Sapienza University of Rome, Rome, Italy
Institute of Clinical Sexology, Rome, Italy
Kore University of Enna, Enna, Italy
An increasing number of people use the Internet for Online Sexual Activities (OSA). This sexual revolution has resulted in both positive and negative aspects, enriching sexual functioning but also providing other risks for criminal, negative and harmful sexual conducts, or Online Sexual Problems (OSP). A deeper understanding of Internet sexuality is therefore important for practitioners who work in the psychological and sexological fields. Current studies on Internet sexuality span a broad spectrum with respect to data collection: interviews, questionnaires, observations, content analyses and Internet log file recordings have all been used. The aim of this paper is to offer the most complete overview of these instruments focusing on the strengths and weaknesses of different tools currently available to assess different dimensions of OSA, and to suggest a simple screener for OSP. A systematic search of published online sexual activities inventories was performed using PsychInfo and Pubmed (1993 to July 2013). Although many of them are adequate for their own purposes, our review revealed a lack of standardized, internationally (culturally) accepted tools that are epidemiologically validated in general populations and that can be used to investigate OSA and to assess OSP. The definitions of OSA and OSP continue to change and basic tools are essential to have a broader idea of the phenomenon and of the challenges and possibilities emerging from the double link between the Internet and sexuality. More accurate instruments are also necessary to help advanced clinical diagnosis and treatment for OSP.
Keywords: self-report questionnaires; scales; online sexual activities (OSA); online sexual problems (OSP); internet sexuality
A growing number of people use Internet for Online Sexual Activities (OSA) and its consumption is rapidly increasing (Döring, 2009). OSA refer to the Internet use for any activity that involves sexuality for the purposes of recreation, entertainment, exploration, support, education, commerce and/or seeking out sexual or romantic partners (Boies, 2004). In the last years, a strong double link has arisen between sexuality and this new medium: first, the Internet represented a novel arena for existing sexual practices; secondly, the Internet offered the chance to discover new sexual interests. This new sexual revolution has led to both positive and negative aspects, facilitating and enriching sexual functioning but also furnishing other risks for criminal, negative and harmful sexual conducts, or Online Sexual Problems (OSP). Such difficulties include negative financial, legal, occupational, relational as well as personal repercussions from OSA. The wide variety of problems arising from Internet use include overuse in general and problems related to specific activities such as pornography, sexual exploitation, harassment, infidelity, fraud, and isolative-avoidant use (Mitchell, Becker-Blease, & Finkelhor, 2005). The ‘problem’ may range from a single incident to a pattern of excessive involvement. The consequences may involve feelings of guilt, loss of a job/relationship, higher risk of sexually transmitted infections, among others. Clinicians and educators are increasingly being called upon to offer advice and counselling to clients and families about problems stemming from Internet use (Mitchell, Sabina, Finkelhor, & Wells, 2009). A deeper understanding of Internet sexuality is therefore important for practitioners who work in the psychological and sexological fields.
The empirical research on Internet sexuality has grown steadily since 1993. The most researched area to date has been the consumption of Internet pornography, which also has the greatest intensity of use compared to the other areas of Internet sexuality (cybersex, sex shop, sex education). In terms of methodology, current studies span a broad spectrum with respect to data collection: interviews, questionnaires, observations, content analyses, and Internet log file recordings have all been used. As is generally the case with social science research, standardized written surveys are the most common method. Alongside ad hoc questionnaires, new psychometric survey instruments have rarely been introduced (Döring, 2009) and tested to explore different kinds of OSA. The empirical literature on measuring OSA is still relatively sparse. One difficulty in measuring these behaviors derives from the fact that cybersex addiction has not yet any official diagnostic criteria, so decisions for item inclusion and diagnostic thresholds may be decided ad hoc. Accurate measurement is a fundamental key in the assessment and treatment of cybersex addiction, and in distinguishing non problematic online sexual behavior from cybersex addiction and other OSP (Green, Carnes, Carnes, & Weinman, 2012).
