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  Technology-Based Communication and the Development of InterpersonalCompetencies Within Adolescent Romantic Relationships: A PreliminaryInvestigation  Jacqueline Nesi University of North Carolina at Chapel Hill Laura Widman North Carolina State University Sophia Choukas-Bradley and Mitchell J. Prinstein University of North Carolina at Chapel Hill This study investigated longitudinal associations between adolescents’ technology-based communication and the devel-opment of interpersonal competencies within romantic relationships. A school-based sample of 487 adolescents (58%girls;  M age  =  14.1) participated at two time points, one year apart. Participants reported (1) proportions of daily com-munication with romantic partners via traditional modes (in person, on the phone) versus technological modes (textmessaging, social networking sites) and (2) competence in the romantic relationship skill domains of negative assertionand conflict management. Results of cross-lagged panel models indicated that adolescents who engaged in greater pro-portions of technology-based communication with romantic partners reported lower levels of interpersonal competen-cies one year later, but not vice versa; associations were particularly strong for boys. The ubiquitous use of technology among youthprovides a new context for the establishment andmaintenance of intimate relationships in adoles-cence (Subrahmanyam & Greenfield, 2008). Over89% of adolescents report using social networkingsites (Lenhart, 2015) and 92% report text messagingwith their romantic partners (Lenhart, Smith, &Anderson, 2015). Further, it is common for adoles-cents to use technology to resolve arguments anddiscuss sensitive family or health-related issueswith romantic partners (Lenhart et al., 2015; Wid-man, Nesi, Choukas-Bradley, & Prinstein, 2014).Although it is well established that romantic rela-tionships provide a critical context for adolescents’development of social competence (Collins & Stein- berg, 2006), little is known regarding how technol-ogy-based communication may affect this process.Social competence is a multidimensional con-struct, with two particular domains that may beimportant to adolescent romantic relationships:negative assertion (the ability to assert displeasurewith others or stand up for oneself) and conflictmanagement (the ability to work through disagree-ments and solve problems; Buhrmester, Furman,Wittenberg, & Reis, 1988). These skills are particu-larly salient within the context of romantic relation-ships, where they influence relationshipsatisfaction, negotiation of autonomy and generalsocioemotional competence (Collins, 2003).The rising popularity of computer-mediatedcommunication tools (e.g., texting, social media)has shifted the way youth communicate withromantic partners (Lenhart et al., 2015). Cues-fil-tered-out theories suggest that some of these toolscontain fewer nonverbal cues than traditional inter-actions; this may make technology-based communi-cation less “rich” (Walther, 2011). On the one hand,technologies with fewer cues may provide a safespace for adolescents to practice self-disclosureand communicate asynchronously (Koutamanis,Vossen, Peter, & Valkenburg, 2013), thus providingopportunities for greater relationship maintenance,self-disclosure, and intimacy (Valkenburg & Peter,2011). On the other hand, these technologies may This work was supported in part by National Institutes of Health Grants R01-MH85505 and R01-HD055342 awarded toMitchell J. Prinstein and R00-HD075654 awarded to Laura Wid-man. This work was also supported in part by funding from theNational Science Foundation Graduate Research Fellowship(DGE-1144081) awarded to Jacqueline Nesi. Any opinion, find-ings, and conclusions or recommendations expressed in thismaterial are those of the authors and do not necessarily reflectthe views of the NIH or NSF.Requests for reprints should be sent to Jacqueline Nesi,Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599. E-mail:nesi@email.unc.edu ©  2016 The Authors Journal of Research on Adolescence  ©  2016 Society for Research on AdolescenceDOI: 10.1111/jora.12274  JOURNAL OF RESEARCH ON ADOLESCENCE, ***(*), 1–7  result in lower quality interactions. Indeed, somework suggests that technology-based communica-tion is associated with less warmth and affection,fewer expressed affiliation cues, and lower feelingsof bonding (Sherman, Michikyan, & Greenfield,2013; Subrahmanyam &   Smahel, 2011).While technology may simply supplement tradi-tional forms of interaction (Valkenburg & Peter,2007), in some situations technology may providea substitute for youths’ traditional communication(Szwedo, Mikami, & Allen, 2012). If technology- based communication is replacing traditionalcommunication for some adolescents, and sometechnological tools lack the “richness” necessaryfor practicing complex romantic relationship inter-actions (Sherman et al., 2013; Walther, 2011),higher proportions of technology-mediated com-munication could adversely affect young people’ssocial skill development and relationship satisfac-tion (Luo, 2014). This may be particularly true of high-conflict interactions, wherein more interper-sonal cues are required to express and managenegative affect (Burge & Tatar, 2009). However,research has yet to examine the role of technol-ogy-mediated communication in the romantic rela-tionships of middle or high school–agedadolescents, or the role such communication mayplay over time.Additionally, little is known about potential gen-der differences in the role of technology in thedevelopment of