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. Author manuscript; available in PMC: 2020 Nov 1.
Published in final edited form as: Psychol Violence. 2019 Nov;9(6):644–652. doi: 10.1037/vio0000234

Social Intelligence Attenuates Association between Peer Victimization and Depressive Symptoms among Adolescents

Stephen J Lepore 1, Wendy Kliewer 2
PMCID: PMC6822980  NIHMSID: NIHMS1016935  PMID: 31673477

Abstract

Objective:

Peer victimization is linked to psychological distress, but some youth are less affected than others. Identifying protective factors can inform prevention programs. Using longitudinal data from 7th graders we tested the role of social intelligence as a protective factor in the relation between peer victimization and depressive symptoms.

Method:

Students (N = 986; 54% female; 43% non-white) from three schools provided self-report data via computer-assisted survey interviews in the fall (Time 1, T1) and spring (Time 2, T2) of 7th grade.

Results:

Females reported more depressive symptoms and less physical victimization than males but did not differ from males on social intelligence or relational victimization. Regression analyses controlling for T1 depressive symptoms and other potential confounds revealed that both physical and relational victimization were positively and significantly associated with T2 depressive symptoms, but the strength of the relation varied by gender and by social intelligence. Specifically, the associations between victimization and depressive symptoms were stronger among females than males and among those with low or moderate rather than high social intelligence.

Conclusions:

Social intelligence may protect youth from the psychological harms of peer victimization and could be an effective target of prevention programming.

Keywords: social intelligence, peer victimization, physical victimization, relational victimization, depressive symptoms, resilience

Adolescent peer victimization, which consists of one’s peers attempting to cause bodily or social harm, is common throughout the world. Results of large, cross-national studies suggest that 13 to 34% of adolescents have experienced peer victimization globally (Craig et al., 2009; Fleming & Jacobsen, 2010). Recent U.S. prevalence data show that approximately 20% of high-school students (Kann et al., 2016) and 16% of middle-school children (CDC, 2015) experienced peer victimization over a one-year period. Victimization that causes physical harm to the body may be more common among boys than girls, whereas victimization that causes harm to social relationships appears to be experienced equally by boys and girls (Casper & Card, 2017). Peer victimization can result in immediate and lasting symptoms of anxiety and depression (van Geel et al., 2014), and has been linked to suicide (Klomek, Sourander, & Gould, 2010). Given the prevalence and adverse effects of peer victimization, it is critical to identify factors that might protect youth from peer victimization. By identifying modifiable protective factors (e.g., Helms et al., 2015; Kaynak, Lepore, Kliewer, & Jaggi, 2015; Kaynak, Lepore, & Kliewer, 2011; Kliewer, Lepore, Oskin, & Johnson, 1998), such as social intelligence, we may be able to develop and disseminate interventions that enhance these factors.

Social Intelligence as a Resilience Factor

Resilience generally means positive adaptation despite adversity (Luthar, 2006). It has been described as a capacity to resist or recover quickly from adversity, but also as an ability to recover gradually or to function successfully in some life domains despite experiencing deficits in other domains (Lepore & Revenson, 2006). In the context of peer victimization, for example, some children may show no adverse consequences, some may initially experience distress but eventually recover, and still others may be unaffected in one domain, such as academics, but be adversely affected in another domain, such as emotional well-being.

Because peer victimization occurs in the context of social relationships, social intelligence could be an important resilience factor. As early as 1937, social intelligence was identified as a unique faculty that allows individuals to understand and manage people (Thorndike & Stein, 1937). Contemporary theory maintains that social intelligence includes knowledge of self and of others that enables individuals to behave appropriately and effectively in social situations (Salovey & Mayer, 1989; Weis & SuB, 2005). Other theorized components of social intelligence include perceptual, cognitive-analytical, and behavioral abilities or skills (Bjorkqvist, 2007; Björkqvist, Österman, & Kaukiainen, 2000). With respect to perceptual ability, individuals high in social intelligence can accurately perceive moods in self and others through verbal and non-verbal cues. In terms of cognitive-analytical ability, individuals high in social intelligence understands social rules, can de-code social situations, and understand the thoughts and feelings of self and others. And, finally, in terms of behavioral ability, individuals high in social intelligence can act in socially acceptable ways in different situations and effectively influence others’ behaviors. Many of the competencies associated with social intelligence rely on emotional intelligence, which includes skills in identifying, expressing, understanding, managing, and using emotions adaptively (Salovey & Pizarro, 2003). Emotional intelligence has been identified as a subcomponent of the broader construct of social intelligence (Crowne, 2009; Salovey & Mayer, 1989).