To date, to the best of our knowledge, no review articles have been published that provide a systematic outline of questionnaires and scales for the evaluation in this field. The aim of this paper is to offer the most complete overview of these instruments focusing on the strengths and weaknesses of different questionnaires currently available to assess different dimensions of OSA, and to suggest a simple screener for OSP.
A systematic search of published online sexual activities inventories was performed using PsychInfo and Pubmed (1993 to July 2013). In an effort to identify the instruments used in basic research or in clinical settings, the search terms ‘inventories’, ‘questionnaires’, ‘interviews’ and ‘structured interviews’ were combined consecutively with the following terms: ‘Internet sexuality’, ‘online sexual activities’, ‘online sexual problems’, ‘cybersex’, ‘cybersexual addiction’. The search was limited to English-language papers in which evaluation of some kind of OSA and/or cybersexual addiction diagnosis were described. Moreover, only manuscripts reporting the entire version of the inventory and its psychometric features were considered. In Figure 1, a flow chart of study selection procedure is provided.
Figure 1. Flow chart of study selection procedure.
Although many instruments are adequate for their own purposes, our review revealed a lack of standardized, internationally (culturally) acceptable questionnaires that are truly epidemiologically validated in general populations and that can be used to investigate OSA and to assess OSP. The great majority of the studies, in fact, were carried out using data taken from surveys and questionnaires posted on websites, that were not evaluated on their psychometric properties (Albright, 2008; Boies, Cooper, & Osborne, 2004; Cooper, Griffin-Shelly, Delmonico, & Mathy, 2001; Cooper, Månnson, Daneback, Tikkanen, & Ross, 2003; Cooper, Scherer, & Mathy, 2004; Corley & Hook, 2012; Daneback, Cooper, & Månsson, 2005; Daneback, Månsson, & Ross, 2007; Grov, Gillespie, Royce, & Lever, 2011; Ross, Daneback, Månsson, Tikkanen, & Cooper, 2003; Ross, Månsson, & Daneback, 2012). McKenna, Green, and Smith (2001) created some indexes from their 25-item survey, however they did not provide psychometric properties for the overall questionnaire, so it is difficult to use it as a tool to efficaciously evaluate OSA.
Some studies used the interview as an instrument to assess OSA (Couch, 2008; Mitchell, Finkelhor, Wolak, Ybarra, & Turner, 2011; Mustanski, Lyons, & Garcia, 2011; Valkyrie, 2011; Waskul, 2002). Psychometric properties for these interviews were not evaluated.
Few questionnaires specifically focus on OSA and OSP measurement.
Internet Sex Screening Test
The Internet Sex Screening Test (ISST; Delmonico, 1997) is a 25 true-false item test. ISST total scores provide a classification of the subjects into three categories: low risk (1-8), at risk (9-18) and high risk (> 19). Factor analysis identified seven factors. The first factor, Online Sexual Compulsivity, a measure of online sexual problems, has six items and Cronbach’s α = 0.86. Second, Online Sexual Behaviour-Social (OSB-S), a measure of the tendency to engage in interpersonal interactions with others during online sexual behaviour (e.g., sex-related chat rooms), has five items and α = .78. Third, Online Sexual Behaviour- Isolated (OSB-I), a measure of the tendency to engage in solitary online sexual behaviour (e.g., viewing pornography), has four items and α = .73. Fourth, Online Sexual Spending (OSS), a measure of the tendency to purchase sexual material and/or join sex-related groups or websites via the Internet, has three items and α = .61. The fifth factor is Interest in Online Sexual Behaviour, a measure of the tendency to use the computer for sexual pursuits (e.g., bookmarking sexual sites), has two items and α = .51. Cronbach alphas for scales four and five are modest, and this can be viewed as the biggest limitation of this instrument. Two items that do not load on the main five factors are interpreted as single item scales because they measure important aspects related to the theory of OSB. The first item measured the tendency to access sexual sites from computers other than the home computer and is entitled Non-home Computer Use for OSB. The second single item scale measures the tendency to view illegal sexual material on the Internet and was entitled Accessing Illegal Sexual Material (Delmonico & Miller, 2003). Chronbach’s alpha for the total inventory is not provided.
