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Merrill-Palmer Quarterly, Volume 60, Number 3, July 2014, pp. 302-327 (Article) 3XEOLVKHGE\:D\QH6WDWH8QLYHUVLW\3UHVV

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M e r r i l l - P a l m e r Q u a rt e r ly , V o l . 6 0 , N o . 3

Relations Among Multiple Types of Peer Victimization, Reactivity to Peer Victimization, and Academic Achievement in Fifth-Grade Boys and Girls Michael T. Morrow  Arcadia University Julie A. Hubbard and Lauren E. Swift  University of Delaware

This study examined the relations between multiple types of peer victimization, affective reactivity to victimization, and academic achievement. Participants (179 fifth-grade boys and girls) completed repeated daily measures of peer victimization and negative affect; a standardized measure of achievement was collected concurrently. The daily measure of peer victimization was best represented by five factors: physical victimization, verbal victimization, social manipulation, property attacks, and social rebuff. While controlling for race/ethnicity, children’s reports of being socially manipulated by peers were negatively related to their overall achievement. In addition, affective reactivity to social manipulation negatively related to achievement while accounting for reported experiences of social manipulation. No other victimization or reactivity variables related to achievement. Findings are discussed with a focus on implications for school bullying prevention and intervention.

For some children, school is not only a place for learning and ­socialization but also a place for bullying and victimization. Approximately 10% of elementary and middle-school students report being regularly victimized by peers (Kochenderfer & Ladd, 1996; Olweus, 1978; Perry, Kusel, & Michael T. Morrow, Department of Psychology; Julie A. Hubbard and Lauren E. Swift, Department of Psychology. This research was supported by a grant from the Spencer Foundation. We thank JeanPhillipe Laurenceau for his statistical consultation, as well as the project’s undergraduate research ­assistants for their hard work and dedication. Most of all, we appreciate the help of the children, parents, teachers, and principals who made this project possible. Address correspondence to Michael T. Morrow, 124 Boyer Hall, 450 South Easton Road, Arcadia University, Glenside, PA 19038. Phone: (215) 572-4765. Fax: (215) 881-8758. E-mail: [email protected]. Merrill-Palmer Quarterly, July 2014, Vol. 60, No. 3, pp. 302–327. Copyright © 2014 by Wayne State University Press, Detroit, MI 48201.

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Perry, 1988). Peer victimization has been reported by children as young as kindergarteners (Kochenderfer & Ladd, 1996), and, by late elementary school, individual differences in victimization appear increasingly stable (Perry, Hodges, & Egan, 2001). Peer victimization is associated with multiple aspects of psychosocial functioning, including anxiety, depressive symptoms, loneliness, and low self-esteem (Boivin & Hymel, 1997; Boivin, Hymel, & Bukowski, 1995; Egan & Perry, 1998; Kochenderfer & Ladd, 1996; Olweus, 1978, 1993). In terms of school functioning, victimized children report feeling less happy at school and lower levels of school liking and also display greater school avoidance than their nonvictimized peers (Boulton & Underwood, 1992; Kochenderfer & Ladd, 1996). Beyond these broader school adjustment variables, researchers have explored links between children’s peer relations and academic achievement. A number of studies have examined associations of academic achievement with sociometric peer acceptance (the extent to which a child is liked and disliked by peers; McDougall, Hymel, Vaillancourt, & Mercer, 2001). In general, peer acceptance appears positively related to academic achievement, such that youth who are less accepted tend to display lower levels of concurrent achievement and less academic progress over time. Ladd, Kochenderfer, and Coleman (1997) found that U.S. kindergarteners’ peer acceptance positively predicted their academic progress over the school year. Similar results were found in a sample of Dutch junior high school students in which peer acceptance positively predicted promotion to the next grade (Lubbers, Van Der Werf, Snijders, Creemers, & Kuyper, 2006). Wentzel (2003) also demonstrated that peer acceptance was positively linked to grade-point average in a U.S. sample of sixth through eighth graders. While these studies provide an important foundation for understanding the link between children’s peer relations and academic functioning, additional research is needed to examine the role of children’s actual experiences with peers. As noted by multiple theorists, peer acceptance captures only the attitudes that peers have about particular children. In contrast, peer victimization describes peers’ behavior toward other children (Boivin, Hymel, & Hodges, 2001), which may or may not be driven by their attitudes toward those children (Sandstrom & Zakriski, 2004). Although peer victimization can occur covertly, it is nonetheless a more direct experience than peer acceptance. Accordingly, children’s academic achievement may have a stronger association with their peer victimization than with their level of peer acceptance. In an international meta-analysis, Nakamoto and Schwartz (2010) reviewed 33 studies examining concurrent relations between peer victimization and academic achievement in elementary, middle, and high school.

