Transitions between Subclasses of Bullying andVictimization when Entering Middle SchoolAnne Williford1*, Aaron J. Boulton1, and Jeffrey M. Jenson2

1University of Kansas, Lawrence, Kansas2University of Denver, Denver, Colorado

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .We examined the effects of depressive symptoms, antisocial attitudes, and perspective‐taking empathy on patterns of bullying andvictimization during the transition from late elementary (4th grade to 5th grade) to middle school (6th grade) among 1,077students who participated in the Youth Matters (YM) bullying prevention trial. Latent transition analysis was used to establishclasses of bullying, victimization, bully‐victimization, and uninvolvement. The intervention had a positive impact on children asthey moved from elementary to middle school. More students in the YM group transitioned from the involved statuses to theuninvolved status than students in the control group during the move to middle school. Elementary school bullies with higherlevels of depressive symptomswere less likely than other students tomove to an uninvolved status in the first year ofmiddle school.Students who held greater antisocial attitudes were more likely to be a member of the bully‐victim status than the uninvolvedstatus during the move to middle school. Perspective‐taking empathy, however, was not a significant predictor of status changeduring the transition to middle school. Implications for school‐based prevention programs during the move to middle school arenoted. Aggr. Behav. 40:24–41, 2014. © 2013 Wiley Periodicals, Inc.

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Keywords: bullying; victimization; early adolescence; latent transition analysis

INTRODUCTION

Bullying is defined as an act of peer aggression in whichamore powerful child or adolescent repeatedly exerts actualor perceived power over a weaker victim (Olweus, 1993).Bullying incidents lead to significant individual and socialconsequences for many students. Victims frequently reportincreased feelings of loneliness, depression, social anxiety,and peer rejection, and often experience poorer schooladjustment and academic performance than other youth(Haynie et al., 2001; Juvonen, Graham, & Shuster, 2003;Marini, Danes, Bosacki, & YLC‐CURA, 2006;Unnever, 2005; Schwartz, Gorman, Nakamoto, &Toblin, 2005). Although bullies stand to benefit from theirbehavior by gaining power and status among their peers(Hawley, 2003), investigators have also found that bulliesare more likely to participate in delinquent behavior and tohave less overall empathy and lower school commitmentthan their peers (Cunningham, 2007; Jolliffe &Farrington, 2006; Mouttapa, Valente, Gallaher, Rohrbach,& Unger, 2004; Unnever, 2005). Thus, the need forprevention and intervention, particularly in school settings,is clear.A variety of individual, classroom, and school‐wide

bullying prevention programs have been developed

and tested in elementary and middle schools during thepast 20 years (Jenson, 2010; Farrington & Ttofi, 2009).A common approach to preventing or reducingbullying in schools is to implement interventionsthat help children develop effective peer negotiation,conflict management, and empathy skills. Onesuch approach is the Youth Matters (YM) program,a classroom‐based intervention that promotes thehealthy development of children and youth by teachingsocial and cognitive skills, encouraging positiverelationships between students, and creating prosocialclassroom and school norms about aggressivebehavior (Jenson, Dieterich, Rinner, Washington, &Burgoyne, 2006). Findings from a group‐randomizedtrial of the YM intervention revealed significantlyless victimization among students who participated in

�Correspondence to: Anne Williford, Assistant Professor, School ofSocial Welfare, University of Kansas, Twente Hall, Room 305, 1545 LilacLane, Lawrence, KS 66044. E‐mail: awilliford@ku.edu

Received 16 July 2012; Accepted 30 June 2013

DOI: 10.1002/ab.21503Published online 9 September 2013 in Wiley Online Library(wileyonlinelibrary.com).

AGGRESSIVE BEHAVIORVolume 40, pages 24–41 (2014)

© 2013 Wiley Periodicals, Inc.

the program compared to students who receivedroutine school services and activities (Jenson &Dieterich, 2007; Jenson, Dieterich, Brisson, Bender,& Powell, 2010). In addition, a test of the interventionusing latent class analysis (LCA) revealed that studentsin the YM group transitioned from membership inbully, victim, and bully‐victim classes to an unin-volved group between the 4th and 6th grades atsignificantly higher rates than students in the controlcondition (Jenson, Brisson, Bender, & Williford, inpress). Findings from these analyses support theefficacy of YM, especially in the first year ofintervention (grade 4) and during the first year ofmiddle school (grade 6) when experimental effectswere strongest.Bullying and peer victimization in late childhood to

early adolescence, an age range of approximately 9–14years old, is an area of particular interest to researchers,teachers, and school administrators. Evidence suggeststhat rates of bullying often increase during this period asyoung people renegotiate their peer group status andsearch for new social identities (Eccles, Wigfield, &Schiefele, 1998; Harter, 1988; Kelly, Raines, Stone, &Frey, 2010). However, few studies have examinedpatterns of bullying and victimization during the criticaltransition from childhood to early adolescence, adevelopmental phase that coincides with a move fromelementary to middle school for a majority of youngpeople in the United States.In this paper, we extend prior investigations of the YM

program in several key ways. First, previously publishedYM reports focused on the effects of the interventionon rates of bullying and victimization (Jenson &Dieterich, 2007; Jenson et al., 2010; Jenson, Brisson,Bender, and Williford (in press)) and on membership inbully and victim groups at discrete time points amongcontrol participants only (Williford, Brisson, Bender,Jenson, & Forrest‐Bank, 2011). An important extensionof prior YM investigations in the current study is theapplication of latent transition analysis (LTA) toexamining longitudinal patterns of bullying and victimi-zation. Second, to our knowledge, no study to date hasexamined the influence of individual characteristics ontransitional patterns of both bullying and victimizationsubgroups. Thus, the present investigation is the firststudy, to date, to assess the influence of covariates on thetransitional patterns of bully, victim, bully‐victim, anduninvolved youth during the move from elementary tomiddle school. Accordingly, the purpose of this study isto investigate whether depressive symptoms, antisocialattitudes, and perspective‐taking empathy affect transi-tion patterns between bully, victim, bully‐victim, anduninvolved classes during themove from elementary (5thgrade) to middle school (6th grade).

Types and Characteristics of Bullying andVictimization in Childhood and EarlyAdolescence

Bullying occurs in both an overt and a relationalcontext in school and classroom settings. Overt bullyingis characterized by behaviors such as name‐calling,hitting, kicking, pushing, or by the expression of physicalintimidation and threats directed at individuals with theintention of causing physical harm (Little, Henrich,Jones, & Hawley, 2003; Olweus, 1993). Relationalbullying uses relationships as a primary means to inflictharm on others (Crick & Grotpeter, 1995; Putallaz,Kupersmidt, Coie, McKnight, & Grimes, 2004) andincludes behaviors such as talking about others (e.g.,gossiping, breaking confidences, rumor spreading) andemploying exclusionary actions (e.g., ignoring, ostraciz-ing) (Crick & Grotpeter, 1995; Owens, Shute, &Slee, 2000; Paquette & Underwood, 1999; Pepler, Craig,Yuile, & Connolly, 2004; Underwood, 2003).Studies have consistently found that certain social and

behavioral characteristics are associated with bullyingbehavior and peer victimization. For example, bullies aremore likely to participate in other forms of antisocialconduct, havemore antisocial peers and greater antisocialattitudes, and evidence less social competence, lowerlevels of overall empathy and friendship quality thanother children (Bollmer, Milich, Harris, & Maras, 2005;Cunningham, 2007; Haynie et al., 2001; Jolliffe &Farrington, 2006; Mouttapa et al., 2004; Olweus, 1991;Unnever, 2005). However, it is also important to note thatin some cases bullies are actually perceived by their peersas being socially powerful or influential (Vaillancourt,Hymel, & McDougall, 2003). Juvonen et al. (2003)found that aggressive youth often enjoyed higher socialstatus than other children in school. At the same time,however, they noted that many students avoid socialcontacts with peers who act aggressively toward others.Victims on the other hand consistently report higherlevels of internalizing problems, such as anxiety anddepression, and lower levels of self‐esteem and socialcompetence than other children (Haynie et al., 2001;Juvonen et al., 2003; Marini et al., 2006; Paquette &Underwood, 1999; Roland, 2002; Unnever, 2005).Further, victims experience lower friendship quality, acondition that may be related to lower levels of overallsocial competence (Bollmer et al., 2005).Of note, low levels of empathy have been hypothesized

to predict bullying behavior (Olweus, 1991), an assertionthat is supported by findings from a recent study in whichlow total empathy—a combination of both affective andcognitive empathy—was associated with violent bully-ing among boys and indirect bullying among girls(Jolliffe & Farrington, 2006). Higher levels of empathy

Aggr. Behav.