interpersonal competencies. Thereare known gender differences in the frequency of technology use, with adolescent girls reportingmore social media use and texting than boys (Len-hart, 2015), but such research has not clarified howtechnology use differentially affects girls and boys.A separate, long-standing line of work indicatesthat relationship skills differ by gender, with girlsreporting higher levels of intimacy, self-disclosure,and positive conflict  –  resolution strategies withinsame-gender friendships beginning in childhood(Rose & Rudolph, 2006). Girls may thus enterromantic relationships better prepared for handlingintimacy and conflict (Maccoby, 1998). It is possiblethat increases in technology-based communicationare more detrimental to boys’ development of romantic relationship competencies, as girls mayhave developed stronger foundations of relation-ship skills through childhood friendships.This study utilized a longitudinal cross-laggeddesign to examine associations between adoles-cents’ communication patterns and the develop-ment of interpersonal competencies withinromantic relationships over 1 year. It washypothesized that greater levels of technology- based communication versus traditional forms of communication with romantic partners would benegatively associated with interpersonal competen-cies over time. It also was hypothesized that thisassociation would be stronger for boys. METHODSParticipants This study included 487 participants (58.0% girls;ages 13  –  16;  M age  =  14.1; 48.5% White/Caucasian,23.8% Hispanic/Latino, 20.6% African American/Black, 7.1% other ethnicities). Participants were85.9% heterosexual, 0.6% gay/lesbian, 5.5% bisex-ual, and 8.0% unsure/other; for multiple groupanalyses, both heterosexual and sexual minorityyouth were present in each gender group.All seventh and eighth grade students fromthree rural, low-income schools ( n =  1,463) wererecruited for a study of peer relations and healthrisk behaviors. Consent forms were returned by1,205 families (82.4%), with 900 granting consentfor participation (74.7%). Baseline data were col-lected from 868 students (32 consented adolescentshad moved, were absent, or declined participation).The current study utilizes data from the 1-year (T1)and 2-year (T2) follow-ups, when relevant mea-sures were administered. Retention exceeded 88%at T1 ( n  =  790) and T2 ( n  =  772).Only participants who reported having had adating partner within the past year at both timepoints were included in analyses. A dating part-ner was defined as “a boyfriend/girlfriend orsomeone you like ‘more than friends’ who youhave ‘talked to’ or ‘hung out with’.” This defini-tion was developed based on past literature (e.g.,Furman & Hand, 2006), as well as pilot testingand focus groups. Of the 734 participants whoparticipated at both T1 and T2, 66.5% ( n  =  488)reported having dating partners at both waves.One participant was missing data on all otherstudy variables. Thus, the final sample included487 participants.No significant differences in age or ethnicitywere found between these participants and thosewho reported no romantic relationships at eitherwave ( n  =  233). Girls were more likely than boysto report relationships at both time points( v 2 =  6.49,  p  <  .05). Adolescents’ proportion of engagement in technology-based communication atT1 did not predict whether they reported a rela-tionship at T2. 2 NESI, WIDMAN, CHOUKAS-BRADLEY, AND PRINSTEIN  Procedure Following informed assent procedures, surveyswere administered in classrooms via computer-assisted self-interviews. Each participant received a$10 gift card at both time points. All measureswere collected at both waves. Measures Proportion of technology-based versus tradi-tional communication with partner.  Participantswere oriented to the construct of   technology-basedcommunication , with  technology  defined as “texting,Facebook, and other social media (e.g., Twitter,Instagram, Snapchat, Tumblr).” Relative frequen-cies of the use of technology, versus traditionalforms of communication, were assessed by asking,“How much do you communicate with your datingpartners using your voice (in person or phone call)versus using technology on a typical day?” Thesedefinitions of   technology  and  traditional  communica-tion were chosen based on cues-filtered-outapproaches (Walther, 2011). Specifically, phone andin-person communication are similar in naturegiven their allowance for immediate feedback andmultiple vocally based interpersonal cues, com-pared to text messaging and social networkingsites. Responses were indicated on a 9-point scale(1  =  I communicate with my romantic partners mostlyin person/on phone calls , 5  =  About half in person/onphone calls and about half using technology , and 9  =  I communicate with my romantic partners mostly usingtechnology. We rarely communicate in person/on phonecalls ). Higher scores indicated higher proportionsof technology-based communication relative to tra-ditional communication. This measure was devel-oped through a focus group and two pilot samplesof 437 high school students. Interpersonal competencies within romanticrelationships.  