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Overall, results revealed a significant yet modest negative relation, such that higher levels of victimization appear linked to lower levels of achievement. Several methodological variables (the reporter of peer victimization, the index of achievement, the presence of shared method variance, and the national setting of the study) were found to moderate this relation. However, gender did not play a moderating role; thus, the negative relation between victimization and achievement appears consistent for boys and girls. Several studies have explored the association between peer victimization and academic achievement among late elementary-age children. In a large U.S. sample of third-, fourth-, and fifth-grade students, self-reported victimization was linked to lower scores on standardized achievement tests (Glew, Fan, Katon, Rivara, & Kemic, 2005). Additionally, Buhs (2005) observed that U.S. fifth-grade students who reported being victimized displayed greater decrements in achievement throughout the school year than did nonvictimized students; they also found that students’ academic ­self-competence and classroom engagement largely explained the link between victimization and decreased achievement. More recently, Buhs, Ladd, and Herald (2006) completed a 6-year prospective study assessing a sample of U.S. students from kindergarten through fifth grade. They tested a sophisticated model in which kindergarten levels of peer acceptance contribute to changes in academic achievement through two mediating mechanisms: chronic peer maltreatment and changes in classroom engagement. Consistent with the results of previous studies, earlier peer acceptance positively predicted changes in academic achievement. Moreover, two mediational relations were observed within this pathway: Chronic peer exclusion mediated the relation between earlier peer acceptance and changes in class participation, whereas changes in class participation mediated the relation between chronic peer exclusion and changes in achievement. Together, these works (Buhs, 2005; Buhs et al., 2006; Glew et al., 2005) offer support for a connection between peer victimization and academic achievement in elementary school and initial evidence for the mediating role of classroom engagement. Nevertheless, additional research is needed to assess the link between peer victimization and academic achievement thoroughly, particularly with respect to the diversity of possible victimization experiences. Peer victimization takes many forms, and researchers have emphasized the importance of studying multiple types of victimization (e.g., Sandstrom & Cillessen, 2003). Several researchers have used factor analyses to assess d­ifferent types of peer victimization (e.g., Crick & Grotpeter, 1996; Crick, Casas,  &  Ku,  1999; Mynard & Joseph, 2000; Sandstrom & Cillessen,

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2003). Across these studies, four types of peer victimization have been identified: physical victimization, verbal victimization, social manipulation, and property attacks. Physical victimization refers to physical attacks (e.g., being hit, kicked, pushed, scratched, or bitten), whereas verbal victimization reflects verbal assaults (e.g., being teased, taunted, called names, or cursed at). Social manipulation includes the experience of behaviors that peers use to damage children’s relationships with others (e.g., convincing others to turn against a child or blocking a child from playing with others). Peers may also victimize children by stealing, damaging, or hiding their belongings, which has been referred to as property attacks. Other researchers have discussed the construct of social rebuff, which captures experiences of being ignored, left out, or excluded by peers (Buhs et al., 2006; Dodge, 1983; Dodge, Coie, & Brakke, 1982; Putallaz & Wasserman, 1989). Although these experiences may appear to overlap with social manipulation, we hypothesize that they are distinct (yet related) types of peer victimization. As framed in this study, social manipulation is orchestrated by peers who influence others to treat children in negative ways. In contrast, social rebuff is not mediated by a third party in this manner and occurs directly between perpetrators and targets. To our knowledge, few studies have investigated potential links between academic achievement and different types of peer victimization. In a notable exception, Woods and Wolke (2004) interviewed a sample of U.K. schoolchildren (ages 6–9 years) and examined the relations of their academic achievement with their reports of physical and relational victimization. Based on our review, the authors’ relational victimization variable corresponds best with social manipulation, as just described. Results revealed a positive concurrent relation between academic achievement and relational victimization (but not physical victimization) for the 6- and 7-year-old students. Accordingly, certain types of victimization may be linked to children’s academic achievement, whereas others are not. Buhs and colleagues (2006) also included two types of chronic victimization (peer exclusion and peer abuse) in their aforementioned study. Per our understanding, peer exclusion appeared similar to social rebuff but also included general experiences of being picked on. In contrast, peer abuse seemed to be an aggregate of verbal victimization, physical victimization, and social manipulation. Chronic peer exclusion and abuse both negatively correlated with changes in academic achievement. However, in their broader model, peer exclusion maintained its connection to achievement (accounting for the mediating role of class participation), whereas peer abuse did not (accounting for the mediating role of school avoidance). Although quite distinct, these two studies (Buhs et al., 2006; Woods & Wolke, 2004)