In a conflict situation, a high level of social intelligence could be immediately protective if it enables an individual to de-escalate the conflict through various means, such as negotiation, humor, withdrawal, or self-assertion. Social intelligence also could promote resilience through effective psychological and behavioral coping post-victimization, such as mobilizing social support from others (e.g., Rowsell, Ciarrochi, Deane, & Heaven, 2016), using socially acceptable ways to express aggression indirectly (Kaukiainen, Bjorkqvist, Österman, & Lagerspetz, 1996; Wallenius, Punamäki, & Rimpelä, 2007), and regulating negative emotional responses to victimization. To the extent that social intelligence can help youth to tap social, behavioral and emotional resources to respond to peer victimization, it may diffuse stress, instill feelings of efficacy, prevent isolation, and promote a positive self-image—all powerful antidotes to the psychological distress that can accompany peer victimization. Importantly, because social intelligence is comprised of teachable social-emotional skills and competencies (Dowswell & Chessor, 2014), it could be an important target of interventions to help protect youth from the adverse psychological effects of peer victimization.

Hypotheses and Study Overview

This study tested the primary hypotheses that: (1) the positive association between physical victimization by peers and depressive symptoms would be weaker in youth relatively high in social intelligence than in youth relatively low in social intelligence and (2) the positive association between relational victimization by peers and depressive symptoms would be weaker in youth relatively high in social intelligence than in youth relatively low in social intelligence. In addition to our two a priori hypotheses, we conducted exploratory analyses to examine the association between child gender and exposure to and psychological response to peer victimization. One recent study showed no association between adolescent gender and level of social intelligence (Pabian & Vandebosch, 2016). However, there is evidence that adolescent boys are more likely to be victimized than adolescent girls (C. R. Cook, Williams, Guerra, Kim, & Sadek, 2010), and that adolescent girls are at greater risk for depression than adolescent boys (Mojtabai, Olfson, & Han, 2016). Hence, we sought to explore the role of gender on the associations in this study.

To address the study questions, we conducted a secondary analysis of longitudinal data drawn from a multi-wave, two-group randomized controlled trial, called “Writing for Health.” The trial was designed to test whether a behavioral intervention using in-classroom expressive writing exercises (Lepore & Smyth, 2002) could promote adjustment among adolescents exposed to community and peer violence. Participants were adolescents in the 7th grade. This is an important age group in which to address our questions because the transition to middle school is associated with increased exposure to bullying (Card & Hodges, 2008) and internalizing problems (Salk, Hyde, & Abramson, 2017). Those in the experimental group of the parent study wrote for 20 minutes once a week for 6 weeks about their thoughts and feelings toward violence, whereas those in the control group wrote for a parallel duration about daily routines and topics unrelated to violence.

Methods

Participants

Participants were 986 seventh graders (53.7% female; M age = 12.81, SD = 0.48, range = 11.4 – 16.6 years) from three schools within Philadelphia, PA and Richmond, VA metropolitan areas. The sample was racially and ethnically diverse: 24.7% identified as Latino/a; 56.9% identified as White, 21.5% Black or African American, 5.6% Asian, 2.7% American Indian or Alaskan Native, 4.2 as Native Hawaiian or other Pacific Islander and 9.0% identified as multiracial. One fifth of the sample (22.1%) resided in a single-parent household. The original trial recruited 1274 adolescents and 986 (77%) of them received parental consent and provided assent to participate.

Procedures

The appropriate Institutional Reviewer Boards approved study procedures. After receiving signed parental consent and youth assent forms, measures were administered in class using a computer-assisted survey interview (CASI, Sawtooth Software, Inc.). Each respondent could read the survey items and hear them using individual headset-equipped laptops. Time 1 (T1) surveys were administered in fall semester and Time 2 (T2) surveys were administered 6 months later in the spring semester. Data were collected between 2008 and 2011.

Measures

Depressive symptoms.

