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Loneliness, social support, and preference for online social interaction: the mediating effects of identity experimentation online among children and adolescentsChinese Journal of CommunicationVol. 4, No. 4, December 2011, 381–399 Loneliness, social support, and preference for online social interaction:the mediating effects of identity experimentation online among childrenand adolescents School of Journalism and Communication, The Chinese University of Hong Kong, Hong Kong This study explores the practices of online social activities among children andadolescents in order to uncover the connections between preferences for onlinesocial interaction and loneliness, social support, and the mediating effect ofidentity experimentation online. Data were gathered from a random sample of 718youngsters aged 9 to 19. Analyses revealed that individuals who are lonely andhave a lower level of ofﬂine social support ﬁnd opportunities for identityexperimentation online more gratifying than those who are less lonely or notlonely. Both loneliness and social support ofﬂine were found signiﬁcantly relatedto preference for online social interaction, but the relationships were mediated byidentity experimentation online. Finally, it was found that age differences exist. Inparticular, individuals aged 9 to 14 who are lonely and those aged 15 to 19 withlittle social support show a signiﬁcant preference for online social interaction.
Implications for future research into identity experimentation online and socialrelationship are discussed.
Keywords: children and adolescents; identity experimentation online; loneliness;preference for online social interaction; social support Past research on the preference for online communication and social interaction hasfocused on the following question: What, if any, pathological effect does preferencefor online communication have on ofﬂine social relationships (Joinson, 2004; Thayer& Ray, 2006), and what negative outcomes may result (Caplan, 2003; Kraut et al.,1998; Moody, 2001)? The present study marks an important shift from this focus byattempting to uncover an underlying process to explain how two psychosocialvariables, namely loneliness and perceived social support ofﬂine, might affect thepreference for social interaction online among adolescents. In the past, much research Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 has focused on several developmental challenges children and adolescents face today,particularly in the Internet age. They include identity formation (Schwartz & Pantin,2006), increased independence (Larson, Richards, Moneta, Holmbeck, & Duckett,1996), emotional openness on the Internet (Leung, 2003), risk-taking (Gullone &Moore, 2000), importance of peers (Haynie, 2002), and puberty and sexual develop-ment (Brown, Halpern, & L’Engel, 2005). In this study, we explore the interrelation-ships among the reasons for online social interaction, including psychosocialwell-being (i.e., loneliness and social support) and identity experimentation online.
ISSN 1754-4750 print/ISSN 1754-4769 onlineq 2011 The Communication Research Centre, The Chinese University of Hong Konghttp://dx.doi.org/10.1080/17544750.2011.616285http://www.tandfonline.com In particular, we investigate the effects of online identity experimentation asmediators.
There is growing evidence that adolescents use the Internet to experiment with their identities. Valkenburg, Schouten, and Peter (2008) found that over half of 9- to18-year-olds who use the Internet had pretended to be someone else whilecommunicating by e-mail, instant messaging (IM), or chat line. Adolescents alsospend a great deal of time posting photographs, videos, and personal information onpopular websites such as Facebook and YouTube to reveal their preferred identity.
Because they experiment with ways of expressing themselves online, some researchershave argued that the Internet is changing the way adolescents prefer to communicatewith each other about their identities (Eagle, 2007). Today’s youth are confrontedwith a media environment that is rapidly changing. Technologies are proliferating,merging, and becoming more interactive. Information and communicationtechnologies (ICT) give them more control over their identities than spontaneousface-to-face encounters because they have time to think about what they want to sayand how they want to represent themselves. The anonymity afforded by ICT allowsadolescents to construct “alternative” identities, positioning themselves differently inonline space than in ofﬂine space. Playing with identity is often promoted as a “fun”thing to do. Numerous writers have described the thrill of escape from the conﬁnes ofthe body (Turkle, 1995; Valkenburg et al., 2008). Past research suggests thatdisembodied forms of communication are particularly appealing to young peoplebecause in the adult world of ofﬂine space they are commonly treated as lessknowledgeable, less serious, and less competent than adults (Leung, 2003, 2004).
Moore and Schultz (1983) investigated the personal characteristics associated with adolescent loneliness as well as coping strategies. Loneliness was found to beassociated with reluctance to take social risks. Feelings of not being cared for and lackof being intimately tied to others may also have direct, negative effects on seekingalternative means to obtain social support. Coupled with feelings of sadness andhopelessness, adolescents reported engaging in various activities to cope withloneliness, including passively watching television or listening to music (Austin, 1985;Canary & Spitzberg, 1993). Today, the widespread use of the Internet, especiallysocial networking sites (SNS), blogs, online games, and instant messaging (IM) suchas MSN, seems to provide numerous options and channels for adolescents to copewith loneliness (Moody, 2001). As a result, they may prefer online social interactionto obtain emotional support and affectionate companionship. This study evaluatesthe hypothesis that loneliness and lack of social support in the ofﬂine world maymotivate adolescents to seek social relationships in the online world. In particular, Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 this research attempts to examine the mediating effects of identity experimentationonline in attenuating or strengthening the effects of loneliness and social support inthe preference for online social interaction.
