Cyberporn use and Rape Myths Acceptance: Are we dealing with risky associations?

The literature reported links between pornography and Rape Myths Acceptance (RMA). The most exposed participants to pornography would be desensitized by its content and minimize rape and violence against women. Studies associating cyberporn use and RMA remain scarce. Few studies have linked compulsive cyberporn use to RMA, or to attraction to particular pornographic images, or to moral incongruence related to cyberporn use. This study aimed to explore links between RMA and compulsive cyberporn including arousing pornographic styles and pornography moral perception (moral incongruence) in a cyberporn users sample. The sample comprised 1584 participants (1000 men; 557 women; 27 non-binary). Participants completed the Compulsive Internet Use Scale adapted to cyberporn use, Acceptance of Modern Myths about Sexual Aggression scale, and answered questions about their amount and frequency of use, preferences, and moral perception of pornography. We conducted Bravais-Pearson and Chi-Square correlations, k-means nonhierarchical clustering, and Student's t-test. We identified two types of cyberporn user, "low-risk" and "highrisk". Compared to the low-risk group, the high-risk group had higher rape myth acceptance scores, were more aroused by scenes depicting domination, humiliation, submission, and young people, had higher compulsive cyberporn use scores, spent more time and had more frequent use of cyberporn. Analysis showed that men in the high-risk group had a stronger negative moral perception of pornography than men in the low-risk group. We also found that some pornographic styles had stronger associations with compulsive cyberporn use and RMA. The present study provides current data on cyberporn use and its association with RMA. Further studies should explore variables mediating these relationships

Compulsive cyberporn and relationships with coercive sexual manipulation: Is there any risky association

International audienceCyberporn seems to be more addictive than other classic porn supports (e.g. magazines). Beyond its addictive risk, it would be linked to the highlighting of sexual performances without consideration of relationships and human encounters. The literature showed associations between cyberporn and the attitudes, beliefs, and sexual preferences of its users. Women most exposed to porn videos appear to be more likely to normalize rapes and violence against women. Research demonstrated that users of pornographic material are more likely to commit sexual assault. These observations invite us to think about Rape Myths Acceptance (RMA), sexual consent, and their place in the practices of compulsive cyberporn users. This study aimed to explore links between compulsive cyberporn use, RMA, and Relationships with Coercive Sexual Manipulation (RCSM), committed and endured, in a cyberporn users sample. The sample was constituted of 1584 participants (1000 men; 557 women; 27 non-binary). Participants were assessed using Compulsive Internet Use Scale adapted to cyberporn use, Acceptance of Modern Myths about Sexual Aggression scale, and Sexual Experiences Survey. We used Student's t-test, Bravais-Pearson simple correlations, Spearman correlations, and Mann-Whitney test. Results showed that compared to men with no committed RCSM, men with committed RCSM presented more compulsive cyberporn use and greater RMA. Women with committed RCSM presented more RMA and no difference in cyberporn use compared to women with no committed RCSM. Participants with endured RCSM did not present any difference compared to those with no endured RCSM. These results reveal links that should be more investigated through sexual and psychological variables in future research

Female cybersex users: What characteristics of sexual motivations and personality traits?

Cybersex includes all observable sexual activities, practiced on the Internet and dedicated to sexual gratification. It includes sex chats, online sex games, pornography consumption, etc. Cybersex could shift towards a compulsive use that would impact the quality and satisfaction of life of its followers. The aim of this research is to explore the profile of female cybersex users in the general population through their sexual motivations, their personality traits, and their quality and satisfaction of life. We recruited 293 women with a mean age of 23.60 (75.73% were heterosexual, 2.20% were homosexual, and 22.05% were bisexual). The majority were in a relationship. The questionnaire included the Compulsive Internet Use Scale adapted to cybersex, the Sexual Functions Scale, the Big Five Inventory-10-Fr, the General Health Questionnaire and the Life Satisfaction Scale. We used k-means cluster analysis, ANOVA, Bravais-Pearson simple correlations, and Pearson chi-squares. We distinguished (a) a cluster with women having low cybersex use, low scores in psychiatric disorders and better life satisfaction, and (b) a cluster with women with high cybersex use, high scores in psychiatric disorders and lower life satisfaction. Women with high cybersex use appear to be characterized by sexual motivations of novelty, dominance, recognition, and conformity, lower extraversion and conscientiousness traits, and greater neuroticism. The characteristics of female cybersex users remain poorly investigated. We provided results that allow the understanding of their profiles in terms of sexual motivations and personality traits. Further studies should be considered to complete our findings

Autour de sexualité et consentement

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Impacts of Sexual Desire and Motives on the Compulsive use of Cybersexuality

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Strength of Pornography Craving Experience (PCE-S): The validation of a new specific measure

