does life satisfaction predict victimization experiences in adolescence?

Psychology in the Schools, Vol. 45(8), 2008 C© 2008 Wiley Periodicals, Inc.Published online in Wiley InterScience (www.interscience.wiley.com) DOI: 10.1002/pits.20336

DOES LIFE SATISFACTION PREDICT VICTIMIZATION EXPERIENCES INADOLESCENCE?

KELLIE MARTIN, E. SCOTT HUEBNER, AND ROBERT F. VALOIS

University of South Carolina

Longitudinal relationships between adolescents’ life satisfaction and peer victimization and proso-cial experiences were assessed. A total of 417 students in Grades 6 – 8 completed the Multidi-mensional Students’ Life Satisfaction Scale (MSLSS: Huebner, 1994) and the Children’s SocialExperience Questionnaire – Self Report (SEQ-SR: Crick & Grotpeter, 1996) on two occasions(Time 1 and Time 2), 1 year apart. The results revealed that Time 1 life satisfaction scores did notadd to the prediction of Time 2 overt victimization scores but did add to the prediction of Time 2relational victimization scores and prosocial experiences. Additionally, Time 1 overt victimization,relational victimization, and prosocial experiences did not significantly add to the prediction ofTime 2 general life satisfaction. However, the predictive equations for Time 1 relational victimiza-tion and prosocial experiences approached significance, suggesting the possibility of bidirectionaleffects between life satisfaction and relational victimization and prosocial peer experiences. Mostinterestingly, lower levels of life satisfaction appeared to be a newly identified risk factor fortwo qualitatively distinct types of adverse peer relationships (relational victimization and lack ofprosocial experiences). C© 2008 Wiley Periodicals, Inc.

Psychology has focused primarily on the identification and treatment of psychopathologicalsymptoms. A recent emphasis on “positive psychology” has emerged within the field, which ad-vocates for the identification of personal strengths and environmental resources that foster optimaldevelopment (Seligman & Czikszentmihalyi, 2000). Optimal psychological development reflects asense of well-being that extends beyond the absence of psychopathological symptoms (Greenspoon& Saklofske, 2001).

Although a variety of constructs have been proposed as indicators of psychological well-being,one widely agreed upon construct is life satisfaction (LS). LS is defined as the cognitive appraisalof the quality of life as a whole (Diener, Suh, Lucas, & Smith, 1999). LS reports of adolescentsshow significant test–retest reliability (Huebner, Funk, & Gilman, 2000); however, they fluctuatesignificantly in response to life experiences (Bearsley & Cummins, 1999) and planned interventions(Farrell, Valois, & Meyer, 2003).

Although early research with adults focused on the antecedents of individual differences inLS, recent meta-analytic research indicates that LS is not simply an epiphenomenon, that is, merelya by-product of individual differences in personality and life experiences (Lyubormirsky, King, &Diener, 2005). Rather, the research suggests that LS is an important determinant of outcomes thatare beneficial to individuals, families, and communities. Adults high in LS show greater successin terms of interpersonal, occupational, and physical functioning, suggesting that LS is central tomental and physical health (Lyubormirsky et al., 2005).

Although research on the LS of children and youth has lagged behind that of adults, researchershave also begun investigating individual differences in LS in youth (see Huebner, 2004, for a review).A burgeoning interest in youth LS has revealed a variety of correlates including demographic vari-ables (e.g., socioeconomic status [SES]), personality traits (e.g., extraversion), cognitive processing(e.g., attribution styles), and interpersonal variables (e.g., parent and peer relationships; Huebner,Suldo, & Gilman, 2006). Similar to that of adults, child and youth perceptions of the quality oftheir interpersonal relationships, such as family and friends, are among the strongest correlates oftheir overall LS (see Huebner, Suldo, & Gilman, 2006, for a review). For an example related to

Correspondence to: Scott Huebner, Ph.D, Dept. of Psychology, University of South Carolina, Columbia, SC29208. E-mail: [email protected]

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706 Martin, Huebner, and Valois

interpersonal variables, Furr and Funder (1998) observed the interpersonal behavior of older youth(i.e., college students) paired with a target college student in a dyadic interaction. The target studentsshowed individual differences in personal negativity (a variable composed of self-reports of LSand self-esteem). The partners of students with higher levels of personal negativity became moredomineering, condescending, and detached from the interaction, all within 15 minutes. This studysuggested the possibility that linkages between LS and negative peer interactions may occur amongyounger age groups as well. A study by Martin and Huebner (2007) supported this notion, showingthat adolescents with lower LS were more likely to experience overt and relational victimization andfewer prosocial interactions.