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suggest that social types of victimization may play a c­ ritical role in the victimization–achievement relation. The first goal of the present study was to examine the relations of fifth graders’ academic achievement with the five types of peer victimization outlined earlier. We generally hypothesized that children who report higher levels of victimization will display lower levels of overall achievement (i.e., an aggregate of reading and math achievement). However, we chose to explore these relations without making precise predictions for each type of victimization. To our knowledge, no specific theories have been advanced to explain why academic achievement may be more strongly associated with certain types of victimization than others. Nevertheless, Buhs and colleagues (2006) suggest that social victimization (e.g., peer exclusion) is more strongly linked to academic functioning because it is more likely to minimize children’s opportunity to engage with and learn from peers. Based on these ideas and previous findings (Buhs et al., 2006; Woods & Wolke, 2004), we were especially interested in the relations of academic achievement with the two types of social victimization (social rebuff and social manipulation) assessed in this study. The second goal of the current investigation was to explore whether fifth graders’ affective reactivity to peer victimization is linked to their academic achievement. To accomplish this, we repeatedly assessed children’s daily negative affect and daily peer victimization, which enabled us to estimate their affective reactivity to each type of victimization measured. Researchers have begun to explore individual differences in children’s reactivity to social experiences and have observed wide variation in their reactions (e.g., Nishina & Juvonen, 2005; Sandstrom, Cillessen, & Eisenhower, 2005). Moreover, several studies have linked peer victimization to disturbed emotional responses, including elevated physiological arousal, emotion dysregulation, and anger intensity (Champion & Clay, 2007; Hanish, Eisenberg, Fabes, Spinrad, & Schmidt, 2004; Shields & Cicchetti, 2001; Woods & White, 2005). To our knowledge, previous research has not considered affective reactivity to victimization in relation to achievement. Nonetheless, children’s emotional responses to victimization may be linked to their achievement as much as (or even more than) the actual level of victimization they experience. We hypothesized that affective reactivity to victimization would be negatively related to overall achievement, while accounting for reported levels of victimization. Again, we did not make specific predictions for reactivity to each type of victimization. However, we were particularly curious about the relations of children’s academic achievement with their affective reactivity to social manipulation and social rebuff.

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To meet the goals of the current study, we used a daily-diary design. At the end of each of 8 school days, children completed measures of the different types of peer victimization they experienced that day, as well as the negative affect they generally felt that same day. We computed scores for different types of victimization by averaging children’s reports across the 8 days. Compared to traditional self-report measures of peer victimization, this daily assessment approach likely reduced retrospective bias by minimizing the time between episodes of victimization and reports of their occurrence (Bolger, Davis, & Rafaeli, 2003). Furthermore, this methodology enabled us to assess children’s affective reactivity to peer victimization by analyzing the extent to which their negative affect fluctuated from day to day as a function of the different types and levels of victimization they experienced. To estimate children’s affective reactivity to victimization, we assessed the within-day covariation of their negative affect and peer victimization. This approach is consistent with daily-diary researchers’ methods for computing affective and cognitive reactivity to daily events (Affleck, Tennen, Urrows, & Higgins, 1994; Bolger & Schilling, 1991; Nezlek, Feist, Wilson,  & Plesko, 2001). We considered assessing the covariation of children’s negative affect and peer victimization across days (e.g., victimization on one day and affect on the following day), but this method is more consistent with the estimation of daily carryover effects (see Wenze, Gunthert, Forand, & Laurenceau, 2009) rather than daily reactivity. Moreover, we expected children’s daily affect to fluctuate considerably more with victimization experienced on the same day than with victimization encountered days prior. Method

Participants Participants were recruited from eight fifth-grade public school classrooms within one school district in a Mid-Atlantic state. Parental consent forms were distributed to 225 children, and 201 returned their forms (89% return rate). Of these children, 188 received their parents’ permission to participate (94% consent rate for returned forms; 84% consent rate overall). Prior to data collection, six children with parental permission transferred out of participating classrooms. In addition, three were removed from the data set because of missing demographic or achievement data. Thus, the final sample consisted of 179 children (104 boys and 75 girls). Parents reported the following race/ethnicity for their children: 35% European American, 32% African American, 17% Latino American, 9% mixed, 3% Asian American,

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1% Native American, and 3% did not report. Across the school district, 39% of students qualified for free or reduced-price lunch, and every school was designated as low income. Overall, 164 of the 179 children completed daily measures of ­victimization and negative affect on all 8 days. The remaining 15 children completed the measures on at least 3 days. Scores for victimization and affective reactivity were computed across all available days for all ­children. Standardized academic achievement scores were available for all 179 ­children. Thus, the final data set did not include any missing data.

Procedure The first author or a graduate-level assistant (accompanied by at least two undergraduate assistants) group-administered daily measures of peer victimization and negative affect to the participating children across 8 consecutive school days. Undergraduate assistants circulated within the classrooms to answer children’s questions or read measures aloud to children identified by their teachers as having reading difficulties. The measures were collected during the final 30 minutes of each school day and took approximately 10 minutes to complete. A child assent form administered on the first day of data collection stated that the study would last 8 days and that participants could withdraw at any time. Children were verbally reminded of their right to withdraw during each subsequent collection. At approximately the same point in the school year, children completed the Measures of Academic Progress (MAP) to assess academic achievement; this testing was completed by the school district as part of its assessment of students’ academic progress. Of note, we did not collect daily child-report data on the days that students completed their achievement tests. However, we made an effort to collect these data within several weeks of the testing date in each classroom; we visited some classes before and others after their testing dates. We do not view this variation as a significant threat to this study for at least three reasons: First, we aimed to assess concurrent relations among our target constructs. Second, each of the final constructs was measured or computed to reflect relatively stable child characteristics. Third, we used an analytical approach designed to account for classroom-level variability. Accordingly, between-classroom differences in the order of the data ­collection and testing likely had little effect on the relations observed in this study.