A Latent Transition Analysis 25

have been found among bystanders, or uninvolved youth,particularly among youth who may be more likely todefend victims (Caravita, Di Blasio, & Salmivalli, 2009;Gini, Albiero, Benelli, & Altoè, 2007; Nickerson, Mele,& Princiotta, 2008). Thus, understanding the role ofempathy in predicting class membership in bullyand uninvolved subclasses as well as understandinghow empathy may influence transitions among thesesubclasses is highly relevant, particularly in light ofcommon prevention approaches that target empathy skillbuilding (i.e., Olweus Bullying Prevention Program;Olweus, 1993).In sum, bullying and victimization are complex

behaviors characterized by overt and relational formsof aggression. Involvement in bullying increases thelikelihood of adopting antisocial attitudes and engagingin other forms of antisocial behavior for many of theyouth involved. Youth who engage in bullying also oftenevidence lower levels of empathy. Thus, lower levels ofempathy and higher levels of antisocial attitudes arethought to be key characteristics differentiating bulliesfrom other children. For victims, higher levels ofinternalizing difficulties are common, with depressionand social anxiety being important factors distinguishingvictims from bullies and those uninvolved. For unin-volved or bystander youth, empathymay be a particularlysalient characteristic for understanding how childrenmayeither remain uninvolved or transition to an uninvolvedsubclass during themove tomiddle school. The transitionfrom childhood to adolescence, simultaneous with themove from elementary to middle school for many youngpeople in the United States, is a particularly vulnerablephase for some youth, whichmay account for the changessome studies have reported in bullying and victimizationinvolvement.

Bullying and Victimization During theTransition to Middle School

The transition from late childhood to early adolescencerepresents a developmental period of rapid emotional andphysical changes. Many young people experiencepersonal insecurity and social uncertainty as a result ofthese changes (Adams, Bartlett, & Bukowski, 2010). Inaddition, a majority of youth in the United States movefrom smaller and more supportive elementary schoolsettings to larger and less‐personal middle school settingsas they enter adolescence. As youth enroll and beginmiddle school, they are often confronted by the need toform new friendships and re‐negotiate their peer groupstatus and social identities (Eccles et al., 1998; Kellyet al., 2010). While most youth navigate these changesrather well (Adams et al., 2010; Pellegrini &Long, 2002), others find it difficult to adjust and formnew friendships during this transitional period. More

important, changes in peer relationships during the movefrom elementary to middle school have been associatedwith increases in bullying and peer victimization(Pellegrini & Long, 2002; Williford et al., 2011).Relatively few longitudinal studies have examined

actual patterns of bullying and victimization as childrenleave elementary school and enroll in secondaryeducation. However, some evidence suggests thataggressive behavior among students who bully theirpeers is relatively stable during the transition fromelementary school to middle school (Adams, Bukowski,& Bagwell, 2005; Camodeca, Goossens, Terwogt, &Schuengel, 2002; Huesmann, Eron, Lefkowitz, &Walder, 1984). In other words, a notable proportion ofchildren who bully their classmates in elementary schoolcontinue to be perpetrators during middle school. Thisfinding is consistent with work in developmentalpsychopathology that suggests a progression of involve-ment in delinquency and other antisocial conduct forsome youth as they move from childhood to adolescence(Loeber & Hay, 1997). Consequently, it is likely thatcertain individual characteristics may influence whetherchildren remain bullies during the move to middle schoolor may transition into other subgroups.The assessment and interpretation of changes and

patterns in bullying and victimization over time ischallenging. Common approaches to understandingbullying and victimization subgroups have generallyemployed traditional classification systems that usearbitrary cut‐off points (e.g., Solberg & Olweus, 2003).Recently, several investigators (e.g., Giang & Graham,2008; Nylund, Asparouhov, & Muthén, 2007) havesuggested that understanding the complex nature ofbullying and victimization requires more sophisticatedanalytic approaches. To this end, investigators havebegun to focus on victimization and bullying typologiesusing person‐oriented analyses such as LCA and LTA.These techniques are discussed in more detail below butwe briefly note here that LCA is used to identifyunobserved heterogeneous subgroups at a single point intime and LTA is used to understand how people transitionbetween the unobserved subgroups over time. Althoughstudies in this area are still relatively few in number, somegeneral patterns have emerged. When looking atvictimization separately, there appear to be distinctsubgroups of children based on the severity of thevictimization as opposed to the type (e.g., physical,verbal). Nylund, Bellmore, Nishina, and Graham (2007)found three distinct subclasses of victimization: avictimized class, a sometimes victimized class, and anon‐victimized class. The sometimes victimized classwas characterized by children who had a higherprobability of being called names but a lower probabilityof experiencing more severe victimization. A similar

Aggr. Behav.

26 Williford et al.

structure was found in a study by Wang, Iannotti, Luk,and Nansel (2010) using a different measure ofvictimization. To our knowledge, a typology of bullyingonly has not been examined using LCA or LTA.When examining bullying and victimization together, a

four class solution—bullies, victims, bully‐victims, anduninvolved children—appears to be the most plausible.Lovegrove, Henry, and Slater (2012) identified thissolution in a sample of 3,114 American students in 40middle schools across 13 different states. Giang andGraham (2008) found a similar solution in a comparablylarge sample (N¼ 2,144) although the bully‐victim classwas further comprised of two subgroups that dependedon whether victimization or bullying behaviors weremore likely. Finally, previous analyses using YM dataJenson, Brisson, Bender, and Williford (in press) found afour class‐solution best fit the data and revealed groupscharacterized as bullies, victims, bully‐victims, anduninvolved youth at each of the three time points in4th, 5th, and 6th grades.Although research on unobserved subtypes of bullying

and victimization is increasing, relatively little work hasbeen conducted to examine how bully and victim groupschange over time. In one of two noteworthy exceptions,Pepler, Jiang, Craig, and Connolley (2008) examined thetrajectories of bullying for four different subgroups ofchildren over a seven year period that included thetransition from K‐8 schools (kindergarten through 8thgrade) to high school. These four groups included studentswho reported consistently high rates of bullying, studentswho reported early moderate levels of bullying butdecreased over time, students who reported low initiallevels of bullying but increased to moderate levels overtime, and students who did not bully others consistentlyover time. The authors also found that childrenwith higherlevels of self‐ (e.g., aggressive), family (e.g., parentalconflict), and peer (e.g., peer conflict) risk were morelikely to experience consistent bullying or an increase inbullying trajectories over time. Moreover, Nylund (2007)identified three classes of victimization by degree amongmiddle school students and examined how the studentstransitioned between classes over time using LTA.Overall,she found that students weremore likely to transition to theless victimized classes over time. She also found that earlyexposure to victimization in middle school had a residualeffect such that students victimized early in middle schoolwere more likely to remain in the victimized class.Students in this class felt less safe at school, more sociallyanxious, andmore depressed throughout grades 6, 7, and 8than other students. Importantly, school safety, anxiety,and depression were included as time‐varying predictorsof class membership at each time point but were notspecified as predictors of the probability of transitioning toother classes over time. To date, studies in this area have

not examined predictors of transition between subgroupsof bullies and victims over time.In sum, longitudinal studies spanning late childhood

and early adolescence have led to a deeper understandingof the desistance and persistence of bullying andvictimization as students enter middle school. However,these investigations have been limited primarily todescriptive accounts of membership in bully, victim,bully‐victim, and uninvolved groups at discrete timepoints (e.g.,Williford et al., 2011). Further, with very fewexceptions (e.g., Nylund, 2007), investigators have notfocused on patterns of bullying and victimization duringthe early adolescent or middle school years. Finally,longitudinal investigations spanning late childhood andearly adolescence are lacking, particularly amongsamples of predominantly low‐income, minority childrenand adolescents.

The Present Study

The move from elementary to middle school is acritical developmental period for young people. Yetrelatively little is known about how behaviors such asbullying and victimization change during this importantdevelopmental phase. To that end, this study uses LTA toexamine the transition patterns among bully, victim,bully‐victim, and uninvolved classes of youth during themove from late elementary to middle school. Currentlimitations of LTA restrict our analyses to individual levelcharacteristics. Thus, the impact of depressive symp-toms, antisocial attitudes, and perspective‐taking empa-thy on the transition probabilities between involved anduninvolved subgroups is examined in the currentanalyses. Our hypotheses are: (1) higher levels ofdepressive symptoms in grade 5 will increase thelikelihood of children staying in a victim class ortransitioning into a victim class from other classes asstudents transition into middle school; (2) higherantisocial attitudes in grade 5 will increase the likelihoodof children staying in a bully and/or bully‐victim class ortransitioning into a bully and/or bully‐victim class fromother classes as students transition into middle school; (3)higher levels of perspective‐taking empathy in grade 5will increase the likelihood of children staying in anuninvolved class or transitioning into an uninvolved classfrom other classes as students transition into middleschool; and (4) lower levels of perspective‐takingempathy in grade 5 will increase the likelihood ofchildren staying in a bully class or transitioning into abully class from other classes as students transition intomiddle school. We frame these hypotheses with regard tograde 5 measurements of the predictors because thesemeasurements immediately precede the transitions ofinterest (e.g., transitions during the move from elemen-tary to middle school).