The vast majority of the extant LS research with children and youth has focused on thepresumed antecedents of individual differences in LS (Huebner, 2004). Most studies have involvedone-shot correlational designs, with few studies using experimental or longitudinal designs aimedat distinguishing the antecedents from the consequences of individual differences in LS (Huebner,2004). Thus, little is known about the directionality of the relationships between LS and othervariables. For example, with respect to the Martin and Huebner (2007) study, it is not clear whetherlow LS precedes victimization, with LS serving as a risk factor, or whether victimization precedes LS.

Thus, the purpose of this study was to investigate further the relationships between LS andvictimization experiences of adolescents, using a longitudinal design and multiple types of peer vic-timization experiences. The current study used the Crick and Grotpeter (1995) tripartite conceptual-ization of victimization, consisting of overt victimization (e.g., verbal and physical threats/attacks),relational victimization (e.g., social exclusion, spreading rumors), and reduced prosocial experiences.Crick and Grotpeter (1996) investigated prosocial experiences in conjunction with peer victimiza-tion, finding that prosocial experiences added significant variance to the prediction of loneliness,depression, and social avoidance. Thus, a relative lack of prosocial experiences was considered asdamaging as experiencing peer victimization.

Given that the directionality of the relationships between LS and peer experiences remainsunknown, two hypotheses were evaluated. One hypothesis was that adolescents who experiencefrequent peer victimization and infrequent prosocial experiences are at risk for lower levels of LSin the future. A second hypothesis was that low levels of LS put adolescents at risk for future peervictimization and lack of prosocial experiences.

Regarding the first hypothesis, Storch and colleagues (2004) theorized that threatening peerinteractions create and reinforce negative self-evaluations, leading to social avoidance. The inter-nalization of negative peer feedback was expected to result in increased distress due to negativeself-attributions. In support of this theory, Storch and colleagues demonstrated predicted relation-ships between peer victimization and social phobia, anxiety, and depressive symptoms (Storch &Masia-Warner, 2004; Storch et al., 2004). In support of the alternative hypothesis, the Lyubormirsky,King, and Diener meta-analysis (2005) suggested that reduced LS could be a determinant of increasedvictimization and decreased prosocial experiences.

Specifically, based on the work of Storch and colleagues, the following hypotheses were testedusing two waves of data collection (T1 and T2), 1 year apart:

1. Time 1 levels of overt victimization predict Time 2 levels of LS, controlling for Time 1 LS;2. Time 1 levels of relational victimization predict Time 2 levels of LS, controlling for Time 1

LS; and3. Time 1 levels of prosocial experiences predict Time 2 levels of LS, controlling for Time 1

LS.

Consistent with the work of Lyubormirsky et al. (2005), the reverse hypotheses were assessedusing Time 1 levels of LS to predict Time 2 levels of overt victimization, relational victimization, and

Psychology in the Schools DOI: 10.1002/pits

Life Satisfaction and Victimization 707

prosocial experiences, controlling for Time l levels of overt victimization, relational victimization,and prosocial experiences. Because it seemed likely that negative peer experiences (e.g., peervictimization and lack of prosocial experiences) should result in decreased LS in youth, the moreinteresting finding was expected to involve possible support for the latter set of hypotheses, that is,that lower LS would be a precursor to negative peer experiences. Such a finding would provide somepreliminary support for the notion that LS is a key antecedent of important interpersonal problemsin adolescence as well as adulthood. If both sets of hypotheses were supported, then the possibilityof bidirectional relationships would have to be considered.

METHOD

Participants

At Time 1, 571 (226 boys and 345 girls) students in Grades 6–8 from five public middle schoolsin a rural school district near a small Southeastern U.S. city were participants. The sample included203 sixth graders, 182 seventh graders, and 186 eighth graders. Their mean age was 13.0 (standarddeviation [SD] = 1.03 years). A total of 44.3% were African American, 43.1% were Caucasian,3.2% were Asian, 1.2% were Hispanic, 2.1% were American Indian, and 6.1% represented otherethnic groups. Also, 51% reported receiving free or reduced lunch (i.e., low SES).