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Measures Peer victimization.  Children reported on their daily peer ­victimization experiences by using a newly developed daily assessment tool, largely drawn from Mynard and Joseph’s (2000) self-report scale. Their measure ­consists of four 4-item subscales: physical victimization, verbal v­ictimization, social manipulation, and property attacks. Because the ­original instrument was developed for British children, we reworded several items to sound more familiar to U.S. children. We also borrowed several items from Sandstrom and Cillessen’s (2003) checklist. This measure includes a peer exclusion subscale comprised of items describing experiences of being left out by peers; we borrowed three items from this subscale to create a social rebuff subscale for our daily measure. Of note, we transferred one item (“A kid refused to talk to me”) from Mynard and Joseph’s social manipulation subscale to our social rebuff subscale. Furthermore, we added one item (“When I tried to play with one kid, another kid would not let me”) from Sandstrom and Cillessen’s checklist to our social manipulation scale. Thus, our daily checklist included five 4-item subscales to assess physical victimization, verbal victimization, social manipulation, property attacks, and social rebuff (see Table 1 for items). For each item, children were asked to circle the number of times they experienced an event “today at school” on a scale from “zero” to “four or more”. Scores were computed for each type of peer victimization by summing children’s responses for the four items within each subscale across the total number of days they reported. Total subscale scores were then averaged across each child’s total number of days, which resulted in five victimization variables: Physical Victimization, Verbal Victimization, Social Manipulation, Property Attacks, and Social Rebuff. Cronbach’s alpha values were calculated for each subscale by using item scores averaged across the total number of days reported; each subscale evidenced adequate internal consistency (Table 2). Negative affective reactivity to peer victimization.  To assess daily negative affect, we designed a four-item measure loosely derived from the Positive and Negative Affect Schedule for Children (PANAS-C; Laurent et al., 1999). The original PANAS-C consists of 27 emotion words; children are asked to rate on a 5-point scale how often they have felt each emotion “during the past few weeks.” Three items (sad, mad, and nervous) were drawn from this scale to assess daily negative affect. One additional item (embarrassed) was added to capture feelings of

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Merrill-Palmer Quarterly Table 1.  Daily peer victimization items

Type

No.

Physical victimization

1

A kid hit or pushed me.

2

A kid kicked me.

3

Another kid beat me up.

4

A kid hurt my body in some other way.

5

A kid called me mean names.

6

A kid said something mean about me.

7

A kid made fun of the way I look.

8

A kid made fun of me for some other reason.

9

A kid tried to get me in trouble with my friends.

10

A kid tried to make my friends turn against me.

11

When I tried to play with one kid, another kid

Verbal victimization

Social manipulation

Item

would not let me. Property attacks

Social rebuff

12

A kid made other people not talk to me.

13

A kid took something of mine without permission.

14

A kid tried to break something of mine.

15

Another kid stole something from me.

16

A kid damaged something of mine on purpose.

17

A kid ignored me.

18

A kid refused to talk to me.

19

Kids would not let me join their game.

20

Kids had a secret and would not tell me.

humiliation. Children were asked to rate the degree to which they felt each emotion “today at school.” Children’s daily negative affect scores were computed by averaging the four items within a day, with higher scores indicating stronger feelings of negative affect. Cronbach’s alpha was modest (.69) and computed in the same manner as the peer victimization subscales. We calculated affective reactivity scores for each child by computing the within-day slope between their daily victimization scores and daily negative affect scores across all available days. To accomplish this, we used HLM 7 (Raudenbush, Bryk, Cheong, Congdon, & du Toit, 2011) to test five separate models with two levels: 1,413 repeated daily

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Table 2.  Descriptive statistics for raw variables Variable

Min.

Max.

M

SD

Skewness

α

Physical victimization (PV)

0.00

8.13

0.54

1.21

3.71

.85

Verbal victimization (VV)

0.00

13.17

0.95

1.86

3.57

.93

Social manipulation (SM)

0.00

11.00

0.51

1.35

5.15

.93

Property attacks (PA)

0.00

9.75

0.49

1.17

5.20

.90

Social rebuff (SR)

0.00

12.33

0.71

1.56

4.40

.84

Affective reactivity to PV

0.00

0.05

0.03

0.01

−1.34

—

Affective reactivity to VV

−0.02

0.06

0.03

0.01

−0.77

—

Affective reactivity to SM

−0.02

0.11

0.05

0.02

−0.58

—

Affective reactivity to PA

−0.01

0.06

0.03

0.01

−0.74

—

Affective reactivity to SR

0.00

0.06

0.03

0.01

−0.17

—

−2.07

2.25

−0.00

0.92

0.04

—

Achievement

Note. Alpha (α) represents an average of the within-day alpha values for each peer ­victimization variable. Alpha values could not be calculated for the affective reactivity ­variables or for achievement.

reports (Level 1) nested within 179 children (Level 2). In each model, children’s daily negative affect was entered as the dependent variable, and one type of victimization was entered as a group-centered Level 1 predictor with a random slope. We calculated individual slopes for each child by summing two residual values from each model: the unique empirical Bayes slope estimate for each child and the average slope across children. Practical ­discussions of this procedure are provided by Hox (2010) and Raudenbush and Bryk (2002). With this approach, we obtained five reactivity scores (Affective Reactivity to Physical Victimization, Verbal Victimization, Social Manipulation, Property Attacks, and Social Rebuff) that represent the average degree that a child’s negative affect fluctuates from day to day in relation to the level of victimization experienced.