Aggr. Behav.

A Latent Transition Analysis 27

We also hypothesize that the transitions between grades4 and 5 will differ from the transitions between grades 5and 6 as children move from an elementary to a middleschool context. In light of evidence that changes in peerrelationships during this move have been associated withincreases in bullying and peer victimization (Pellegrini &Long, 2002; Williford et al., 2011), we expect thatchildren may be more likely to transition into the bullyand bully/victim from other subclasses as they move into6th grade. Specifically, we believe the number of studentsin these classes will increase over time and that theprobabilities of transitioning between classes will not beequivalent for the transition from grade 4 to 5 compared tothe transition from grade 5 to 6. Finally, consistent withprior YM findings Jenson, Brisson, Bender, andWilliford(in press), we hypothesize that intervention participantswill transition into the uninvolved class more frequentlythan control group participants.Knowledge of the factors that contribute to transitions

from involved to uninvolved bully and victim subclasses iscritical to increasing the efficacy of bullying prevention andintervention efforts. Finding the optimal time to deliverpreventive interventions is also critical. Some investigatorshave argued that delivering interventions in later elemen-tary school, just prior to the move to middle school, maybetter prepare students for a successful transition (Jenson,Powell, & Forrest‐Bank, 2011). Given that antisocialattitudes, empathy, and depressive symptoms are found tobe critical markers of bullying and victimization classmembership, examining how these characteristics affecttransition patterns is particularly relevant.

METHOD

Participants

The data for this study were collected during a group‐randomized trial of the YM program in 28 publicelementary schools in Denver, Colorado; 4th and 5thgrade classrooms in 14 experimental and 14 controlgroup schools participated in the investigation. In thecontrol schools, 674 eligible students were contacted forparticipation. Of these, 68% consented, 16% declined,and 16% did not return the consent form, resulting in acontrol‐group sample size of 462 consented students. Inschools receiving YM, 928 eligible students werecontacted for participation of which 76% consented,11% declined, and 14% did not return the consent. Thus,at baseline the experimental group contained 702students. Of these 1,164 students, only 1,077 studentscompleted study measures on at least one measurementoccasion and thus this number comprises the final samplefor this study.Gender was balanced in both groups (49% female in

the control group; 53% female in the intervention group).

Participants averaged 10.2 years old (SD¼ .50) at thebaseline. The sample was diverse with the majority ofstudents in the control group reporting being Latino/a(51%) followed by American Indian, Asian American, ormixed race/ethnicity (21%), African‐American (17%),and Caucasian (11%). In the experimental group, 65% ofparticipants reported being Latino (65%), again followedby Indian, Asian American, or mixed race/ethnicity(14%), African‐American (13%), and Caucasian (8%).These proportions were similar to those found in thelarger Denver public school district (Jenson &Dieterich, 2007).Although our primary hypotheses centered on the

effects of depressive symptoms, antisocial attitudes, andempathy on the transition patterns during the move tomiddle school for students in general, many of theanalyses were conducted for the overall sample as well asthe intervention and control groups separately. Becausesome of the students in the sample were exposed to anintervention, we decided it was necessary to provideresults separately for the two treatment conditions toexamine the effects of the covariates regardless ofwhether students were exposed to an intervention.

Procedure

Students responded to surveys administered in the falland spring of the 2003–2004 and 2004–2005 academicyears while enrolled in elementary school. YM imple-mentation lasted for both years and a 12‐month follow‐upwas conducted after completion of the program in 2005.The program is curriculum‐based, consisting of 10modules administered over the course of a singleacademic year. Each module is designed to fosterpositive interactions between adults and students in theschool setting and instill peer and social norms againstbullying. The modules are interactive and encouragecreativity and critical thinking. Only the spring measure-ments in 4th, 5th and 6th grade were used. Thus, theinitial time point in the analyses was the spring of 4thgrade, followed by spring of 5th grade, with the last timepoint being the spring of 6th grade, which occurredduring students’ first year in middle school.

MeasuresBullying/victimization. Variables from the global

scales of the Revised Olweus Bully/Victim Question-naire (Olweus, 1996) were used as the latent class/statusindicators in this study. This questionnaire has two six‐item global scales, one of which measures the extent towhich the respondent engages in bullying behaviors andthe other the extent to which the respondent is a target ofsuch behaviors. The response format is a five‐point Likertscale (1¼ “never”, 2¼ “only once or twice”, 3¼ “two orthree times a month”, 4¼ “about once a week”, and

Aggr. Behav.

28 Williford et al.

5¼ “several times a week”). The scale items forvictimization are prompted with the statement, “Haveyou been bullied since the beginning of the school year inone or more of the following ways?”. The six items thatfollow are: (a) I was called mean names, made fun of, orteased in a hurtful way; (b) other students kept me out ofthings on purpose, excluded me from their group offriends, or completely ignored me; (c) I was hit, kicked,pushed, or shoved around; (d) other students spread falserumors about me and tried to make others dislike me; (e) Ihad money or other things taken from me or damaged;and (f) I was threatened or forced to do things I did notwant to do. Two of these items reflect relational (orindirect) aggression and the other four reflect overt(direct) aggression (Little et al., 2003). The six itemsfrom the bullying scale are similar with the exception thatthe prompt and question wording asks the respondenthow often they have performed the behavior towardsanother classmate. The OBVQ is frequently used inbullying research and has demonstrated desirablepsychometric properties in several studies (e.g., Kyr-iakides, Kaloyirou, & Lindsay, 2006). For the victimiza-tion items in grades 4, 5, and 6, the ordinal alphacoefficient (Zumbo, Gadermann, & Zeisser, 2007) was.88, .88, and .90. For the bullying items, ordinal alphawas .94, .92, and .91, in grades 4, 5, and 6.For the present analysis, the items were dichotomized

according to criteria suggested in Solberg and Olweus(2003). This was done for several reasons. First,preliminary analyses using the original ordinal metricresulted in convergence issues due to the large number ofparameters being estimated. Second, grade‐specific LCAanalyses did not result in discernible class solutions, evenfor those with the best relative model fit. Third, previousstudies on bully/victim typologies have also useddichotomous outcomes (Lovegrove, Henry, & Slater,2012)—including a previous study using this sample(Williford et al., 2011)which has resulted in a replicabletypology that matches theoretical assertions regardingbullying subgroups. Finally, the cutoff value we used toclassify student responses has been empirically derivedand is often used for prevalence estimation (Solberg &Olweus, 2003). Specifically, if a student responded to the“two or three times a month” category or higher, theyreceived a score of 1 for the item. All responses for lowercategories were assigned a score of 0.Depressive symptoms. Depressive symptoms

were measured by a nine‐item scale adapted fromlongitudinal studies conducted by the Social Develop-ment Research Group (https://www.uwsrd.org/sdrg/in-dex.asp) asking respondents about their feelings in thepast month. The response scale was a three‐point Likertscale (“not true”, “sometimes true”, “true”) with itemsassessing activity enjoyment (“I didn’t enjoy anything at

all”, “I did everything wrong”), lethargy (“I felt so tired Ijust sat around and did nothing”), overall confidence andself‐concept (“I felt that there are a number of good thingsabout me”, “I felt I was able to do things as well as mostpeople,” “I thought I could never be as good as otherkids”), focus and restlessness (e.g., “I found it hard to payattention and focus”, “I was very restless [couldn’t sit stillor be quiet]”), and loneliness (e.g., “I felt lonely”). Two ofthe items were positively worded and thus reverse‐coded.The ordinal alpha was .80.Antisocial attitudes. To assess antisocial atti-