Survey Created by Goodson and Colleagues
A survey instrument was created by Goodson, McCormick, and Evans (2000) to document college students’ attitudes and behavior when using the Internet for three main functions: (a) obtaining information related to sexuality (for school, work-related projects, or personal information); (b) establishing and maintaining relationships (such as using e-mail or participating in chat groups); (c) sexual gratification (sexual arousal and/or entertainment). The questionnaire consists of eight sections: A through H, with most questions being Likert scales (4-5 points). In addition to questions about e-mail and Internet use, the instrument contains items measuring practices, and outcome expectations and expectancies for the three functions just described. All outcome expectations and expectancy scales demonstrated appropriate internal consistency (Cronbach αs ranging from .76 to.95) and temporal stability over a 2-week period (Pearson αs ranged from .69 to .78). The scales were also factor-analyzed; the resulting factor structure accounted for 68.8% of the variance (Goodson, McCormick, & Evans, 2001). Chronbach’s alpha for the total inventory is not provided.
Cyber-Pornography Use Inventory
The Cyber-Pornography Use Inventory (CPUI; Grubbs, Sessoms, Wheeler, & Volk, 2010) is a 31-item self-report inventory composed of 3 subscales. Most questions are Likert scales ranging from either strongly agree to strongly disagree (7 points) or from never to always (5 points). Several items in the CPUI were taken from the ISST, and all of these, except for the items on the Online Sexual Behavior-Social subscale of the ISST, were made specific to online pornography, instead of general online sexual behavior, in order to develop a measure specific to pornography use. Whereas the original ISST was targeted toward general online sexual compulsivity and addiction, the CPUI was designed to specifically target areas related to Internet pornography. Additional items were developed and added to the test. Several reverse-coded items were included throughout the scales to create a more rounded assessment instrument. This made the Compulsivity scale 11 items long and the Social scale 6 items long, while the Isolated subscale and the Interest subscale remained their original lengths of 4 items and 2 items respectively. A 12-item subscale assessing guilt regarding pornography usage and a 5-item subscale assessing effort invested in obtaining pornography were also developed and included in the inventory. The Guilt scale was included to specifically assess levels of discomfort and self-reproach that might be associated with Internet pornography use, particularly within a religious population. The Efforts scale was founded on the diagnostic criteria for both Pathological Gambling and Substance Dependence that evaluate the exorbitant efforts placed into obtaining an addictive substance or behavior. Finally, the Online Sexual Spending subscale of the original was removed from this version of the instrument. Items were found to load on 3 factors. The first factor, termed Addictive Patterns, contains 18 items. The internal reliability coefficient of the factor is .89. The second factor revealed by the factor analysis was termed Guilt Regarding Online Pornography Use. It consists of 8 total items, with an internal reliability coefficient of .83. The third factor was termed Online Sexual Behavior-Social, as it was in the ISST. The scale consists of five items, with a reliability coefficient of .84. Chronbach’s alpha for the total inventory is not provided.
Online Sexual Experience Questionnaire
The Online Sexual Experience Questionnaire (Shaughnessy, Byers, & Walsh, 2011) has 9 items developed to examine participants’ non-arousal (2 items), solitary-arousal (4 items), and partnered-arousal (3 items) OSA experience. Participants rated the frequency with which they had engaged in each behavior during the past month on a 6-point Likert scale, ranging from never (0) to once a day or more (5). The Cronbach’s α of the questionnaire is .77. Three subscales were created using the mean scores: Non-Arousal OSA, Solitary-Arousal OSA, and Partnered arousal OSA.