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Academic achievement. This was assessed by using the MAP (Northwest Evaluation Association, 2004), a state-aligned, computerized, adaptive, RIT (Rasch unit)-scaled assessment program. MAP assessments are developed from a large pool of items that have been calibrated for their difficulty on the RIT scale (Cronin, Dahlin, Adkins, & Kingsbury, 2007). This scaling approach eliminates the possibility of floor and ceiling effects and insures that items reflect students’ current performance rather than their grade level. Children completed tests of math and reading achievement. The ­reading test assessed word recognition, vocabulary, reading comprehension, and literary response and analysis. The math test assessed numeric reasoning, algebraic reasoning, geometry and measurement, and quantitative reasoning. Test–retest reliabilities for the MAP among fourth and fifth graders are high (r = .90–.91). The tests have also demonstrated convergent validity by correlating with standardized achievement tests, including the Stanford Achievement Test, 9th edition (SAT9) and the Iowa Test of Basic Skills (Form K), yielding correlations ranging from .69 to .84 and from .80 to .88, respectively (Northwest Evaluation Association, 2004). Achievement scores were calculated for each child by averaging their standardized math and reading scores. Results

Confirmatory Factor Analyses First, we investigated the factor structure of the peer victimization measure by testing a series of CFA models using Mplus 5.1 (Muthén & Muthén, 2007). Each model included 20 indicators that corresponded to the 20 peer victimization items, averaged across the 8 days. Because all 20 indicators were significantly skewed (skewness = 2.65–7.17), we attempted to normalize them. Three transformations (logarithmic, square root, and negative reciprocal) were performed, but none reduced skewness to an acceptable level for any item. Therefore, we tested the models with the raw indicators by using maximum-likelihood estimation with robust standard errors (MLR), which enabled us to obtain parameter estimates, standard errors, and chi-square statistics that were robust to nonnormality (Huber, 1981). To evaluate model fit, we examined the chi-square statistic and three additional indices: the root mean square error of approximation (RMSEA), the comparative fit index (CFI), and the standardized root mean square residual (SRMR). RMSEA values less than or equal to .08, CFI values greater than or equal to .90, and SRMR values less than .10 indicate

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reasonable model fit (Kline, 2005). We began by testing our ­hypothesized model (Figure 1), which contained five correlated factors each uniquely measured by four indicators. Results provided modest support for model fit,

Figure 1.  Hypothesized five-factor model for the peer victimization measure. Indicator labels correspond with the item numbers in Table 1. Factor loadings are standardized. All loadings and correlations are statistically significant at p < .01.

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χ (160) = 506.23, p = .00; RMSEA = .11; CFI = .85; SRMR = .08. All standardized factor loadings were significant and greater than .55. ­ Additionally, all standardized factor correlations were positive and significant. We then tested the hypothesized model against six competing models. We first compared it to a one-factor model (a single factor measured by all 20 indicators). Next, we tested a series of models to account for the high factor correlations observed in the hypothesized model; four pairs of factors correlated at above .80 (Figure 1). Thus, we designed four separate models to determine whether each pairs’ indicators were better represented by a single factor rather than two unique factors. To accomplish this, we tested four 4-factor models in which all of the items from one pair of highly correlated factors were collapsed to measure a single factor. The items from the following factor pairs were merged across these tests: Verbal Victimization and Social Manipulation, Verbal Victimization and Social Rebuff, Social Manipulation and Property Attacks, and Social Manipulation and Social Rebuff. Finally, we tested a two-factor model to assess whether all four highly correlated factors were better represented as a single factor. This model included the hypothesized Physical Victimization factor, along with one additional factor that was measured by all of the items from the remaining four factors. To compare the hypothesized model to the six competing models, we employed Satorra and Bentler’s (2001) formula (SB ∆χ2) for evaluating differences among chi-square values obtained through MLR. The ­hypothesized model fit significantly better than the two- and four-factor models, SB ∆χ2(4 or 9) = 220.19–487.89, all ps = .00. However, a negative chi-square value was computed in comparing the hypothesized model to the one-factor model. To correct for this, we attempted to conduct a strictly positive Satorra-Bentler chi-square test (Asparouhov & Muthén, 2012; Bryant & Satorra, 2012) but encountered identification problems that we were unable to diagnose. As an alternative, we examined two predictive fit indices: the Akaike information criterion (AIC) and the Bayes information criterion (BIC). Both indices revealed that the hypothesized model (AIC = −264.99, BIC = −41.87) fit better than the one-factor model (AIC = 403.94, BIC = 595.18). Collectively, these results indicate that five factors offer a better structural representation of the peer victimization measure than do fewer factors. 2

