Next Article in Journal
Individual Difference Predictors of Attitudes toward Polyamorous Targets and Likelihood to Date a Polyamorous Partner in a Student Sample
Previous Article in Journal
The Dual-Pathway Model of Respect in Romantic Relationships
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sexes
Volume 5
Issue 3
10.3390/sexes5030025
sexes-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Gender Differences in Sexting and Its Association with Well-Being and Intimate Partner Violence Victimization from Adolescence to Old Age

by
M. Pilar Matud
Department of Clinical Psychology, Psychobiology and Methodology, Universidad de La Laguna, 38200 San Cristobal de La Laguna, Spain
Sexes 2024, 5(3), 335-350; https://doi.org/10.3390/sexes5030025
Submission received: 27 June 2024 / Revised: 23 July 2024 / Accepted: 19 August 2024 / Published: 30 August 2024
(This article belongs to the Section Sexual Behavior and Attitudes)
Browse Figures
Review Reports Versions Notes

Abstract

:
Research has shown that sexting is an increasingly common behavior, especially among teens and young adults. However, despite numerous studies, the relevance of sexting to people’s well-being is unclear. The present study seeks to determine the relevance of gender in sexting behavior and its association with psychological well-being and intimate partner violence victimization across the life cycle, from adolescence to old age. This study was cross-sectional, and the sample consisted of 6719 women and men from the general Spanish population who were assessed by six questionnaires measuring sexting behavior, psychological distress, psychological well-being, life satisfaction, self-esteem, and intimate partner violence victimization. The results showed that participation in sexting was higher in men than in women at all stages of the life cycle studied, although the differences were not statistically significant among adolescents. Greater sexting behavior was associated with greater intimate partner violence victimization, an association that was stronger for adolescents. And although the magnitude of the association was small, more sexting was also associated with greater psychological distress and lower psychological well-being in all age groups except older women. Our study results allow us to conclude that sexting behavior may pose risks to the well-being of citizens.

1. Introduction

Advances in communication technology have had a significant impact on people’s lives, including the sharing of sexually explicit or suggestive images, text, or video through electronic media, a phenomenon known as sexting. Sexting has been defined in different ways that vary in terms of the actions involved (receiving, sending, and forwarding), the types of media (images, text, and video), the sexual characteristics, and the modes of transmission [1,2]. Definitions range from very broad conceptualizations that include all types of visual and written content to specific definitions that include only a specific type of content [1,2], only the act of sending suggestive or sexually explicit images [3], or only the sending of self-made sexually explicit images [4,5]. Despite the diversity of definitions and its consideration as a multidimensional construct reflecting many types of sexting [6], sexting generally refers to the exchange of text messages and/or images with sexually suggestive or explicit content via mobile phones or the Internet [7,8,9,10,11,12,13].
The Internet and new communication technologies have become tools for socialization [1]. Many aspects of youth development, including sexual behavior, have been influenced by the advent of digital technology and Internet-connected smartphones [14]. Although it has been suggested that such tools are particularly valued by adolescents and young adults [3,15] as they become more accessible and easier to use, they are used by people of virtually all ages, and their use is nearly universal [16]. Smartphones allow people to have a mobile connection to the Internet, including websites, email, messaging services, and social media platforms [17] such as Facebook, Instagram, and WhatsApp. As a result, technology-mediated communication has become a popular form of interpersonal communication [10,15], including sexual and/or romantic relationships [16]. There is evidence that many people engage in sexual interactions through computer-mediated media, usually in the form of sexually explicit words, images, or videos [4,10,15].
There is no consensus on the prevalence of sexting [18,19], although many studies have been conducted, mostly among adolescents and young adults. It has been argued that it is a complex issue due to different conceptualizations and definitions of sexting [1,19]. Furthermore, the prevalence of sexting has increased in recent years [2,18] and varies by age [1,18,19,20,21] and method of sexting, with a higher prevalence on mobile devices compared to computers [18]. In addition, receiving sexts is more common than sending sexts [1,9,18,19]. And there is evidence that older age predicts greater sexting among adolescents but not adults [19]. In a systematic literature review of articles published between January 2000 and August 2013 [19], the estimated mean prevalence of sexting in studies of individuals aged 18 years or older was 53.31%, and 48.56% for sending sexts with photos. And in a meta-analysis of 18 studies published between 2012 and 2015, rates ranged from 0.9% to 60% [1]. In a meta-analysis of 39 studies conducted between 1990 and June 2016 with 110,380 participants under the age of 18, the mean prevalence of sending sexts was 14.8% and the mean prevalence of receiving sexts was 27.4% [18], with rates increasing with age. And in a meta-analysis of the prevalence of sexting among individuals aged 18–29 years, which included data from 18,122 individuals, the prevalence of sending was 38.3%, receiving was 41.5%, and reciprocal sexting was 47.7%, while the prevalence of nonconsensual forwarding of sexts was 15% [9].
Although it has been suggested that sexting can be considered a normal form of sexual experimentation and communication [4,9,22,23], and that for many adolescents it may serve as a first step toward experimenting with real-life sexual contact [2], and has become a normative behavior in which most college and high school students engage [22], there is evidence that it can also be a negative experience [7,12]. Some research has shown that sexting is associated with risky behaviors, including alcohol and drug use [7,24,25,26], and risky sexual behaviors [27], including unprotected sex and sex with multiple partners [3,7,25,26]. Results from studies that have examined the relationship between sexting behaviors and psychosocial outcomes have also been inconsistent. Although some studies have found no association between sexting and mental health (see the review by Doyle et al. [28]), other studies have found that sexting behaviors are associated with greater psychological distress and mental health symptomatology [7,19,20,26,29,30,31], as well as lower self-esteem [25]. Though research examining the relationship between sexting and well-being is sparse [19], research has found that sexting behaviors are associated with lower well-being [19] and that high sexting behaviors predict a decrease in positive emotions [29]. Sexting has also been associated with cyberbullying [29,32], intimate partner violence [8,27,33,34], and sexual violence [27,33,34,35], particularly when sexting is nonconsensual, and it has been suggested that coerced sexting may be a form of intimate partner violence [34].

