Teenagers’ experiences with online sexual/romantic activities were associated with experiences of offline sexual/romantic activities. Multiple regressions showed that age (older) and risk behaviour contributed to higher engagement in offline sexual/romantic activities. In contrast, only higher risk behaviour contributed to higher engagement in online sexual/romantic activities for boys, but for girl several factors, such as age (younger), lower body esteem, higher risk- and problem behaviour contributed to higher engagement in online sexual/romantic activities. We discuss this result from a gender perspective.
Keywords: sexuality; online; offline; adolescence; well-being
doi: 10.5817/CP2014-1-7
Adolescent sexual activity is often conceptualized as a problematic or risky behaviour. In contrast, many scholars theorize that sexual activity during adolescence is closely linked to general well-being and agency (Horne & Zimmer-Gembeck, 2005). The debate regarding adolescent sexuality has focused too narrowly on what is to be regarded as proper, or not, while ignoring the complex dimensions of sexuality and the importance of sexual identity as a developmental task (Haffner, 1998). This debate has been intensified since the Internet has become an everyday arena for adolescents’ sexual self-exploration, with sexual activities online typically viewed as problematic. However, the Internet can be regarded as an arena where, if used wisely, adolescents can be provided with support and have safe experiences, which can influence the development of their sexual health positively (DeHaan, Kuper, Magee, Bigelow, & Mustanski, 2012). To be able to understand and to guide adolescents in sexual identity formation requires an understanding of the links between well-being and sexual activities, not only in traditional (offline) settings, but also in online settings. This study contributes to the understanding of adolescents’ well-being and sexuality by examining the link between adolescents’ well-being and off- as well as online sexual/romantic activities. Furthermore, the study contributes to greater understanding of sexual development for boys and girls in both traditional and new settings taking into count age and pubertal timing.
Well-being has been studied from several perspectives having the individuals’ mental, physical, emotional, and/or social well-being in focus. Several studies, however, have paid extra attention to psychosocial well-being, including aspects such as; the individual’s sense of relatedness to others, that one’s life has direction and meaning, self-esteem, and psychosocial adjustment (for an overview see Rayle, 2005). In the current study we will focus on dimensions of relatedness (‘relational satisfaction’), self-esteem (‘personal satisfaction’) and psychosocial adjustment (‘destructive behaviour’).
Previous studies have primarily examined the links between adolescents’ well-being and sexuality in traditional settings, e.g. dating, having intercourse and being in an intimate peer relationship. In this body of literature, studies point in different directions. Vrangalova and Savin-Williams (2011) show a positive link between being sexually active and positive well-being, by allowing them to experience pleasure or helping them build positive personal characteristics such as autonomy, connectedness and confidence, however other studies reveal a negative link (e.g., Ciairano, Bonino, Kliewer, Miceli, & Jackson, 2006; Valois, Zullig, Huebner, Kammermann, Drane, 2002). There are at least three possible reasons why such differences in findings might occur. One is that several scholars show that the nature of the link between well-being and sexual activity has to do with pubertal timing. The effects of early maturation are usually negative for girls and can include problems such as depressed mood, negative body image, substance use, early sexual activity and conflict with parents (Lynne, Graber, Nichols, Brooks-Gunn, & Botvin, 2007; Mendle, Turkheimer, & Emery, 2007; Skoog, 2013; Westling, Andrews, Hampson, Peterson, & Pubertal, 2008). For boys, the effects of early maturation are less clear, but seem to be positive in some ways and negative in others (for a review see Stattin & Skoog, in review). Early-maturing boys tend to have more positive body images and are more popular than other boys (Graber, Lewinsohn, Seeley, & Brooks-Gunn, 1997). However, early maturing boys also tend to become involved earlier in delinquency, sex, and substance use (Steinberg, 2011; Westling et al., 2008; Wichstrom, 2001).A study with American teenagers (Vrangalova & Savin-Williams, 2011) showed that both girls and boys that were either on-time or early-onset (had an earlier sexual debut than the group norm) reported higher well-being than those that were late-onset (had a later sexual debut than the group norm). An explanation might be that if adolescents regard their sexual debut as being in line with others of the same age (on-time) their behaviour matches peer group norms.
A second explanation for the unclear pattern of findings regarding adolescent well-being and sexual activity could be the types of sexual and romantic experiences that are sought. For example, an Italian study (Ciairano, Bonino, Kliewer, Miceli, & Jackson, 2006) while revealing a negative link between sexually active teenagers and well-being, also found a positive link between dating and well-being. This result suggests that dating and sexual activity should be kept apart when studying them. A third explanation is whether the type of sexual behaviour we ask adolescents about is properly regarded as sexual risk behaviour. For example, a study among teenagers in the Slovak Republic (Kalina et al., 2011) showed that lower ratings of well-being (in this study indicated by greater levels of anxiety/depression) were linked to greater sexual risk behaviour (e.g. unsafe sex, sex after alcohol consumption). However the types of online sexual activities that can be counted as sexual risk behaviour have yet to be fully explored and defined.
The Internet has brought about a radical change in how adolescents live their lives and has become an ordinary everyday context (Thurlow & McKay, 2003) and arena for sexual activities. Online sexual activities include passive activities such as viewing sexual images, watching movies or listening to conversations about sex, but also more active activities like flirting, posting images, and having webcam sex. The Internet is frequently regarded as a problematic arena for sexual and romantic sexual activities. EU kids online, one of the largest studies in the area (Livingstone, Ólafsson, O’Neill, & Donoso, 2012), show that between 10 and 11 % of 11-16 year olds have participated in risky activities on the Internet (e.g. seen or received sexual images, meeting with someone from the Internet face-to -face). However, Subrahmanyam and Greenfield (2008) note that adolescents' online interactions may have benefits, such as relieving social anxiety, as well as costs. Furthermore, adolescents are sometimes able to find valuable support and information through online interactions.