Level of depressive symptoms was measured at both T1 and T2 with the 10-item Children’s Depression Inventory Short Form (CDI-S), which is a widely used, reliable, and validated measure (Kovacs, 1992). The CDI-S, which was derived from the larger 27-item CDI by deleting those items with lower inter-item correlations, has been found to be similar to the CDI with respect to reliability and validity in adolescent populations (e.g., de la Vega et al., 2016; Libby & Glenwick, 2010) and sensitivity and specificity to detecting depression in hospitalized patients aged 9–12 years (Allgaier et al., 2012). The CDI-S is comprised of 10 sets of three statements that follow the same stem, and respondents choose the statement that best describes them (e.g., Do I feel sad? “0 = I am sad once in a while”; “1 = I am sad many times”; “2 = I am sad all the time”) over the prior two weeks. Scores are summed, ranging from 0 to 20. A score of 3 or greater suggests clinical caseness. Internal consistency was good at both waves in the present study sample (Cronbach’s alpha = 0.85 at T1 and .86 at T2).

Peer victimization.

Level of peer victimization was measured at T1 using the 6-item relational and 6-item overt physical victimization subscales from the Problem Behavior Frequency Scales (PBFS), which is a reliable and validated measure of the frequency of victimization by adolescent peers in the prior month (Farrell, Sullivan, Goncy, & Le, 2016). Respondents indicate how often (“1 = never”; “2 = 1–2 times”; “3 = 3–5 times”; “4 = 6–9 times”; “5 = 10–19 times”; “6 = 20 or more times”) in the past month they were victimized by peers. Subscales consisting of six relational victimization items (e.g., “someone spread a false rumor about you”) and six overt physical victimization items (e.g., “been hit by another kid) were positively correlated (r = .56, p<.001). Scores for each subscale are generated by averaging across items, ranging from 1 to 6.

Internal consistency of each scale was good in the present study sample (Cronbach’s alpha = .77 for overt physical victimization and .82 for relational victimization).

Social intelligence.

We used the revised, self-report version (Wallenius et al., 2007) of the 10-item Peer-Estimated Social Intelligence Scale to measure level of social intelligence in adolescents (Kaukiainen, Bjorkqvist, Osterman, Lagerspetz, & Forsblom, 1995). Self- and peer-estimated scores on social intelligence have been shown to be positively and significantly correlated in adolescents, with correlations ranging from .17 to .55 (all p’s <.001) depending on the age group (Kaukiainen et al., 1999). Respondents indicate how often (“1 = never”; “2 = seldom”; “3 = occasionally”; “4 = often”; “5 = very often”) they are socially intelligent (e.g., “you fit in easily with new people and new situations”; “you are able to get your wishes carried out”; “you easily notice if others lie”). Scores are averaged across items, ranging from 1 to 5. Internal consistency was good in the present study sample (Cronbach’s alpha = .88).

Control variables.

In addition to prior depressive symptoms, we included measures of the following control variables: experimental intervention condition (“0 = control”; “1 = experimental”) and dummy codes (0/1) for the three schools (dummy code 1 based on school location: “1 = Philadelphia school 1”; “0 = Richmond school”; dummy code 2 based on school socioeconomic status (SES): “1 = higher SES school”; “0 =lower SES schools”). SES categories were determined by percentage of students receiving subsidized lunches in the school. Two schools were categorized as low SES, one in Philadelphia and one in Virginia with over 51% of students receiving subsidized lunch, and one school in Virginia was categorized as high SES, with fewer than 6% of students receiving a subsidized lunch. Gender (“0 = female”; “1 = male”) was included as a second moderator variable.

Analytic Strategy

Descriptive information on the study sample including associations among variables is presented first, followed by multivariable analyses. Prior to conducting analyses, we imputed missing data using procedures in SPSS (Version 25, IBM Corporation, 2017). We imputed five data sets and average values were used in the analyses. Comparisons of students with complete versus incomplete data revealed more missing data among males (9.6%) than females (4.5%) and among students from the Philadelphia school (11.8%) than students from the Richmond schools (4.7%) (all p’s<.05). Missing data were not related to the major study variables, overt physical and relational victimization, social intelligence, and depressive symptoms.

Linear regression was used to test the two primary hypotheses as well as the exploratory investigation of the role of gender. We ran two separate regression models, the first with T1 overt physical victimization by peers as the predictor variable, and the second with T1 relational victimization by peers as the predictor variable. In both models T2 depressive symptoms was the dependent variable, and social intelligence and gender were included as moderator variables in the models. Additional variables included in both the physical and relational victimization models were three 2-way interaction terms (victimization X gender, social intelligence X gender, and victimization X social intelligence) and one 3-way interaction term (victimization X social intelligence X gender). These interaction terms allowed us to determine whether the positive association between either physical or relational victimization and depressive symptoms was attenuated by social intelligence (Hypotheses 1 and 2), and if this pattern of attenuation was similar or different for males and females (exploratory analyses). Significant interactions were plotted by calculating simple slopes for the effects of the predictor on the outcome at specified values (low = one standard deviation above the mean, medium = the mean value, high = one standard deviation above the mean).