Literature review, hypotheses, and research questions Online identity experimentation and preference for online social interaction An identity is the cognitive and effective understanding of who and what we are(Schouten, 1991, p. 413). From the perspective of symbolic interaction, part of thisunderstanding of who and what we are based on a reﬂexive evaluation, which is the way that we believe others see us (Solomon, 1983). Markus and Nurius (1986)proposed the idea of self-conception, which included the “now selves” (the self as itpresently is perceived by an individual), and the “possible selves” (images of the selfthat have not yet been realized but that are hoped for or feared). An individual’sidentity is composed of some combination of these two. Markus and Nurius (1986)also pointed out that possible selves can be considered cognitive bridges between thepresent and the future that specify how individuals may change how they are now towhat they will become.
According to Erikson (1994), forming identity and developing a coherent sense of the self is a key developmental task in adolescence and more important than anyearlier or later developmental stage. Turkle (1995) argued that the Internet is a placefor identity experimentation, providing space for self-exploration and redeﬁnition ofidentity for the possible self. Identity formation includes self-deﬁnition, which asks,“Who am I?” and experimentation with identity, which indicates testing differentaspects of social roles. The Internet allows adolescents to grasp their identity moreeasily and intensively; thus, the freedom to experiment with self-expression is attrac-tive to them (Blinka & Smahel, 2009; Yurchisin, Watchravesringkan, & McCabe,2005). Because blogs allow for the archiving of an adolescent’s memories, feelings,and reactions to various impetuses, they seem to be an ideal tool for working withidentity (Huffaker & Calvert, 2005).
For adolescents whose real lives are troubled by low self-esteem, boredom, lack of social support, or unsatisfactory personal relations, they may ﬁnd identityexperimentation more gratifying in the online communication environment, such asonline games, chat rooms, ICQ (I seek you), blogs, or social networking sites such asFacebook and MySpace. Past research on virtual communities is replete with storiesof the masks of age and race, gender and class, as well as for almost every aspect ofidentity (e.g., McCrae, 1996; Stone, 1991). This so-called freedom to recreate or toobscure some aspects of the self online allows the exploration and expression ofmultiple and fragmented selves of human existence (Gackenbach, 1998). Accordingto Turkle (1995), the “self” represented in multi-user domains or multi-usedimensions (MUD) is decentralized, ongoing, anonymous, invisible, and multiple.
As a result, an unparalleled opportunity to play with one’s identity and to “try out”new ones is possible. MUDs make possible the construction of an identity that is so“ﬂuid” and “multiple” that one can live through electronic self-representations withunlimited identities (Turkle, 1995) and, as a result, bolster one’s status, gain respect,and raise self-esteem. Similar to MUDs, a more novel and compelling discourse onsocial networking sites also possesses these special properties of ﬂuid identity, Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 allowing anonymous persona, invisibility, multiplicity, which is sometimes ongoingfor adolescent Internet users. These qualities are at the root of the holding power ofﬂuid identity and the evocative potential of online social interactions. However, fewsocial scientiﬁc works have examined the ways in which identity experimentationmight be related to Internet use or more speciﬁcally to the preference for online socialinteraction.
This study also attends to another predictor of preference for online socialinteraction: psychosocial health. For example, the loneliness experienced by some adolescent Internet users might be an indication of psychosocial distress. In broadterms, loneliness is deﬁned as a sense of deprivation in one’s social relationships(Murphy & Kupshik, 1992). Lonely people generally feel less socially competent thanother people in face-to-face situations (Leung, 2001; Spitzberg & Canary, 1985).
In their analysis of loneliness and social uses of the Internet, Morahan-Martin andSchumacher (2003) found that lonely individuals used the Internet and e-mail moreoften and were more likely to use the Internet for emotional support than others.
The reason, as explained by McKenna, Greene and Gleason (2002), might be thatlonely individuals are somewhat more likely to feel they can better express their realselves with others on the Internet than they can with those they know ofﬂine. A recentstudy by Valkenburg and Peter (2008) found that lonely adolescents used the Internetto experiment with their identity and that the social competence of lonely adolescentsbeneﬁted signiﬁcantly from these online identity experiments. Leung (2002) alsofound that loneliness is related to valence, accuracy, and the dimensions of self-disclosure in ICQ (I seek you) chat; appropriate, honest, positive, and accurate self-disclosure in ICQ might lead to decreased loneliness when one feels understood,accepted, and cared about.