Pornography use remains a common sexual activity with potentially addictive use in part of some people. Even though craving is being recognized as an important characteristic of addictive behaviors, we note a lack of a specific validated instrument measuring the pornography craving experience. The present study aimed at adapting and validating an instrument measuring the users' strength of pornography craving experience (PCE-S). Items from the "strength" part of the Craving Experience Questionnaire (CEQ) were adapted to pornography use and used to create the PCE-S. The PCE-S was then administered online to 1584 Englishspeaking participants aged 18 to 75 years old (M = 33.18; SD = 10.84]; 63.1% male, 35.2% female, and 1.7% non-binary). All participants completed an assessment of the Compulsive Cyberporn Use (CIUS adapted for cyberporn). Confirmatory factorial analysis (CFA) was used to examine the construct structure validity; Cronbach alpha coefficient, corrected itemtotal correlation, and discriminant analysis were used to assess the instrument's psychometric properties. After using the modification indices to improve the initial model, a relatively good fit for the three-factor model was confirmed. Concurrent validity with the compulsive cyberporn use (CCU) measure was demonstrated. The PCE-S discriminated between participants with high CCU scores and others with low CCU scores. A specific pornography craving experience instrument scale, based on the Elaborated Intrusion theory of desire seems to capture key constructs of the theory and correlate with measures of compulsive cyberporn use

Smartphone apps for mental health and wellbeing: A usage survey and machine learning analysis of psychological and behavioral predictors

Objective Despite the availability of thousands of mental health applications, the extent to which they are used and the factors associated with their use remain largely unknown. The present study aims to (a) assess in a representative US-based population sample the use of smartphone apps for mental health and wellbeing (SAMHW), (b) determine the variables predicting the use of SAMHW, and (c) explore how a set of variables related to mental health, smartphone use, and smartphone “addiction” may be associated with the use of SAMHW. Methods Data was collected via online questionnaire from 1989 adults. The data gathered included information on smartphone use behavior, mental health, and the use of SAMHW. Latent class analysis was used to categorize participants. Machine learning and logistic regression analyses were used to determine the most important predictors of SAMHW use and associations between predictors and outcome variables. Results While two-thirds of participants had a statistically high probability for using SAMHW, nearly twice more had high probability for using them to improve wellbeing compared to using them to address mental health problems (43% vs. 18%). In both groups, these participants were more likely to be female and in the younger adult age bracket than male and in the adult or older adult age bracket. According to the machine learning model, the most important predictors for using the relevant smartphone apps were variables associated with smartphone problematic use, COVID-19 impact, and mental health problems. Conclusion Findings from the present study confirm that the use of SAMHW is growing, particularly among younger adult and female individuals who are negatively impacted by problematic smartphone use, COVID-19, and mental health problems. These individuals tend to bypass traditional care via psychotherapy or psychopharmacology, relying instead on smartphones to address mental health conditions or improve wellbeing. Advising users of these apps to also seek professional help and promoting efforts to prove the efficacy and safety of SAMHW would seem necessary

Assessment of the Popularity and Perceived Effectiveness of Smartphone Tools That Track and Limit Smartphone Use: Survey Study and Machine Learning Analysis.

International audienceBACKGROUND: Problematic smartphone use, like problematic internet use, is a condition for which treatment is being sought on the web. In the absence of established treatments, smartphone-provided tools that monitor or control smartphone use have become increasingly popular, and their dissemination has largely occurred without oversight from the mental health field. OBJECTIVE: We aimed to assess the popularity and perceived effectiveness of smartphone tools that track and limit smartphone use. We also aimed to explore how a set of variables related to mental health, smartphone use, and smartphone addiction may influence the use of these tools. METHODS: First, we conducted a web-based survey in a representative sample of 1989 US-based adults using the crowdsourcing platform Prolific. Second, we used machine learning and other statistical tools to identify latent user classes; the association between latent class membership and demographic variables; and any predictors of latent class membership from covariates such as daily average smartphone use, social problems from smartphone use, smartphone addiction, and other psychiatric conditions. RESULTS: Smartphone tools that monitor and control smartphone use were popular among participants, including parents targeting their children; for example, over two-thirds of the participants used sleep-related tools. Among those who tried a tool, the highest rate of perceived effectiveness was 33.1% (58/175). Participants who experienced problematic smartphone use were more likely to be younger and more likely to be female. Finally, 3 latent user classes were uncovered: nonusers, effective users, and ineffective users. Android operating system users were more likely to be nonusers, whereas younger adults and females were more likely to be effective users. The presence of psychiatric symptoms did not discourage smartphone tool use. CONCLUSIONS: If proven effective, tools that monitor and control smartphone use are likely to be broadly embraced. Our results portend well for the acceptability of mobile interventions in the treatment of smartphone-related psychopathologies and, potentially, non-smartphone-related psychopathologies. Better tools, targeted marketing, and inclusive design, as well as formal efficacy trials, are required to realize their potential