At Time 2, 417 of the 571 students participated, yielding a return rate of 73.0%. The closeproximity of the schools to a large military base likely contributed to the attrition from Time 1to Time 2. The Time 2 sample included 4 sixth grade, 150 seventh grade, 137 eighth grade, and127 ninth grade students. Their mean age was 13 years, 11 months (SD = 1.02 years). A total of40.9% of the participants were African American, 45.9% were Caucasian, 2.8% were Asian, 1.2%were Hispanic, 2.4% were American Indian, and 6% represented other ethnic groups. Also, 52%reported receiving free or reduced lunch.

Chi-square tests on demographic variables between students who participated at Time 1 onlyand those participating at Time 1 and Time 2 were conducted to assess bias related to attrition. Therewas no association between time and gender (χ2 (1) = .326, p > .01), race (χ2 (5) = 7.07, p > .01),or SES (χ2 (1) = 5.77, p > .01), suggesting comparability across groups.

Differences in LS, overt victimization, relational victimization, and prosocial experiences werealso assessed between students participating at Time 1 only versus students participating at Times 1and 2. Time 1 only students did not differ on Time 1 LS (t(563) = .574, p > .01), overt victim-ization (t(563) = −.584, p > .01), relational victimization (t(563) = −1.042, p > .01), or prosocialexperiences (t (563) = −.342), p > .01).

Procedures

Approval was obtained from the referent university and school district institutional reviewboards. At Time 1, consent forms were mailed to parents asking for permission for their child toparticipate in both waves of data collection. A total of 3,710 parental consent forms were distributedacross the five schools. All students who received parent consent assented at Time 1 (15.4%). AtTime 2, initial participants were recruited to participate and student assent was obtained again.

Data collection procedures were similar at Time 1 and Time 2. Trained research assistantspresented instructions and were available throughout the collection to answer questions. Studentswere assembled in groups of 20–100 at their respective schools; the size of the groups dependedon available space, as well as the amount of adult assistance available to promote efficient datacollection. Students were told that their responses would remain confidential, informed of their rightto withdraw from the study at any time, and asked to complete all measures in the packet. The orderof presentation of the LS and victimization measures was counterbalanced. Before completing the



study measures, students answered a brief series of demographic questions regarding age, gender,race, and SES (free or reduced rate lunch).

Measures

Multidimensional Students’ Life Satisfaction Scale (MSLSS: Huebner, 1994). The MSLSSis a 40-item self-report scale assessing general LS in children from 8 to 18 years old. Responsesinvolve a 6-point Likert Scale (1 = strongly disagree to 6 = strongly agree). The general LS scorewas obtained by summing items and dividing by 40.

Studies of the MSLSS have consistently demonstrated good psychometric properties (seeHuebner & Gilman, 2002 for a review). Alpha coefficients ranged from .90 to .92. Test–retestreliability across a 4-week interval was .81 for the total score. For the current sample, alphas were.83 and .80 for Time 1 and Time 2, respectively. Concurrent validity has been demonstrated throughmeaningful correlations with other self-report LS indexes and parent reports. Weak relationshipswith demographics (e.g., gender) have been established (Huebner, 1994; Huebner, Laughlin, Ash,& Gilman, 1998).

Children’s Social Experiences Questionnaire – Self Report (CSEQ-SR: Crick & Grotpeter,1996). The CSEQ-SR consists of three subscales: Overt Victimization, Relational Victimization,and Prosocial Experiences. The subscales measure the frequency of particular experiences (1 = never,2 = almost never, 3 = sometimes, 4 = almost all the time, and 5 = all the time). The Overt Victim-ization subscale assesses the frequency with which other students harm or threaten to harm one’sphysical well-being. The Relational Victimization subscale assesses how often students attempt toharm one’s peer relationships. The Prosocial Experiences scale measures how often one is the targetof supportive acts. Responses to each subscale were summed to yield a composite score rangingfrom 5 to 25.

Crick and Grotpeter (1996) initially validated the CSEQ-SR on 474 students in Grades 3–6.Principal Components Analysis supported the three subscales. Alphas were .78, .80, and .77 for theOvert, Relational, and Prosocial scales, respectively.