Internet Addiction Test – Sex
The Internet Addiction Test – Sex (IATsex; Brand, Laier, Pawlikowski, Schchtle, Schöler, & Altstötter-Gleich, 2011) is a modified version of the IAT in which the terms ‘online’ or ‘Internet’ in the original IAT were replaced by the terms ‘online sexual activity’ and ‘Internet sex sites’ respectively. This instrument aims to assess subjective complaints in everyday life due to online sexual activities and potential symptoms of cybersex addiction. This version consists of 20 items, and the Likert scale used ranges from 1 to 5 (‘rarely’ to ‘always’), resulting in a potential score between 20 and 100. Internal consistency (Cronbach’s α) of this scale is .84.
Internet Usage Scale for Sexual Purposes-Modified
The Internet Usage Scale for Sexual Purposes-Modified (Velezmoro, Negy, & Livia, 2012) is a modified version of the survey by Goodson et al. (2000). This 25-item modified scale measures participants’ use of the Internet for: (1) viewing Sexually Explicit Material (SEM); (2) seeking out sexual partners; (3) seeking sex-related information. These three domains were based on the utility subscales used in the study by Goodson and colleagues with some items being modified to refer to attitudes consistent with the current study. Participants responded to statements using a 4-point Likert scale, with response options ranging from1 (Never) to 4 (Frequently). Scores were averaged, with higher scores reflecting more usage of the Internet for sexual purposes. The Cronbach reliability alphas are .88 (English) and .84 (Spanish) for the Finding Partners Online subscale, .88 (English) and .80 (Spanish) for the Information Seeking subscale, and .81 (English) and .78 (Spanish) for the SEM subscale respectively.
In Table 1, features of the various instruments described are shown.
Table 1. Self-reported questionnaires on Online Sexual Activites (OSA) and Online Sexual
Problems (OSP), reported in alphabetical order.
Some questionnaires, regarding overall compulsive internet use or sexual addiction, has specific items addressing OSA.
Sexual Addiction Screening Test – Revised
The Sexual Addiction Screening Test – Revised (SAST-R; Carnes, Green, & Carnes, 2010) is a 45-item screener for detecting potential cases of sexual addiction. The SAST-R consists of the 20-item Core scale, measuring the general construct of sexual addiction; 4 subscales measuring constituent components: Preoccupation (4 items), Loss of control (4 items), Relationship disturbance (4 items) and Affective disturbance (5 items); the 6-item Internet scale, measuring Internet-related sexual activity; 3 scales of 6 items each measuring behaviors more specifically salient to heterosexual men, homosexual men, and women (both hetero- and homosexual); and 5 items measuring associated constructs not on any scale. Reliability for the Core and SAST-R Internet are .86 and .79 respectively. The six SAST-R Internet items coheres quite well, with item total correlations ranging from .41 to .69, which was expected, as the scale is intended to measure a unitary construct. (Green, Carnes, Carnes, & Weinman, 2012).
Sexual Dependency Inventory – Revised
The Sexual Dependency Inventory – Revised (SDI-R; Green et al., 2012) is an update of the version published in the mid-1990s (Carnes & Delmonico, 1996). This version is an inventory of 206 items measured using a 6-point Likert scale which assesses the frequency and emotional salience of the majority of potentially problematic sexual behaviors. The items of the SDI-R tend to be specific to narrowly defined sexual behaviors, which when combined into scales, produce dimensional indices of circumscribed domains of sexual behaviors. The Behavior scales of the SDI-R measure self-reported frequencies of specific sexual behaviors (frequency items), grouped into scales based on the results of principal components analysis, followed by verification through content analysis. The Clinical scales of the SDI-R were also developed through principal components analysis, but using the “power” items, which measure how much emotional salience a respondent attaches to a given sexual behavior. This version of the SDI-R includes new items added to measure cybersex, constituting a 15-item Internet Sex Behavior scale measuring frequency of specific cybersex behaviors (α = .89), and a 19-item Preoccupied Online Anonymous Clinical scale measuring preoccupation with anonymous online sex (α = .89). Cronbach alpha for this new version of the inventory was not reported in the article.