Gender and Sexting

Research on the existence of gender differences in sexting behavior has yielded mixed results. Results from meta-analyses of the prevalence of sexting in adolescence and young adulthood have shown that while some of the studies analyzed found no differences in the prevalence of sexting between boys and girls, other studies found that girls were more likely to sext, while other studies found that boys were more involved in sexting [1,18,19]. However, the existence of differences between boys and girls in sexting behavior also depended on other variables, including the definition of sexting, the type of sexting, and the mode of transmission [1,7]. For example, a study by Lippman and Cambell [36] of adolescents aged 12–18 years found that although girls were not more likely to sext, they were more likely to be pressured to do so, especially by boys. However, another study found that consensual sexting was more common among boys than girls [7]. And while conduct problems were not significant predictors of sexting among boys, they were significant predictors of sexting among girls, being associated with a greater likelihood of sending, receiving, and forwarding sexts [37]. There is also evidence that adolescent boys have more positive attitudes toward sexting than girls, while girls have higher perceptions of the risks associated with receiving and forwarding sexts, and boys are more likely to forward received messages [38]. Differences have also been found in the effects of receiving sexts, which are more likely to be harmful to girls and have more negative consequences for girls than for adolescent boys [39,40,41]. However, the evidence is not complete, as the association between sexting and risk behaviors and mental health problems among high school students was found to be higher among boys than girls [7].
Gender has been proposed to be a central factor in sexting [40,41,42], influenced by the double standard of sexuality, which results in boys’ and girls’ sexual behavior being evaluated differently. Sexually active behavior and attitudes toward sexuality are evaluated positively for boys but negatively for girls. Applied to sexting, this results in girls being negatively evaluated and labeled when they send sexual images, experiencing negative consequences when such images become public, and experiencing a more negative impact on their reputations than boys [40]. While images of adolescent girls’ bodies in peer networks would be used to devalue and shame them, boys’ possession of such images would increase their popularity because they could “collect” them and show them to other boys [43]. It has been suggested that adolescent girls are more likely to be criticized for engaging in sexting, e.g., being labeled a “slut”, or not engaging in sexting, e.g., being labeled a “prude”, while boys are not subject to such criticism [36].
Although many studies have been conducted on sexting, its risk factors, and its association with mental health symptoms, most studies have focused on adolescents and young adults, and few studies have been conducted with adults [44]. Therefore, the main goal of the present study was to analyze sexting behavior across the life cycle, from adolescence to old age. This study was conducted from a gender perspective, so all data were analyzed and presented in a disaggregated way for women and men. Thus, the present study seeks to determine the relevance of gender in sexting behavior and its association with psychological well-being and intimate partner violence victimization across the life cycle, from adolescence to old age.

2. Materials and Methods

2.1. Participants and Procedure

This study was cross-sectional, and the sample consisted of 6719 people from the general Spanish population, of whom 2204 (32.8%) identified themselves as men and 4515 (67.2%) as women. Sampling was convenience-based, with data collected between 2 April 2021 and 31 July 2023. Although the COVID-19 pandemic persisted, most of the Spanish population was vaccinated, and there were virtually no social restrictions due to the pandemic. Initially, a total of 6795 people completed the online questionnaire, but 76 were excluded, 35 because they did not provide their age, 41 because they answered the gender question as “non-binary” (n = 31) or gender fluid (n = 8), and 2 because they did not want to provide their gender. Their ages ranged from 16 to 79 years, and they had different sociodemographic characteristics, as shown in Table 1, which presents the main characteristics of women and men, comparisons of the means of age and number of children, and the percentages of women and men in terms of education level, occupation, and marital status. As can be seen in Table 1, there was diversity in their level of education, although those with only basic education were in the minority (19.6% of men and 16.2% of women). There was also diversity in their occupation, although almost half (45.9% of men and 49.8% of women) were students. More than half (73.2% of men and 66.9% of women) had never been married or lived with their partner; 23.4% of men and 27.8% of women had been married and/or lived with their partner. Eighty-one percent of the men and 76% of the women had no children, with the number of children ranging from one to nine, although the most common number of children was two (12% of the total sample) or one (9.3% of the total sample). There were no statistically significant differences between women and men in terms of age, but there were differences in the other sociodemographic characteristics. Men were more likely than women to have a secondary education, to be employed, and to have never been married, while women were more likely than men to have a university education, to be a student, and to be married or living with a partner. In addition, the mean number of children was higher for women than for men.
Participation was voluntary and anonymous, and no incentives were offered to participants. Participants were recruited through the social networks of undergraduate and graduate students with training in psychological assessment and research who were trained to participate in data collection. These students shared the link to the questionnaire through their social networks and received credit for sharing the link after verifying that the tests had been completed. Participants who accessed the link were presented with the informed consent document and, if they consented, proceeded to the online questionnaire, first completing demographic information and then the six questionnaires described in the following section. The present study is part of a larger study on new technologies, violence, and psychological well-being and was approved by the Research Ethics and Animal Welfare Committee of the University of La Laguna (Registration Number CEIBA 2022-3130).

2.2. Measures

2.2.1. Sexting Behaviors

Sexting behaviors were assessed using the Spanish version [45] of the Sexting Behavior Scale [46]. The scale consists of 29 items that are scored on a 5-point Likert-type scale, with higher scores indicating more sexting. The 29 items are grouped into 3 factors: (1) Actual sexting participation, consisting of 9 items that collect information on the frequency of sending and receiving sexually provocative text messages or images via mobile phone, email, and/or social networking sites; (2) Active sexting disposition, consisting of 16 items that assess the individual’s disposition toward actively engaging in sexting by collecting data on the number of people with whom sexting is practiced, the type of relationship with the person (boyfriend, girlfriend, someone sexually attracted to the person, or friends), situations (e.g., “I sext when I am at home”, “I sext when I am bored”), and motivations (e.g., “I sext because I want to start dating”); (3) Emotional Expression in Sexting, consisting of 4 items that provide information about the feelings and emotions that sexting evokes in the person (e.g., “Sexting makes me feel embarrassed”, “Sexting makes me feel happy”). For the sample of the present study, the internal consistency (Cronbach’s alpha) of the 9 items of the actual sexting participation factor was 0.90, that of the 16 items of active sexting disposition was 0.91, and that of the 4 items of emotional expression in sexting was 0.54. The internal consistency of the 29 items comprising the total scale was 0.93.

2.2.2. Psychological Well-Being

Psychological well-being was assessed using the Flourishing Scale [47]. This is an 8-item scale that assesses broad and important aspects of positive psychosocial functioning, such as feelings of competence, positive relationships, engagement and interest, optimism, and meaning and purpose in life. Examples of items include “I lead a purposeful and meaningful life” and “I am optimistic about my future”. Each item is answered on a 7-point scale, and high scores indicate that the person feels positive about himself or herself positively in several important areas. In the present study, we used the Spanish translation of the Flourishing Scale, which is available on the website of the first author of this study. The Cronbach’s alpha for the current sample was 0.89.

2.2.3. Life Satisfaction

Life satisfaction was measured using the Satisfaction with Life Scale (SWLS) [48], a 5-item scale designed to assess the respondent’s satisfaction with life as a whole [49]. Examples of items include “In most ways my life is close to my ideal” and “I am satisfied with my life”. The response scale is a 7-point Likert scale, with higher scores indicating greater life satisfaction. In the present study, we used the Spanish translation of the SWLS, which is available on the website of the first author of the original study. The Cronbach’s alpha for the current sample was 0.88.

2.2.4. Self-Esteem

Self-esteem was measured using the Rosenberg Self-Esteem Scale (RSES) [50], a reliable measure of self-esteem whose validity has been supported in many countries [51]. It consists of ten items with statements about feelings of self-esteem and self-acceptance (e.g., “In general, I am satisfied with myself”) that assess global self-esteem. The response scale is four-point, with higher scores reflecting higher self-esteem. The internal consistency for the present study sample was 0.88.

2.2.5. Psychological Distress

Psychological distress was assessed using the Spanish version of the 12-item Goldberg General Health Questionnaire [52]. The GHQ-12 is a brief instrument that has been widely used to assess psychological distress [53,54]. Examples of items are “Lost much sleep over worry” and “Been losing confidence in yourself”. The items were scored using the Likert method, which assigns a weight from 0 to 3 to each score, with higher scores indicating greater psychological distress. In the current sample, the Cronbach’s alpha was 0.90.