In contrast, Kim, LaRose, and Peng (2009) showed that instead of relieving their original problems, individuals who were lonely could develop strong compulsiveInternet use behaviors resulting in negative life outcomes, including harming othersigniﬁcant activities, such as work, school, or signiﬁcant relationships. These negativeoutcomes were expected to isolate individuals from healthy social activities and leadthem into more loneliness (Caplan, 2003). Thus, Caplan (2007) pointed out thatalthough several studies report a signiﬁcant positive correlation between lonelinessand negative outcomes due to Internet use (Caplan, 2002; Morahan-Martin &Schumacher, 2003), the relationship between loneliness and preference for onlinesocial interaction should be further examined. Therefore, this study proposes that: Lonely individuals will ﬁnd experimenting with identity online more gratifyingthan less lonely individuals.
Loneliness is signiﬁcantly (positively) related to preference for online socialinteraction, but the relationship is mediated by online identity experimentation.
In a review of social indicators research, Cobb (1976) deﬁned social support as“information leading the subject to believe that he or she is cared for and loved, thathe/she is esteemed and valued, and he/she belongs to a network of communication Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 and mutual obligation”. Other scholars have deﬁned social support as “interpersonaltransactions involving affect, afﬁrmation, aid, encouragement, and validation of theirfeelings” (Cobb, 1976; Kahn & Antonucci, 1980). House (1986) gave a third deﬁnitionin which social support involves “the ﬂow between people of emotional concern,instrumental aid, information, or appraisal”.
Existing measures of social support are varied because of the different deﬁnitions of social support and the lack of a clear conceptualization of the construct (Donald &Ware, 1984). Recent research, however, has generally attempted to measure thefunctional components of social support. Functional support is the most importantand can be of various types providing the following: 1) “emotional support”, whichinvolves caring, love, and sympathy; 2) “instrumental support”, which provides material aid or behavioral assistance and is referred to by many as tangible support;3) “information support”, which offers guidance, advice, information, or feedbackthat can provide a solution to a problem; 4) “affectionate support”, which involvesexpressions of love and affection; and 5) “social companionship” (also called positivesocial interaction), which involves spending time with others in leisure andrecreational activities (Sherbourne & Stewart, 1991).
A sizeable body of research on social support exists, particularly in the ﬁelds of medicine and health. Social relationships and social support are potent variables thatcan reduce exposure to stress, promote health, and buffer the impact of stress onhealth, thus contributing to increases in various degrees of preference for online socialsupport (Leung, 2007, 2009; Wright, 2000). Other studies have supported the aboveﬁndings. For example, in Germany, Leimeister, Schweizer, Leimeister, and Krcmar(2008) found that virtual relationships for adult patients are established in virtualcommunities and play an important role in meeting patients’ social needs. Virtualrelationships have a strong effect on the virtual support of patients. The emotionalsupport and information exchange delivered through these virtual relationships mayhelp patients to cope better with their illness. In an international survey, Smedemaand McKenzie (2010) also found that online chat had a positive association withsocial support and well-being among individuals with visual impairments.
Furthermore, in a study of online games, Longman, O’Connor, and Obst (2009)found that the players derived social support from participating in a massivelymultiplayer online game called World of Warcraft. Positive relationships weredeveloped between game engagement and levels of in-game social support. Higherlevels of in-game social support were associated with fewer negative psychologicalsymptoms, although this effect was not maintained after controlling for socialsupport derived from the ofﬂine sources. Therefore, we hypothesize the following: Adolescents with lower levels of ofﬂine social support will ﬁnd experimentingwith online identity more gratifying than individuals with higher levels of socialsupport.
Ofﬂine social support is signiﬁcantly related to preference for online socialinteraction, but the relationship is mediated by online identity experimentation.
Differences between children and adolescents Considerable differences in developmental stages exist among children (between birthand puberty) and adolescents (aged 13 – 19). However, because puberty begins at Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 10 – 11 years of age for girls and around 12 – 13 or as late as 14 for boys, this studyconsiders children to be 14 or younger and adolescents to be between 15 and 19.
Adolescence is often characterized as a time of challenge and turbulence (Roth &Brooks-Gunn, 2000). Along with physiological changes that can be quite dramatic,adolescents are faced with increased independence and growing self-discovery.
Scholars of adolescent development refer to these changes as developmentaltransitions or passages between childhood and adulthood (Arnett, 1992). Pastresearch has suggested that during the adolescent development from childhood toadulthood, a wide range of psychological, cognitive, and physiological changes can beobserved. In today’s increasingly age-conscious society, children want to be grown-ups, so it is important to recognize the developmental differences between children and adolescent Internet users in terms of age-differentiated outcomes on mediapreferences, language, and interpersonal interactions.