In Table 2, features of the various instruments described are shown.
Table 2. Self-reported questionnaires regarding overall compulsive internet use or sexual
addiction, with specific items addressing OSA, reported in alphabetical order.
The definitions of OSA and OSP continue to change and basic tools are essential to have a broader idea of the phenomenon and on the challenges and possibilities emerging from the double link between the Internet and sexuality. In the clinical setting, the administration of inventories may help when working with people presenting online sexuality issues. On the other hand, an uncritical use of such inventories may conduct to bias when failing to take into account the complexity of human sexual behavior, or when oversimplifying and trivializing online sexual activities and the problems connected with them with mere numbers, such as the score obtained from an inventory.
Results present some potential for future clinical application as well as research. For initial testing and development, most of the inventories have demonstrated positive potential as research tools and assessment instruments, but the true utility of these will only be determined as they are used and studied more. Data show that just one of the analyzed instruments, the ISST, defines cut-off scores for differentiating problematic users from those who are not problematic. We think that this feature makes it the only useful instrument in the clinical practice of OSA and to assess Cybersexual Addiction. However, some psychometric limitations of the instrument, specifically regarding the internal consistency of some of the subscales, suggest the need to develop new instruments that could be also more congruent with recent theoretical conceptualizations of Cybersexual Addiction, recently included in the DSM V. Table 2 shows two questionnaires focused on non-Internet related behavior that have added a subscale to attempt to address the online aspect; these instruments are especially useful in the clinical evaluation of sexual addiction and dependency, so caution should be given in the clinical use of these for the OSA assessment. Maybe they can be used as a first level investigation on such topics; if their presence seems to be predominant, we suggest the use of more specific questionnaires. Regarding the questionnaires analyzed on OSA, we also suggest the use of the CPUI, when it emerges the need to specifically investigate pornography use.
A limitation of all the described instruments is that they are self-report instruments, based on affirmations directly made by subjects. Results could be strongly conditioned by shame and guilt, especially because the theme of the survey is somehow still stigmatized. Research has, in fact, identified a wide array of factors that appear to influence the accuracy of retrospective self-report of sexual behavior. These factors include the demands of the recall task and related memory error, and the social context of assessment, which can affect self-report bias (Schroder, Carey, & Vanable, 2003). More accurate instruments are however necessary to help advanced clinical diagnosis and treatment for OSP, or to slate patients adequately into the right diagnostic categories for basic research. Future directions of the research on this topic could consist in the ideation of new instruments on OSA and OSP to use in the clinical practice. These should reflect new conceptualizations on Cybersexual Addiction and be internationally validated.
One limitation of the review is that it is based upon a compilation of peer-reviewed English-language literature. This literature largely comes from Europe and North America, much less often from Latin America and Australia, and Asian or African sources are completely absent. The studies referenced thus approach the subject of investigation from a predominantly Western perspective. The review provides little information on both, the online sexual activities in non-Western populations and the non-English academic discourses on these activities.
The importance of the Internet as a medium for the exploration of OSA and as an opportunity to illuminate previously challenging areas of sexual research should also be discussed. The Internet, in fact, is a relatively new method for data collection, and more research is still necessary to understand the ways this method shapes the empirical data emerging from its interrogation. Following Ross (2005), we can still confirm that:
“although no data are free of determination by the method used to extract those data, and by extension no data-based theory is free of the method, we can begin to appreciate the way our "gaze" at sexuality occurs through the electronic filter of the internet - and how it may also enable us to see things at wavelengths not previously visible” (p. 351).