Adolescents consume sexually explicit material due to desires for sexual stimulation and sexual information (see Attwood, 2005). In 1998 Cooper suggested that there are three main factors, called the Triple-A Engine that affect online sexual activity: easy accessibility, easy affordability, and relative anonymity. In a latter review by Hertlein and Stevenson (2010) seven “As” are presented as a way of capturing the nature of Internet and how the Internet can generate problems when it comes to sexual and romantic activates online. Accessibility suggests that the Internet is open and possible to access for everyone from everywhere. In relation to sexual and romantic activates, this means both that regardless of your physical appearance (e.g. look, age, gender) you can get access to sexual activities, but also that when you are in a relationship you can have access to that relationship irrespective of your location and other whereabouts. Anonymity refers to the idea that online sexual and romantic activities can take place without anyone else knowing about it, but also that the person being engaged in such activities is free to construct their online identity as she or he pleases. Affordability means that the Internet is an arena where sexual activities (e.g. pornography) are less expensive, but also that a relationship online does not have to be as expensive as an offline relationship. Approximation refers to the notion that what is experienced on the internet is an approximation of the offline word – one that is sometimes more, and sometimes less accurate. Acceptability refers to the tendency that people are more accepting towards specific phenomena if they take place online, but not offline. Ambiguity means that, as a consequence of acceptability and approximation, it is sometimes hard to draw a line between what is okay/good/moral/etc. and what is not. Accommodation refers to the adjustment people make of their general views (guidelines, working-models) in accordance with their offline behaviour, and when such accommodation is completed, the person will use their adjusted working-models to guide their offline behaviour. What from the beginning not was accepted offline becomes accepted after the adjustment. Several of these “As” might be especially critical for teenagers in their sexual activities and construction of their sexual identity.
One of the most common online sexual activities is viewing pornography. Pornography – defined as sexually explicit media that is primarily intended to arouse the viewer sexually (Malamuth & Huppin, 2005) – has long made up a large part of the Internet. Boys are more exposed to Internet pornography than girls (Peter & Valkenburg, 2008; Sabina, Wolak, & Finkelhor, 2008), with one quarter of 14- to 15-year old boys and 38 % of 16- to 17-year old boys reporting voluntary exposure in the preceding year (Wolak, Mitchell, & Finkelhor, 2007). Internet pornography is thought to be popular among young people because it is anonymous, affordable, and accessible (Cooper, 1998), as well as difficult for parents to monitor (Ko, Yen, Liu, Huang, & Yen, 2009).
According to a recent meta-analysis, exposure to risk-glorifying media is linked to risky behaviours, with an increased exposure being linked to increased risk-taking, risk-positive cognitions and attitudes, and risk-promoting emotions (Fischer, Greitemeyer, Kastenmüller, Vogrincic, & Sauer, 2011). Hence, the meta-analysis shows that risk glorification in the media are a crucial determinant of increased risk-taking in society. One example is the series Jackass (MTV) in which individuals engages in self-harming stunts. Other examples are alcohol glorification in advertisements and games. Adolescents who engage in online interactions with unknown people and explicitly risky online behaviours (e.g., posting personal information or pictures online) report more rule-breaking behaviour and social problems than others (Wolak, Finkelhor, & Mitchell, 2008).
Using different media to access pornography and exposing themselves sexually is a common factor in the everyday lives of adolescents, partly as an enriching phenomenon (e.g. experience pleasure, getting to know one’s own sexuality without physical contact). In previous research, viewing pornography online has been related to distorting sexuality, sexual offences, including sexually harassing peers and sexual coercion, as well as to more general problem behaviours among young people such as aggression, substance use, attention problems, and rule-breaking behaviour (Bonino, Ciairano, Rabaglietti, & Cattelino, 2006; Brown & L’Engle, 2009; Carroll, Padilla-Walker, Nelson, Olson, McNamara Barry, & Madsen, 2008; Ko et al., 2009; Nigård, 2012; Wolak et al., 2007; Ybarra & Mitchell, 2005).
The aim of this study was to determine links between different aspects of adolescents’ well-being and their sexual and romantic activities off- and online. Further, the aim was to illuminate similarities and differences concerning well-being and sexual activities between boys and girls, and between mid- and late-adolescents. In pursuit of this goal, 496 boys and girls in their mid–late adolescence were asked questions about their sexual and romantic activities in both on- and offline contexts. Well-being in this study was measured by soliciting teenagers’ perceptions of their own personal satisfaction, relational satisfaction and destructive behaviours. Furthermore, questions were asked about age and pubertal timing. Previous studies have indicated a link between pubertal timing and both offline sexual/romantic activities (Lynne et al., 2007; Mendle et al., 2007; Skoog, 2013; Stattin & Skoog, in review; Westling et al., 2008; Wichstrom, 2001), as well as online sexual/romantic activities (Skoog, Sorbring, Hallberg, & Bohlin, 2013; Skoog, Stattin, & Kerr, 2009). However, the present study will use cross-sectional data and therefore the direction of the link between online sexual activities and wellbeing is hard to establish.
The teenagers were recruited from a project comprising young people between the ages of 13 to 18, and their parents (Skoog et al., 2013). The current study includes two cohorts, one comprising 245 mid-adolescents (15 years of age; 55 % girls), and another comprising 251 late-adolescents (18 years of age; 49 % girls). A predominant number of the teenagers were born in Sweden (94.8 %), and most lived with both parents (78 %). Of the remainder, 15.3 % lived with their mothers, 4 % with their fathers, and 2.7 % with other relatives or adults.
Of the 496 teenagers all had some experience of sexual/romantic activities. From the beginning the study included 510 teenagers; however 14 did not report any sexual/romantic experiences, either off- or online. In line with the aim of the study, these 14 teenagers were therefore excluded.
The teenagers answered questions concerning online and offline sexual/romantic activities, as well as questions about different aspects of well-being, namely personal satisfaction, relational satisfaction and destructive behaviours. Data on gender, age, living-conditions, ethnic background and pubertal timing was also obtained.
Offline sexual and romantic activities. This measurement has been used previously in other Swedish studies (Skoog et al., 2013). The participants were asked six questions about offline sexual/romantic activities, concerning their experiences of; 1) flirting, 2) dating, 3) kissing, 4) having discussions about sex with friends, 5) accessing pornographic literature or movies, and 6) having sex with someone else. For each question participants indicated their responses on a five-point scale, where alternatives ranged from 1 (never) to 5 (yes, every day). Responses 2-5 were collapsed, creating six dichotomous variables with only two alternatives each; experience vs. no experience. To obtain a score for each person, the 6 items were summed creating a value between 0 and 6 for each person. We performed a Kuder Richardson 20 reliability analysis with the dichotomous (nominal) data for the offline sexual and romantic activities scale. The K R 20 coefficient was .67. The scale was normally distributed having a skewness as well as kurtosis between -2 and +2.