Descriptive Statistics and Bivariate Correlations Table 2 lists the descriptive statistics for the final 11 raw variables. We attempted to normalize all variables with skewness statistics greater than ±0.5. We performed three transformations (square root, logarithmic,

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and negative reciprocal) on each skewed variable. The transformation that reduced skewness to the greatest extent was retained for all subsequent analyses. Logarithmic transformations were retained for the five victimization variables. Of the total number of victimization experiences reported by all the children, verbal victimization was reported as the most frequent (29%), followed by social rebuff (22%). The three remaining types of victimization (physical victimization, social manipulation, and property attacks) accounted for roughly the same percentage of the total number of victimization experiences reported (17%, 16%, and 16%, respectively). Table 3 lists the bivariate correlations among the final 11 variables. Each type of victimization was positively correlated with every other type of victimization. In addition, each type of reactivity positively correlated with every other type of reactivity. All correlations between the five victimization variables and five reactivity variables were negative, one of which was nonsignificant. Only one variable correlated with Achievement—that is, Social Manipulation negatively correlated with Achievement.

Differences in Gender and Race/Ethnicity We examined gender and race/ethnicity differences for all 11 final variables. No significant gender differences emerged. In addition, no racial/ ethnic differences were found for the victimization or reactivity variables. However, significant racial/ethnic differences appeared for Achievement, F(4, 166) = 6.12, p < .001. Bonferroni-adjusted post hoc comparisons indicated that Achievement scores were significantly lower for African American children than Asian American children (p < .04) and European American children (p < .001).

Hierarchical Linear Modeling For our primary analyses, we tested a series of hierarchical linear models by using HLM 7 (Raudenbush et al., 2011). The models included two levels: 179 children (Level 1) from eight classrooms (Level 2). HLM was used to account for potential classroom effects when examining relations between children’s victimization experiences, reactivity to these experiences, and academic achievement. We tested five separate models, with Achievement as the dependent variable (Table 4). In each model, two predictors were entered: one type of victimization and the affective reactivity to that type of victimization. Each Level 1 predictor was entered as an uncentered variable with a random slope. In each model, Race/Ethnicity was entered as a

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.60** –.50 –.27** –.35** –.29** –.10

5. Social rebuff (SR)

6. Affective reactivity to PV

7. Affective reactivity to VV

8. Affective reactivity to SM

9. Affective reactivity to PA

10. Affective reactivity to SR

Note. *p < .05. **p < .01.

.09

.62**

4. Property attacks (PA)

11. Achievement

.62**

3. Social manipulation (SM)

**

.64**

1

2. Verbal victimization (VV)

1. Physical victimization (PV)

Variable

–.40

–.12

–.18*

–.36**

–.44**

–.39**

–.20 **

–.22**

–.40**

–.46**

–.29**

**

–.42 **

.78**

.74**

3

.78**

.65**

.76**

2

–.24** –.08

–.07

–.46**

–.48**

–.39**

–.47**

5

–.28**

–.46**

–.47**

–.33**

–.47**

.63**

4

Table 3.  Bivariate correlations

–.10

.44**

.66**

.69**

–.72**

6

–.01

.64**

.74**

.74**

7

–.05

.59**

.75*

8

.05

.57**

9

.10

10

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Table 4.  Hierarchical linear models predicting achievement df

Coefficient

SE

t ratio

Physical victimization model  Intercept

8

–.02

 Race/ethnicity

8

.13

  Physical victimization (PV)

8

–.10

.39

–.26

  Affective reactivity to PV

8

–14.03

10.80

–1.30

 Intercept

8

–.08

 Race/ethnicity

8

  Verbal victimization (VV)

8

–.59

.30

–1.93

  Affective reactivity to VV

8

–7.68

6.79

–1.13

 Intercept

8

.25

.31

.82

 Race/ethnicity

8

.09†

.04

2.22

  Social manipulation (SM)

8

–1.34*

.42

–3.17

  Affective reactivity to SM

8

–9.83

3.85

–2.56

 Intercept

8

–.31

.36

–.86

 Race/ethnicity

8

.11

.04

  Property attacks (PA)

8

–.52

  Affective reactivity to PA

8

–1.45

 Intercept

8

–.51

 Race/ethnicity

8

.12

  Social rebuff (SR)

8

  Affective reactivity to SR

8

*

.42

–.04

.04

3.12

Verbal victimization model .10*

.29

–.29

.04

2.67

Social manipulation model

*

Property attacks model *

2.61 –1.08

7.74

–.19

.33

–1.56

.04

3.09

–.30

.31

–.97

3.46

9.73

.36

Social rebuff model *

Note. †p < .10. *p < .05.

covariate because of its relations with the achievement variables. Given the lack of gender differences in achievement, gender was not included. Across models, Social Manipulation related negatively to Achievement. Affective Reactivity to Social Manipulation also related negatively to Achievement, while accounting for the association between Social Manipulation and Achievement. No other peer victimization or affective