Albright, J. M. (2008). Sex in America online: An exploration of sex, marital status, and sexual identity in Internet sex seeking and its impacts. The Journal of Sex Research
, 175-186. http://dx.doi.org/10.1080/00224490801987481
Boies, S. C., Cooper, A., & Osborne, C. S. (2004). Variations in Internet-related problems and psychosocial functioning in online sexual activities: Implications for social and sexual development of young adults. CyberPsychology & Behavior, 7, 207-230. http://dx.doi.org/10.1089/109493104323024474
Brand, M., Laier, C., Pawlikowski, M., Schchtle, U., Schöler, T., & Altstötter-Gleich, C. (2011). Watching pornographic pictures on the Internet: Role of sexual arousal ratings and psychological–psychiatric symptoms for using Internet sex sites excessively. Cyberpsychology, Behavior, and Social Networking, 14, 371-377. http://dx.doi.org/10.1089/cyber.2010.0222
Carnes, P. J., & Delmonico, D. L. (1996). Sexual Dependency Inventory-revised. Minneapolis, MN: Positive Living Press.
Carnes, P., Green, B., & Carnes, S. (2010). The same yet different: Refocusing the Sexual Addiction Screening Test (SAST) to reflect orientation and gender. Sexual Addiction & Compulsivity, 17, 7–30. http://dx.doi.org/10.1080/10720161003604087
Cooper, A., Griffin-Shelley, E., Delmonico, D. L. & Mathy, R. (2001). Online sexual problems: Assessment and predictive variables. Sexual Addiction and Compulsivity, 8, 265 – 283. http://dx.doi.org/10.1080/107201601753459964
Cooper, A., Scherer, C., & Mathy, R. M. (2004). Overcoming methodological concerns in the investigation of online sexual activities. CyberPsychology & Behavior, 4, 437-447.http://dx.doi.org/10.1089/109493101750526999
Cooper, A., Månnson, S. A., Daneback, K., Tikkanen, R., & Ross, M. W. (2003). Internet sexuality in Scandinavia. Sexual and Relationship Therapy, 18, 277-291.
Corley, M. D., & Hook, J. N. (2012). Women, female sex and love addicts, and use of the Internet. Sexual Addiction & Compulsivity, 19, 53-76. http://dx.doi.org/10.1080/10720162.2012.660430
Couch, D. (2008). Online dating and mating: The use of the Internet to meet sexual partners. Qualitative Health Research, 18, 268-279. http://dx.doi.org/10.1177/1049732307312832
Daneback, K., Cooper, A., & Månsson, S. A. (2005). An Internet study of cybersex participants. Archives of Sexual Behavior, 34, 321-328. http://dx.doi.org/10.1007/s10508-005-3120-z
Daneback, K., Månsson, S. A., & Ross, M. W. (2007). Using the Internet to find offline sex partners. CyberPsychology & Behavior, 10, 100-107. http://dx.doi.org/10.1089/cpb.2006.9986
Delmonico, D. L. (1997). Internet Sex Screening Test. Retrieved from: http://www.sexhelp.com
Delmonico, D. L., & Miller, J. A. (2003). The Internet Sex Screening Test: A comparison of sexual compulsives versus non-sexual compulsives. Sexual and Relationship Therapy, 18, 261-276. http://dx.doi.org/10.1080/1468199031000153900
Döring, N. M. (2009). The Internet’s impact on sexuality: A critical review of 15 years of research. Computers in Human Behavior, 25, 1089-1101. http://dx.doi.org/10.1016/j.chb.2009.04.003
Goodson, P., McCormick, D., & Evans, A. (2000). Sex and the Internet: A survey instrument to assess college students’ behavior and attitudes. CyberPsychology & Behavior, 3, 129–149. http://dx.doi.org/10.1089/109493100315987
Goodson, P., McCormick, D., & Evans, A. (2001). Searching for sexually explicit materials on the Internet: An exploratory study of college students’ behavior and attitudes. Archives of Sexual Behavior, 30, 101-118. http://dx.doi.org/10.1023/A:1002724116437