2.2.6. Cyberviolence and Offline Intimate Partner Violence Victimization

Cyber and offline intimate partner violence victimization was assessed using the victimization version of the Cyber and Offline Intimate Partner Violence Questionnaire (COIPVQ, [55]). It consists of 23 items that assess behaviors of violence, abuse, and control of an intimate partner exercised in person (offline) and/or through the use of technologies and social networks (cyberviolence) and is structured into four scales: (1) face-to-face psychological violence, consisting of 6 items (e.g., “He/she has made fun of what you believe and/or what you say, think…”); (2) cyberviolence, consisting of 8 items (e.g., “He/she has posted and/or shared intimate photos or videos of you without your consent”); (3) physical violence, consisting of 7 items (e.g., “He/she has pushed you and/or grabbed you and/or pushed you away violently”); (4) sexual violence, consisting of 2 items (e.g., “He/she has forced you to do sexual acts that you did not want to do and/or did not like by using force or blackmail”). The response format is a 6-point Likert scale, with higher scores indicating greater frequency and intensity of violence. In the present study, the internal consistency (Cronbach’s alpha) of the 23 items that make up the total questionnaire was 0.94, that of the 6 items that assess face-to-face psychological violence was 0.87, that of the 8 items that assess cyberviolence was 0.86, that of the 7 items that assess physical violence was 0.90, and that of the 2 items that assess sexual violence was 0.83.

2.2.7. Demographics

Participants were asked to report their gender (with response options woman, man, other), age, education level, partnership status, number of children, and employment status.

2.3. Statistical Analysis

Descriptive analyses were conducted to determine the sociodemographic characteristics of the sample and the distribution of the study variables, as well as the frequency with which people engage in sexting behaviors. Comparisons between women and men on sociodemographic characteristics were performed using a t-test for continuous variables and chi-squared for categorical variables. Cronbach’s alpha coefficient was used to analyze internal consistency. Factorial analyses of variance (ANOVAs) were conducted to determine whether there were differences between women and men and between the different life cycle stages analyzed in both total sexting and the factors of actual sexting participation and active sexting disposition. The life cycle stages studied were as follows: (1) adolescence, which included individuals between the ages of 16 and 18; (2) youth, which included individuals between the ages of 19 and 25; (3) adulthood, which included individuals between the ages of 26 and 39; (4) midlife, which included individuals between the ages of 40 and 59; and (5) old age, which included individuals 60 years of age or older. The independent variables were gender (women, men) and age group (adolescence, youth, adulthood, midlife, old age). The dependent variables were scores on the actual sexting participation factor in the first ANOVA, scores on the active sexting disposition factor in the second ANOVA, and total sexting score in the third ANOVA. Bivariate associations between these sexting measures and the study variables were calculated using Pearson’s correlation coefficient, except for education level, which was calculated using Spearman’s Rho coefficient because it is an ordinal variable. The emotional expression in sexting factor was not included in the analyses because its internal consistency was very low (0.54), but the scores of the four items that comprise it are included in the total score of the scale because the internal consistency of the 23 items that comprise the scale was very high (0.93). Statistical analyses and graphs were performed using IBM SPSS Statistics for Windows, version 29.

3. Results

Descriptive analyses showed that most individuals (92.5% of men and 90.2% of women) had sent and/or received sexually provocative text messages or images via mobile phone, email, or social networking sites at least once in their lifetime. The percentage for receiving sexts was higher (91.5% of men and 89.1% of women) than for sending sexts (76.4% of men and 70.4% of women). Sexting behavior was statistically significantly (p < 0.001) and negatively associated with age (r = −0.26 for men and r = −0.38 for women) and with number of children (r = −0.22 for men and r = −0.33 for women) and positively associated with education level, although the effect size for education level was trivial (r = 0.06, p = 0.008 for men and r = 0.09, p < 0.001 for women). The analysis of the number of participants in each age group considered in the present study showed that 9.8% of the sample (9.1% of men and 10.1% of women) were adolescents (ages 16–18 years), 49.9% (51.5% of men and 49.1% of women) were young people (ages 19–25 years), 19.9% (20.7% of men and 19.5% of women) were in adulthood (ages 26–39 years), 17.2% (15.5% of men and 18.0% of women) were in midlife (ages 40–59 years), and 3.2% (3.2% of men and 3.2% of women) were classified as old age (ages 60–79 years).

3.1. Gender Differences in Sexting by Life Cycle Stage

Table 2 shows the main results of the ANOVAs with gender (women, men) and age group (adolescence, youth, adulthood, midlife, old age) as factors and the sexting measures as dependent variables. As can be seen, the Gender × Age Group interaction was only statistically significant when the dependent variable was the active sexting disposition factor (see Figure 1). In all analyses, the main effects of gender and age group were statistically significant. The effect size was small for gender and medium for age.
Post hoc analyses with the Games–Howell adjustment showed the existence of statistically significant differences (p < 0.001) between women and men on the active sexting disposition factor in all age groups except adolescents (p = 0.38) and older adults (p = 0.94). As seen in Figure 1, men had higher scores than women in all age groups. Young men had the highest scores on the Actual sexting participation factor, with differences that were statistically significant for all groups except adult men. Adult men also scored higher than all other groups except young men, with statistically significant differences except for adolescent boys (p = 0.18). In addition, adolescent boys scored higher than older and midlife men and women. Young women scored higher than all other women and higher than midlife and older men. The scores of adolescent and adult women were very similar, and both groups scored higher than midlife and older women and men. In addition, midlife women’s scores were higher than those of older women (p = 0.03), and midlife men’s scores were higher (p < 0.001) than those of older women and men.
Figure 2 shows women’s and men’s scores on the actual sexting participation factor. Post hoc analyses with the Games–Howell adjustment showed the existence of statistically significant differences (p < 0.001) between women and men in all age groups except adolescents (p = 0.78). As seen in Figure 2, men scored higher than women. Young men scored highest on this factor, and the differences were statistically significant for all groups except adolescents (p = 0.06) and adult men (p = 0.41). Adult men also scored higher than all other groups except adolescent men and young men and women. Adolescent men and women scored higher than older and midlife men and women. Young women scored higher than all other groups except young, adolescent, and adult men. Adult women scored higher than midlife and older women and men, and midlife men scored higher than older women and men, while midlife women only scored higher than older women.
Figure 3 shows the total sexting score for women and men in the five age groups studied. Post hoc analyses with the Games–Howell adjustment revealed statistically significant differences (p < 0.001) between women and men in all age groups except adolescents (p = 0.42) and older adults (p = 0.06). As shown in Figure 3, men scored higher than women. Young men scored higher than all other groups except adult men (p = 0.95). Adult men also scored higher than all other groups except adolescent men and young men. Adolescent men and women scored higher than midlife and older men and women. Young women scored higher than all women and higher than midlife and older men. Adult women scored higher than midlife and older women and men, and midlife men scored higher than older women and men, while midlife women scored higher than older women.