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reactivity variables were significantly linked to Achievement. Finally, Race/Ethnicity significantly related to Achievement in each model except the one including Social Manipulation and Affective Reactivity to Social Manipulation. Discussion The current study was aimed to advance our understanding of the links between peer victimization and academic achievement in two ways: First, we investigated the relations of multiple types of peer victimization with concurrent levels of academic achievement in reading and math. Second, we explored whether affective reactivity to peer victimization was associated with academic achievement, beyond actual experiences of peer ­victimization. To our knowledge, this study was the first to address each of these goals. Of the five types of victimization studied, only children’s social manipulation experiences related to their academic achievement. Children who reported more frequent social manipulation displayed lower overall achievement. Additionally, the only reactivity variable that related to academic achievement was affective reactivity to social manipulation. Moreover, this relation held while accounting for the effect of social manipulation on achievement. Thus, the frequency of fifth graders’ social manipulation and their emotional reactivity to these events were each uniquely linked to their academic difficulty. We were surprised to find that no other type of peer victimization (or affective reactivity to other types of victimization) related to a­cademic achievement. Although we did not propose specific hypotheses, we expected additional types of peer victimization to correlate with a­ cademic difficulty. Along with social manipulation, it seems plausible that other v­ ictimization experiences could impact children in ways that hinder their academic performance. The results of previous research suggest that ­children’s overall levels of peer victimization are negatively associated with their academic achievement (Nakamoto & Schwartz, 2010). However, at least two s­ tudies reveal that social types of victimization are more robustly linked to ­children’s academic achievement than are other types (Buhs et al., 2006; Woods & Wolke, 2004). Expanding upon this work, the results of current study indicate that the general link between victimization and achievement in preadolescence may be driven largely by experiences of socially manipulative behavior. Multiple factors may explain the unique link between socially manipulative peer victimization and academic achievement. From a developmental

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perspective, social manipulation may be particularly potent in preadolescence. At this time, connections to peers through friendships and crowd affiliations become increasingly important to youth (Brown, Eicher, & Petrie, 1986; Crockett, Losoff, & Peterson, 1984), and socially manipulative behavior increases in frequency (Björkqvist, Lagerspetz, & Kaukiainen, 1992; Scheithauer, Hayer, Petermann, & Jugert, 2006; Werner & Hill, 2010). As children place greater value on their peer relations, the experience of social manipulation, which functions to damage those r­elations, may be especially salient and hurtful. Accordingly, the distinct relation of social manipulation with children’s functioning (including their academic progress) may be enhanced during this period. Furthermore, the nature of social manipulation may differ from other types of victimization in ways that uniquely potentiate its effects. For instance, of the five types of victimization studied, social manipulation is most likely to occur covertly (outside of the target’s awareness) and indirectly (orchestrated by a third party). For this reason, it may be more likely to lead children to ruminate, worry, and feel helpless about these experiences. At school, students may spend valuable class time pondering who was behind their manipulation or fretting that it will happen again. Moreover, without knowledge of the perpetrator(s), children may come to believe that the situation is beyond their control. Together, these cognitive and emotional reactions may prevent students from attending school, ­participating in classroom activities, completing work, and, ultimately, learning. In contrast, other types of victimization that are more overt and direct in nature may be less likely to lead to these responses. While previous research suggests that classroom engagement partially explains the link between peer victimization and decreased achievement (Buhs, 2005; Buhs et al., 2006), future studies should test various indicators of school engagement (e.g., attendance, avoidance, participation, and work completion) as mediators of the relations between different types of ­victimization and academic achievement. For instance, Buhs and colleagues (2006) found that chronic peer exclusion predicted changes in classroom participation and school avoidance, whereas peer abuse predicted only school avoidance. Furthermore, researchers should explore the cognitive and emotional responses to victimization that potentially impair school engagement. Studies indicate that peer victimization is associated with daily feelings of anxiety (Nishina & Juvonen, 2005), rumination (Barchia & Bussey, 2010; Rudolph, Troop-Gordon, & Granger, 2011), and negative attributions (Gibb et al., 2006; Graham & Juvonen, 1998). However, it remains unclear whether specific types of victimization are more likely to contribute to these outcomes and whether certain cognitive and emotional

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responses mediate the links between different victimization experiences and classroom engagement. Although the relations between peer victimization and affective ­reactivity to peer victimization were not a central focus of this study, these findings warrant discussion. It has been theorized that children who are targeted and chronically harassed by peers may respond to their v­ ictimization with high levels of physiological arousal and emotional dysregulation, which impairs their ability to adaptively cope with these experiences (Perry, Hodges, & Egan, 2001). Moreover, the visible signs of these reactions may reinforce the perpetrators’ behavior and contribute to further abuse over time (Perry, Williard, & Perry, 1990). As noted, studies have documented positive relations between peer victimization and ­disturbed emotional responding (Champion & Clay, 2007; Hanish et al., 2004; ­ Shields & Cicchetti, 2001; Woods & White, 2005). In this study, we observed consistent negative relations between peer victimization and affective reactivity to victimization, such that increasing levels of victimization were associated with decreasing levels of r­ eactivity. These findings do not support the notion that victimized children are more emotionally reactive to their victimization experiences; rather, the ­children who reported less frequent victimization appeared more e­motionally responsive to these events. Children who endure ongoing victimization might eventually habituate to these experiences, such that these events progressively lose their emotional impact. As repeated victimization takes its toll on children’s well-being, their reactivity to these experiences may decelerate over time. Subgroups of children might also display distinct profiles of reactivity along the continuum of victimization experienced. For instance, children who experience moderate levels of victimization may habituate to these experiences, whereas the few who encounter extreme victimization may become sensitized to these events. It is also worth noting that we did not assess physiological reactivity to victimization; instead, we measured affective reactivity in terms of daily fluctuation in self-reported emotions. Children’s subjective emotion and physiological arousal could fluctuate in different patterns when confronted with victimization (Bollmer, Harris, & Milich, 2006). Moreover, children’s ability to regulate these responses while being victimized may influence their risk for further victimization. Thus, affect, arousal, and regulation should all be considered in future research exploring the links between peer victimization and reactivity to these experiences. At a very preliminary level, the current findings may have implications for intervention. School bullying prevention programs could focus particular attention toward reducing socially manipulative behavior among