Using the longitudinal trial data allowed us to predict depressive symptoms while statistically controlling for the influence of prior (T1) depressive symptoms. This is important because of evidence from multiple longitudinal studies showing a reciprocal relation between peer victimization and internalizing problems (Reijntjes, Kamphuis, Prinzie, & Telch, 2010). As previously noted, data were collected in the context of an intervention trial. The intervention had no effect on predictors or outcomes, but to be conservative the experimental intervention condition was included as a covariate in all analyses. Because data were collected from multiple schools, we controlled for school (location and SES) in the modeling, as well. We evaluated the influence of outliers using Cook’s D distance measure (D. R. Cook & Weisberg, 1982) and removed outliers as appropriate.

Results

Descriptive Statistics and Correlations among Study Variables

Table 1 shows the reported prevalence of exposure to peer victimization by victimization type and gender. Participants reported experiencing a mix of both overt physical victimization and relational victimization experiences. Gender differences in mean levels of victimization, depressive symptoms, and social intelligence were examined using t-tests. Females reported more depressive symptoms than males at T1, t(984) = 2.04, p = .04 (Mfemales = 2.35, SD = 3.15; Mmales = 1.95, SD = 3.02) and T2, t(984) = 4.49, p < .001 (Mfemales = 2.41, SD = 3.40; Mmales = 1.55, SD = 2.54), but did not differ from males on social intelligence, t(984) = 1.66, p = .10 or on relational victimization, t(984) = 0.64, p = .54. Males reported more overt physical victimization than females, t(984) = 3.57, p < .001 (Mfemales = 1.36, SD = 0.55; Mmales = 1.50, SD = 0.64). The pattern of gender differences was identical prior to imputing the missing data.

Table 1.

Percentage of Youth Ever Experiencing Peer Victimization in the Prior Month at Time 1 by Victimization Type and Gender (N = 986)

Males (n = 457) Females (n = 529) Overall Sample
Physical Victimization
 Been pushed or shoved by another kid 47.4 33.5 39.9
 Been yelled at or called mean names by another kid 42.4 36.6 39.3
 Been hit by another kid 41.7 26.3 33.4
 Another kid tried to get you to fight 31.6 21.4 26.1
 Another kid threatened to hit/physically harm you 17.8 13.4 15.5
 Threatened/injured by someone with a weapon 4.4 3.8 4.1
Relational Victimization
 Someone spread a false rumor about you 29.9 37.3 33.9
 A kid tried to keep others from liking you by saying mean things about you 32.2 33.1 32.7
 A kid told lies about you to make other kids not like you anymore 21.9 28.7 25.5
 Been left out of an activity on purpose 16.9 16.1 16.5
 A kid who was mad at you tried to get back at you by not letting you be in their group 9.9 15.5 13.9
 A kid said they won’t like you unless you did what they wanted you to do 9.3 11.0 10.2
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Table 2 shows the means, standard deviations, and Pearson’s zero-order correlations among the major study variables. Most students (76%) reported being victimized at least once in the prior month, but the mean levels of physical and relational victimization were modest. Social intelligence was well distributed, encompassing the entire range of the 5-point scale. On average, students reported moderate levels of depressive symptoms, with no significant change from T1 to T2, F(1, 985) = 2.67, p = .10. Over a quarter of the sample scored >3, or possible caseness, at T1 (27%) and T2 (26%) on the CDI-S. Table 2 also shows at both time points level of depressive symptoms was positively associated with physical and relational victimization and negatively associated with social intelligence.

Table 2.

Descriptive Information on and Correlations among Study Variables (N = 986).

2 3 4 5 6 7 8 M SD
1.CDI (T2) .52*** .29*** .37*** −.13*** .02 −.08* −.09** 2.01 3.06
2.CDI (T1) - .37*** .43*** −.14*** .02 −.05 −.05 2.17 3.10
3.Physical Victimization (T1) - .55*** −.08* .06 −.12*** −.16*** 1.42 0.59
4.Relational Victimization (T1) - −.07* −.02 −.09** −.08** 1.35 0.60
5.Social Intelligence - .01 .22*** .22*** 3.14 0.81
6. Intervention Condition - −.01 0
7. Schools: Richmond v Philly - .82***
8. Schools: High v Low SES
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Notes: Intervention condition was coded 0 = control, 1 = intervention. SES = Socioeconomic status. Schools were coded by location (0 = Richmond, 1 = Philadelphia) and SES (0 = Higher SES, 1 = Lower SES). CDI = Children’s Depressive Inventory – Short Form. SES = Socioeconomic status. T1 = Time 1. T2 = Time 2.