The Interpersonal CompetenceQuestionnaire (ICQ; Buhrmester et al., 1988) wasused to assess negative assertion (e.g., “Turningdown a request by your dating partner that isunreasonable”;  a  =  .84 and .91 at T1 and T2,respectively) and conflict management (e.g.,“Admitting that you might be wrong when a dis-agreement with your dating partner begins to buildinto a serious fight”;  a  =  .83 and .90) with adoles-cents’ current or most recent dating partner.Responses were indicated on a 5-point scale (1  =  I am very bad at this , 3  =  I am okay at this , and 5  =  I am very good at this ). Several items were rewordedto accommodate the sample’s reading level. Eachsubscale contained eight items; however, one itemwas dropped from each scale due to low factorloadings. Analysis Plan Hypotheses were examined within a structuralequation modeling (SEM) framework in Mplus 7.0.Negative assertion and conflict management at T1and T2 were estimated as latent variables by creat-ing three parcels of items for each variable, withitems randomly assigned to parcels. Using parcelsallowed for increased parsimony, fewer chances forcorrelated residuals or dual loadings, and reduc-tions in sampling error (MacCallum, Widaman,Zhang, & Hong, 1999). A confirmatory factor anal-ysis demonstrated the unidimensionality of eachvariable.Cross-lagged panel models were used, providinga useful framework for testing the strength of tem-poral relations between variables collected throughlongitudinal, nonexperimental designs (Finkel,1995). Four separate models were specified as fol-lows: (1) a baseline model with only autoregressivepaths (i.e., paths from negative assertion at T1 toT2, conflict management at T1 to T2, and propor-tions of technology-based communication at T1 toT2); (2) a model with these autoregressive effectsand paths from T1 proportions of technology-basedcommunication to T2 negative assertion and con-flict management; (3) a model with the autoregres-sive effects and paths from T1 negative assertionand conflict management to proportions of T2 tech-nology-based communication; and (4) a fully cross-lagged model with autoregressive effects and all T1variables predicting all others at T2. In these mod-els, all T1 predictors and T2 error terms were cor-related with one another (Martens & Haase, 2006).Models were compared using chi-square differencetests to determine the optimally fitting model (Bol-len & Curran, 2006). Moderation by gender wasthen tested using a multiple group SEM. RESULTSDescriptives Descriptive statistics examined patterns of technol-ogy-based versus traditional forms of communica-tion and gender differences in those patterns(Table 1). Correlations between all variables werealso calculated (Table 2). TECHNOLOGY AND ROMANTIC RELATIONSHIP COMPETENCIES 3  Roughly one-third of participants (34.9%)reported that, on a typical day, they communicatedwith their dating partners approximately half thetime using technology and half the time throughtraditional communication forms (in person orphone calls), another third (32.3%) reported usingprimarily traditional forms, and the remainingthird (32.8%) reported that the majority of their communication with partners occurred viatechnology. Associations Among Technology-BasedCommunication, Negative Assertion, and ConflictManagement Four cross-lagged panel models were constructed(see Table 3). Chi-square difference testing indi-cated that Model 2 was the optimally fitting andmost parsimonious model; the added constraints of this model over Model 1 resulted in a significantimprovement in fit, while those of Model 3 didnot. In addition, Model 4 did not provide a signifi-cant improvement in fit over Model 2, suggestingthat the more parsimonious model (Model 2)should be retained. Paths from T1 negative asser-tion and conflict management to T2 proportions of technology-based communication were not signifi-cant in any models. Tests of Measurement Invariance and Gender Moderation First, measurement invariance was establishedacross gender groups. Tests of measurement invari-ance revealed consistent factor structure, and nostatistical benefit when allowing factor loadings, Dv 2 (8)  =  7.337,  p  =  .50, and all but one of the indi-cator intercepts,  Dv 2 (6)  =  11.43,  p  =  .08, to vary TABLE 1Descriptive Statistics  Full Sample Girls BoysGender Comparison M  ( SD )  N M  ( SD )  n M  ( SD )  n t  ( df  )Time 1 variablesNegative assertion 3.67 (0.82) 484 3.75 (0.81) 279 3.58 (0.83) 205 2.20 (482)*Conflict management 3.61 (0.81) 483 3.46 (0.80) 279 3.83 (0.77) 204   5.08 (481)***Proportions of technology-basedromantic partner communication a 4.85 (2.32) 449 4.83 (2.40) 264 4.89 (2.25) 185   0.24 (447)Time 2 variablesNegative assertion 3.82 (0.78) 483 3.81 (0.79) 280 3.28 (0.93) 203 6.73 (481)***Conflict management 3.37 (0.89) 483 3.40 (0.82) 280 3.34 (0.98) 203 0.69 (481)Proportions of technology-basedromantic partner communication a 5.04 (2.11) 485 5.02 (2.19) 281 5.05 (2.00) 204   0.15 (483) Note .  a Higher scores indicate greater proportions of technology-based communication (texting, social media) relative to traditionalcommunication (in person, phone calls) with romantic partners. *p  <  .05; *** p  <  .001.TABLE 2Bivariate Associations by Gender 1 2 3 4 5 6 1. T1 negative assertion  –   .33*** .10 .47*** .24***   .092. T1 conflict management .38***  –   .02 .14* .44***   .053. T1 proportions of technology-based romantic partner communication a .14   .08  –   .01   .00 .13*4. T2 negative assertion .30*** .09   .15*  –   .53**   .095. T2 conflict management .06 .27***   .27*** .65***  –    .026. T2 proportions of technology-based romantic partner communication a .02 .15* .09   .04 .01  –  Note . Results for girls reported above the diagonal. T1  =  Time 1; T2  =  Time 2. a Higher scores indicate greater proportions of technology-based communication (texting, social media) relative to traditional commu-nication (in person, phone calls) with romantic partners. *p  <  .05; ** p  <  .01; *** p  <  .001. 4 NESI, WIDMAN, CHOUKAS-BRADLEY, AND PRINSTEIN
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