Online sexual and romantic activities. The participants were asked a general “gateway question” about sexual/romantic activities on Internet. This question read “Have you ever done any of the following on Internet?” and was followed by a number of alternatives, such as “sought information about sex/visited pornographic sites or sex chat-rooms/posted pictures and movies of yourself/ flirted/experienced sexually explicit material such as images, videos or text on the Internet”. The question required a yes or no answer. The purpose was to ascertain that only participants with online sexual experiences were asked more specific questions. Teenagers who answered “no” on the gateway question bypassed all the specific questions about online sexual/romantic activities. Teenagers that answered “yes” on the gateway question were asked the follow-up questions. This measurement has been used previous in other Swedish studies (Skoog et al., 2013). The teenagers were asked questions concerning their experiences of; 1) flirting, 2) looking for a boyfriend/girlfriend, 3) visiting pornographic sites, 4) chat-rooms discussions about sex, 5) posting pictures and movies of oneself that can be considered sexual, and 6) using a web-cam. For each question participants indicated their responses on a five-point scale where alternatives ranged from 1 (never) to 5 (yes, every day). Due to a floor effect, response alternatives 2-5 were collapsed, creating six dichotomous variables with only two alternatives each; experience vs. no experience. To obtain a score for each person, the 6 items were summed creating a value between 0 and 6 for each person. We performed a Kuder Richardson 20 reliability analysis with the dichotomous (nominal) data for the online sexual and romantic activities scale. The K R 20 coefficient was .81. The scale was normally distributed having a skewness as well as kurtosis between -2 and +2.
Well-being
1. Personal satisfaction was measured with two instruments: Youth Quality of Life Scale (Edwards, Huebner, Connell, & Patrick, 2002; Patrick, Edwards, & Topolski, 2002) and Body Esteem Scale for Adolescents and Adults (Mendelson, Mendelson, & White, 2001). The Youth Quality of Life Scale (Patrick et al., 2002; Swedish translation of the YQOL by Topolski, Edward, Huebner, Conell, & Patrick, 2002) measures quality of life in a more general sense during adolescence, including items on sense of self, environment and social life (41 questions). There is a contextual part of the original version that has 15 items and a short version measuring the perception of life situation comprising 8 items. When using the short version, some of the contextual items can be added. In this study 9 items are used: 8 items from the original short version and one additional item aimed at capturing the existential dimension of being a teenager. Hence, the teenagers answered 9 questions (e.g. “I enjoy life”) on which they indicated their degree of satisfaction in relation to each statement on an 11-point scale ranging from 0 (not at all), to 10 (to a high degree/completely). To obtain a score for each person, the 9 selected items were summed and divided by 9. The scale yielded high internal consistency; α = .82 (for all), α = .83 (for girls) and α = .81 (for boys).The Body Esteem Scale for Adolescents and Adults (BESAA) measures body satisfaction and has been translated into Swedish and validated in Sweden (see Erling & Hwang, 2004). The scale has three subscales and one of them - The Body Esteem Appearance-was used in this study. This subscale measures general feelings about one’s appearance (e.g., “I like what I see when I look in the mirror”). On 10 items the teenager indicates their degree of agreement with each statement on a 5-point Likert scale ranging from 0 (never) to 4 (always). To obtain a score for each person the 10 items were summed and divided by 10. The subscale yielded or had high internal consistency; α = .92 (for all), α = .93 (for girls) and α = .89 (for boys).
2. Relational satisfaction was measured with three instruments: Inventory of Parent and Peer Attachment for Mothers, Inventory of Parent and Peer Attachment for Fathers and Inventory of Parent and Peer Attachment for Peers (Armsden & Greenberg, 1987) Inventory of Parent and Peer Attachment (IPPA) is an instrument that is used to assess children’s and adolescents’ self-perceptions of the degree of trust, quality of communication and the extent of anger and disaffection within the context of their personal relationships. The instrument has been translated and used in Sweden in previous studies (Sorbring, Hallberg, Bohlin, & Skoog, manuscript). Each scale consists of 25 items (e.g. “My mother respects my feelings”, ”My father understands me”, “My friends care about how I feel”) measured on a 5-point Likert scale ranging from 1 (not true) to 5 (very true). On both the mother-scale and the father-scale, one item was taken away (“I wish I had another mother/father”), which leaves the mother- and the father-scales with 24 items each. To obtain a score for each person, the 24/25 items were summed and divided by 24/25 for each scale. The scales yielded high internal consistency: scale about mothers α = .94 (for all), α = .95 (for girls) and α = .92 (for boys), scale about fathers α = .94 (for all), α = .94 (for girls) and α = .94 (for boys) and scale about friends α = .93 (for all), α = .95 (for girls) and α = .92 (for boys).