*

p < .05;

**

p < .01;

***

p < .001.

Results of Key Hypothesis Testing

Table 3 summarizes the regression analyses predicting T2 depressive symptoms from either physical or relational victimization, social intelligence, gender, and their interactions, controlling for T1 depressive symptoms, intervention condition, school location, and school SES. The model with physical victimization as the predictor variable explained 32% of the variation in T2 depressive symptoms, and was significant, F(11, 971) = 42.20, p < .001. Three outliers were removed from this analysis. As seen in the top half of Table 3, there were main effects of physical victimization, social intelligence, and previous levels of depressive symptoms, as well as physical victimization X social intelligence and physical victimization X gender interactions. The physical victimization X social intelligence interaction is depicted in the top half of Figure 1 (Hypothesis 1). As shown in the figure, at low and medium levels of social intelligence, but not at high levels of social intelligence, there were significant positive associations between physical victimization and depressive symptoms at T2, controlling for prior depressive symptoms and other potential confounds. The top of Figure 2 shows the plot of the physical victimization X gender interaction: there was a positive relation between physical victimization and T2 depressive symptoms after adjusting for potential confounds, but the relation was stronger for females than males.

Table 3.

Regression Analysis Summary for Models Predicting Time 2 Depressive Symptoms (N = 986)

Predictor Unstandardized B Std Error 95% CI for B p
Predictor: Physical Victimization
Intervention condition .03 .16 −.29 to .34 .85
School location −.07 .31 −.67 to .53 .81
School SES −.16 .29 −.72 to .41 .59
Gender 1.66 1.81 −1.88 to 5.21 .36
Depressive symptoms (T1) .45 .03 .40 to .51 < .001
Physical victimization (PV; T1) 4.92 .88 3.19 to 6.65 < .001
Social intelligence (SI) 1.42 .39 .65 to 2.19 <.001
PV X SI −1.32 .27 −1.85 to −.79 < .001
PV X Gender −2.53 1.21 −4.90 to −.15 .04
SI X Gender −.61 .57 −1.72 to .50 .28
PV X SI X Gender .69 .38 −.06 to 1.44 .07
Predictor: Relational Victimization
Intervention condition .10 .16 −.21 to .41 .52
School location −.01 .30 −.61 to .58 .96
School SES −.18 .29 −.74 to .38 .53
Gender 2.44 1.68 −.85 to 5.73 .15
Depressive symptoms (T1) .43 .03 .37 to .48 < .001
Relational victimization (RV; T1) 4.87 .78 3.34 to 6.40 <.001
Social intelligence (SI) 1.26 .36 .56 to 1.96 <.001
RV X SI −1.18 .24 −1.65 to −.71 <.001
RV X Gender −2.77 1.18 −5.08 to −.47 .02
SI X Gender −.68 .53 −1.71 to .36 .20
RV X SI X Gender .65 .38 −.09 to 1.39 .09
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Notes: Intervention condition was coded 0 = control, 1 = intervention. SES = Socioeconomic status. PV = Physical victimization. RV = Relational victimization. SI = Social intelligence. Schools were coded by location (0 = Richmond, 1 = Philadelphia) and SES (0 = Higher SES, 1 = Lower SES). Gender was dichotomous (0 = female, 1 = male) CDI-S = Children’s Depressive Inventory – Short Form. T1 = Time 1.

Figure 1.

Figure 1.

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Plots of the Relation Between Victimization at Time 1 and Depressive Symptoms Time 2 by Level of Social Intelligence, Controlling for Depressive Symptoms at Time 1 and Other Confounds.

Figure 2.

Figure 2.

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Plots of the Relation Between Victimization at Time 1 and Depressive Symptoms at Time 2 by Gender, Controlling for Depressive Symptoms at Time 1 and Other Confounds.

The model with relational victimization as the predictor variable also was significant, F(11, 972) = 44.33, p < .001, explaining a similar amount of variation in T2 depressive symptoms, 33%, as the model using physical victimization. Two outliers were removed from this model. As shown in the bottom half of Table 3, similar to the model with physical victimization, there were main effects of relational victimization, social intelligence, and previous levels of depressive symptoms, as well as significant relational victimization X social intelligence (Hypothesis 2) and relational victimization X gender interactions. The plot of the relational victimization X social intelligence interaction is shown in the bottom half of Figure 1, and mirrors that seen for physical victimization. The bottom of Figure 2 shows the plot of the relational victimization X gender interaction, which also mirrors what was seen for physical victimization.