Storch, Crisp, Roberti, Bagner, and Masia-Warner (2005) supported the use of the CSEQ-SRwith adolescents. Confirmatory factor analysis again supported the three factors. Alpha coefficientswere .60 for Overt Victimization, .78 for Relational Victimization, and .82 for Prosocial Experiences.Test–retest reliability coefficients were .57 for Overt Victimization, .53 for Relational Victimization,and .73 for Prosocial Experiences. For the current samples at Time 1 and Time 2, respectively, alphacoefficients were .82 and .84 (Overt), .79 and .85 (Relational), and .81 and .85 (Prosocial).

Validity has been further supported in that the rejected children reported more overt victim-ization than did popular or controversial children and more relational victimization than all othergroups (popular, average, neglected, controversial). Average children also reported more relationalvictimization than did popular, controversial, or neglected ones. Finally, popular children reportedmore prosocial experiences than did rejected children (Crick & Grotpeter, 1996).

RESULTS

Means and SD values for LS, overt victimization, relational victimization, and prosocial expe-riences at both time points are summarized in Table 1. Means and SD values for these variables atboth time points are consistent with past research (e.g., Gilman, Huebner, & Laughlin, 2000; Storchet al., 2005).

Before proceeding, normality of criterion variables (e.g., Time 2 LS, overt victimization,relational victimization, and prosocial experiences) was assessed by plotting histograms. Uponplotting histograms, distributions for Time 2 LS and Time 2 prosocial experiences appeared to be



Table 1Means and Standard Deviations (SD) for General Life Satisfaction, Overt Victimization, Relational Victimiza-tion, and Prosocial Experience Scores at Times 1 and 2

Time 1 Time 2

Variable Mean SD Mean SD

General Life Satisfaction 4.71 0.71 4.40 0.72Overt Victimization 8.47 4.02 8.31 4.19Relational Victimization 9.42 4.35 9.20 4.64Prosocial Experiences 17.95 4.53 18.38 4.20

normal. However, it was observed that the Time 2 overt and relational victimization scores werepositively skewed (1.68 and 1.36, respectively). This finding was not unexpected given past researchindicating that victimization experiences are directed toward a minority of students (Perry, Kusel,& Perry, 1988). Despite this violation of the normality assumption, parametric tests proceeded asplanned for several reasons.

Of primary importance, the effect of the violation of the normality assumption on significancetests depends on the sample size, with problems occurring only with small samples (Cohen, Cohen,West, & Aiken, 2003). With large sample sizes, non-normality does not lead to serious problemswith significance tests. Moreover, both square root and log transformations were conducted, andneither changed the shape of the distributions. Additionally, the intercorrelations of study variablesdid not differ across nontransformed and transformed data.

A p value of .01 was selected as the criterion for significance for all parametric tests. Zero-ordercorrelations among all variables at both time points were calculated and reported in Table 2. The1-year stability coefficient was .52 for overt victimization, .49 for relational victimization, .56 forprosocial experiences, and .61 for LS.

Analyses were conducted to assess which Time 1 demographic variables needed to be controlledwhen predicting Time 2 LS, overt victimization, relational victimization, and prosocial experiences.A series of analyses of variance (ANOVAs) were run to assess meaningful relationships between

Table 2Zero-Order Correlations among General Life Satisfaction (GLS), Overt Victimization (OV), Relational Victim-ization (RV), and Prosocial Experiences (PE) for Time 1 and Time 2

Time 1 Time 2

GLS OV RV PE GLS OV RV PE

GLS 1.00 −.31∗ −.28∗ .48∗ .61∗ −.25∗ −.28∗ .42∗

OV — 1.00 .69∗ −.24∗ −.26∗ .52∗ .40∗ −.30∗

Time 1 RV — — 1.00 −.12∗ −.25∗ .38∗ .49∗ −.19∗

PE — — — 1.00 .42∗ −.24∗ −.19∗ .56∗

GLS — — — — 1.00 −.32∗ −.33∗ .47∗

OV — — — — — 1.00 .75∗ −.32Time 2 RV — — — — — — 1.00 −.25∗

PE — — — — — — — 1.00

∗p < .01.