tudes, students responded to a five‐item scale from theCommunity that Cares (CTC) survey (Glaser, Van Horn,Arthur, Hawkins, & Catalano, 2005). The items wererated on a four‐point Likert scale, ranging from “notwrong at all” to “very wrong,” in relation to a range ofantisocial behaviors (“Stay away from school all daywhen their parents think they are at school,” “Pick a fightwith someone,” “Cheat on a test at school,” “Smokecigarettes,” “Steal something worth more than 5dollars”). A large validation study (N¼ 172,628)suggested the antisocial attitudes scale demonstratedadequate construct validity and had an equivalent factorstructure over five different racial/ethnic categories andboth genders (Glaser et al., 2005). The ordinal alphacoefficient in the current sample was .91.Perspective‐taking empathy. The perspective‐

taking subscale of the Interpersonal Reactivity IndexDavis (1980) was used to assess perspective‐takingempathy on a four‐point Likert scale (YES!, yes, no,NO!). Items ask respondents in general whether theyconsider others’ feelings (“Before I dis someone I try toimagine how I would feel,” “When I’mmad at someone Itry to imagine how they feel,” “I try to understand myfriends better by imagining what things are like forthem”) and whether they weigh both sides of a situationequally (“I believe there are two sides to every question”,“When my friends are having a disagreement I listen toboth sides”). The perspective‐taking subscale has shownsufficient internal and test–retest reliability in previousstudies (e.g., Davis, 1980) as well as evidence ofconstruct validity (Davis, 1983). Specifically, thesubscale related in predictable ways to measures ofsocial functioning, emotionality, self‐esteem, and sensi-tivity to others, as well as other unidimensional empathyscales. In the current study, the ordinal alpha coefficientwas .86.

Analytic Procedures

LTAwas used to analyze the data. LTA is used to modeldiscrete or stage‐wise development within the structuralequation modeling (SEM) framework (Collins &Lanza, 2010). In SEM, unobserved latent variables aredefined by a set of observed variables. These latent

Aggr. Behav.

A Latent Transition Analysis 29

variables are theoretically free of measurement error. Theprimary advantage of SEM over other statisticaltechniques, then, is the unattenuated, error‐free estima-tion of relationships between unobserved constructs.Latent variables in SEM often represent continuousvariables such as attitudes, beliefs, or affect. However, inLTA the latent variables are categorical and representunobserved classes of individuals. An example LTAmodel is shown in path diagram form in Figure 1a. In thediagram, c1 and c2 are the categorical latent variablesrelated to the same set of observed variables at twoseparate occasions. Several distributional forms arepossible for the observed variables. The latent variablesc1 and c2 represent two or more classes of individuals ateach time point. The nature of the classes is implied bythe observed response patterns that typify each class. InLTA, individuals are allowed to switch classes (i.e.,transition) over time, or remain in the same class. As aconsequence, the term status is commonly used insteadof class to denote the time‐specific classification ofpersons. For the remainder of this article, we use the term

class in reference to a latent subgroup in a cross‐sectionalmodel and the term status in reference to a latentsubgroup in a longitudinal model.Three types of parameters are estimated in LTAmodels

with categorical indicators: item‐response probabilities,status prevalences, and transition probabilities (Lanza &Collins, 2008). For binary observed variables such asthose used in the present study, an item responseprobability represents the probability that an individualwill endorse an item conditional on their statusmembership. Item response probabilities are useful forunderstanding the nature or quality of the latentsubgroups. Status prevalences quantify the estimatedproportion of a sample belonging to a specific status. Thestatus prevalences will sum to 1 at each time point whichimplies the exclusive and exhaustive classification ofindividuals. Finally, estimated logistic regression coef-ficients from the multinomial logistic regression of latentstatus variables on earlier latent status variables are usedto calculate transition probabilities which describe thetendency for individuals in a given latent status to remainin the same status or transition to another status betweenmeasurement occasions.We analyzed the data in accordance with steps outlined

by Nylund (2007), which were abbreviated for the presentstudy. First, descriptive statistics were calculated todescribe the observed variables and covariates (Step 0).Next, we verified LCA results from Jenson, Brisson,Bender, and Williford (in press) (Step 1) by estimatingunconditional LTA models to determine the optimalnumber of latent statuses (Step 2). Unconditional in thiscase means that predictor variables were not yet included,such as the model in Figure 1a. An optimal model wasselected and transition probabilities were inspected.Included in this step were tests of prevalence equality(i.e., did the sizes of the statuses change over time?) as wellas stationarity (i.e., are the transition probabilities equalover time?). In the final step, predictors of latent statusmembership in the 5th grade as well as the transitionprobabilities between the 5th and 6th grade were evaluated(Step 3). Note that the 4th grade latent status was notincluded in the final model as our focus was on thetransition between elementary and middle school. A pathdiagram of this model, referred to as the conditional model,is shown in Figure 1b. The dashed line from the set ofpredictors to the arrow between the 5th and 6th grade latentstatus variables implies that the transition probabilities arebeing expressed as a function of the predictors.Muthén andAsparouhov (2011) indicate that this relationship isessentially an interaction between the initial latent statusvariable and one or more predictor variables.The optimal number of statuses in the LTAmodels was

determined by comparing the fit of several models.Models were compared according to the Bayesian

b

Gender | Ethnicity | Depression | Antisocial Attitudes | Empathy

5th

y3y2y1

6th

y3y2y1

a

c1

y3y2y1

c2

y3y2y1

Fig. 1. Latent transition analysis path diagrams. In this figure, boxesrepresent observed variables, circles represent categorical latent statusvariables, one‐headed arrows represent multinomial logistic regres-sion paths, and two headed arrows represent variances. In (a), anunconditional LTAmodel is specified. The regression arrow representsthe transitions that occur between the two latent status variables, c1and c2. In (b), the status prevalences in the 5th grade and the transitionprobabilities (dashed line) in the 6th grade are predicted by the set ofvariables in the box. Due to the specification of the transitionprobabilities being a function of the predictor variables, the effects ofthe predictors on the 6th grade prevalences are not actually estimated(see Muthén & Asparouhov, 2011).

Aggr. Behav.

30 Williford et al.

Information Criterion (BIC; Raftery, 1995). Lowervalues of the BIC, which corrects for differences inmodel degrees of freedom, are reflective of better data‐to‐model fit. Also, an entropy statistic is reported thatreflects latent class separation (Celeux & Soromenho,1996). The entropy value can range between 0 and 1 withvalues closer to 1 reflecting greater class separation.There is no cutoff value associated with this statistic andit is generally not used for model comparison, but it canbe informative of solutions with low class separation. Alarge simulation study found that the BIC was the bestindicator of the true number of latent classes among allinformation criterion (Nylund et al., 2007a).All models were estimated in Mplus Version 7.0

(Muthén & Muthén, 2012). Missing data were accom-modated via full‐information maximum likelihood(FIML), which is one of the two “state‐of‐the‐art”approaches for dealing with missing data (Enders, 2010).As opposed to imputation procedures, FIML is anestimation‐based procedure that uses all available dataduring optimization and provides unbiased parameterestimates and standard errors given the assumption of aMAR or missing at random process. In order to addressthe multilevel data structure (i.e., students nested withinclassrooms), a robust maximum likelihood estimationprocedure was used that provides corrections to modelstandard errors and the chi‐square value (cf. Hox, Maas,& Brinkhuis, 2010). Finally, LTA models are known toproduce local solutions with maximum likelihoodestimation, which means that optimal parameter esti-mates were not found despite convergence beingreached. As such, it is recommended to optimize severalsets of random starting values during model estimation(Collins & Lanza, 2010;Muthén and Asparouhov, 2011).If the model likelihood value replicates for at least somestarting value sets, then it is likely that a global andtherefore optimal solution of FIML estimates has beenobtained. Each model was estimated using 100 randomstarting value sets; any issues pertaining to convergenceare noted hereafter.

RESULTS

Step 0: Descriptive Statistics

Descriptive statistics for the 12 status indicatorvariables are provided in Table I. Results are reportedseparately by grade. For each grade, the proportion ofstudents endorsing a given item is reported in the firstcolumn, and the item intraclass correlation coefficients(ICCs) are presented in the second column. Each ICCvalue represents the proportion of variance attributed toclassroom‐level differences. As noted earlier, clusterswere defined as a shared teacher. For each item, greaternumbers of students endorsed the victimization items as

compared to the bullying items in both grades. Thispattern was expected as most studies report greater ratesof self‐reported victimization among children comparedwith self‐reporting bullying (Nansel et al., 2001). Withthe exception of two items—items 1 and 3 in Table I—theproportion of students endorsing each victimization itemdecreased by the 6th grade. Similarly, the proportion ofstudents endorsing each bullying item either increased ordid not change for 5 of the 6 items.

