction criteria

The following are questions about your use of Internetpornography. Please answer honestly and to the best of your knowledge.Your answers are entirely anonymous and cannot be traced to any identifyinginformation. All answers should be in reference to the last 12 months.

1. Do you spend a lot of time thinking about Internet pornographyeven when you are not using it or planning when you can use it next?(Not at all/Rarely/Sometimes/Often)

2. Do you feel restless, irritable, moody, angry, anxious, or sadwhen attempting to cut down or stop your use of Internet pornography,or when you are unable to use Internet pornography? (Not at all/Rarely/Sometimes/Often)

3. Do you feel the need to use Internet pornography for increasingamounts of time? (Not at all/Rarely/Sometimes/Often)

4. Do you feel the need to use more intense or immersive formsof Internet pornography to receive the same amount of excitement orarousal that you used to? (Not at all/Rarely/Sometimes/Often)

5. Do you feel that you should use less Internet pornography butare unable to cut back on the amount of time you spend using it? (Notat all/Rarely/Sometimes/Often)

6. Do you lose interest in or reduce participation in other recreationalactivities (hobbies, meetings with friends) due to Internet pornography?(Not at all/Rarely/Sometimes/Often)

7. Do you continue to use Internet pornography even though youare aware of negative consequences, such as not getting enough sleep,being late to school/work, spending too much money, having argumentswith others, or neglecting important duties? (Not at all/Rarely/Sometimes/Often)

8. Do you continue to use Internet pornography for masturbationeven though you are experiencing an inability or difficulty in achievingsexual arousal? (Not at all/Rarely/Sometimes/Often)

9. Do you continue to use Internet pornography for masturbationeven though you are experiencing an inability or difficulty in achievingorgasm? (Not at all/Rarely/Sometimes/Often)

10. Do you continue to use Internet pornography for masturbationeven though you are experiencing bodily pain? (Not at all/Rarely/Sometimes/Often)

11. Do you try to keep your family or friends from knowing howmuch you use Internet pornography? (Not at all/Rarely/Sometimes/Often)

12. Do you use Internet pornography to escape from or forget aboutpersonal problems? (Not at all/Rarely/Sometimes/Often)

13. Do you use Internet pornography to relieve uncomfortable feelingssuch as guilt, anxiety, helplessness, or depression? (Not at all/Rarely/Sometimes/Often)

14. Does your use of Internet pornography add risk for potentiallylosing significant relationships, jobs, educational or career opportunities?(Not at all/Rarely/Sometimes/Often)

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  • Vasey, P. L., & Abild, M. (2013). A billion wicked thoughts: What the Internet tells us about sexualrelationships. Archives of Sexual Behavior, 42(6), 11011103. doi:10.1007/s10508-013-0170-5

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Voon, V., Mole, T. B., Banca, P., Porter, L., Morris, L., Mitchell, S., Lapa, T. R., Karr, J., Harrison, N. A., Potenza, M. N., & Irvine, M. (2014). Neural correlates of sexual cue reactivity in individuals with andwithout compulsive sexual behaviours. PloSOne, 9(7), e102419. doi:10.1371/journal.pone.0102419

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wilson, G. (2014). Your brain on porn: Internet pornography and the emerging scienceof addiction. Margate, Kent: Commonwealth Publishing.

    • Search Google Scholar
    • Export Citation
  • Wilson, G. D. (1997). Gender differences in sexual fantasy: An evolutionaryanalysis. Personality and Individual Differences, 22(1), 2731. doi:10.1016/S0191-8869(96)00180-8

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wong, U., & Hodgins, D. C. (2013). Development ofthe Game Addiction Inventory for Adults (GAIA). Addiction Research & Theory, 22(3), 195209.doi:10.3109/16066359.2013.824565

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Wuensch, K. L. (2014). Curvilinear bivariate regression. In East Carolina University Department of Psychology. Retrieved from http://core.ecu.edu/psyc/wuenschk/MV/multReg/Curvi.docx

    • Search Google Scholar
    • Export Citation
  • Wynne, H. (2003). Introducing the Canadian Problem Gambling Index. Edmonton, AB: Wynne Resources.

  • Ybarra, M. L., & Mitchell, K. J. (2005). Exposure to Internet pornography among children and adolescents:A national survey. CyberPsychology & Behavior, 8(5), 473486. doi:10.1089/cpb.2005.8.473

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Yoder, V. C., Virden, T. B., III, & Amin, K. (2005). Internet pornography and loneliness:An association? Sexual Addiction & Compulsivity, 12(1), 1944. doi:10.1080/10720160590933653

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Young, K. S. (2004). Internet addiction a new clinical phenomenon andits consequences. American Behavioral Scientist, 48(4), 402415. doi:10.1177/0002764204270278

    • Crossref
    • Search Google Scholar
    • Export Citation
  • Zillmann, D., & Bryant, J. (1986). Shifting preferencesin pornography consumption. CommunicationResearch, 13(4), 560578. doi:10.1177/009365086013004003

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

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2020  
Total Cites 4024
WoS
Journal
Impact Factor
6,756
Rank by Psychiatry (SSCI) 12/143 (Q1)
Impact Factor Psychiatry 19/156 (Q1)
Impact Factor 6,052
without
Journal Self Cites
5 Year 8,735
Impact Factor
Journal  1,48
Citation Indicator  
Rank by Journal  Psychiatry 24/250 (Q1)
Citation Indicator   
Citable 86
Items
Total 74
Articles
Total 12
Reviews
Scimago 47
H-index
Scimago 2,265
Journal Rank
Scimago Clinical Psychology Q1
Quartile Score Psychiatry and Mental Health Q1
  Medicine (miscellaneous) Q1
Scopus 3593/367=9,8
Scite Score  
Scopus Clinical Psychology 7/283 (Q1)
Scite Score Rank Psychiatry and Mental Health 22/502 (Q1)
Scopus 2,026
SNIP  
Days from  38
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Days from  37
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Acceptance 31%
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2019  
Total Cites
WoS
2 184
Impact Factor 5,143
Impact Factor
without
Journal Self Cites
4,346
5 Year
Impact Factor
5,758
Immediacy
Index
0,587
Citable
Items
75
Total
Articles
67
Total
Reviews
8
Cited
Half-Life
3,3
Citing
Half-Life
6,8
Eigenfactor
Score
0,00597
Article Influence
Score
1,447
% Articles
in
Citable Items
89,33
Normalized
Eigenfactor
0,7294
Average
IF
Percentile
87,923
Scimago
H-index
37
Scimago
Journal Rank
1,767
Scopus
Scite Score
2540/376=6,8
Scopus
Scite Score Rank
Cllinical Psychology 16/275 (Q1)
Medicine (miscellenous) 31/219 (Q1)
Psychiatry and Mental Health 47/506 (Q1)
Scopus
SNIP
1,441
Acceptance
Rate
32%

 

Journal of Behavioral Addictions
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Journal of Behavioral Addictions
Language English
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2011
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2021 Volume 10
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Founder Eötvös Loránd Tudományegyetem
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ISSN 2062-5871 (Print)
ISSN 2063-5303 (Online)

Senior editors

Editor(s)-in-Chief: Zsolt DEMETROVICS

Assistant Editor(s): Csilla ÁGOSTON

Associate Editors

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

Editorial Board

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

 

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