3. Destructive behaviours were measured with two instruments: Adolescent Risk Taking Questionnaire (Gullone, Moore, Moss, & Boyd, 2000) and Problem behaviour Delinquency (Magnusson, Dunér, & Zetterblom, 1975). The Adolescent Risk Taking Questionnaire (ARQ) measures teenagers’ risk perception and risk behaviours and has been translated and used in Sweden in previous studies (Bohlin & Erlandsson, 2007).The original measurement had 44 items divided up into two subscales: Risk Judgment and Risk Behaviours. In this study a short-form containing 16 items from the Risk Behaviours subscale was used. Each item states a potentially risky activity which the teenagers rated on a 5-point Likert scale, ranging from 1 (I have never done it) to 5 (I do it very often) indicating extent to which they had engaged in the following activities in the preceding year: smoking, getting drunk, stealing cars and going for joyrides, sniffing gas or glue, underage drinking, staying out late, driving without a license, having unprotected sex, teasing and picking on people, cheating, leaving school, taking drugs, under-eating, talking to strangers, meeting someone they got to know on the Internet and having sex with someone on a first date. To obtain a score for each person the 16 items were summed and divided by 16. The scales obtained high internal consistency; α = .87 (for all), α = .84 (for girls) and α = .89 (for boys). The Problem behaviour/Delinquency Scale measured the extent to which the teenager engaged in delinquent behaviour. It is a Swedish instrument that has been used and validated in previous studies (Magnusson et al., 1975; Persson, Kerr, & Stattin, 2007). On a 5-point Likert scale, ranging from 1 (never) to 5 (more than 10 times) the teenager rated the extent to which they had been engaged in activities during the previous year, including behaviours such as breaking into houses, taking bicycles, motorcycles and cars without permission, shoplifting, vandalizing, smoking hashish and using other drugs, hitting someone so hard that he or she needed hospital treatment, hurting someone with a knife or some other weapon and threatening or forcing someone to do something he or she did not want to do. To obtain a score for each person the 23 items were summed and divided by 23. Although the scale yielded higher internal consistency for boys than for girls, it was acceptable for both boys and girls; α = .90 (for all), α = .80(for girls) and α = .93 (for boys).
Pubertal timing
For boys: We measured boys’ pubertal timing (i. e., pubertal development in relation to same-age, same-sex peers) with the widely used Pubertal Development Scale (PDS; Petersen, Crockett, Richards, & Boxer, 1988). Research has demonstrated that the PDS has good psychometric properties, including high reliability and validity (Brooks-Gunn, Warren, Rosso, & Gargiulo, 1987; Dick, Rose, Pulkkinen, & Kaprio, 2001). The Swedish version of the scale has been used in previous studies (Skoog et al., 2013) and correlates with other aspects of pubertal timing as expected. Responses are given on four-point scales, from 1 = No development to 4 = Development is complete. The wording of the answer options differed slightly for the different items to suit the wording of particular items. The items concerned skin changes, height spurt, body hair development, voice change, and beard growth. The minimum and maximum scores on the total scale were 5 and 20, respectively (M = 15.8, SD = 2.63; α = .72). Higher scores indicate earlier pubertal timing.
For girls: Because girls experience puberty about two years ahead of boys, most of them had completed puberty at the time of the data collection. Therefore we used age at menarche as the measure of pubertal timing for the female participants. As with the PDS, age at menarche is one of the most common measures of pubertal timing in the literature. Girls were asked an open question concerning how old they were at menarche in years and months. One percent of girls had not experienced menarche at the time of the data collection. Those girls were not included in the analyses concerning pubertal timing. The median age at menarche was 12.8 years, which mirrors the mean age of menarche in a large body of studies on age at menarche (Herman-Giddens, 2006).
Contact was established with seven secondary and upper secondary schools in the western parts of Sweden who provided the names, addresses, and telephone numbers of pupils. The teenagers, as well as their parents, received a letter in which they were informed about the study as a whole, their children’s personal involvement, their right to refrain from or subsequently withdraw from participation, and also how the material was to be used. The letter was sent out to 1296 adolescents and their families. Among this 510 teenagers (39%) chose to take part in the study. As described above, however, only the youth who had offline sexual experiences were part of this study, resulting in 496 participants. Written consent was collected from the parents of the teenagers in the younger cohort (mid-adolescents), and from teenagers themselves in the older cohort (late-adolescents). In the younger cohort teenagers who had permission from their parents were asked verbally if they wanted to take part in the study and received written information about the study. In each of the classes in the study, we held a drawing for movie tickets. All students in the class were entered into the drawing, regardless of whether or not they took part in the study. Additionally, all classes were paid 500 SEK (approximately 50 euros) each. The Regional Ethical Review Board in Gothenburg, Sweden approved the study.
The teenagers completed computerized questionnaires during school-time. To ensure that no information would be accessible for anyone other than the researchers, the computers were brought to the schools by the research team and were without internet access. The computers were placed in the room in a way to minimise the possibility for participants to be able to view each other’s screens. Instructions on how to fill in the questionnaires were given orally by the research team. The data collection was administrated by a member of the team; either a research assistant supported by a doctoral student or one of the researchers, or both. The data was collected in 2009 and 2010.
Initially, descriptives of teenagers’ on- and offline sexual/romantic activities are presented. To be able to examine mean differences between two groups (e.g. boys and girls, mid- and late-adolescents), independent samples t-tests were performed. Cohen’s d were calculated to explore effect sizes. According to Cohen (1998), an effect size below .20 is regarded as small, around .50 as medium, and above .80 as large. Bivariate relationships between variables were tested by calculating correlation coefficients. The primary focus of the analyses was to detect associations between well-being and off- and online sexual/romantic activities. This was done by using multiple regression analysis. Four regression analyses were calculated: Off- and online sexual/romantic activities were treated as dependent variables in separate analysis, and separate analyses were conducted for girls and boys. In each regression analysis we controlled for age and pubertal timing.
All of the 496 teenagers that took part in the study had experiences of offline sexual/romantic activities and 54 % of the teenagers also had experiences of online sexual and romantic activities (see Table 1). Younger girls had significant fewer experiences of offline sexual/romantic activities than had older girls (t (256) = -6.38, p < .001; d = .78). The same was true for boys: younger boys had fewer experiences than older boys, both concerning offline activities (t (236) = -6.38, p < .001; d = .83) and online (t (256) = -3.97, p < .001; d = .52). Comparing boys and girls within the same age group only showed a significant difference concerning online activities among late-adolescents, showing that girls had fewer experiences than boys (t (249) = -6.26, p < .001; d = .79).
In the sections that follow, the relationship between adolescent boys’ and girls’ well-being, as well as age and pubertal timing, and off- and online sexual/romantic experiences were analysed by first calculating bivariate correlation (see Table 2 and 3) and second by regression analyses (see Table 4). According to the correlation coefficients, experiences of online sexual/romantic activities were positively associated by experiences of offline sexual/romantic activities for both girls and boys. Age was positively correlated with offline sexual activities both for girls and boys, but only for boys concerning experiences of online sexual activities. Girls who hit puberty earlier had more experiences of online sexual activities than other girls; however no correlation was found between pubertal timing and offline activities. For boys there was a significant correlation between earlier pubertal timing and more experiences of offline as well as online sexual activities.