Step 1/2: Unconditional LTA

In the Nylund (2007) study, cross‐sectional LCAmodels were estimated at each timepoint to determine theoptimal number of time‐specific classes. An uncondi-tional LTA model was then estimated to verify that anoptimal number of statuses was satisfactory over time.These were considered Steps 1 and 2, respectively.Grade‐specific LCA models for the data used in thepresent study are reported in Jenson, Brisson, Bender,andWilliford (in press); recall that a four‐class solution—bullies, victims, bully‐victims, and uninvolved students—was found to be optimal. As such, we skipped Step 1and proceeded to estimate an unconditional LTA modelto verify the results in Jenson, Brisson, Bender, andWilliford (in press). Specifically, several unconditionalmodels (i.e., no covariates were included) were estimatedto validate the 4‐status solution in the 4th, 5th and 6thgrades. For these and all subsequent models, the item‐

response probabilities were specified as invariant overtime in order to ensure the same statuses were beingmeasured in each grade (Collins & Lanza, 2010). Onceagain, solutions ranging between 2 and 6 latent statuseswere considered. Model fit information is providedTable II. The lowest BIC value was found for the 5‐statussolution and the second lowest was found for the 4‐statussolution. However, inspection of the item‐responseprobabilities revealed a fifth latent status that wasuninterpretable and did not conform to any of thetheoretical structures previously mentioned. Therefore,although the 4‐status solution was the second‐best fittingsolution, we believe it was the most interpretable andproceeded to use it for the final conditional model.Item‐response probabilities for the unconditional LTA

model are presented in Table III. Recall that an itemresponse probability represents the probability thatmembers of a particular class or status will endorse agiven item. For the first status shown in the first column,item response probabilities were high for name calling,excluding other students, hitting/kicking, and spreadingrumors. The other item response probabilities were low,and thus this status was labeled as the Bully status. Thestatus in the second column showed an opposite patternin which probabilities were high for being called names,being excluded, being hit, kicked, or shoved, and having

Aggr. Behav.

A Latent Transition Analysis 31

rumors spread about the respondent. Thus, this status waslabeled the Victim status. The third latent status had highitem response probabilities for all items with theexception the items concerning stealing and forcing orthreatening other students; however, even these item‐

response probabilities were non‐ignorable. This statuswas clearly characterized by severe victimization andbullying and also had the lowest prevalence at each timepoint. We labeled this status the Bully/Victim class.Finally, the status in the final column had low itemresponse probabilities for all items, and was thus labeledthe Uninvolved status.Status prevalences and transition probabilities for the

unconditional LTA model are presented in Table IV. Inthe upper panel of Table IV, we provide the estimatedprevalences of each latent status across grades 4, 5, and 6.The results are presented for the overall sample as well asthe intervention and control conditions. Chi‐squaredifference tests were conducted to determine whetherthere were significant changes in status membershipduring the transition from grades 4 to 5 and from grades 5to 6. Beforewe present these results, however, we caution

that the sample sizes were largely unequal between thethree groups and thus the size of the prevalence estimatesare just as important for interpretation. In all three groups,predicted membership in the Bully status increased overtime, although the increases were not significant.Conversely, membership in the Victim status decreasedover time. The decrease was significant for the overallsample during both transitions and between the 4th and5th grade for students in the intervention. A consistentpattern for the Bully/Victim status was found across thethree groups. Specifically, the number of students in theBully/Victim status decreased between grades 4 and 5(significantly for the overall sample and the twosubsamples) but then increased between grades 5 and 6(significantly for the overall sample and the interventionsubsample). Although one could say this result suggeststhe transition to middle school appears to be in favor ofstudents in the control condition, we note that: (a) theintervention condition had a substantially greater numberof participants compared to the control condition; (b) theincrease in membership was approaching significance inthe control condition; and (c) the prevalence estimateswere nearly identical. Finally, the number of students inthe Uninvolved condition increased for the interventionsubsample but decreased in the control subsample. In theoverall sample, a significant increase occurred betweengrades 4 and 5 but remained stable during the transition tomiddle school. In summary, it appears students becamemore aggressive during the transition to middle school assuggested by the increased number of moderatelyaggressive (Bully) and severely aggressive (Bully/Victim)students in all three groups. Also, in accordance withprevious research (Nylund, 2007), the number ofstudents in the Victim status decreased over time in allthree groups and the number of students in the

TABLE I. Response Category Proportions and ICC Values for OBVQ Items

4th grade 5th grade 6th grade

p ICC p ICC p ICC

1. I was called names or teased .54 .02 .54 .04 .55 .012. Other students excluded/ignored me .45 .03 .44 .05 .34 .023. I was hit, kicked, or shoved .37 <.01 .28 <.01 .29 <.014. Other students spread rumors about me .46 .04 .43 .03 .41 .035. I had money or things taken from me .30 .03 .28 .01 .25 .026. I was forced/threatened into doing things .24 <.01 .17 .03 .17 .087. I called another student names .38 .05 .40 .02 .53 .038. I excluded/ignored another student .27 .02 .24 .05 .27 <.019. I hit, kicked, or shoved another student .21 .11 .18 .06 .24 <.0110. I spread rumors about another student .17 <.01 .15 .12 .17 .0311. I stole from another student .08 .11 .07 .02 .09 <.0112. I forced/threatened another student .10 .05 .07 <.01 .08 <.01

Note. p, proportion of students endorsing item; ICC, intraclass correlation coefficient. Itemwording has been altered for brevity. To calculate ICCs, we used theformula tB/[tBþ s2] where tB represents the between‐groups variance and s

2 represents the within‐groups variance. With binary items, a logistic distributionwas assumed for the within‐level variance term (Hedecker, 2008). This distribution has a variance of p2/3, which changes the formula to tB/[tBþ (p2/3)].

TABLE II. Model Fit Information for Unconditional LTAModels

p Entropy BIC

Two‐status solution 29 .63 28,192.48Three‐status solution 50 .65 27,368.45Four‐status solution 75 .66 26,998.11Five‐status solution 104 .68 26,935.69Six‐status solutiona — — —

Note. p, number of free parameters; BIC, Bayesian Information Criterion.aThe likelihood was not replicated. A local solution was likely and thusmodel results are not provided.

Aggr. Behav.

32 Williford et al.

Uninvolved status increased for the intervention subsam-ple but decreased for the control sample, consistent with aprior YM investigation Jenson, Brisson, Bender, andWilliford (in press).In the remaining panels of Table IV, we present the

transition probabilities for the transition from grade 4 to 5(middle panel) and grade 5 to 6 (lower panel). Theelements in these panels represent the probability that amember of a given row status (e.g., Bully) will remain inthe same status (e.g., Bully; which is on the diagonal ofthe matrix) or transition to a different status (e.g., Victim;which is on the off‐diagonal of the matrix) at thesubsequent timepoint. Again, the results have beenpresented for the overall sample as well as theintervention and control groups. A test of stationarity(cf. Nylund, 2007) was conducted to determine whether

the transition probabilities were equivalent between thetwo transition periods. Chi‐square difference testsrevealed that the transition probabilities were not equalbetween transition points for the overall sample [Dx2(12)¼ 43.850, p< .01] and the intervention subsample[Dx2(12)¼ 41.317, p< .01]. Statistically, the probabili-ties were equal for the control group [Dx2(12)¼ 12.317,p¼ .42] although we again note that the sample size wasmuch smaller in this subsample compared to the othergroups and some of the transition probabilities appearedconsiderably different over time in this group.Some interesting patterns emerged in these matrices.

For example, the Bully/Victim class had low stability inthe intervention subsample over time (4th! 5th grade:.20; 5th! 6th grade: .22) but a large increase occurredfor the control subsample (.42; .70). Similarly, there was

TABLE III. Item‐Response Probabilities for Unconditional LTA

Latent status

Bully Victim Bully/victim Un‐involved

Item‐response probabilitiesI was called names or teased .46 .83 .91 .23Other students excluded/ignored me .26 .67 .87 .14I was hit, kicked, or shoved .22 .53 .80 .05Other students spread rumors about me .39 .69 .89 .11I had money or things taken from me .19 .43 .74 .07I was forced/threatened into doing things .10 .29 .76 .02I called another student names .91 .37 .91 .16I excluded/ignored another student .55 .19 .77 .06I hit, kicked, or shoved another student .51 .12 .69 .03I spread rumors about another student .40 .07 .66 .02I stole from another student .17 .02 .42 .01I forced/threatened another student .20 .02 .44 <.01

Note. Item wording has been altered for brevity. Item response probabilities greater than .50 are in boldface to facilitate interpretation.