3.2. Bivariate Associations of Sexting with Study Variables for Women and Men

Table 3 shows the results of the bivariate correlations between the three measures of sexting and the study variables in the adolescent group, disaggregated by gender. As can be seen, for both genders, more sexting behavior is associated with greater victimization by intimate partner violence, both cyber and offline psychological violence, physical violence, and sexual violence, although the magnitude of the association with sexual violence is smaller for girls. Table 3 also highlights that the magnitude of the association between all types of intimate partner violence with active sexting and total sexting is greater for boys, where some of the correlation coefficients are large, than for girls. Although the effect size is small, more sexting is also associated with lower psychological well-being and more psychological distress. In addition, for girls, more sexting behaviors are also associated with lower life satisfaction.
Table 4 presents the results of the bivariate correlations between the three measures of sexting and the study variables for the youth group, disaggregated by gender. Again, for this age group, more sexting behavior is associated with greater victimization by both cyberviolence and offline psychological intimate partner violence, as well as physical and sexual violence, although the effect size is small, especially for girls. Some statistically significant correlation coefficients are also observed between all measures of sexting and psychological distress, psychological well-being, and life satisfaction, but the effect size is very small, and in some cases negligible. Nevertheless, there is some tendency for greater psychological distress and lower psychological well-being among young people who engage in more sexting behaviors.
Table 5 presents the results of the bivariate correlations between the three measures of sexting and the study variables for the adult group, disaggregated by gender. As can be seen, although the magnitude of the association is small, more sexting behavior is associated with greater total, cyberviolence and offline psychological intimate partner violence victimization. More sexting is also associated with greater physical violence victimization, except in the case of actual sexting participation for men. The results in Table 5 also show that the strongest association between intimate partner violence and sexting is in men’s active sexting disposition, which is associated with all types of intimate partner violence victimization, although the effect size of the association is small. In addition, for both genders, greater actual sexting participation is associated with lower self-esteem and greater psychological distress, as well as lower life satisfaction for women, although the effect size of the association is small.
Table 6 shows the bivariate correlation coefficients between the three measures of sexting and the study variables for the midlife group, disaggregated by gender. As can be seen, more sexting behavior is associated with greater intimate partner violence victimization, except in the case of women’s active sexting disposition. Actual sexting participation is the factor most strongly associated with more intimate partner violence victimization, also highlighting that the association between sexting and intimate partner violence victimization is stronger for men than for women. For both women and men, more sexting is associated with greater psychological distress, lower psychological well-being, and lower life satisfaction. It is also associated with lower self-esteem for women, although the magnitude of the association is small.
Table 7 shows the bivariate correlation coefficients between the three measures of sexting and the study variables for the older group, disaggregated by gender. As can be seen, there is only one statistically significant correlation coefficient among women, indicating that women with a more active sexting disposition report more cyberviolence from their intimate partner. For men, most of the correlation coefficients between sexting and intimate partner violence are equal to or greater than 0.20, although they are not statistically significant due to the small sample size of older men who participated in this study. Nevertheless, the data suggest that for older men, more sexting is associated with greater intimate partner violence victimization and greater psychological distress.

4. Discussion

The present study aimed to analyze gender differences in sexting behavior across the life cycle, from adolescence to old age. It also sought to determine the relevance of sexting to intimate partner violence, psychological distress, and psychological well-being for women and men at different stages of the life cycle. The definition of sexting considered in this study is very broad and was measured using a scale that allowed us to obtain three measures: (1) actual participation in sexting, which assesses the frequency with which sexually provocative text messages or images are sent or received via mobile phone, email, and/or social networks; (2) active sexting disposition, which assesses the number of people with whom sexts have been exchanged, the frequency with which sexting is done with different people, and the situations and motivations involved in sexting; (3) total score, which includes the sum of both factors plus four items that collect information about the effects of sexting behavior on the person who engages in it.
The overall analysis of the presence of sexting in the sample studied showed that most participants had ever sent or received a sext, with receiving being more common than sending, findings consistent with those of previous studies [1,9,18,19]. Recent research in other countries has also found that most respondents had received or sent a sext [12,22,56], with a higher prevalence of sexting than in previous studies [22,56], suggesting that sexting is an increasingly common behavior in the population.
An analysis of sending and/or receiving sext across the life cycle showed that this behavior was more common among men than women, with statistically significant differences in all stages examined except adolescence. Although the evidence on gender differences in sexting prevalence is inconclusive [1,11,18,19], studies of adults in other countries have also found that sexting is more common among men than women [56]. Studies of emerging adults have also found that sexting is more common among men than women [20]. In the current study, the highest prevalence of sexting was among young people (between 19 and 25 years of age), which is consistent with previous research [9,18,19,21]. Although the differences varied slightly depending on the type of measure considered (actual participation in sexting, active sexting disposition, and total sexting), the prevalence of sexting behavior among women and men varied across the life cycle, increasing during youth relative to adolescence, decreasing slightly among men and more markedly among women during adulthood, and decreasing significantly during midlife and old age, with sexting being less common in these two life stages. And although the differences between women and men were statistically significant for actual participation in sexting in old age, there were no statistically significant differences for active sexting disposition and total sexting.
While it has been argued that sexting may be a normal form of sexual experimentation and communication [4,9,22,23,44], and may positively influence adults’ romantic relationships [10], the association found in the present study between sexting and intimate partner violence, as well as measures of psychological distress and well-being, cautions against the risk of sexting. While it has been suggested that the risk of sexting for sexual behavior and its negative psychological correlates [7,19,20,25,26,29,30,31] may not be real for older people [57], the present findings do not support this assertion.
Although the magnitude of the association varied and was small for most age groups, more sexting was associated with more intimate partner violence victimization at all stages of the life cycle examined, findings consistent with those of previous research [8,27,33,34,35,40,58,59]. This association was stronger among adolescents, where sexting behavior was found to be associated with more total intimate partner violence victimization and was statistically significantly associated with victimization by all types of intimate partner violence examined: cyberviolence, offline psychological violence, physical violence, and sexual violence. Although the magnitude of the association varied according to the measure of sexting considered and the type of violence, it is noteworthy that the association between sexting and sexual violence was stronger for adolescent boys than for girls. Also, the association between active sexting disposition and intimate partner violence victimization was stronger for boys than for girls. Although the reason for this may be unknown, studies in Spain found that adolescent girls were more aware than boys of the risk associated with sending and/or receiving sexts [38], which could explain this lower association between sexting and intimate partner violence victimization among girls than among boys. This is a hypothesis that should be tested in future research.
Even though the strength of the association was smaller than in adolescence and varied slightly depending on the type of intimate partner violence considered, the measure of sexting, and the life cycle stage, the results of the present study showed that more sexting was associated with greater intimate partner violence victimization at all life cycle stages examined, except for older women. Among older women, sexting was independent of the intimate partner, although a more active sexting disposition was associated with greater intimate partner cyberviolence. In addition, among older women, sexting was independent of psychological distress and well-being, as well as women’s self-esteem. Although the reasons why sexting is less associated with negative outcomes among older women are unknown, it is important to keep in mind that this group had the lowest sexting scores, and it may be that sporadic involvement in sexting does not have negative consequences. Alternatively, it may be that older women are more mature and have greater control over romantic relationships and their outcomes, hypotheses that should be tested in future research.
While the strength of the association between sexting and psychological distress was low or very low and varied slightly across age groups, except among older women, more sexting was associated with lower well-being and greater psychological distress among women and men. It was also associated with lower life satisfaction among midlife women and men, adolescent girls, and adult women. These findings are consistent with other studies that have found sexting to be associated with more psychological symptomatology and lower well-being [7,20,29,30,31,34]. In addition, sexting participation was associated with lower self-esteem among adult women and midlife women, which is consistent with other studies that have found sexting to be associated with lower self-esteem [25,60], and that its effects are greater among women than men [39,40,41], as it is more associated with lower self-esteem and life satisfaction among women.
There are several limitations to this study. The first is that it is a cross-sectional study, and therefore, cause–effect relationships cannot be established. Although the sample was large, it was a convenience sample; in addition, the number of men, although large (n = 2204), was much smaller than the number of women, and men made up only 32.8% of the total sample. In addition, the numbers of people in each age group were uneven, with much fewer older people, which affects the power to detect statistically significant effects. There may also be cohort effects; because different age groups are being compared, the different groups are from different generations (cohorts), with different backgrounds, technological experiences, and educational environments. Thus, the differences found cannot be attributed solely to developmental stage. Furthermore, although several measures of sexting were used, they did not distinguish between consensual and nonconsensual sexting. In addition, it is worth considering the difficulties of measuring sexting with questionnaires developed primarily for young people, with content that may not be as relevant to adults or older people. Finally, there were no measures of variables that other studies have shown to be positively associated with sexting, such as partner sexual satisfaction.
It is recommended that future studies be conducted longitudinally, with probability samples of similar size of women and men, as well as different age groups, and assess sexting with measures that distinguish between consensual and nonconsensual sexting. Developing more appropriate measures for cross-age comparisons may also be a line of future research. Given the evidence brought by this paper on the relevance of sexting beyond youth, it is warranted to advance measurement by considering different developmental stages.