Table 3Hierarchical Regression Analyses Predicting Time 2 Levels of Overt Victimization, Relational Victimization,and Prosocial Experiences From Time 1 General Life Satisfaction Scores

Step & Variable B SEB β �R2 �F

Time 2 Overt VictimizationGender −2.18 .40 −.26 .07 29.29∗

Time 1 Overt Victimization .51 .05 .49 .22 123.57∗

Time 1 General Life Satisfaction −.50 .25 −.09 .007 4.05Relational Victimization

Time 1 Relational Victimization 4.60 .48 .46 .21 107.92∗

Time 1 General Life Satisfaction −1.02 .28 −.16 .025 13.08∗

Prosocial ExperiencesGender 3.42 .39 .40 .16 75.80∗

Time 1 Prosocial Experiences .426 .04 .48 .21 129.64∗

Time 1 General Life Satisfaction 1.07 .26 .19 .025 16.67∗

Note. SE = standard error.∗p < .01.

Time 1 gender, race, and SES with Time 2 variables. Gender significantly related to Time 2 LS(F (1, 563) = 8.77), Time 2 overt victimization (F (1, 411) = 29.29), and Time 2 prosocial expe-riences (F (1, 405) = 75.79). Specifically, girls (mean [M] = 7.41) reported lower levels of overtvictimization than boys (M = 9.59), but girls (M = 19.72) reported higher levels of prosocial experi-ences than boys (M = 16.30) at Time 2. These findings were consistent with past research (Crick &Grotpeter, 1996; Martin & Huebner, 2007; Storch et al., 2005). Although past research demonstratednegligible effects of gender, girls in this study (M = 4.50) reported higher levels of LS than did boys(M = 4.27) at Time 2, yielding an effect size of .31. Although this was a statistically significantdifference, the practical difference was thus “small” according to Cohen (1988), consistent with pastresearch (Huebner et al., 2006). Neither race nor SES meaningfully related to any Time 2 variablesof interest.

The effect of grade level on Time 2 variables was also assessed by calculating Pearson productmoment correlations, yielding only one significant relationship, between grade and Time 2 LS(r = −.18). Thus, as grade increased, LS scores at Time 2 were lower. This finding was consistentwith past research showing a decline in LS scores with age (Chang, McBride-Chang, Stewart, &Au, 2003; Suldo & Huebner, 2004; Ullman & Tatar, 2001).

Two sets of hierarchical regression analyses were conducted to test the two major hypotheses.First, three separate regression analyses were conducted to assess the potential of Time 1 LS scoresto predict Time 2 levels of overt victimization, relational victimization, and prosocial experiences.The results of these analyses are shown in Table 3. Time 1 LS did not add to the prediction ofTime 2 overt victimization above what was explained by gender and Time 1 overt victimization(b =−.09, �F (1, 409) = 4.05, �R2 = .007). Time 1 LS significantly added to the prediction ofTime 2 relational victimization scores beyond what was explained by Time 1 relational victimization(b =−.16, �F (1, 405) = 13.08, �R2 = .025). Also, Time 1 LS added to the prediction of Time 2prosocial experiences beyond what was explained by gender and Time 1 prosocial experiences(b = .19, �F (1, 403) = 16.68, �R2 = .025).

Next, three separate regression analyses were conducted to assess the potential of Time 1 overtvictimization, relational victimization, and prosocial experiences to predict Time 2 LS. Results are



Table 4Hierarchical Regression Analyses Predicting Time 2 General Life Satisfaction Scores from Time 1 OvertVictimization, Relational Victimization, and Prosocial Experiences

Step & Variable B SEB β �R2 �F

Time 2 General Life SatisfactionGender, Grade −.17 .04 −.19 .06 11.51∗

Time 1 General Life Satisfaction .59 .04 .59 .31 186.00∗

Time 1 Overt Victimization −.01 .01 −.06 .003 1.63Time 2 General Life Satisfaction

Gender, Grade −.17 .04 −.19 .06 11.51∗

Time 1 General Life Satisfaction .59 .04 −.19 .31 186.00∗

Time 1 Relational Victimization −.01 .01 −.09 .006 3.86Time 2 General Life Satisfaction

Gender, Grade −.17 .04 −.19 .06 11.51∗

Time 1 General Life Satisfaction .59 .04 −.19 .31 186.00∗

Time 1 Prosocial Experiences .02 .01 .11 .008 4.75

Note. SE = standard error.∗p < .01.