TABLE IV. Estimated Prevalences and Transition Probabilities for Grades 4, 5, and 6

Overall Intervention Control

BL VI BV UI BL VI BV UI BL VI BV UI

Estimated prevalences4th grade .12 .39 .12 .37 .11 .41 .13 .35 .17 .30 .12 .415th grade .17 .37� .07� .39� .14 .38� .07� .40 .22 .30 .08� .396th grade .24 .25� .10� .40 .21 .26 .11� .42 .34 .18 .10 .39

Transition probabilities (4th! 5th grade)BL .60 .05 .00 .35 .59 .10 .00 .31 .54 .08 .09 .29VI .03 .62 .09 .26 .00 .59 .12 .30 .07 .67 .04 .22BV .30 .26 .31 .13 .33 .38 .20 .09 .24 .15 .42 .19UI .13 .24 .00 .64 .09 .24 .00 .67 .19 .18 .00 .63

Transition probabilities (5th! 6th grade)BL .66 .02 .13 .20 .59 .00 .19 .22 .82 .02 .01 .16VI .16 .52 .10 .23 .18 .48 .11 .24 .18 .48 .12 .23BV .09 .33 .42 .16 .00 .63 .22 .15 .11 .05 .70 .18UI .18 .08 .04 .70 .14 .09 .05 .72 .23 .06 .02 .68

Note. Item wording has been altered for brevity. BL, bully status; VI, victim status; BV, bully/victim status; UI, uninvolved status. Transition probabilitiesreflect the probability of transition from a latent status in grades 4 and 5 (rows) to another latent status in grades 5 and 6 (columns).�p< .05.

Aggr. Behav.

A Latent Transition Analysis 33

a large increase in the stability of the Bully status for thecontrol subsample (.54, .82) but not for the interventionsubsample (.59, .59). In the Uninvolved status, stabilityincreased over time for the Bully and the Bully/Victimstatuses. Thus, aggressive students in the controlsubsample were more likely to remain in their respectiveclass when transitioning to middle school, but the jumpdid not emerged in the intervention subsample. Anothernoticeable difference is seen for the transition from theBully/Victim status to the Victim status. For theintervention subsample, the probability of this transitionrose considerably during the move to middle school (.38;.63). For the control subsample, the probability of thistransition was small and decreased over time (.15; .05).Because of these differences in the transition probabili-ties, we estimated the final conditional model for the threesubsamples separately.

Step 3: Conditional LTA

In the final step of the analysis, predictors of statusmembership in the 5th grade and the transitionprobabilities were added to the unconditional model.We did not consider the 4th grade in these final models aswe were primarily interested in predictors of transitionsduring the move to middle school, and, as shown earlier,the transition probabilities were different between thetwo transition points. Unfortunately, the models for allsubsamples encountered estimation errors. The largestlikelihood value was not replicated, indicating that localsolutions may have been encountered. Furthermore,several of the multinomial logistic regression coefficientswere fixed during estimation. These coefficients weretending toward negative or positive infinity because ofsparse data in transition probability matrix.Because these effects were of primary importance to

our study, we employed two alternative analytic

strategies to evaluate the predictors. First, we alteredthe model according to the binomial logistic regressionapproach described in Lanza and Collins (2008; see alsoCollins & Lanza, 2010). In this model, the three involvedcategories (i.e., Bully, Victim, Bully/Victim) were com-bined in the 6th grade such that only two transitionprobabilities were observed for each status in the 5thgrade: the probability of transitioning to the aggregateInvolved status and the probability of transitioning to theUninvolved status. We refer to this as the binomial LTAmodel hereafter. Second, we used posterior probabilitiesof status membership to classify individuals into statusesfor grades 5 and 6. Then, for each status in grade 5, aseparate multinomial logistic regression was estimatedsuch that membership in grade 6 was regressed onto theset of covariates. As such, we teased apart the effects ofthe covariates on specific transitions (as opposed to theaggregate Involved status). In the following sections, theeffect of each predictor on grade 5 status membership andthe transition probabilities are summarized.Depressive symptoms. Odds ratios and 95%

confidence intervals for the effect of depressivesymptoms on status prevalences in the 5th grade areshown in Table V. Recall that the regression of acategorical latent variable representing status member-ship onto one ormore predictor variables is amultinomiallogistic regression. In this model, the Uninvolved statusserved as the reference group. As in previous tables, theresults in Table Vare presented separately for the overallsample, intervention condition, and control condition.The upper panel provides the effects of the threepredictors on the latent status prevalence of the Bullystatus (versus theUninvolved status). Similarly, the otherpanels present the effects of the predictors on the latentstatus prevalence of the Victim (middle) and Bully/Victim(lower) statuses relative to the Uninvolved status. Odds

TABLE V. Effect of Predictors on Grade 5 Status Prevalences

OR (95% CI)

Overall Intervention Control

Bully vs. uninvolvedDepression 17.05�� {3.29, 88.41} 25.84� {1.55, 431.38} 7.59 {.64, 90.65}Anti‐social attitudes 3.36�� {1.71, 6.57} 2.65 {.93, 7.53} 8.31�� {2.28, 30.30}Perspective‐taking empathy .43�� {.22, .81} .36 {.13, 1.02} .49 {.22, 1.12}

Victim vs. uninvolvedDepression 33.68�� {13.04, 87.01} 36.20�� {9.81, 133.49} 27.69�� {5.45, 140.47}Anti‐social attitudes 1.07 {.53, 2.16} .85 {.41, 1.78} 1.95 {.36, 10.69}Perspective‐taking empathy 1.28 {.85, 1.92} .97 {.55, 1.71} 1.91� {1.00, 3.63}

Bully/victim vs. uninvolvedDepression 50.55�� {13.04, 196.17} 84.86�� {14.01, 513.37} 28.11�� {3.99, 198.15}Anti‐social attitudes 4.68�� {2.23, 9.84} 2.83�� {1.34, 5.98} 14.59�� {3.08, 69.06}Perspective‐taking empathy .97 {.47, 1.98} .62 {.30, 1.30} 1.53 {.58, 4.04}

�p< .05.��p< .01.���p< .001.

Aggr. Behav.

34 Williford et al.

ratios above 1.0 suggest that students were more likely tobe in a specific involved status (e.g., Bully) as opposed tothe Uninvolved status as their scores on the predictorincreased. Odds ratios less than 1.0 suggest the reverse.Depressive symptoms was a significant predictor ofmembership in the three involved statuses versus theUninvolved status. Specifically, students with higherlevels of depressive symptoms were more likely to bemembers of the Bully, Victim, or Bully/Victim statusescompared to the Uninvolved status. This held for theoverall sample as well as the two subsamples althoughthe effect of depressive symptoms on membership in theBully status versus the Uninvolved status in the controlgroup was just non‐significant. Still, it appears that levelsof depressive symptoms affected students’ involvementin bullying other students as well as being victimized.Depressive symptom levels were also predictive of

transitions over time. Results of the binomial logisticregression model are found in Table VI. In Table VI, theodds ratios represent the effect of the three predictorvariables on the transitions from students’ grade 5 statusto their grade 6 status. For these results, the Involvedstatus served as the reference group. Therefore, oddsratios above 1.0 suggest that students were more likely totransition to (or remain in) the Uninvolved status versusthe aggregate Involved status; odds ratios below 1.0imply the opposite.According to the results presented in Table VI, it

appears that students in the Bully status in 5th grade wereless likely to transition to the Uninvolved status versusthe Involved status when they were evidenced higher

depressive symptoms. The effect was significant in theoverall sample (OR: .05) but not significant in the twosubsamples. However, the odds ratios for the interven-tion (.01) and control (.27) subsamples suggestedthe effect was in a similar direction, particularly forthe intervention subsample. To determine which of theInvolved statuses students with higher levels of depres-sive symptoms were more likely to transition to, amultinomial regression analysis was conducted usingthe posterior status membership probabilities. As before,the Uninvolved status served as the reference group.Results suggest that students in the Bully status weremore likely to stay in the Bully status or transition to theother two Involved statuses (not reported in table: BullyOR: 164.02; Victim OR: 13359.72; Bully/Victim OR:79.83). The odds ratios here are quite high which canoccur with small sample sizes and relatively commonevents (Osborne, 2006); still, the results seem to suggestthat students who are aggressive at the end of elementaryschool and have higher levels of depressive symptomsare at greater risk for maintaining bullying behaviors orbecoming a victim when transitioning to middle school.Unfortunately, the number of participants in the 5thgrade Bully status in each subsample was too small toallow for trustworthy results from the multinomiallogistic regressions. Finally, we note that there was asignificant result in the binomial LTA model for thecontrol group such that students in theUninvolved statuswith higher levels of depressive symptoms were morelikely to remain in the Uninvolved status over time(OR: 352.48).