Green, B. A., Carnes, S., Carnes, P. J., & Weinman, E. A. (2012). Cybersex addiction patterns in a clinical sample of homosexual, heterosexual, and bisexual men and women. Sexual Addiction & Compulsivity, 19, 77-98. http://dx.doi.org/10.1080/10720162.2012.658343
Grov, C., Gillespie, B. J., Royce, T., & Lever, J. (2011). Perceived consequences of casual online sexual activities on heterosexual relationship: A U.S. online survey. Archives of Sexual Behavior, 40, 429-439. http://dx.doi.org/10.1007/s10508-010-9598-z
Grubbs, J. B., Sessoms, J., Wheeler, D. M., & Volk, F. (2010). The Cyber-pornography use inventory: The development of a new assessment instrument. Sexual Addiction & Compulsivity, 17, 106–126. http://dx.doi.org/10.1080/10720161003776166
McKenna, K. Y. A., Green, A. S., & Smith, P. K. (2001). Demarginalizing the sexual self. The Journal of Sex Research, 38, 302-311. http://dx.doi.org/10.1080/00224490109552101
Mitchell, K. J., Becker-Blease, K. A., & Finkelhor, D. (2005). Inventory of problematic Internet experiences encountered in clinical practice. Professional Psychology: Research & Practice, 36, 498-509. http://dx.doi.org/10.1037/0735-7028.36.5.498
Mitchell, K. J., Finkelhor, D., Wolak, J., Ybarra, M. L., & Turner, H. (2011). Youth Internet victimization in a broader victimization context. Journal of Adolescent Health, 48, 128-34. http://dx.doi.org/10.1016/j.jadohealth.2010.06.009
Mitchell, K. J., Sabina, C., Finkelhor, D., & Wells, M. (2009). Index of problematic online experiences: item characteristics and correlation with negative symptomatology. CyberPsychology & Behavior, 12, 707-711. http://dx.doi.org/10.1089=cpb.2008.0317
Mustanski, B., Lyons, T., & Garcia, S. C. (2011). Internet use and sexual health of young men who have sex with men: A mixed-methods study. Archives of Sexual Behavior, 40, 289-300. http://dx.doi.org/10.1007/s10508-009-9596-1
Ross, M. W. (2005). Typing, doing, and being: Sexuality and the Internet. The Journal of Sex Research, 42, 342-352. http://dx.doi.org/10.1080/00224490509552290
Ross, M. W., Daneback, K., Månsson, S. A.,Tikkanen, R., & Cooper, A. (2003). Characteristics of men and women who complete or exit from an on-line Internet sexuality questionnaire: A study of instrument dropout biases. The Journal of Sex Research, 40, 396-402. http://dx.doi.org/10.1080/00224490209552205
Ross, M. W., Månsson, S. A., & Daneback, K. (2012). Prevalence, severity, and correlates of problematic sexual Internet use in Swedish men and women. Archives of Sexual Behavior, 41, 459-466. http://dx.doi.org/10.1007/s10508-011-9762-0
Schroder K. E. E., Carey M. P., & Vanable, P. A. (2003). Methodological challenges in research on sexual risk behavior: II. Accuracy of self-reports. Ann Behav Med, 26, 104–123. http://dx.doi.org/10.1207/S15324796ABM2602_03
Shaughnessy, K., Byers, E. S., & Walsh, L. (2011). Online sexual activity experience of heterosexual students: Gender similarities and differences. Archives of Sexual Behavior, 40, 419-427. http://dx.doi.org/10.1007/s10508-010-9629-9
Valkyrie, Z. C. (2011). Cybersexuality in MMORPGs: Virtual sexual revolution untapped. Men and Masculinities, 14, 76-96. http://dx.doi.org10.1177/1097184X10363256/
Velezmoro, R., Negy, C., & Livia, J. (2012). Online sexual activity: Cross-national comparison between United States and Peruvian college students. Archives of Sexual Behavior, 41, 1015–1025. http://dx.doi.org/10.1007/s10508-011-9862-x
Waskul, D. D. (2002). The naked self: Being a body in televideo cybersex. Symbolic Interaction, 25, 199–227. http://dx.doi.org/10.1525/si.2002.25.2.199
Sapienza, University of Rome
Via di Grottarossa 1035-1037
Phone: 0039 3484454786