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preadolescent students. Leff and colleagues’ (2010) Preventing Relational Aggression in Schools Everyday (PRAISE) curriculum stands out as a promising program aimed to minimize social victimization among ­students in urban schools. PRAISE includes components to promote adaptive social cognition, perspective taking and empathy, and prosocial bystander responding. While these techniques are likely to impact multiple types of aggression, the curriculum targets deficits linked to social aggression and tailors its content toward managing relational victimization. Socially aggressive students are also provided with leadership training to learn to influence peers through prosocial approaches. Given the current results, it may also be important to help children cope with social manipulation in order to prevent academic difficulties. Schools could offer direct academic support to victims of social manipulation or to students who appear to be highly reactive to these experiences. Such support might include classroom accommodations to help students maintain focus and engagement throughout the school day, along with tutoring services to assist students who are (or are at risk of) struggling academically. It may also be beneficial to teach students effective ways to cope with social manipulation in order to buffer its potential impact on their academic functioning. Swearer, Grills, Haye, and Tam Cary (2004) recommend teaching youth a variety of cognitive–behavioral skills (e.g., relaxation methods, cognitive restructuring, and problem solving) to cope with peer victimization. As in the PRAISE program, this type of training could be tailored to manage incidents of social victimization (e.g., by deep breathing after learning of hurtful gossip or by making more adaptive attributions for being excluded). It is important to note several limitations of the current study. First, the sample was limited to fifth-grade students; thus, the findings should not be generalized outside of this developmental period. Second, at only 179 ­students, the sample size was somewhat small; low statistical power may have limited our ability to detect effects. Perhaps associations between other types of victimization and academic achievement would have emerged in a larger sample. With our small sample, we decided not to test g­ ender as a moderator of the victimization—achievement relations. Although metaanalytical findings suggest that gender does not ­moderate the link between achievement and overall levels of victimization (Nakamoto &  Schwartz, 2010), it is worth exploring whether gender influences achievement’s associations with different types of victimization and reactivity to these experiences. Third, we conducted a relatively high number of statistical tests, which inflated our risk of making Type I errors. Additionally, a majority of the

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relations examined were not statistically significant. Thus, the current findings should be interpreted cautiously. However, a consistent pattern of results emerged: Only social manipulation and affective reactivity to social manipulation correlated with achievement. In light of previous research (Woods & Wolke, 2004), we believe this concise pattern of results provides further support for unique associations between preadolescents’ social manipulation and achievement. Fourth, peer victimization was assessed solely though self-reports; additional data from peers or teachers, along with alternate measurement methods (e.g., observations), would provide a more robust picture of v­ ictimization. Fifth, the study was concurrent in nature; thus, conclusions cannot be drawn about temporal relations among the constructs. Throughout this article, we likely implied a model in which earlier ­victimization contributes to later achievement; however, the reverse pattern is also plausible. Card and Hodges (2008) outlined dual models: one in which peer victimization is a risk factor for decreased academic achievement and another in which poor achievement is a risk factor for increased victimization. Accordingly, pathways between victimization and achievement may be bidirectional and warrant further study. Sixth, the relations between daily peer victimization and daily negative affect are also likely to be bidirectional. Although we framed these daily relations as an estimate of children’s affective reactivity to peer ­victimization, they could also reflect the degree to which children’s daily victimization experiences fluctuate in relation to their daily negative affect; thus, the findings for our affective reactivity variables should be interpreted with some caution. In future daily-diary studies, researchers could explore the directional links among children’s peer victimization and negative affect by examining potential carryover effects. Even with the noted limitations, the results of the current ­investigation suggest that social manipulation, and affective reactivity to this type of ­victimization, may be important factors in preadolescent students’ ­academic struggles. Future work in this area may help to address the impact of peer victimization on children’s school functioning and ultimately help students achieve their optimal level of academic success. References Affleck, G., Tennen, H., Urrows, S., & Higgins, P. (1994). Person and ­contextual features of daily stress reactivity: Individual differences of undesirable daily events with mood disturbance and chronic pain intensity. Journal of Personality and Social Psychology, 66, 329–340.

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