TABLE VI. Effect of Predictors on Transition Probabilities Between Grades 5 and 6

OR (95% CI)

Overall Intervention Control

Bully! uninvolved (vs. involved)Depression .05� {.00, .83} .01 {.00, 7.70} .27 {.00, 21.80}Anti‐social attitudes .78 {.28, 2.15} 1.66 {.10, 28.62} .07 {.00, 1.42}Perspective‐taking empathy .67 {.18, 2.49} .07 {.00, 68.65} 3.17 {.32, 31.89}

Victim! uninvolved (vs. involved)Depression 1.07 {.38, 2.99} 1.03 {.14, 7.78} .67 {.18, 2.53}Anti‐social attitudes 2.75 {.95, 7.94} 9.51� {1.45, 62.36} .31 {.02, 4.85}Perspective‐taking empathy 1.92� {1.06, 3.46} 2.14 {.82, 5.60} 3.69 {.69, 19.71}

Bully/victim! uninvolved (vs. involved)Depression .23 {.00, 23.03} —a {—, —} 30.30 {.00, —}Anti‐social attitudes 2.51 {.69, 9.19} —a {—, —} 1.60 {.23, 11.06}Perspective‐taking empathy 1.36 {.30, 6.22} —a {—, —} 8.76 {.74, 104.06}

Uninvolved! uninvolved (vs. involved)Depression 3.45 {.02, 625.16} .98 {.07, 13.29} 352.48�� {4.74, —}Anti‐social attitudes .21� {.04, .99} .30 {.08, 1.12} 1.63 {.01, 474.38}Perspective‐taking empathy .43 {.16, 1.15} .66 {.26, 1.67} .05 {.67, 9.77}

Note. Confidence intervals not reported were very large and tending toward infinity.aEstimate tending toward positive or negative infinity.�p< .05.��p< .01.

Aggr. Behav.

A Latent Transition Analysis 35

Antisocial attitudes. Students’ antisocial attitudeswere also predictive of their status membership in the 5thgrade. Specifically, students who reported greater levelsof antisocial attitudes were significantly more likely to bea member of the Bully and Bully/Victim statusescompared to the Uninvolved status. This was true forall three subsamples with the exception of a just non‐significant finding for the Bully versus Uninvolvedstatuses in the intervention condition.There were two transitions predicted by students’

antisocial attitudes. In the overall sample, students withhigh levels of antisocial attitudes that were in theUninvolved status were more likely to transition into theInvolved status after transitioning to middle school (OR:.21). Results from the multinomial logistic regressionanalyses suggested that this held true only for thetransition into the Bully/Victim status (OR: 10.95). Thatis, students in the Uninvolved status were 10.95 morelikely to transition to the Bully/Victim status versusstaying in the Uninvolved status during the transition tomiddle school. In the intervention condition, studentswith high levels of anti‐social attitudes in the Victimstatus were more likely to transition to the Uninvolvedstatus as opposed to the Involved status. However, theseresults were not found in the multinomial logisticregression analyses, thus making conclusions regardingthe effect of antisocial attitudes on this specific transitionsomewhat limited.Perspective‐taking empathy. For the most part,

perspective‐taking empathy did not predict statusmembership in grade 5. In the overall sample, studentswith higher levels of empathy were less likely to be amember of the Bully status versus the Uninvolved status.In the control condition, students with higher levels ofempathyweremore likely to be in theVictim status versusthe Uninvolved status. However, all other effects werenon‐significant.Perspective‐taking empathy was also a limited predic-

tor of transition patterns during the move to middleschool. Only one significant effect was found: In theoverall sample, students in the Victim status were morelikely to transition to the Involved status versus theUninvolved status. However, the results of the multino-mial logistic regression were non‐significant for all threestatuses versus the Uninvolved status. Therefore, wecannot conclusively say that perspective‐taking empathyis a predictor of transitions between bullying andvictimization latent statuses during the transition tomiddle school.

DISCUSSION

This study examined the effects of covariates on thebullying and victimization patterns of students moving

from elementary to middle school using data from agroup‐randomized trial of the YM intervention. Theprimary aims of the investigation were to examinewhether transitional patterns differed (1) for YMparticipants as compared to controls, (2) between grades5 and 6 as childrenmoved from an elementary to amiddleschool context; and (3) as a function of depressivesymptoms, antisocial attitudes, and perspective‐takingempathy.The unconditional LTA suggested a four‐status

solution was the most interpretable and optimal solutionamong those considered; this finding is consistent withprior YM results (Jenson, Brisson, Bender, and Williford(in press); Williford et al., 2012) and with substantivetheory (Solberg & Olweus, 2003). Examination of theitem response probabilities suggested the following fourlatent statuses: Bully, Victim, Bully‐Victim, and Unin-volved. It is important to note, however, that the itemresponse probability for the Bully status was quite highfor the verbal bullying item and approximately .50 forexclusionary and physical bullying behaviors. Overt(both verbal and physical items) and relational itemswererelatively high for the Victim status and very high for theBully‐Victim status, suggesting that these statuses areaffected by all forms of bullying behavior.Several interesting transition patterns were found for

the Bully, Victim, Bully‐Victim, and Uninvolved latentstatuses. In general, victimization decreased over time asevidenced by the descriptive statistics and the statusprevalences. This finding replicates results reported byNylund (2007), suggesting a general decline in rates ofvictimization during late childhood and early adoles-cence. In the current sample, on average, bullyingincreased over time. More specifically, it appears thatbullying behavior decreased between grades 4 and 5 butincreased during the transition to middle school. Thispattern was observed in both the descriptive statistics aswell as the bully and victim status prevalence changes.Thus, as hypothesized, transitional patterns differedbetween 5th and 6th grades as youth moved fromelementary to middle school. This finding is consistentwith evidence that rates of bullying may increase duringthe transition to a new school environment, as youth re‐negotiate their friendships and status in the peer group(Eccles et al., 1998; Kelly et al., 2010; Pellegrini &Long, 2002; Williford et al., 2011).The number of students in the Uninvolved status

decreased in the control group but increased in theintervention condition. While not significantly different,these findings are consistent with prior YM evidence,suggesting that the intervention had a positive impact onchildren as theymoved from elementary tomiddle schoolJenson, Brisson, Bender, and Williford (in press).Another noticeable difference was found for the

Aggr. Behav.

36 Williford et al.

transition from the Bully/Victim status to the Victim statusamong intervention participants where the probability ofthis transition rose considerably during the move tomiddle school. It is possible that YM lessons targetingsocial and cognitive skills may have improved bully‐victims’ abilities to regulate their emotions thus reducingtheir aggressive behavior. It is also plausible that theseskills had relatively effect on reducing risk for continuedvictimization during the move to middle school.However, an additional investigation is needed tosubstantiate this claim. Of note, the transition probabili-ties were significantly different between the twotransition points (grades 4–5 vs. grades 5–6). This wastrue for the overall sample and the intervention condition,but not the control condition (which had the lowestsample size of the three). Thus, it is interesting andimportant to predict the transitions during the move tomiddle school because they differ when compared to thetransition between grades 4 and 5 when childrenremained in the same school context.Several notable results were found for the effects of

depressive symptoms, antisocial attitudes, and perspec-tive‐taking empathy on status membership in the 5thgrade and during themove tomiddle school. Specifically,students with higher levels of depressive symptoms weremore likely to be members of the Bully, Victim, or Bully/Victim statuses than the Uninvolved status. This findingwas consistent for the overall sample and the interventiongroup. Interestingly, and contrary to our expectations,depressive symptoms did not emerge as a significantpredictor for the Victim status during the move to middleschool. Thus, hypothesis 1 was not supported. The lackof findings pertaining to the relationship betweendepressive symptoms and Victim status during themove to middle school is surprising. It may be thatstudents who have been victimized during elementaryschool anticipate and look forward to more positivesocial interactions as they transition to middle school. Inthe face of such optimism or new experiences, middleschool victims may assess their depressive symptomsdifferently than they did when they were a year or twoyounger. Alternatively, it may be that self‐reports ofdepressive symptoms among elementary and earlymiddle school students are far from stable. Regardless,this finding requires closer examination in future studies.Of note, however, students in the Bully status in 5th

grade were less likely to transition to the Uninvolvedstatus versus the any of the three Involved status whentheywere reported higher levels of depressive symptoms.This finding suggests that elementary school bullies thatexperience higher levels of depressive symptoms may beat risk for remaining a bully and/or becoming a victimwhen transitioning to middle school. Prior evidence hasfound that youth who engage in indirect forms of