5. Conclusions

Sexting is a widespread behavior in the Spanish population that is present throughout the life cycle, from adolescence to old age, being particularly prevalent among young men and women and decreasing with age for both genders. Participation in sexting is higher among men than among women at all stages of the life cycle, although the differences are not statistically significant among adolescents.
Sexting is associated with greater victimization by intimate partner violence, an association that is stronger for adolescents than for the other stages of the life cycle. Although the magnitude of the association is small, more sexting is also associated with greater psychological distress and lower psychological well-being in all age groups, except for older women, perhaps because this is the group with the lowest sexting practice. The results of our study allow us to conclude that sexting may constitute a risk to the well-being of both women and men.

Funding

This research received no external funding.

Institutional Review Board Statement

This study was conducted in accordance with the Declaration of Helsinki and approved by the Ethics Committee of the University of La Laguna (protocol code CEIBA 2022-3130, 7 February 2022).

Informed Consent Statement

Informed consent was obtained from all subjects involved in this study.

Data Availability Statement

Data supporting the conclusions of this study are available from the author upon request.

Conflicts of Interest

The author declares no conflicts of interest.

References

  1. Barrense-Dias, Y.; Berchtold, A.; Surís, J.C.; Akre, C. Sexting and the Definition Issue. J. Adolesc. Health 2017, 61, 544–554. [Google Scholar] [CrossRef]
  2. Van Ouytsel, J.; Walrave, M.; De Marez, L.; Vanhaelewyn, B.; Ponnet, K. Sexting, pressured sexting and image-based sexual abuse among a weighted-sample of heterosexual and LGB-youth. Comput. Hum. Behav. 2021, 117, 106630. [Google Scholar] [CrossRef]
  3. Benotsch, E.G.; Snipes, D.J.; Martin, A.M.; Bull, S.S. Sexting, substance use, and sexual risk behavior in young adults. J. Adolesc. Health 2013, 52, 307–313. [Google Scholar] [CrossRef]
  4. Van Ouytsel, J.; Walrave, M.; De Marez, L.; Vanhaelewyn, B.; Ponnet, K. A first investigation into gender minority adolescents’ sexting experiences. J. Adolesc. 2020, 84, 213–218. [Google Scholar] [CrossRef]
  5. Van Ouytsel, J.; Dhoest, A. The prevalence, context and perceptions of sexting among non-heterosexual men from various generations in Belgium. Comput. Hum. Behav. 2022, 126, 107031. [Google Scholar] [CrossRef]
  6. Kokkinos, C.M.; Krommida, C.; Markos, A.; Voulgaridou, I. A Latent Profile Analysis of Greek University Students’ Sexting Profiles: Associations with Big Five Personality Traits. Arch. Sex. Behav. 2024, 53, 1129–1140. [Google Scholar] [CrossRef]
  7. Frankel, A.S.; Bass, S.B.; Patterson, F.; Dai, T.; Brown, D. Sexting, Risk Behavior, and Mental Health in Adolescents: An Examination of 2015 Pennsylvania Youth Risk Behavior Survey Data. J. Sch. Health 2018, 88, 190–199. [Google Scholar] [CrossRef]
  8. Morelli, M.; Bianchi, D.; Baiocco, R.; Pezzuti, L.; Chirumbolo, A. Not-allowed sharing of sexts and dating violence from the perpetrator’s perspective: The moderation role of sexism. Comput. Hum. Behav. 2016, 56, 163–169. [Google Scholar] [CrossRef]
  9. Mori, C.; Cooke, J.E.; Temple, J.R.; Ly, A.; Lu, Y.; Anderson, N.; Rash, C.; Madigan, S. The prevalence of sexting behaviors among emerging adults: A meta-analysis. Arch. Sex. Behav. 2020, 49, 1103–1119. [Google Scholar] [CrossRef]
  10. Coduto, K.D. Theorizing Interpersonal and Technological Dimensions of Privacy in the Exchange of Sexual Communication. Sexes 2024, 5, 71–84. [Google Scholar] [CrossRef]
  11. Rice, E.; Craddock, J.; Hemler, M.; Rusow, J.; Plant, A.; Montoya, J.; Kordic, T. Associations between Sexting Behaviors and Sexual Behaviors Among Mobile Phone-Owning Teens in Los Angeles. Child Dev. 2018, 89, 110–117. [Google Scholar] [CrossRef]
  12. Schokkenbroek, J.M.; Ponnet, K.; Van Ouytsel, J.; Walrave, M.; Hardyns, W. Receive, forward, repeat: The link between sexting intention, sexting attitudes, and non-consensual sexting behaviours. Telemat. Inform. 2023, 84, 102036. [Google Scholar] [CrossRef]
  13. Barroso, R.; Ramião, E.; Figueiredo, P.; Araújo, A.M. Abusive Sexting in Adolescence: Prevalence and Characteristics of Abusers and Victims. Front. Psychol. 2021, 12, 610474. [Google Scholar] [CrossRef]
  14. Dodaj, A.; Prijatelj, K.; Kuterovac Jagodić, G. Sexting Behavior Among Youths: Nature, Determinants, and Consequences. Psihol. Teme 2024, 33, 171–189. [Google Scholar] [CrossRef]
  15. Drouin, M.; Tobin, E. Unwanted but consensual sexting among young adults: Relations with attachment and sexual motivations. Comput. Hum. Behav. 2014, 31, 412–418. [Google Scholar] [CrossRef]
  16. Montanaro, E.; Temple, J.; Ersoff, M.; Jules, B.; Jaliawala, M.; Kinkopf, D.; Webb, S.; Moxie, J. “Just lmk WhenYouWanttoHaveSex”: An Exploratory–Descriptive Qualitative Analysis of Sexting in Emerging Adult Couples. Sexes 2024, 5, 9–30. [Google Scholar] [CrossRef]
  17. Courtice, E.L.; Shaughnessy, K. Four Problems in Sexting Research and Their Solutions. Sexes 2021, 2, 415–432. [Google Scholar] [CrossRef]
  18. Madigan, S.; Ly, A.; Rash, C.L.; Van Ouytsel, J.; Temple, J.R. Prevalence of Multiple Forms of Sexting Behavior Among Youth: A Systematic Review and Meta-analysis. JAMA Pediatr. 2018, 172, 327–335. [Google Scholar] [CrossRef]
  19. Klettke, B.; Hallford, D.J.; Mellor, D.J. Sexting prevalence and correlates: A systematic literature review. Clin. Psychol. Rev. 2014, 34, 44–53. [Google Scholar] [CrossRef]
  20. Gámez-Guadix, M.; de Santisteban, P. “Sex Pics?”: Longitudinal Predictors of Sexting Among Adolescents. J. Adolesc. Health 2018, 63, 608–614. [Google Scholar] [CrossRef]