Taking particular care to consider the theoretical constructs of loneliness, social support, and identity experimentation in this study, we intend to investigate howthese concepts and individual differences, in terms of level of perceived psychosocialhealth experienced by children (aged 9 – 14) and adolescents (aged 15 – 19), and theironline activities can predict their degree of preference for online social interaction.
Therefore, we posed the following research question: To what extent can demographics, loneliness, ofﬂine social support, onlineidentity experimentation, and intensity of social networking activities onlinepredict the preference for online social interaction among (a) the 9 – 14-year-oldsand (b) the 15 – 19-year-olds? Data were gathered from a probability sample of 718 children and adolescents using aface-to-face structured questionnaire interview from December 2008 to February2009. Respondents were eligible members of households randomly generated by theCensus and Statistics Department in Hong Kong. If there was more than one eligiblerespondent living in the household, the person who was between the ages of 9 and 19and had had the most recent birthday was interviewed. The interviewers were traineduniversity students. A total of 238 households were discarded when interviewersfound them vacant, for non-residential use, or ineligible, as well as when theinterviewers had no response after having visited more than three times or weresimply refused by the respondents. Of the 2,304 qualiﬁed households, 718 successfullycompleted the questionnaires, which resulted in a 31.5% response rate. Parents ofchildren under the age of 12 were requested to be present to attend the interview whenthe interviewees experienced difﬁculty answering the questions.
The sample consisted of 44.4% males and 55.6% females. The mean age was 14.46, with 14.9% in the age group of 9 – 11, 73% in the 12 – 17 year old group, and12.1% in the 18 – 19 year old group. This age distribution resembled very closely the2008 population census in Hong Kong. Of the 718 respondents, 15.3% wereelementary school students, 38.6% were junior high students, 32.4% were high schoolstudents, and 17.3% were high school graduates. In terms of family income, the meanwas in the income bracket of US$1,928 – $2,571 a month, with 10.4% earning lessthan US$1,028 a month, and 9.3% more than US$5,141 a month. In particular, Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 within the 9 – 14 age group (n ¼ 344), the mean age was 12.2, with 52.6% female, andall were in grade 8 or lower. For the 15 – 19 age group (n ¼ 374), the mean age was16.53, with 58.3% female, and over 87% were in grades 9 to 12.
The construct, preference for online social interaction, was measured using 13 itemssimilar to Caplan’s (2002, 2003) studies on the preference for online social inter-action. A 5-point Likert scale was used with 1 ¼ strongly disagree or very unlike me and 5 ¼ strongly agree or very much like me. Sample items included, “Treated betteronline than in face-to-face relationships”; “feel safer relating to others online ratherthan face-to-face”; “more conﬁdent socializing online than ofﬂine”; “morecomfortable with computers than people”; “I am willing to give up some of my face-to-face relationships to have more time for my online relationships”; “my relationshipsonline are more important to me than many of my face-to-face relationships”; and“I am happier being online than I am ofﬂine”. Reliability alpha was high at .83.
For the current study, items from Turkle (1995), Leung (2002), and Valkenburg andPeter (2008) were adopted and used to measure online identity experimentation.
Respondents were asked how much they agreed that the Internet is particularlygratifying for them to: “to try out new identities”; “to escape from who they are”;“experience things they can’t in the real world”; and “live out a fantasy”. A 5-pointLikert scale, with 1 ¼ strongly disagree and 5 ¼ strongly agree, was used in ratingthe four items. Reliability alpha was acceptable at .78.
Loneliness was measured with the UCLA loneliness scale (Russell, Peplau, &Cutrona, 1980). Reliability alpha was high at .83.
To assess social support, a battery of 19 items within four subscales developed by theRand and medical outcome study (MOS) teams was adopted with slight modiﬁcations.
The ﬁve original dimensions of social support were reduced to four; emotional supportand informational support were merged because they were highly correlated andoverlapped considerably. As a result, the four support subscales were “tangible”,“affectionate”, “social companionship”, and “emotional or informational”. It wasrecommended that the subscale scores rather than the total score be used (McDowell &Newell, 1996). Moreover, items from the tangible support subscale were excludedbecause tangible support mainly refers to medical or health related assistance fromfriends or close relatives rather than affective or emotional support. Respondents wereasked how often each of the support items measured in the remaining three dimensionswas available ofﬂine. A 5-point scale was used, where 1 ¼ none of the time, 2 ¼ a little ofthe time, 3 ¼ some of the time, 4 ¼ most of the time, and 5 ¼ all of the time. A principalcomponents factor analysis extracted three factors and explained 72.2% of the variance.
Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 Table 1 shows the three factors: “emotional and informational” support (alpha ¼ .85),“affectionate” (alpha ¼ .87), and “social companionship” (alpha ¼ .82).
All inventory items for the ofﬂine social support scale, online identity experimentation, and preference for online social interaction underwent extensivepilot testing to insure that the items were comprehensible and relevant to the sample.
The pilot testing included back-translation checks and open-ended probes.
Respondents were asked how often they used Facebook, IM/MSN, forums, and blogsusing a 5-point Likert scale, with 1 ¼ never and 5 ¼ very often. The intensities of Table 1. Factor analysis of social support.
10. Someone to do something enjoyable with Scale: 1 ¼ Never and 5 ¼ Always. N ¼ 704 (total variance: 72.20%) these four activities were combined to create a composite SNS intensity variable witha reliability alpha equal to .81.
Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 Demographic information on the respondents such as age, gender, education, andmonthly family income were assessed.
Relating loneliness and online identity experimentation H1.1 hypothesized that lonely individuals ﬁnd online identity experimentation moregratifying than less lonely or non-lonely individuals. To test this hypothesis, a simpleregression procedure was conducted with identity experimentation entered as the dependent variable and loneliness as the predictor. The result shows that lonelinesswas a signiﬁcant predictor of identity experimentation (b ¼ .17, p , .001), whichindicates that psychosocially distressed adolescents, especially those who are lonely,tended to value and enjoy the opportunity of experimenting with identities or afantasy online. Thus, H1.1 was fully supported.
Mediating effect of online identity experimentation between loneliness and preferencefor online social interaction H1.2 predicted that an individual’s level of loneliness predicts the preference for onlinesocial interaction, but that this relationship is mediated by online identityexperimentation experiences. To test this hypothesis, a series of hierarchicalregression analyses were conducted to determine the extent to which the varianceexplained by the dependent variable by the target predictors was due to the proposedmediator (Baron & Kenny, 1986; Judd & Kenny, 1981). As shown in Table 2, inregression equation 1, only the target predictor (i.e., loneliness) was entered on theﬁrst step to determine the variance it explained. This variance may containcomponents that are mediated by some other variable (here, experimentation withidentity online) and that are unique to the target predictors (i.e., direct or unmediatedby any other variables). In the next step, the proposed mediator (i.e., experimentationwith identity online) was entered into the equation. At this point, any increment in thevariance explained was necessarily due to the unique (residual) effect of the proposedmediator. In regression equation 2, the order of entry for the predictors was reversed.
The mediator was entered at the ﬁrst step and the target predictor was entered second.
Entering the mediator at the ﬁrst step determined the variance in the dependentvariable that they explained, both uniquely and in conjunction with the targetpredictor. The target predictor was entered in the second step, and any increment inexplained variance represented the direct (unmediated) effect of the predictor on thedependent variable.
As shown in Table 2, results from the regression model in equation 1 indicated that, after controlling for demographic variables and explaining 7% of the variance,loneliness (b ¼ .19, t ¼ 3.95, p , .001) by itself accounted for 3% of the variancein preference for online social interaction R 2 ¼ .03, F(1, 619) ¼ 16.19, p , .001.
In contrast, when the inﬂuence of online identity experimentation (b ¼ .43, t ¼ 9.91,p , .001) was entered in the second step, loneliness only accounted for 3% ofvariance in preference for online social interaction. However, on its own, onlineidentity experimentation accounted for 17% of the variance of the dependent variable Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 R 2 ¼ .17, F(1, 618) ¼ 39.56, p , .001.
Similarly, the hierarchical regression results in equation 2, with online identity experimentation entered ﬁrst in the ﬁrst block, also indicated that identityexperimentation (b ¼ .44, t ¼ 10.2, p , .001) was signiﬁcantly and positively linkedto the preference for online social interaction. After controlling for demographicvariables and explaining 7% of the variance, online identity experimentationexplained 19% of the total variance in preference for online social interactionR 2 ¼ .19, F(1, 619) ¼ 47.92, p , .001. When loneliness (b ¼ 14, t ¼ 3.31, p , .01)was then entered in the second step, loneliness only accounted for 1% of the variance.
By itself, identity experimentation explained 19% and a total of 27% from allpredictors.
Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 Overall, loneliness has a moderate independent effect on the preference for online social interaction. In contrast, satisfaction from online identity experimentation had arelatively large independent effect on the preference for online social interaction,accounting for 17 – 19% of the variance controlling for loneliness. The Sobel testrevealed t ¼ 4.13, p , .001. Therefore, as hypothesized, the mediation analysis fullysupports the predicted indirect effect of loneliness on preference for online socialinteraction, and this effect was mediated by online identity experimentation.