Looking at the well-being variables, both girls and boys that reported more problem behaviours and/or more risk behaviours also reported more experiences of offline as well as online sexual/romantic activities. There was a negative correlation, both for girls and boys, showing that adolescents with lower body esteem reporter more experiences of online sexual/romantic activities. This association was not found concerning offline sexual/romantic activities. A negative association was also found between girls’ relationships with peers, mothers and fathers, showing that girls who had poorer relationship satisfaction (in relation to peers, mothers and fathers) reported more online sexual/romantic activities. For boys the only significant link was between poorer relation to their father and reporting more online sexual/romantic activities. No association was found concerning offline sexual/romantic activities and relationship satisfaction.
Multiple regression analyses were used to examine the relative role of well-being variables for online and offline sexual/romantic activities. We calculated regression estimations for girls and boys separately. Age and pubertal timing were entered first in the analyses. Age was associated with an elevated score concerning offline sexual/romantic activities for both girls and boys. For boys there was no association between age and online sexual/romantic activities, however for girls the association was significantly negative. Pubertal timing did not predict either on- or offline sexual/romantic activities. Looking at the well-being variables, both girls and boys risk behaviours were associated with an elevated score concerning off-, and online sexual/romantic activities. For girls there was also a strong association between problem behaviour and online sexual/romantic activities. Furthermore, there was a negative association between girls’ reported body esteem and reported online sexual/romantic activities. Altogether the variables explained 31% of the total variation in offline activities for boys, 18% of the total variation in online activities for boys, 38% of the total variation in offline activities for girls and 25% of the total variation in online activities for girls.
Adolescents spend much of their time online. Some of this time they spend engaged in various forms of sexual activity. What does this mean for adolescents’ well-being? The literature on whether there is a positive or negative link between sexual activities in general and well-being points in different directions (e.g. Ciairano et al., 2006; Vrangalova & Savin-Williams, 2011). When it comes to online sexual activity, we know even less. By allowing yourself to experience pleasure and build positive personal characteristics and confidence online, activities can be seen as positive (e.g. Vrangalova & Savin-Williams, 2011), while there are negative aspects too, including higher exposure to unwanted explicit material (e.g. Ciairano et al., 2006; Valois et al., 2002). This study contributes to the understanding of adolescents’ well-being and sexuality by examining the link between adolescents’ well-being and off- as well as online sexual/romantic activities taking factors which are strongly linked to sexual development - age and pubertal timing - into account.
First, teenagers’ experiences with online sexual/romantic activities were associated with experiences with offline sexual/romantic activities. In other words, the more adolescents engaged in sexual activities in one context, the more they engaged in sexual activities in the other. This is in line with the media practice model (Brown, 2000), which states that adolescents actively choose to expose themselves to media as a reflection of who they are or who they want to become, something which seems to be true regarding the use of internet sexuality as well (Ngo, Ross, & Ratliff, 2008). It fits with the idea of the seven “As” that characterize internet (Hertlein & Stevenson, 2010). With age, we should expect an increase in the ability to balance sexual and romantic activities both off- and online.
Second, the bivariate analyses revealed both similarities and differences between off- and online links towards well-being, pubertal timing and age. Offline experiences were linked to early pubertal timing (only for boys); older age; and risk and problem behaviour. Engaging in online sexual/romantic activities was linked to early pubertal timing, older age (only for boys), low body-esteem and risk and problem behaviour. Furthermore, engaging in online sexual/romantic activities was for girls linked to poor relationships with mothers, fathers, and peers and for boys to poor relationships with fathers. Previous research has linked early pubertal timing to engaging in online sexual activities among adolescents (Skoog et al., 2009, 2013), but to our knowledge this has previously only been demonstrated for boys. Results indicate this may also be the case for girls. Given that early puberty has been repeatedly linked to sexual activities in offline settings for girls, this finding is not surprising (e.g., Stattin, Kerr, & Skoog, 2011). That we did not corroborate this general finding in the present study was, on the other hand, surprising. Perhaps at the age of the current sample, the effects of pubertal timing for girls’ sexual/romantic activities offline, as least as measured here, are no longer relevant because virtually all girls have reached sexual maturity. Boys’ mature a few years later than girls, which could explain why we did find a link between pubertal timing and offline sexual/romantic activities for boys.
Engaging in offline sexual/romantic activities was not linked to any of the relational variables, however looking at the bivariate correlations we found that engaging in sexual/romantic activities online is linked to the quality of relationships with significant others (i.e., parents and peers), particularly for girls. Similar results have previous been found, for example showing that a link between parental trust and teenagers experiences of inappropriate material, such as pornographic material, violent and bloody material and persecution and agitation against a person or group of people (Sorbring & Lundin, 2012). However, little is done on this area and the results from the current study add important information to the literature. Future research is needed to understand why there is a link between teenagers online behaviour and their relations with significant others.
Third, although engaging in off- and online sexual/romantic activities were correlated with several aspects of adjustment, when we tested the correlates’ unique effects on off- and online sexual/romantic activities, only a few variables remained significant. Age (older) and risk behaviour contributed to higher engagement offline sexual/romantic activities. For boys only higher risk behaviour contributed to greater engagement in online sexual/romantic activities, however for girls several factors, such as age (younger), lower body esteem, higher risk- and problem behaviour contributed to greater engagement in online sexual/romantic activities. In this study, both girls’ and boys’ risk behaviours were associated with more off-, and online sexual/romantic activities and for girls there was also a strong association between problem behaviour and online sexual/romantic activities. This finding reflects previous studies showing that risky Internet use is linked to problem behaviour and social problems in traditional contexts (Fischer, Greitemeyer, Kastenmüller, Vogrincic, & Sauer, 2011; Wolak, Finkelhor, & Mitchell, 2008) and also a recent retrospective study which indicated that early exposure to sexually explicit material was linked to sexual risk taking, including having unprotected sex, even in adulthood (Sinkovic, Stulhofer, & Bozic, 2012). What are the reasons for this link?