summarized in Table 4. Time 1 overt victimization scores did not add to the prediction of Time 2LS beyond what was explained by gender, grade, and Time 1 LS (b = −.06, �F (1, 370) = 1.63,�R2 = .003). Time 1 relational victimization scores did not add to the prediction of Time 2 LSbeyond variance explained by gender, grade, and Time 1 LS, using the relatively stringent alpha of.01 (b = −.09, �F (1, 370) = 3.86, �R2 = .006). However, this prediction approached significance(p < .05). Time 1 prosocial experiences also did not add to the prediction of Time 2 LS beyond thatexplained by, gender, grade, and Time 1 LS (b = .11, �F (1, 370) = 4.75, �R2 = .008). However,this prediction also approached significance (p < .03).

DISCUSSION

Previous cross-sectional analyses established a linear association between LS and peer victim-ization and prosocial experiences (Martin & Huebner, 2007). Using a longitudinal design, this studyinvestigated two hypotheses related to the directionality of these relationships: (1) Time 1 levels ofLS predict Time 2 levels of overt victimization, relational victimization, and prosocial experiences(controlling for Time 1), and (2) Time 1 levels of overt victimization, relational victimization, andprosocial experiences predict Time 2 levels of LS (controlling for Time 1). Unequivocal support wasestablished for the first hypothesis, for two of the three peer relationship variables. Although Time 1LS did not predict Time 2 levels of overt victimization, it did add to the prediction of Time 2 relationalvictimization and prosocial experiences. Regarding the second hypothesis, equivocal support wasfound for the same peer relationship variables. Although Time 1 overt victimization experiences didnot predict Time 2 LS, the equation for Time 1 relational victimization and prosocial experiencesapproached significance, suggesting the possibility of bidirectional effects between LS and relationaland prosocial experiences. Future research is needed to clarify these relationships.

The potential for peer experiences to lead to decreased LS in adolescents seems intuitive giventhe extant literature suggesting that peer victimization and lack of prosocial experiences lead tofuture maladjustment (Buhs & Ladd, 2001; Colarossi & Eccles, 2003; Demaray, Malecki, Davidson,Hodgson, & Rebus, 2005; Gladstone, Parker, & Malhi, 2006). In contrast, the finding that low LS is



a precursor of relational and prosocial experiences is more interesting, as it points toward a newlyidentified individual difference variable (i.e., LS) that puts youth at risk for negative peer interactions.

Relational peer victimization and lack of prosocial experiences may appear quite similar uponinitial examination, however, research supports that the two are conceptually and empirically dif-ferentiable (Crick & Grotpeter, 1996; Storch et al., 2005). Relational victimization refers to theexperience of negative behaviors aimed at damaging one’s social standing in the peer group, im-plying some level of intentional malice whereas (lack of) prosocial experiences refer to neglect oravoidance from one’s peers, without intentional malice (Crick & Grotpeter, 1996). Thus, the findingsindicate that low LS puts students at risk for two distinctive types of negative peer experiences.

The explanation for the finding that lower LS predicts relational victimization and prosocialexperiences, but not overt victimization is unclear. However, the findings are consistent with pastresearch investigating the interpersonal outcomes of LS in adults suggesting that the negative inter-actions experienced by dissatisfied individuals tend to involve neglect rather than overt victimization(Staw, Sutton, & Pelled, 1994).

Whatever the case, dissatisfied students appear to be at greater risk for relational victimizationand/or fewer prosocial experiences compared to satisfied students. This finding is also consistentwith the work of Furr and Funder (1998), which demonstrated that unhappy undergraduate studentsare disliked and avoided by others, even during interactions as brief as 15 minutes. In fact, thecurrent study offers a methodological advance by using longitudinal data over a 1-year time-frame,suggesting that low LS serves as a risk factor for future interpersonal problems. This research alsogives further credence to the position of Lyubormirsky et al. (2005) that high LS is not a mereepiphenomenon, rather it represents a protective strength that facilitates positive future outcomes.

The current study has several limitations. To begin, the sample was not representative ofthe population of U.S. adolescents. Generalizations from this study should be made with caution.Another weakness was that the data were derived exclusively from self-reports, increasing sharedmethod variance. Future researchers should consider the use of multiple methods (peer and teacherreports).