aggression may be at a higher risk for internalizingproblems such as depression and social anxiety (Card,Stucky, Sawalani, & Little, 2008). Thus, furtherinvestigations may benefit from modeling the form ofbullying behavior that may place childhood bullies at riskduring the move the middle school and target mentalhealth symptoms in prevention efforts specifically in thelatter elementary school grades. Limitations in samplesize prevented us from being able to further classify oursample of largely low‐income, ethnic minority youth bytype of bullying behavior. However, given evidencenoting increased challenges and barriers for low‐income,ethnic minorities in accessing appropriate mental healthcare (Alegría et al., 2002; Peskin, Tortolero, Markham,Addy, & Baumler, 2007; Pumariega, Rogers, &Rothe, 2005), understanding how depressive symptomsmay place youth at risk is a particularly importantdirection for future research on these populations. Thismay be especially critical for Latino youth wherelanguage barriers and immigrant status may furthercomplicate access to mental health treatment.Students who reported greater levels of antisocial

attitudes were significantly more likely to be a member ofthe Bully and Bully/Victim statuses compared to theUninvolved status. However, results from the multino-mial logistic regression analyses suggested that this heldtrue only for the transition into the Bully/Victim statusduring the move to middle school. Thus, hypothesis 2was partially supported. Students who bully and arevictimized by peers have reported higher levels ofexternalizing problems (e.g., antisocial conduct, antiso-cial peer influence, lower school commitment) andelevated internalizing problems (e.g., depression, socialanxiety, loneliness, and self‐esteem) when compared toother subgroups (Cunningham, 2007; Haynie et al.,2001; Juvonen et al., 2003; Mouttapa et al., 2004). Thus,it is likely that antisocial attitudes may be an importantcharacteristic that may place bully‐victims at risk duringthe move to middle school, particularly when othercharacteristics are present such as higher levels ofdepressive symptoms. Accordingly, prevention andintervention efforts are especially important for bully‐victims and may assist them in making more successfultransitions to the middle school context.Last, in the overall sample, students with higher levels

of empathy were less likely to be a member of the Bullystatus versus the Uninvolved status, consistent with priorempirical evidence (Caravita et al., 2009; Giniet al., 2007; Jolliffe & Farrington, 2006; Nickersonet al., 2008). Yet, contrary to our expectations, empathydid not emerge as a particularly important characteristicfor predicting the transitions for bullies or uninvolvedyouth based on results of the multinomial logisticregression. Thus, hypotheses 3 and 4 were not supported.

Aggr. Behav.

A Latent Transition Analysis 37

It is possible that the measure of empathy used in thepresent study may not have captured empathy specific tobully and victim subgroups. We used a global measure ofperspective‐taking empathy, often considered a measureof cognitive empathy (see Galinsky, Maddux, Gilin, &White, 2008). In fact, Jolliffe and Farrington (2006)found low affective empathy to be more predictive ofinvolvement in bullying, particularly for girls, ascompared to low cognitive empathy. Thus, a specificmeasure of empathy toward victims or a measure ofaffective empathy may be a more sensitive measure and abetter predictor of transitions between bully and victimsubclasses during the move to middle school.

Study Limitations

TheYMprogramwas tested using a group‐randomizeddesign in public schools that were representative of alarge urban area. Despite the strengths associated withconducting a randomized trial, several limitations arepertinent to the current analyses. First and foremost,current limitations of LTA prevented us from examiningboth individual and contextual effects as multilevelmodels are not yet available in this analytic framework.Thus, we could not examine the degree to whichenvironmental or contextual effects influenced transi-tional patterns. This limitation is particularly important tonote as the field moves increasingly away fromcharacterizing bullying and peer victimization as merelyindividual level phenomena. In fact, an evolutionaryperspective on bullying suggests that aggressive behaviormay serve as an adaptation to certain environmentalcontexts (Berger & Rodkin, 2012; Hawley, 1999, 2003;Hawley, Card, & Little, 2007). In this sense, peer groupnorms may support the use of aggressive behavior toestablish peer group dominance and status (Berger &Rodkin, 2012; Estell, Farmer, Pearl, Van Acker, &Rodkin, 2008). This perspective implies that transition-ing to a new school setting may either disrupt bullyingbehavior or encourage it depending on whether prevail-ing peer group norms support aggressive hierarchyascension (e.g., Hawley, 2011). Consequently, bullyingmay be best understood as a complex interaction betweenindividual characteristics and the social environment(e.g., bioecological model of human development; seeBronfenbrenner, 1986, 2005). Thus, future studies wouldbe benefit by incorporating analytic techniques that allowfor the examination of both individual and contextualpredictors of transitional patterns over time.Second, it is likely that statistical power was low for the

LTA models. When examining how covariates influencetransitions, the total sample is divided into smallersubsets, one for each specific transitional pattern.Therefore, some of the more unlikely transitions (e.g.,Bully to Victim status) had low sample sizes and the

power to detect predictor effects may have beeninsufficient. This is especially true for the subgroupanalyses which were run separately for the interventionand control conditions. Two approaches were used tomitigate this problem: (a) A binomial logistic regressionapproach in which students in the four statuses in grade 5transitioned into either an Involved or Uninvolved status;and (b) Posterior probabilities of status membership wereused to classify individuals into time‐specific statuses;these were then used to run multinomial logisticregressions. Although this allowed for some effectsfrom the binomial approach to be disentangled,classification was based on the estimated model andthus results may to some extent be based on samplingerror. Still, some interesting effects were found, andfuture studies with a larger sample size should beconducted to disentangle these effects.Third, the observed indicator variables were dichoto-

mized. Although the cutoff point used has been studiedempirically (Solberg & Olweus, 2003), dichotomizationof variables results in the loss of information. The effectof this information loss, if any, would likely be theattenuation of variable relationships and the loss ofstatistical power (MacCallum, Zhang, Preacher, &Rucker, 2002). However, preliminary models in whichthe full scale was used demonstrated poor class/statusseparation, and many models did not converge. Finally,the generalization of findings is constrained not only bythe sample used, but also the lag of measurement. Thespace between observations was 1 year, and it is likelythat many transitions occurred during the unobservedtime between measurements. Promising advances areoccurring in the development of continuous time models(Voelkle, Oud, Davidov, & Schmidt, 2012), althoughthese have not yet been applied to LTA.

CONCLUSION

The transition from childhood to early adolescence,often characterized by a corresponding move fromelementary to middle school, is a particularly vulnerabledevelopmental period for young people. Thus, our resultspoint to several possible bullying prevention andintervention strategies for students entering earlyadolescence and moving from elementary to middleschool settings.Bullies in the present study who reported high levels of

depressive symptoms were less likely to move to anuninvolved status than other youth and thus more likelyto either remain a bully or become both a bully and victimas they moved from elementary to middle school. Thus,school‐based prevention programs may be improved byincluding additional content relevant to mental healthsymptoms like depression and anxiety. This finding is

Aggr. Behav.

38 Williford et al.

particularly important given the difficulties low‐income,minority youth often face in accessing appropriatementalhealth care (Alegría et al., 2002; Peskin et al., 2007;Pumariega et al., 2005). In fact, Peskin and colleaguesassert that low‐incomeminority groupsmay be less likelythan other groups to seek and use mental health treatmentdue to poor access, high costs, and potential mistrust oftreatment providers. These factors bring to bear thecritical importance of understanding the role of depres-sive symptoms in transitional patterns between bully andvictim subclasses among the samples of largely low‐income, Latino students like the one used in the presentstudy. Accordingly, adding a mental health interventioncomponent to existing bullying prevention efforts mayassist in addressing existing barriers often facing low‐income and minority groups.Our results also indicate that increases in antisocial

attitudes between elementary and middle school contrib-uted to bullying behavior and peer victimization by the6th grade. Interventions that incorporate elements ofpositive youth development may be particularly helpfulin reducing antisocial attitudes as children mature andenter adolescence (Catalano, Berglund, Ryan, Lonczak,& Hawkins, 2004; Jenson, Alter, Nicotera, Anthony, &Forrest‐Bank, in press; Lerner, Almerigi, Theokas, &Lerner, 2005).To date, a majority of programs and interventions

aimed at preventing or reducing bullying and peervictimization have focused on elementary schoolstudents. Many of these programs have yielded short‐term reductions in bullying and peer victimization in theyears preceding the move to middle school. Findings inthis report suggest that interventions aimed at reducingaggression and victimization during the transition fromelementary to middle school should receive greaterattention from practitioners and policymakers.

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