  21. Choi, H.J.; Mori, C.; Van Ouytsel, J.; Madigan, S.; Temple, J.R. Adolescent Sexting Involvement over 4 Years and Associations with Sexual Activity. J. Adolesc. Health 2019, 65, 738–744. [Google Scholar] [CrossRef]
  22. Thorne, E.; Babchishin, K.M.; Fisico, R.; Healey, L. Sexting in Young Adults: A Normative Sexual Behavior. Arch. Sex. Behav. 2024, 53, 593–609. [Google Scholar] [CrossRef]
  23. Falconer, T.; Quinn-Nilas, C.; Milhausen, R. Body image self-consciousness, sexting, and sexual satisfaction among midlife Canadians. Can. J. Hum. Sex. 2022, 31, 46–63. [Google Scholar] [CrossRef]
  24. Temple, J.R.; Le, V.D.; van den Berg, P.; Ling, Y.; Paul, J.A.; Temple, B.W. Brief report: Teen sexting and psychosocial health. J. Adolesc. 2014, 37, 33–36. [Google Scholar] [CrossRef]
  25. Ybarra, M.L.; Mitchell, K.J. “Sexting” and its relation to sexual activity and sexual risk behavior in a national survey of adolescents. J. Adolesc. Health 2014, 55, 757–764. [Google Scholar] [CrossRef]
  26. Mori, C.; Temple, J.R.; Browne, D.; Madigan, S. Association of Sexting with Sexual Behaviors and Mental Health among Adolescents: A Systematic Review and Meta-Analysis. JAMA Pediatr. 2019, 173, 770–779. [Google Scholar] [CrossRef]
  27. Clancy, E.M.; Howard, D.; Chong, S.; Klettke, B. Dream It, Do It? Associations between Pornography Use, Risky Sexual Behaviour, Sexual Preoccupation and Sexting Behaviours among Young Australian Adults. Sexes 2021, 2, 433–444. [Google Scholar] [CrossRef]
  28. Doyle, C.; Douglas, E.; O’Reilly, G. The outcomes of sexting for children and adolescents: A systematic review of the literature. J. Adolesc. 2021, 92, 86–113. [Google Scholar] [CrossRef]
  29. Alonso, C.; Romero, E. Sexting behaviour in adolescents: Personality predictors and psychosocial consequences in a one-year follow-up. Ann. Psychol. 2019, 35, 214–224. [Google Scholar] [CrossRef]
  30. Van Ouytsel, J.; Van Gool, E.; Ponnet, K.; Walrave, M. Brief report: The association between adolescents’ characteristics and engagement in sexting. J. Adolesc. 2014, 37, 1387–1391. [Google Scholar] [CrossRef]
  31. Chaudhary, P.; Peskin, M.; Temple, J.R.; Addy, R.C.; Baumler, E.; Shegog, R. Sexting and Mental Health: A School-Based Longitudinal Study among Youth in Texas. J. Appl. Res. Child. 2017, 8, 11. [Google Scholar] [CrossRef]
  32. Van Ouytsel, J.; Lu, Y.; Ponnet, K.; Walrave, M.; Temple, J.R. Longitudinal associations between sexting, cyberbullying, and bullying among adolescents: Cross-lagged panel analysis. J. Adolesc. 2019, 73, 36–41. [Google Scholar] [CrossRef]
  33. Titchen, K.E.; Maslyanskaya, S.; Silver, E.J.; Coupey, S.M. Sexting and Young Adolescents: Associations with Sexual Abuse and Intimate Partner Violence. J. Pediatr. Adolesc. Gynecol. 2019, 32, 481–486. [Google Scholar] [CrossRef]
  34. Drouin, M.; Ross, J.; Tobin, E. Sexting: A new, digital vehicle for intimate partner aggression? Comput. Hum. Behav. 2015, 50, 197–204. [Google Scholar] [CrossRef]
  35. Kobulsky, J.M.; Cederbaum, J.A.; Wildfeuer, R.; Grest, C.V.; Clarke, L.; Kordic, T. Comparing the prevalence of sexual behaviors and victimization among adolescents based on child welfare system involvement. Child Abus. Negl. 2022, 134, 105883. [Google Scholar] [CrossRef]
  36. Lippman, J.R.; Campbell, S.W. Damned If You Do, Damned If You Don’t… If You’re a Girl: Relational and Normative Contexts of Adolescent Sexting in the United States. J. Child. Media 2014, 8, 371–386. [Google Scholar] [CrossRef]
  37. Mariamo, A.; Martin-Storey, A.; Déry, M.; Tomasiello, M.; Temcheff, C.E. Conduct problems and sexting: Gender differences. Comput. Hum. Behav. 2024, 154, 108152. [Google Scholar] [CrossRef]
  38. Rodríguez-Castro, Y.; Alonso-Ruido, P.; González-Fernández, A.; Lameiras-Fernández, M.; Carrera-Fernández, M.V. Spanish adolescents’ attitudes towards sexting: Validation of a scale. Comput. Hum. Behav. 2017, 73, 375–384. [Google Scholar] [CrossRef]
  39. Livingstone, S.; Görziga, A. When adolescents receive sexual messages on the internet: Explaining experiences of risk and harm. Comput. Hum. Behav. 2014, 33, 8–15. [Google Scholar] [CrossRef]
  40. Wood, M.; Barter, C.; Stanley, N.; Aghtaie, N.; Larkins, C. Images across Europe: The sending and receiving of sexual images and associations with interpersonal violence in young people’s relationships. Child. Youth Serv. Rev. 2015, 59, 149–160. [Google Scholar] [CrossRef]
  41. Burén, J.; Holmqvist Gattario, K.; Lunde, C. What Do Peers Think About Sexting? Adolescents’ Views of the Norms Guiding Sexting Behavior. J. Adolesc. Res. 2022, 37, 221–249. [Google Scholar] [CrossRef]
  42. Reed, L.A.; Boyer, M.-P.; Meskunas, H.; Tolman, R.M.; Ward, L.M. How do adolescents experience sexting in dating relationships? Motivations to sext and responses to sexting requests from dating partners. Child. Youth Serv. Rev. 2020, 109, 104696. [Google Scholar] [CrossRef]
  43. Ringrose, J.; Harvey, L.; Gill, R.; Livingston, S. Teen girls, sexual double standards and ‘sexting’: Gendered value in digital image exchange. Fem. Theory 2013, 14, 305–323. [Google Scholar] [CrossRef]
  44. Macdowall, W.G.; Reid, D.S.; Lewis, R.; Perez, R.B.; Mitchell, K.R.; Maxwell, K.J.; Smith, C.; Attwood, F.; Gibbs, J.; Hogan, B.; et al. Sexting among British adults: A qualitative analysis of sexting as emotion work governed by ‘feeling rules’. Cult. Health Sex. 2023, 25, 617–632. [Google Scholar] [CrossRef] [PubMed]
  45. Chacón-López, H.; Romero-Barriga, J.F.; Aragón-Carretero, Y.; Caurcel-Cara, M.J. Construcción y validación de la Escala de Conductas sobre Sexting (ECS). Rev. Esp. Orientac. Psicopedag. 2016, 27, 99–115. [Google Scholar] [CrossRef]
  46. Dir, A.L.; Cyders, M.A.; Coskunpinar, A. From the bar to the bed via mobile phone: A first test of the role of problematic alcohol use, sexting, and impulsivity-related traits in sexual hookups. Comput. Hum. Behav. 2013, 29, 1664–1670. [Google Scholar] [CrossRef]