Risk-glorifying media is linked to risky behaviours, with an increased exposure being linked to increased risk-taking (Fischer et al., 2011). Recent research on risk taking has shown that young women tend to involve themselves in the same types of risky activities as men, including sexual activities, but that their perceptions of the activity differ from those of boys. While girls tend to evaluate an activity as being a risky even though they engaged in it, the same tendency is not observed among boys (Abbot-Chapman, Denholm, & Wyld, 2007; Bohlin & Erlandsson, 2007). Although young women nowadays have more opportunities to test their limits and also, to some extent, see risk taking as a positive way of enhancing life skills, the dissonance between doing and thinking can explain why girls report lower degree of well-being. This dissonance can also be linked to our result that there was a negative association between girls’ body esteem and online sexual/romantic activities, as well as a negative link between girls’ age and online sexual/romantic activities. Younger girls are sometimes more negatively affected by sexual activities online (e.g. grooming, sexual abuse, see van den Heuvel, van den Eijnden, van Rooij, & van de Mheen, 2011). For more or less everyone, online sexual activities are accessible, affordable and anonymous, compared to offline sexual activities (Cooper, 1998), phenomena that might be extra attractive for young people leading a phenomenon where girls that are not mature enough to be engaged in sexual activity can be active online. Another explanation could be that those girls who do not have high body-esteem turn to the Internet to find an arena to explore sexual and romantic activities. This explanation is in line with the significant however moderate correlations showing that girls who are sexually active both off- and online also report having poorer relationships with friends and parents, indicating that they might have relationships in which they do not feel safe and comfortable and instead turn to an alternative arena (Sorbring, Bohlin, Andersson, & Lundin, in press; Suzuki & Calzob, 2004). Many teenagers see the Internet as a safer and more protected environment for exploring sexuality and other identity process (Sorbring et al., in press; Suzuki & Calzo, 2004).
It seems to be hard to escape the conclusion that being sexually active online during adolescence is linked to negative outcomes. Before we, as developmental scholars, accept this finding, we need to know more about whether the link is universal or if it applies only to certain subgroups or under certain conditions. Another key question is the direction of the link between online sexual activity and well-being. Do teenagers that are sexually and romantically active on the Internet have feelings of reduced well-being because of that involvement, or, do such feelings precede the use of Internet as a sexual and romantic arena? Several researchers (see Hertlain & Stevenson, 2010 for an overview) have indicated that sexual and romantic relationships online differ in numerous ways from offline relationships. For example, it might be hard for a young person to detect if sexual activity online is a good or bad approximation of sexual activities offline, and therefore it might also be difficult to decide whether the activity is acceptable or not. Doubts concerning approximation, ambiguity and acceptability (Hertlain & Stevenson, 2010), might lead to poorer well-being. If feelings of inadequacy and powerlessness are properly handled, the use of different media to access pornography and to expose oneself sexually can be an enriching phenomenon (Nigård, 2012). As mentioned, Vrangalova and Savin-Williams (2011) have shown that greater well-being is associated with sexual activities, when this is in line with the group norms of the peer group. Although we did not ask about the group norm in the current study, it is reasonable to speculate that, especially among boys, have had more, instead of less experience of sexual activities, is perceived positively by peers. It is also worth noting that there was no link between lower body esteem and offline sexuality, as found for online sexuality. This result supports the discussion above in that either online sexuality contributes to lower body esteem, or the other way around, i.e. that teenagers with lower body esteem are turning away from offline sexuality and instead choosing the Internet as a more physically secure place for their sexuality.
Some limitations of the study should be noted. One particular limitation is that we do not know if the young women experience lower levels of well-being and therefore use the Internet to handle such feelings, or if the reason for lower levels of well-being is that they are already sexually and romantically active online. The data used in this article are cross-sectional and not longitudinal. Specially-designed studies with before- and after measurements are therefore needed as a means of controlling for such factors. Another limitation is that we do not know if there are differences within online sexual and romantic activities. In other words, there could be a great span concerning what the teenager perceives as being a sexual and romantic activity. It is possible that this influenced our results. Therefore in future studies it is necessary to investigate how different activities are valued, something that may differ as a factor of age, gender and culture. Hence, future research and practice should highlight the importance of both gender and age. Since results from this study imply that some online sexual activities are more strongly linked to well-being than others, future studies should deepen research questions about these activities.
Armsden, G. C., & Greenberg, M. T. (1987). The inventory of parent and peer attachment: Individual differences and their relationship to psychological well-being in adolescence. Journal of Youth and Adolescence, 16, 427-454. http://dx.doi.org/10.1007/BF02202939
Attwood, F. (2005). What do people do with porn? Qualitative research into the consumption, use and experience of pornography and other sexually explicit media. Sexuality & Culture, 9, 65–86. http://dx.doi.org/10.1007/s12119-005-1008-7
Bonino, S., Ciairano, S., Rabaglietti, E., & Cattelino, E. (2006). Use of pornography and self-reported engagement in sexual violence among adolescents. European Journal of Developmental Psychology, 3, 265-288. http://dx.doi.org/10.1080/17405620600562359
Bohlin, M., & Erlandsson, S. (2007). Risk behaviour and noise exposure. Noise and Health, 7, 55 – 63. http://dx.doi.org/10.4103/1463-1741.36981
Brooks-Gunn, J., Warren, M. P., Rosso, J., & Gargiulo, J. (1987) Validity of self-report measures of girls’ pubertal status. Child Development, 58, 829-841.
Brown, J. D., & L’Engle, K. L. (2009). X-rated: Sexual attitudes and behaviours associated with U.S. early adolescents’ exposure to sexually explicit media. Communication Research, 36, 129-151. http://dx.doi.org/10.1177/0093650208326465
Carroll, J. S., Padilla-Walker, L. M., Nelson, L. J., Olson, C. S., McNamara Barry, C., & Madsen, S. D. (2008). Generation XXX: Pornography acceptance and use among emerging adults. Journal of Adolescent Research, 23, 6-30. http://dx.doi.org/10.1007/s10508-011-9862-x
Ciairano, S., Bonino, S., Kliewer, W., Miceli, R., & Jackson, S. (2006). Dating, sexual activity and well-being in Italian adolescents. Journal of Clinical Child and Adolescent Psychology, 35, 275-282. http://dx.doi.org/10.1207/s15374424jccp3502_11
Cohen, J. (1988). Statistical power analysis for the behavioural sciences (2nd ed.). Hillsdale, NJ: Lawrence Erlbaum Associates, Publishers.