Relating social support and online identity experimentation H2.1 hypothesized that adolescents with lower levels of ofﬂine social support ﬁndonline identity experimentation more gratifying than individuals with higher levels ofsocial support. To test this hypothesis, a series of multiple regression procedures wereconducted with identity experimentation entered as the dependent variable, and thethree dimensions of social support entered on the ﬁrst step as predictors. Results showthat emotional and informational support (b ¼ 2.10, t ¼ 22.65 p , .01) andaffectionate support (b ¼ 2.11, t ¼ 22.80, p , .01) were signiﬁcant predictors ofidentity experimentation online. These results indicate that individuals who have lessofﬂine emotional and affectionate support tended to have a stronger desire toexperiment with their identity, escape from who they are, or live out a fantasy online.
However, no signiﬁcant relationship was found between the support of socialcompanionship and identity experimentation. Thus, H2.1 was, to a large degree,supported.
Mediating effect of online identity experimentation between social support andpreference for online social interaction H2.2 proposed that ofﬂine social support is signiﬁcantly related to preference foronline social interaction, but that the relationship will be mediated by online identityexperimentation. Similar to testing H1.2, a series of regression analyses wereperformed to determine the extent to which variance explained in the dependentvariable by the predictors was due to the proposed mediator (Baron & Kenny, 1986).
However, since social companionship was not a signiﬁcant predictor for identityexperimentation online, it was excluded from the regression analyses.
As shown in Table 2, results from the regression model in equation 1 indicated that, after controlling for demographic variables explaining 3% of the variance,emotional and informational (b ¼ 2.11, t ¼ 22.85, p , .01) and affectionate Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 (b ¼ 2.08, t ¼ 22.17, p , .05) support by themselves accounted for 2% ofthe variance in preference for online social interaction R 2 ¼ .02, F(3, 640) ¼ 9.49,p , .001. In contrast, when the inﬂuence of identity experimentation (b ¼ .47,t ¼ 14.4, p , .001) was entered in the second step, the two dimensions of socialsupport only accounted for 2% of variance in preference for online social interaction.
On its own, the online identity experimentation accounted for 21% of the variance ofthe dependent variable R 2 ¼ .21, F(2, 638) ¼ 51.28, p , .001.
Similarly, the hierarchical regression results in equation 2 (see Table 2), with online identity experimentation entered ﬁrst in the ﬁrst block, also indicated thatidentity experimentation (b ¼ .47, t ¼ 14.45, p , .001) was signiﬁcantly andpositively linked to preference for online social interaction. After controlling for demographic variables and explaining 3% of the variance, online identityexperimentation explained 22% of the total variance in preference for online socialinteraction R 2 ¼ .22, F(2, 640) ¼ 80.35, p , .001. Then, when emotional andinformational (b ¼ 2.09, t ¼ 22.8, p , .01) and affectionate (b ¼ 2.07, t ¼ 22.09,p , .05) were entered in the second step, social support accounted for an increment ofonly 1% of the variance. By itself, however, identity experimentation predicted 22%above that explained by two dimensions of social support alone for a total of 26% ofthe variance by all predictors. The Sobel test with emotional and informational aspredictor revealed t ¼ 22.55, p , .01, and with affectionate social support aspredictor revealed t ¼ 22.65, p , .01. Therefore, as hypothesized, the mediationanalysis largely supports the predicted indirect effect of social support on thepreference for online social interaction, and this effect was mediated by online identityexperimentation.
Predicting preference for online social interaction To examine the extent to which demographics, loneliness, ofﬂine social support,identity experimentation, and intensity of social networking activities online canpredict preference for online social interaction, two parallel hierarchical regressionswere performed – one for young children (n ¼ 344), aged 9 to 14, and one foradolescents (n ¼ 374), aged 15 to 19 (see Table 3) to uncover signiﬁcant differencesbetween the two groups.
Table 3. Hierarchical regression of demographics, loneliness, social support, online socialidentity gratiﬁcation, and SNS intensity on preference for online social interaction.
Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 Notes: Cell entries are standardized ﬁnal regression coefﬁcients. *** p , .001; ** p , .01; *p , .05; N ¼ 718 As shown in Table 3, demographic variables were entered ﬁrst in the ﬁrst block.