Discussion

We set out to determine if social intelligence contributes to resilience among youth victimized by peers. Our data suggests that it does, by showing that peer victimization was associated with higher depressive symptoms among youth relatively low in social intelligence but not among youth relatively high in social intelligence. To our knowledge, this is the first study to show that social intelligence can have potentially beneficial effects on mental health among youth who are victimized by peers. This was particularly good news in our sample of middle schoolers, as their rates of peer victimization were high, and many (>25%) evidenced high levels of depressive symptoms.

Our data build on prior research demonstrating links between emotional intelligence, which is related to social intelligence, and mental health outcomes in adolescents. For example, a study of Spanish high-school students showed that higher emotional intelligence was associated with lower levels of depressive and anxious symptoms (Fernandez-Berrocal, Alcaid, Extremera, & Pizarro, 2006). However, the current findings also suggest that the psychological benefits of social and emotional intelligence are manifest when youth experience social stressors, such as peer victimization. These data are consistent with the theory that social intelligence can be a resilience factor for victimized youth.

With respect to gender, we found no differences in levels of social intelligence among males and females. Consistent with prior literature, we found that relative to males, females were at lower risk for overt physical victimization (Casper & Card, 2017), higher risk for depressive symptoms (Salk et al., 2017), and more psychologically vulnerable to peer victimization (Bond, Carlin, Thomas, Rubin, & Patton, 2001). Importantly, in the absence of a significant three-way interaction between gender, victimization, and social intelligence, it appears that improving social intelligence would prove to be beneficial in protecting both males and females from victimization.

Limitations

The current study had several strengths, including the longitudinal design, a relatively large and heterogonous sample, psychometrically sound measures, and controls for potential confounds, including prior depressive symptoms. However, there are limitations of the study. In particular, the reliance on youth self-report measures is significant, because it may have inflated associations between variables due to mono-method bias. It is also possible that self-reports of social intelligence are susceptible to self-serving biases, resulting in overestimates of level of social intelligence (Kaukiainen et al., 1999). Observer-based measures might produce different results. Future research will focus on using multiple methods of assessment.

Research Implications

This study did not examine specific mechanisms to explain the potential protective effect of social intelligence for victimized youth. However, based on theory and the qualities of social intelligence, we speculate that high social intelligence provides youth with social, behavioral and emotional skills and resources to effectively respond to victimization experiences. For example, victims high in social intelligence might be able to mobilize support from peers, which can help protect them from future victimization or simply validate their social standing among friends. Further, high social intelligence may promote effective emotional and behavioral responses to victimization experiences that promote feelings of control and self-efficacy. For example, by being able to regulate one’s own emotions or interpret social cues and emotional states in others, youth high in social intelligence might learn how to avoid or defuse social threats from peers. Social belonging, emotion regulation, perceived control, and self-efficacy are well-known resilience factors (Zolkoski & Bullock, 2012). These theoretical questions can be addressed in future research.

Clinical and Policy Implications

The current findings suggest that programs designed to improve social intelligence might help to protect youth from the psychological harm related to peer victimization. One systematic review suggests that school-based Social-Emotional Learning (SEL) interventions are effective at improving social intelligence (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011), though there is a need for more well-controlled trials. SEL interventions target key perceptual, cognitive-analytical and behavioral competencies related to social intelligence, such as recognizing and managing emotions in self and others, perspective taking, understanding social situations, and handling challenging interpersonal situations in a constructive manner (CASEL, 2017). Other kinds of interventions, such as mindfulness interventions (Metz et al., 2013) and parent training interventions (Reid, Webster-Stratton, & Hammond, 2007) also can be effective at enhancing social-emotional competencies. Of course, in addition to identifying and refining evidence-based interventions that promote social intelligence, it will be necessary to implement policies at multiple levels—federal, state, local and school—to ensure adequate dissemination of the programs and access in those communities that can most benefit from the programs.

Acknowledgments

The research was supported by a grant from the National Institute of Mental Health of the National Institutes of Health (R01 MH081166–01). We thank David Sosnowski for his able assistance with data analysis.

Contributor Information

Stephen J. Lepore, Department of Social & Behavioral Sciences, Temple University

Wendy Kliewer, Department of Psychology, Virginia Commonwealth University

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