Cooper, A. (1998). Sexuality and the Internet: Surfing into the new millennium. CyberPsychology & Behaviour, 1, 187– 193. http://dx.doi.org/10.1089/cpb.1998.1.187
DeHaan, S., Kuper, L. E., Magee, J. C., Bigelow, L., & Mustanski, B. S. (2013). The interplay between online and offline explorations of identity, relationships, and sex: A mixed-methods study with LGBT youth. Journal Of Sex Research, 50, 421 – 434. http://dx.doi.org/0.1080/00224499.2012.661489
Dick, D. M., Rose, R. J., Pulkkinen, L. & Kaprio, J. (2001). Measuring puberty and understanding its impact: A longitudinal study of adolescent twins. Journal of Youth and Adolescence, 30, 385-400. http://dx.doi.org/10.1023/A:1010471015102
Edwards, T. C., Huebner, C. E., Connell, F. A., & Patrick, D. L. (2002). Adolescent quality of life, part I: Conceptual and measurement model. Journal of Adolescence, 25, 275-286. http://dx.doi.org/10.1006/jado.2002.0470
Erling, A., & Hwang, P. (2004). Body image in Swedish 10-year old children. Perceptual and Motor Skills, 99, 437-444. http://dx.doi.org/10.2466/pms.99.2.437-444
Fischer, P., Greitemeyer, T., Kastenmüller, A., Vogrincic, C., & Sauer, A. (2011). The effects of risk-glorifying media exposure on risk-positive cognitions, emotions, and behaviours: A meta-analytic review. Psychological Bulletin, 137, 367-390. http://dx.doi.org/10.1037/a0022267
Graber, J., Lewinsohn, P., Seeley, J., & Brooks-Gunn, J. (1997). Is psychopathology associated with the timing of pubertal development? Journal of American Academy of Child and Adolescent Psychiatry, 36, 1768–1776. http://dx.doi.org/10.1097/00004583-199712000-00026
Gullone, E., Moore, S., Moss, S., & Boyd, C. (2000). The adolescent risk-taking questionnaire. Development and psychometric evaluation. Journal of Adolescent Research, 15, 231-250. http://dx.doi.org/10.1177/0743558400152003
Haffner, D. W. (1998). Facing facts: Sexual health for American adolescents. Journal Of Adolescent Health, 22, 453–459.
Herman-Giddens, M. E. (2006). Recent data on pubertal milestones in United States children: The secular trend toward earlier development. International Journal of Andrology, 29, 241–246. http://dx.doi.org/10.1111/j.1365-2605.2005.00575.x
Hertlein, K. M., & Stevenson, A. (2010). The seven “As” contributing to Internet-related intimacy problems: A literature review. Cyberpsychology: Journal of Psychosocial Research on Cyberspace, 4(1), article3. Retrieved from: http://cyberpsychology.eu/view.php?cisloclanku=2010050202&article=1
Horne, S., & Zimmer-Gembeck, M. J. (2005). Female sexual subjectivity and well-being: comparing late adolescents with different sexual experiences. Sexuality Research & Social Policy, 2(3), 25-40. http://dx.doi.org/10.1525/srsp.2005.2.3.25
Jörngården, A., Wettergren, L., & von Essen, L. (2006). Measuring health-related quality of life in adolescents and young adults: Swedisch normative data for the SF-36 and the HADS, and the influence on age, gender and method of administration. Health and Quality of Life Outcomes, 4, article 91. http://dx.doi.org/10.1186/1477-7525-4-91
Kalina, O., Madarasova Geckova, A., Klein, D., Jarcuska, P., Orosova, O., van Dijk, J. P., & Reijneveld, S. A. (2011). Psychosocial factors associated with sexual behaviour in early adolescence. The European Journal of Contraception and Reproductive Health Care, 16, 298 – 306. http://dx.doi.org/10.3109/13625187.2011.586076
Ko, C-H., Yen, J-Y., Liu, S-C., Huang, C-F., & Yen, C-F. (2009). The associations between aggressive behaviours and Internet addiction and online activities in adolescents. Journal of Adolescent Health, 44, 598-605. http://dx.doi.org/10.1016/j.jadohealth.2008.11.011
Livingstone, S., Ólafsson, K., O’Neill, S., & Donoso, V. (2012). How to cope and build online resilience? EU Kids Online. ISSN 2045-256X
Lynne, S., Graber, J. A., Nichols, T., Brooks-Gunn J., & Botvin, G. (2007). Links between pubertal timing, peer influences, and externalizing behaviors among urban students followed through middle school. Journal of Adolescent Health, 40, 181.e7–181.e13. http://dx.doi.org/10.1016/j.jadohealth.2006.09.008
Magnusson, D., Dunér, A., & Zetterblom, G. (1975). Adjustment: A longitudinal study. New York: Wiley.
Malamuth, N. M., & Huppin, M. (2005). Pornography and teenagers: The importance of individual differences. Adolescent Medicine Clinics, 16, 315–326. http://dx.doi.org/10.1016/j.admecli.2005.02.004
Mendle, J., Turkheimer, E., & Emery, R. E. (2007). Detrimental psychological outcomes associated with early pubertal timing in adolescent girls. Developmental Review, 27, 151–171. http://dx.doi.org/10.1016/j.dr.2006.11.001
Mendelson, B. K., Mendelson, M. J., & White, D. R. (2001).Body-esteem scale for adolescents and adults. Journal of Personality Assessment, 76, 90-106. http://dx.doi.org/10.1207/S15327752JPA7601_6
Nigård, P. (2012). Pornografin och sexuell exponering bland unga män och kvinnor. [Pornography and sexual exposure among young men and women]. FOU Rapport 2012:4. Licentiatavhandling.