Being male was found signiﬁcant in predicting preference for online social interactionfor both the 9 – 14 and the 15 – 19 age groups (b ¼ .18, p , .01 and b ¼ .12, p , .05respectively). Results also showed that the 15 – 19 age group with low family monthlyincome (b ¼ 2.15, p , .01) tended to prefer online social interaction. This indicatesthat male adolescents or young adults with little family income may feel that they aretreated better online than in face-to-face relationships, feel safer relating to othersonline rather than face-to-face, are more conﬁdent socializing online than ofﬂine, andthat ofﬂine social activities may cost more money. The demographics block explained3% and 8% of the variance for the 9 – 14 and the 15 – 19 age groups, respectively.
Loneliness (b ¼ .15, p , .01) was found a signiﬁcant predictor in the second block onthe preference for online social interaction for only the 9 – 14 age group. This indicatesthat lonely youth may ﬁnd online social relationships safer and more comfortable,leading to conﬁdence and even more happiness than in face-to-face relationships. Thisblock accounted for 3% of the variance. To our surprise, when social supportvariables were entered in the third block, no signiﬁcant effect was found for the 9 – 14year old group. One possible explanation is that the questions posed to theadolescents in the questionnaire actually asked if they could get social support fromthe “ofﬂine world” when they needed it. For the 9 – 14 age group, if they were satisﬁedwith ofﬂine emotional, informational, and affectionate social support from parents,friends and their ofﬂine social network, social support in the online world may not betheir preferred source of support. In contrast, the results in Table 3 show that socialsupport predictors were found signiﬁcantly and negatively linked to preference foronline social interaction for the 15 – 19 age group (i.e., b ¼ 2.19, p , .01 foremotional & information and b ¼ 2.23, p , .001 for social companionship). Thissuggests that older adolescents, who may have difﬁculties getting socialcompanionship and emotional/informational social support ofﬂine, would prefergetting this support online. An additional 4% of the variance was explained forthis group.
Online identity experimentation was the fourth block in the stepwise regressions.
Results show that identity experimentation was signiﬁcantly linked to preference foronline social interaction both for the 9 – 14 age group (b ¼ .31, p , .001) and for the15 – 19 age group (b ¼ .24, p , .001). This suggests that adolescents who prefer onlinesocial interaction were motivated by their experiences in trying out a new identity andliving a fantasy online. This block explained the largest amount of variance at 12%and 6%, respectively, for both groups. As expected, in the ﬁnal block, SNS intensitywas found a signiﬁcant predictor for preference for online social interaction for both Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 age groups (b ¼ .24, p , .001 and b ¼ .19, p , .01). This means that heavy users ofsocial networking sites such as Facebook, blogs, IM, and forums were accustomed toonline modes of communicating with friends. These are their preferred media.
An additional 3 – 5% of variance were added to the equations and a total of 23% and25% of the variance were accounted for, respectively.
The current study principally supports the hypothesis that loneliness and socialsupport are associated with online identity experimentation. According to the theoriespresented, adolescents who suffer from loneliness ﬁnd online experimentation more gratifying than the less lonely and the non-lonely, which may be because theyperceive that the ﬂuidity of online identity may help them enjoy and experience thingsthey cannot in the real world, such as escaping from who they are, living out a fantasy,and trying out new identities.
Explaining the mediating effect of online identity experimentation The results reported above also support the proposition that online identityexperimentation is a key contributor to preference for online social interaction,indicating that adolescents who are gratiﬁed by having fun trying new identitiestended to prefer online social interaction. In fact, the theory asserts that therelationships between loneliness-preference online and social support-preferenceonline are mediated by online identity experimentation. The ﬁndings support thehypotheses that the relationships between loneliness and social support andpreference for online social interaction are spurious, and that online identityexperimentation is the confounding variable. This suggests that adolescents perceivethat being able to experiment with their identity and connect with peers online play animportant role in the development of a keen preference for online social interaction.
These results are an important contribution to the literature. This perception may bebecause in today’s increasingly age-conscious society, children want to be adults,adults want to be children, and adolescents are preoccupied with maturity and wantto be treated as grown-ups. Scholars are reporting important age-differentiatedoutcomes in media preferences, language, and interpersonal interactions (Leung,2003; Livingstone, 2008; McCann & Giles, 2002). With the popular use of socialnetworking sites, blogs, and instant messaging among adolescents, it is not difﬁcult tounderstand why identity experimentation online for the “possible self”, as argued byTurkle (1995) and Markus and Nurius (1986), has a signiﬁcant inﬂuence on thepreference for online social interaction. In fact, previous research has found thatlonely individuals turned out to have a higher preference for online interactionbecause of the Internet’s greater anonymity. Indeed, many perceive onlinecommunication as the “Prozac of social communication” (Caplan, 2003; Morahan-Martin & Schumacher, 2000).