Nevertheless, this study had unique strengths, including its longitudinal design. This designextended beyond previous research by investigating LS as a possible antecedent of adolescents’interpersonal functioning within the peer context. Future research should investigate the mechanismsthat account for the relationship between LS and negative peer experiences. For example, one possiblemechanism accounting for the LS-peer experiences relationship arises from Fredrickson’s (2001)“broaden and build” model of positive emotions. Based on this model, positive emotions situateindividuals to expand their resources and build their coping skills to navigate future challenges.Perhaps satisfied adolescents, who show frequent positive emotions (Huebner & Dew, 1996), possessbetter coping mechanisms, which facilitate positive peer experiences. Therefore, one possible avenuefor future research is to investigate coping skills as possible mediating mechanisms linking LS andpeer experiences.

Other psychosocial mechanisms may account for the negative peer experiences of dissatisfiedadolescents. One possibility is that satisfied adolescents possess personality characteristics that makethem more or less attractive to their peers. Prior research suggests that, of the most widely researchedpersonality traits, extraversion or the inclination to relate to other people demonstrates significantcorrelations with LS (DeNeve & Cooper, 1998). Perhaps dissatisfied youth also exhibit lower levelsof extraversion, which in turn leads others to avoid them.

This study contributes to the understanding of the consequences of individual differences inLS in early adolescence, specifically in the context of peer victimization. Moreover, the studysuggests new methods for improving prevention efforts related to peer victimization. The mostimportant implication may be that, as part of comprehensive screening programs, efforts to develop



school-wide measurement systems that monitor levels of adolescents’ LS may enhance schoolprofessionals’ ability to identify students who are at risk for peer relationship problems and developeffective intervention programs to prevent or reduce victimization experiences. In addition to theschool context, Huebner et al. (2004) have elaborated on numerous benefits of LS data in thebroader public health care domain. Although the development of empirically validated interventionsto directly enhance LS in youth awaits development, interventions that target the determinants ofindividual differences in LS may offer the most promising avenue at present (see Huebner et al.,2006).

REFERENCES

Bearsley, C., & Cummins, R. A. (1999). No place called home: Life quality and purpose of homeless youths. Journal ofSocial Distress and the Homeless, 8, 207 – 236.

Buhs, E. S., & Ladd, G. W. (2001). Peer rejection in kindergarten as an antecedent of young children’s school adjustment:An examination of mediating processes. Developmental Psychology, 60(23), 550 – 560.

Chang, L., McBride-Chang, C., Stewart, S. M., & Au, E. (2003). Life satisfaction, self-concept, and family relations inChinese adolescents and children. International Journal of Behavioral Development, 27, 182 – 189.

Cohen, J. (1988). Statistical power analysis for the behavioral sciences. New York: Academic Press.Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral

sciences – Third Edition. Mahwah, NJ: Lawrence Erlbaum Associates Publishers.Colarossi, L. G., & Eccles, J. S. (2003). Differential effects of support providers on adolescent mental health. Social Work

Research, 27, 19 – 30.Crick, N. R., & Grotpeter, J. K. (1995). Relational aggression, gender, and social-psychological adjustment. Child Develop-

ment, 66, 710 – 722.Crick, N. R., & Grotpeter, J. K. (1996). Children’s treatment by peers: Victims of relational and overt aggression. Development

and Psychopathology, 8, 367 – 380.Demaray, M. K., Malecki, C. K., Davidson, L. M., Hodgson, K. K., & Rebus, P. (2005). The relationship between social

support and student adjustment: A longitudinal analysis. Psychology in the Schools, 42, 691 – 706.DeNeve, K. M., & Cooper, H. (1998). The happy personality: A meta-analysis of 137 personality traits and subjective

well-being. Psychological Bulletin, 124, 197 – 229.Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological

Bulletin, 125, 276 – 302.Farrell, A., Valois, R. F., & Meyer, A. L. (2003). Impact of the RIPP violence prevention program on rural middle school

students. Journal of Primary Prevention, 24, 143 – 167.Fredrickson, B. L. (2001). The role of positive emotions in positive psychology: The broaden and build theory of positive

emotions. American Psychologist, 56, 218 – 226.Furr, R. M., & Funder, D. C. (1998). A multimodal analysis of personal negativity. Journal of Personality and Social

Psychology, 74, 1580 – 1591.Gilman, R., Huebner, E. S., & Laughlin, J. E. (2000). A first study of the Multidimensional Students’ Life Satisfaction Scale

with adolescents. Social Indicators Research, 52, 135 – 160.Gladstone, G. L., Parker, G. B., & Malhi, G. S. (2006). Do bullied children become anxious and depressed adults? A cross-

sectional investigation of the correlates of bullying and anxious depression. Journal of Nervous and Mental Disease,194, 201 – 208.