  47. Diener, E.; Wirtz, D.; Tov, W.; Kim-Prieto, C.; Choi, D.; Oishi, S.; Biswas-Diener, R. New well-being measures: Short scales to assess flourishing and positive and negative feelings. Soc. Indic. Res. 2010, 97, 143–156. [Google Scholar] [CrossRef]
  48. Diener, E.; Emmons, R.A.; Larsen, R.J.; Griffin, S. The Satisfaction with Life Scale. J. Pers. Assess. 1985, 49, 71–75. [Google Scholar] [CrossRef]
  49. Pavot, W.; Diener, E. Review of the Satisfaction with Life Scale. Psychol. Assess. 1993, 5, 164–172. [Google Scholar] [CrossRef]
  50. Rosenberg, M. Society and the Adolescent Self-Image; Princeton University Press: Princeton, NJ, USA, 1965. [Google Scholar]
  51. Monteiro, R.P.; de Holanda Coelho, G.L.; Hanel, P.H.P.; de Medeiros, E.D.; da Silva, P.D.G. The Efficient Assessment of Self-Esteem: Proposing the Brief Rosenberg Self-Esteem Scale. Appl. Res. Qual. Life 2022, 17, 931–947. [Google Scholar] [CrossRef]
  52. Goldberg, D.P.; Williams, P.; Lobo, A.; Muñoz, P.E. Cuestionario de Salud General GHQ (General Health Questionnaire). Guía Para el Usuario de las Distintas Versiones; Masson: Barcelona, Spain, 1996. [Google Scholar]
  53. Gnambs, T.; Staufenbiel, T. The structure of the General Health Questionnaire (GHQ-12): Two meta-analytic factor analyses. Health Psychol. Rev. 2018, 12, 179–194. [Google Scholar] [CrossRef] [PubMed]
  54. Idowu, O.M.; Adaramola, O.G.; Aderounmu, B.S.; Olugbamigbe, I.D.; Dada, O.E.; Osifeso, A.C.; Ogunnubi, O.P.; Odukoya, O.O. A gender comparison of psychological distress among medical students in Nigeria during the Coronavirus pandemic: A cross-sectional survey. Afr. Health Sci. 2022, 22, 541–550. [Google Scholar] [CrossRef] [PubMed]
  55. Matud, M.P. Cyber and Offline Intimate Partner Violence Questionnaire (COIPVQ); Unpublished Questionnaire; Department of Clinical Psychology, Psychobiology and Methodology, University of La Laguna: Santa Cruz de Tenerife, Spain, 2021. [Google Scholar]
  56. Brodie, Z.P.; Wilson, C.; Scott, G.G. Sextual Intercourse: Considering Social-Cognitive Predictors and Subsequent Outcomes of Sexting Behavior in Adulthood. Arch. Sex. Behav. 2019, 48, 2367–2379. [Google Scholar] [CrossRef]
  57. Currin, J.M.; Hubach, R.D.; Sanders, C.; Hammer, T.R. Sexting Leads to “Risky” Sex? An Analysis of Sexting Behaviors in a Nonuniversity-Based, Older Adult Population. J. Sex Marital. Ther. 2017, 43, 689–702. [Google Scholar] [CrossRef]
  58. Rodríguez-Castro, Y.; Martínez-Román, R.; Alonso-Ruido, P.; Adá-Lameiras, A.; Carrera-Fernández, M.V. Intimate Partner Cyberstalking, Sexism, Pornography, and Sexting in Adolescents: New Challenges for Sex Education. Int. J. Environ. Res. Public Health 2021, 18, 2181. [Google Scholar] [CrossRef]
  59. Couturiaux, D.V.R.; Young, H.; Anthony, R.E.; Page, N.; Lowthian, E.; Melendez-Torres, G.J.; Hewitt, G.; Moore, G.F. Risk Behaviours Associated with Dating and Relationship Violence among 11–16 Year Olds in Wales: Results from the 2019 Student Health and Wellbeing Survey. Int. J. Environ. Res. Public Health 2021, 18, 1192. [Google Scholar] [CrossRef]
  60. Verrastro, V.; Saladino, V.; Eleuteri, S.; Barberis, N.; Cuzzocrea, F. Sexting, Self-esteem, and Social Media: A Comparison among Frequent, Occasional, and Non-Sexting Italian Adolescent Girls. Psychol. Russ. 2023, 16, 3–20. [Google Scholar] [CrossRef] [PubMed]
Sexes 05 00025 g001
Figure 1. Differences in active sexting disposition factor as a function of gender and age group.
Figure 1. Differences in active sexting disposition factor as a function of gender and age group.
Sexes 05 00025 g001
Sexes 05 00025 g002
Figure 2. Differences in actual sexting participation factor as a function of gender and age group.
Figure 2. Differences in actual sexting participation factor as a function of gender and age group.
Sexes 05 00025 g002
Sexes 05 00025 g003
Figure 3. Differences in total sexting score as a function of gender and age group.
Figure 3. Differences in total sexting score as a function of gender and age group.
Sexes 05 00025 g003
Table 1. Sociodemographic characteristics of the study sample and comparisons between men and women.
Table 1. Sociodemographic characteristics of the study sample and comparisons between men and women.
Men
(n = 2204)		Women
(n = 4515)		χ2
n%n%
Education:
Elementary School43119.673116.240.39 ***
Secondary Education95943.7175339.0
University Level80736.7201544.8
No data7 16
Occupation:
Student100745.9224149.826.13 ***
Unemployed1798.23908.7
Retired/Pensioner522.4711.6
Employed94042.9172538.4
Other150.7691.5
No data11 19
Marital status:
Never Married160573.2301266.930.70 ***
Married/Cohabiting51523.4125227.8
Separated/Divorced/Widowed743.42395.3
No data10 12
MSDMSDt
Age28.8212.5729.1812.83−1.09
Number of Children0.340.810.420.84−3.55 ***
Notes: *** p < 0.001.
Table 2. Means (M), standard deviations (SD), and two-way ANOVA statistics for sexting.
Table 2. Means (M), standard deviations (SD), and two-way ANOVA statistics for sexting.
VariableMenWomenANOVA
MSDMSDEffectF Ratioηp2
Actual Sexting Participation
Adolescence7.686.506.804.91Gender59.66 ***0.009
Youth9.226.168.105.17Age172.72 ***0.093
Adulthood8.475.866.764.89G × AG2.080.001
Midlife5.304.983.333.59
Old age3.582.971.582.59
Interaction Gender × Age Group
Active Sexting Disposition
Adolescence7.1410.615.247.30Gender50.57 ***0.007
Youth10.0110.487.408.44Age131.76 ***0.073
Adulthood9.5510.485.567.37G × AG3.26 *0.002
Midlife3.676.951.423.28
Old age1.142.440.682.31
Interaction Gender × Age Group
Total Sexting
Adolescence22.6616.9319.6712.44Gender60.69 ***0.009
Youth27.5716.9023.5013.81Age175.78 ***0.095
Adulthood26.3517.0119.9512.67G × AG2.350.001
Midlife16.0312.6311.457.31
Old age11.465.519.074.72
Interaction Gender × Age Group
Notes: * p < 0.05; *** p < 0.001.
Table 3. Correlations between measures of sexting and study variables for adolescent girls and boys.