Online space as “private” space in a crowded home Another important contribution of the study is the notion that the extensibilityafforded by identity experimentation in the online world enables adolescents to Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 reconﬁgure their social relationships and online identities in online spaces. For many,experimenting with identity online can also help to produce a “private” space in theofﬂine world. Children often have little privacy from parents and siblings within thespatial constraints of the average family home. By claiming that they need peace andquiet to use the Internet for schoolwork (although often they are using it to playgames, surf the Internet for fun, e-mail friends, or pretend to be someone online),some adolescents can appropriate a room at home for themselves. Furthermore, forthe lonely and those who are low in emotional, informational, affectionate, andcompanionship support, online space may be a place for them to feel safer relating andsocializing with others in online rather than face-to-face relationships (often theseothers are classmates or known friends), particularly for those who are more comfortable with computers than people. These adolescents are often willing to giveup some of their face-to-face relationships to have more time for their onlinerelationships.
It is also interesting to note that the relationship between social support and preference for online social interaction was negative. This ﬁnding suggests that thelack of social support ofﬂine motivates adolescents to seek support online. Suchresults are consistent with previous ﬁndings that increased ofﬂine social supportnegatively correlated with the social-compensation viewing motives that includecompanionship, pastime, habit, and escape motivations (Finn & Gorr, 1988; Leung,2007).
Contrasting young children and adolescents The regression analyses revealed three unexpected ﬁndings. First, although lonelinessplayed a signiﬁcant role in the development of preference for online social interaction,it signiﬁcantly predicted preference for online social relationships only for the 9 – 14age group, not for the 15 – 19 age group. One possible explanation is that when the15 – 19 age group are lonely, they have more choices and options to alleviate theirloneliness, for they enjoy far more independence and freedom compared with theyounger group. The 9 – 14 age group are most likely still in junior high school, whilethe 15 – 19 age group are more likely in high school or in college. As such, parentswould exercise a more restrictive or supervisory approach to the younger group, whilethe older adolescents would have more autonomy in their daily activities regardingwhere to go and what to do when they feel lonely (Livingstone, 2008). Thus, the 9 – 14age group may favor online social interaction.
A second unexpected result was the lack of inﬂuence from the dimensions of social support on preference for online social interaction, especially on the 9 – 14 agegroup but not on the 15 – 19 age group. One explanation may be that the 9 – 14 agegroup are still well protected by their parents from whom they can obtain emotional-informational, affectionate, and companionship support. In contrast, the 15 – 19 agegroup are often on their own, particularly when they are in college. As a result, whenthey are in need of social support, especially emotional-informational andcompanionship support in the ofﬂine world, they have the choice of making theattempt to seek support in the online world.
Finally, the lack of inﬂuence from affectionate social support for both age groups on preference for online social interaction may be because the items assessing Downloaded by [Chinese University of Hong Kong] at 19:57 30 November 2011 affectionate social support refer to adolescents wanting support, particularly inseeking others’ love, feeling wanted, sharing private worries and fears, andunderstanding their problems. One possible explanation is that while anonymity, roleplay, and changing identities might be vital to childhood, not all adolescentsparticipate in online activities for these reasons. It is generally known that mostadolescents write blogs and update their Facebook pages on the Internet mostly tocommunicate with people they know and because they want to be popular amongtheir current friends and to ﬁnd new friends (Moinian, 2006). Sharing private worriesand fears or seeking others’ love and feeling wanted online may not be a preferredplace for obtaining affectionate support because online relationships may beimpersonal and shallow (Kraut et al., 1998).
Limitations and suggestions for future research It would be useful to replicate the present study with longitudinal data to investigatelonger term models of the effects of loneliness, social support, and online identityexperimentation on the preference for online social interaction. This future studywould cast light on the temporal ordering of events. The model tested in the presentstudy hypothesized that loneliness and social support might alter the perception of theimportance of online identity experimentation, which in turn would lead to theincreased preference for online social interaction. It could also be argued that identityexperimentation obtained online predisposes an individual to be lonelier or furtherdeprived of opportunities to receive emotional, affectionate, and social companionsupport. Thus, a longitudinal design is required to draw conclusions regardingtemporal order and causality. Further, studies with subjects from other countries arerequired to test further the hypotheses for universality.
The work described in this paper was fully supported by a grant from the Research GrantCouncil of the Hong Kong Special Administrative Region (Project no. CUHK 4315/01H).
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© Psychological Society of South A frica. All rights reserved. South African Journal of Psychology, 40(3), 2010, pp. 241-249 Bipolar Mood Disorder in children and adolescents: in search of theoretic, therapeutic and diagnostic clarity Bruce Christopher Bradfield Psychology Department, University of Cape Town, South Africa firstname.lastname@example.org I address early onset Bipolar Mood Disord