Patrick, D. L., Edwards, T. C., & Topolski, T. D. (2002) Adolescent quality of life, part II: Initial validation of a new instrument. Journal of Adolescence, 25, 287-300. http://dx.doi.org/10.1006/jado.2002.0471
Persson, A., Kerr, M., & Stattin, H. (2007). Staying in or moving away from structured activities: explanations involving parents and peers. Developmental Psychology, 43, 197 – 207. http://dx.doi.org/10.1037/0012-1649.43.1.197
Peter, J., & Valkenburg, P. M. (2008). Adolescents' exposure to sexually explicit internet material and sexual preoccupancy: A three-wave panel study. Media Psychology, 11, 207-234. http://dx.doi.org/10.1080/15213260801994238
Petersen, A. C., Crockett, L., Richards, M., & Boxer, A. (1988). A self-report measure of pubertal status: Reliability, validity, and initial norms. Journal of Youth and Adolescence, 17, 117-133. http://dx.doi.org/10.1007/BF01537962
Rayle, A. D. (2005). Adolescent gender differences in mattering and wellness. Journal of Adolescence, 28, 753–763. http://dx.doi.org/10.1016/j.adolescence.2004.10.009
Sabina, C., Wolak, J., & Finkelhor, D. (2008). The nature and dynamics of Internet pornography exposure for youth. CyberPsychology & Behaviour, 11, 691-693. http://dx.doi.org/10.1089/cpb.2007.0179
Sinković, M., Štulhofer, A., & Božić, J. (2013). Revisiting the association between pornography use and risky sexual behaviours: The role of early exposure to pornography and sexual sensation seeking. Journal of Sex Research, 50, 633-641. http://dx.doi.org/10.1080/00224499.2012.681403
Skoog, T. (2013). Adolescent and adult implications of girls’ pubertal timing. In A.-K. Andershed (Ed.), Girls at Risk: Swedish Longitudinal Research on Adjustment (pp. 9-34). New York: Springer. http://dx.doi.org/10.1007/978-1-4614-4130-4_2
Skoog, T., Sorbring, E., Hallberg, J., & Bohlin, M. (2013). Boys’ pubertal timing measured on the pubertal development scale is linked to online sexual activities. International Journal of Sexual Health, 25, 281-290. http://dx.doi.org/10.1080/19317611.2013.815299
Skoog, T., Stattin, H., & Kerr, M. (2009). The role of pubertal timing in what adolescent boys do online. Journal of Research on Adolescence, 19, 1-7. http://dx.doi.org/10.1111/j.1532-7795.2009.00578.x
Sorbring, E., Bohlin, M., Andersson, A., & Lundin, L. (In press). Att experimentera med sitt själv. Internet och identitetsskapande. [Experimenting with the Self. Internet andidentity-formation]. In E. Sorbring, Å. Andersson, & M. Molin. Attförstå ungdomars identitetsskapande. [Understanding adolescent identity formation]. Stockholm. Liber.
Sorbring, E., Hallberg, J., Bohlin, M., & Skoog, T. (Manuscript). Parental sexual attitudes and Adolescence sexual activities.
Stattin, H., Kerr, M., & Skoog, T. (2011). Early pubertal timing and girls’ problem behaviour: integration of two hypotheses. Journal of Youth and Adolescence, 40(10), 1271-1287. http://dx.doi.org/10.1007/s10964-011-9696-9
Stattin, H., & Skoog, T. (in review). Pubertal timing and its developmental significance for mental health and adjustment.In M. Friedman (Ed.), Encyclopedia of Mental Health (2nd ed.). Academic Press.
Steinberg. L. (2011). Adolescence (9th ed.). Philadelphia: Temple university.
Subrahmanyam, K., & Greenfield, P. (2008). Online communication and adolescent relationships. The Future of Children, 18(1), 119-146. http://dx.doi.org/10.1353/foc.0.0006
Suzuki, L. K., & Calzo, J. P. (2004). The search for peer advice in cyberspace: An examination of online teen bulletin boards about health and sexuality. Applied Developmental Psychology, 25, 685–698. http://dx.doi.org/10.1016/j.appdev.2004.09.002
Thurlow, C., & McKay, S. (2003). Profiling “new” communication technologies in adolescence. Journal of Language and Social Psychology, 22, 94-103. http://dx.doi.org/10.1177/0261927X02250060
Van den Heuvel, A., van den Eijnden, R. J. J. M., van Rooij, A. J., & van de Mheen, D. (2011). Meeting online contacts in real life among adolescents: The predictive role of psychosocial wellbeing and internet-specific parenting. Computers in Human Behaviour, 28, 465-472. http://dx.doi.org/10.1016/j.chb.2011.10.018
Valois, R. F., Zullig, K. J., Huebner, S., Kammermann, S. K., & Drane, J. W. (2002). Association between life satisfaction and sexual risk-taking behaviours among adolescents. Journal of Child and Family Studies, 11, 427-440. http://dx.doi.org/10.1023/A:1020931324426
Vrangalova, Z., & Savin-Williams, R. C. (2011). Adolescent sexuality and positive well-being: A group-norms approach. Journal of Youth and Adolescence, 40, 931 – 944. http://dx.doi.org/10.1007/s10964-011-9629-7
Westling, E., Andrews, J. A., Hampson, S. E., & Peterson, M. (2008). Pubertal timing and substance use: The effects of gender, parental monitoring and deviant peers. Journal of Adolescent Health, 42, 555–563. http://dx.doi.org/10.1016/j.jadohealth.2007.11.002
Wichstrom, L. (2001). The impact of pubertal timing on adolescents’ alcohol use. Journal of Research of Adolescence, 11, 131–150. http://dx.doi.org/10.1111/1532-7795.00007
Wolak, J., Mitchell, K., & Finkelhor, D. (2007). Unwanted and wanted exposure to online pornography in a national sample of youth internet users. Pediatrics, 119, 247-257. http://dx.doi.org/10.1542/peds.2006-1891
Ybarra, M. L., & Mitchell, K. J. (2005). Exposure to Internet pornography among children and adolescents: A national survey. CyberPsychology & Behaviour, 8, 473-486. http://dx.doi.org/10.1089/cpb.2005.8.473
Correspondence to:
Emma Sorbring
University West
SE 461 86 Trollhättan
Sweden
Email: emma.sorbring(at)hv.se
Phone: + 46 520 22 37 12