Greenspoon, P., & Saklofske, D. H. (2001). Toward an integration of subjective well-being and psychopathology. SocialIndicators Research, 54, 81 – 108.

Huebner, E. S. (1994). Preliminary development and validation of a multidimensional life satisfaction scale for children.Psychological Assessment, 6, 149 – 158.

Huebner, E. S. (2004). Research on assessment of life satisfaction of children and adolescents. Social Indicators Research,66, 3 – 33.

Huebner, E. S., & Dew, T. (1996). The interrelationships of positive affect, negative affect and life satisfaction in an adolescentsample. Social Indicators Research, 38, 129 – 137.

Huebner, E. S., Funk, B. A., & Gilman, R. (2000). Cross-sectional and longitudinal psychosocial correlates of adolescent lifesatisfaction reports. Canadian Journal of School Psychology, 16, 53 – 64.

Huebner, E. S., & Gilman, R. (2002). An introduction to the Multidimensional Students’ Life Satisfaction Scale. SocialIndicators Research, 60, 115 – 122.



Huebner, E. S., Laughlin, J. E., Ash. C., Gilman, R. (1998). Further validation of the Multidimensional Students’ LifeSatisfaction Scale. Journal of Psychoeducational Assessment, 16, 118 – 134.

Huebner, E. S., Suldo, S. M., & Gilman, R. (2006). Life satisfaction. In G. G. Bear & K. M. Minke (Eds.), Children’s NeedsIII (pp. 357 – 368). Washington, D.C: National Association of School Psychologists.

Huebner, E. S., Valois, R. F., Suldo, et al. (2004). Perceived quality of life: A neglected component of adolescent healthassessment and intervention. Journal of Adolescent Health, 34, 270 – 278.

Lyubormirsky, S., King, L., & Diener, E. (2005). The benefits of frequent positive affect: Does happiness lead to success?Psychological Bulletin, 131, 803 – 855.

Martin, K. M., & Huebner, E. S. (2007). Peer victimization and prosocial experiences and emotional well-being of middleschool students. Psychology in the Schools, 44, 199 – 208.

Perry, D. G., Kusel, S. J., & Perry, L. C. (1988). Victims of peer aggression. Developmental Psychology, 24, 807 – 814.Seligman, M. E. P. & Csikszentmihalyi, M. (Eds.). (2000). Positive psychology: An Introduction. American Psychologist,

55(1), 5 – 14.Staw, B. M., Sutton, R. I., & Pelled, L. H. (1994). Employee positive emotion and favorable outcomes at the workplace.

Organization Science, 5, 51 – 71.Storch, E. A., Crisp, H., Roberti, J. W., Bagner, D. M., & Masia-Warner, C. (2005). Psychometric evaluation of the social

experience questionnaire in adolescents: Descriptive data, reliability, and factorial validity. Child Psychiatry and HumanDevelopment, 36, 167 – 176.

Storch, E. A., & Masia-Warner, C. (2004). The relationship of peer victimization to social anxiety and loneliness in adolescentfemales. Journal of Adolescence, 27, 351 – 362.

Storch, E. A., Roth, D. A., Coles, M. E., Heimburg, R. G., Bravata, E. A., & Moser, J. (2004). The measurement and impactof childhood teasing in a sample of young adults. Journal of Anxiety Disorders, 18, 681 – 694.

Suldo, S. M., & Huebner, E. S. (2004). The role of life satisfaction in the relationship between authoritative parentingdimensions and adolescent problem behavior. Social Indicators Research, 66, 165 – 195.

Ullman, C., & Tatar, M. (2001). Psychological adjustment among Israeli adolescent immigrants: A report on life satisfaction,self-concept, and self-esteem. Journal of Youth and Adolescence, 30, 449 – 463.


does life satisfaction predict victimization experiences in adolescence?

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