Table 3. Correlations between measures of sexting and study variables for adolescent girls and boys.
Women (n = 458)Men (n = 201)
VariableTotal
Sexting		Actual Sexting ParticipationActive
Sexting
Disposition		Total SextingActual Sexting ParticipationActive
Sexting
Disposition
Psychological well-being−0.12 *−0.12 *−0.12 *−0.19 **−0.15 *−0.23 *
Life satisfaction−0.10 *−0.12 **−0.11 *−0.07−0.07−0.09
Self-esteem−0.03−0.07−0.04−0.10−0.09−0.13
Psychological distress0.13 **0.17 ***0.12 **0.20 **0.21 ***0.22 **
Intimate partner violence:
Total violence0.32 ***0.34 ***0.31 ***0.46 ***0.35 ***0.54 ***
Cyberviolence0.26 ***0.27 ***0.27 ***0.48 ***0.36 ***0.56 ***
Offline psychological violence0.27 ***0.32 ***0.26 ***0.32 ***0.28 ***0.37 ***
Physical violence0.31 ***0.31 ***0.30 ***0.46 ***0.33 ***0.54 ***
Sexual violence0.17 ***0.18 ***0.16 **0.47 ***0.31 ***0.55 ***
Notes: Statistically significant coefficients are indicated in boldface. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table 4. Correlations between measures of sexting and study variables for young women and men.
Table 4. Correlations between measures of sexting and study variables for young women and men.
Women (n = 2218)Men (n = 1135)
VariableTotal SextingActual Sexting Participation Active Sexting DispositionTotal SextingActual Sexting Participation Active
Sexting
Disposition
Psychological well-being−0.07 **−0.07 **−0.08 ***−0.09 **−0.07 *−0.11 ***
Life satisfaction−0.06 **−0.07 **−0.05 *−0.05−0.03−0.08 *
Self-esteem−0.03−0.04−0.04 *−0.04−0.04−0.06
Psychological distress0.06 **0.09 ***0.06 **0.09 **0.09 **0.11 ***
Intimate partner violence:
Total violence0.13 ***0.14 ***0.12 ***0.25 ***0.26 ***0.24 ***
Cyberviolence0.13 ***0.15 ***0.12 ***0.25 ***0.25 ***0.24 ***
Offline psychological violence0.11 ***0.13 ***0.10 ***0.20 ***0.19 ***0.20 ***
Physical violence0.10 ***0.10 ***0.10 ***0.21 ***0.23 ***0.19 ***
Sexual violence0.10 ***0.11 ***0.10 ***0.20 ***0.19 ***0.20 ***
Notes: Statistically significant coefficients are indicated in boldface. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table 5. Correlations between measures of sexting and study variables for adult women and men.
Table 5. Correlations between measures of sexting and study variables for adult women and men.
Women (n = 879)Men (n = 456)
VariableTotal SextingActual Sexting ParticipationActive
Sexting
Disposition		Total SextingActual Sexting ParticipationActive
Sexting
Disposition
Psychological well-being−0.06−0.08 *−0.05−0.06−0.06−0.06
Life satisfaction−0.07 *−0.11 **−0.06−0.09−0.09−0.09
Self-esteem−0.06−0.10 **−0.07 *−0.06−0.10 *−0.05
Psychological distress0.060.10 **0.050.070.10 *0.07
Intimate partner violence:
Total violence0.12 ***0.15 ***0.13 ***0.19 ***0.12 *0.23 ***
Cyberviolence0.14 ***0.17 ***0.14 ***0.22 ***0.17 ***0.24 ***
Offline psychological violence0.11 ***0.13 ***0.12 ***0.17 ***0.11 *0.20 ***
Physical violence0.07 *0.11 **0.07 *0.12 *0.050.16 ***
Sexual violence0.050.07 *0.050.11 *0.060.14 **
Notes: Statistically significant coefficients are indicated in boldface. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table 6. Correlations between measures of sexting and study variables for midlife women and men.
Table 6. Correlations between measures of sexting and study variables for midlife women and men.
Women (n = 814) Men (n = 341)
VariableTotal
Sexting		Actual Sexting Participation Active
Sexting
Disposition		Total SextingActual Sexting Participation Active
Sexting
Disposition
Psychological well-being−0.12 **−0.13 ***−0.11 **−0.17 **−0.17 **−0.15 **
Life satisfaction−0.18 ***−0.21 ***−0.13 ***−0.19 ***−0.22 ***−0.16 **
Self-esteem−0.10 **−0.14 ***−0.10 **−0.08−0.07−0.08
Psychological distress0.20 ***0.23 ***0.17 ***0.18 **0.22 ***0.17 **
Intimate partner violence:
Total violence0.16 ***0.22 ***0.10 **0.30 ***0.38 ***0.28 ***
Cyberviolence0.13 ***0.21 ***0.08 *0.33 ***0.36 ***0.32 ***
Offline psychological violence0.17 ***0.21 ***0.11 **0.23 ***0.33 ***0.19 ***
Physical violence0.12 ***0.17 **0.07 *0.26 ***0.30 ***0.24 ***
Sexual violence0.050.13 ***−0.010.20 ***0.22 ***0.19 ***
Notes: Statistically significant coefficients are indicated in boldface. * p < 0.05; ** p < 0.01; *** p < 0.001.
Table 7. Correlations between measures of sexting and study variables for old age women and men.
Table 7. Correlations between measures of sexting and study variables for old age women and men.
Women (n = 146) Men (n = 71)
VariableTotal SextingActual Sexting ParticipationActive
Sexting
Disposition		Total SextingActual
Sexting
Participation 		Active
Sexting
Disposition
Psychological well-being0.00−0.06−0.05−0.20−0.06−0.20
Life satisfaction0.06−0.100.06−0.17−0.18−0.15
Self-esteem−0.05−0.01−0.07−0.13−0.10−0.16
Psychological distress0.010.020.020.29 *0.33 **0.19
Intimate partner violence:
Total violence−0.020.09−0.030.26 *0.230.23
Cyberviolence0.130.020.17 *0.25 *0.220.23
Offline psychological violence−0.070.06−0.050.24 *0.24 *0.20
Physical violence0.030.14−0.030.200.120.20
Sexual violence0.030.07−0.050.230.180.24 *
Notes: Statistically significant coefficients are indicated in boldface. * p < 0.05; ** p < 0.01; *** p < 0.001.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Matud, M.P. Gender Differences in Sexting and Its Association with Well-Being and Intimate Partner Violence Victimization from Adolescence to Old Age. Sexes 2024, 5, 335-350. https://doi.org/10.3390/sexes5030025

AMA Style

Matud MP. Gender Differences in Sexting and Its Association with Well-Being and Intimate Partner Violence Victimization from Adolescence to Old Age. Sexes. 2024; 5(3):335-350. https://doi.org/10.3390/sexes5030025

Chicago/Turabian Style

Matud, M. Pilar. 2024. "Gender Differences in Sexting and Its Association with Well-Being and Intimate Partner Violence Victimization from Adolescence to Old Age" Sexes 5, no. 3: 335-350. https://doi.org/10.3390/sexes5030025

Article Metrics

Back to TopTop