Effect of Participation in Student Success Skills on Prosocial and Bullying Behavior

Jun 26, 2015 | Article, Volume 5 - Issue 3

Melissa Mariani, Linda Webb, Elizabeth Villares, Greg Brigman

This study involved fifth-grade students (N = 336) from one Florida school district and examined prosocial behaviors, bullying behaviors, engagement in school success skills and perceptions of classroom climate between the treatment group who received the school counselor-led Student Success Skills classroom guidance program, and their peer counterparts (comparison group). Statistically significant differences were found (p values ranged from .000–.019), along with partial eta-squared effect sizes ranging from .01 (small) to .26 (quite large) between groups. Evidence supported the Student Success Skills classroom program as a positive intervention for affecting student engagement, perceptions and behavior. 

Keywords: bullying, prosocial behaviors, Student Success Skills, classroom climate, school counselor

While some forms of youth victimization have steadily declined over the years, bullying occurrences have remained relatively stable (DeVoe et al., 2004; Wang, Iannotti, & Nansel, 2009). Reports have indicated that 30–40% of students admit to regular involvement in bullying behaviors (Bradshaw, O’Brennan, & Sawyer, 2008; Nansel et al., 2001; Spriggs, Iannotti, Nansel, & Haynie, 2007). Additionally, statistics reveal that bullying is much more common among early adolescents than elementary age children (Bradshaw et al., 2008; Olweus, 1993; Ortega & Lera, 2000). In fact, notable increases in the rates of peer aggression occur during the transition years, in both grade 6 (beginning of middle school) and grade 9 (beginning of high school; Olweus, 1993; Ortega & Lera, 2000); therefore, targeting students prior to these peaks would be considered more proactive.

Recent approaches to combat the bullying problem have highlighted the importance of increasing students’ social competencies and coping and social interaction skills (Durlak, Weissberg, Dymnicki, Taylor, & Schellinger, 2011). Greenberg et al. (2003) offered that alternative approaches to managing problem behavior are most beneficial when they simultaneously foster students’ personal and social skills while improving the quality of the school environment. The philosophy behind incorporating these types of programs in schools suggests that in order for students to fully reach their potential, educators must address the whole child (Payton et al., 2008; Saleebey, 2008). Ultimately, building key skills in all children contributes to creating a positive, safe and caring learning environment, one that discourages aggression and violence.

The Consequences of Bullying Behaviors

Bullying can negatively impact victims and bullies, as well as bystanders. Emotionally, victims of bullying report higher levels of fear and anxiety (Gini & Pozzoli, 2009; Reijntjes, Kamphuis, Prinzie, & Telch, 2010), are more socially withdrawn (Roth, Coles, & Heimberg, 2002), and are more likely to experience depression (Ttofi, Farrington, Lösel, & Loeber, 2011) than their peers. In terms of social consequences, victims suffer from increased levels of peer rejection (Gini & Pozzoli, 2009; Reijntjes et al., 2010). Victimization also has been linked to academic consequences, including increased tardiness, absentee and dropout rates (Beale & Scott, 2001; Nansel et al., 2001); poorer grades; and more academic struggles than their peer counterparts (Boulton, Trueman, & Murray, 2008). Similarly, bullies and bystanders experience distinct consequences that contribute to the struggles they experience in school. For example, bullies also may earn poorer grades and have higher absentee and dropout rates than non-aggressive peers (Bernstein & Watson, 1997), and bystanders have reported increased levels of fear about school safety (Olweus, 1993).

The literature further indicates that the actions of those involved in bullying situations, including bystanders, can either enhance or damage a school’s climate (Catalano, Haggerty, Oesterle, Fleming, & Hawkins, 2004; Swearer, Espelage, Vaillancourt, & Hymel, 2010). Carney (2008) concluded that experiencing bullying firsthand, as well as witnessing bullying incidents, can be traumatic for students. It is evident that schools should be concerned about proactively addressing bullying behaviors. If not, significant consequences related to student behavior and academic achievement can abound.

Empirical Support for Student Success Skills

The Student Success Skills (SSS) classroom program (Brigman & Webb, 2010) is based on extensive research reviews (Daly, Duhon, & Witt, 2002; Greenberg et al., 2003; Hattie, Biggs, & Purdie, 1996; Masten & Coatsworth, 1998; Payton et al., 2008; Wang, Haertel, & Walberg, 1994; Zins, Weissberg, Wang, & Walberg, 2004) that identified three key categories of skills needed in order to grow, perform and achieve: (a) cognitive and meta-cognitive skills such as goal setting, progress monitoring and memory skills; (b) social skills such as interpersonal, social problem solving, listening and teamwork skills; and (c) self-management skills such as managing attention, motivation and anger. Recent evidence supporting the use of these skills, valuing the teaching of both academic and social skills in order to promote student growth and success, also can be found in the literature (Winne & Nesbit, 2010; Yeager &Walton, 2011).

SSS is a comprehensive, evidence-based, school counselor-led program that supports development of these key skills in students. This manualized intervention consists of five 45-minute classroom lessons spaced one week apart, beginning in the fall, usually in late August or early September. Three monthly booster sessions are then implemented beginning in January. A total of 20 strategies are introduced and reinforced using a highly engaging “tell-show-do” format known to increase levels of student engagement and motivation. Each SSS lesson follows a structured beginning, middle and end sequence clearly detailed in the SSS manual. (Due to space limitations, readers are encouraged to review the Webb and Brigman [2006] descriptive article on the SSS classroom program).

Five outcome studies testing the effectiveness of SSS classroom and small group programs have resulted in positive effects on both student achievement and behavior, as well as perceived improvement in classroom behaviors (Brigman & Campbell, 2003; Brigman, Webb, & Campbell, 2007; Campbell & Brigman, 2005; León, Villares, Brigman, Webb, & Peluso, 2011; Webb, Brigman, & Campbell, 2005). A recent meta-analysis of these five SSS studies revealed an overall effect size of .29 (large), a medium effect size of .17 (equivalent to an additional half of a year of learning in reading) and a large effect size of .41 (equivalent to an additional full year of learning in math; Villares, Frain, Brigman, Webb, & Peluso, 2012).

While the SSS program has been shown to positively affect student achievement and behavior in general, comparison studies have not examined the impact of SSS on reducing bullying behavior. Consequently, the current study sought to measure the effects of the SSS classroom program administered by school counselors (Brigman & Webb, 2010) on student prosocial behavior, bullying behavior, engagement in school success skills and perceptions of classroom climate. The SSS intervention was selected because the cognitive, social and self-management skills taught in the program are associated with promoting academic and prosocial behaviors in youth, behaviors that enhance a positive school climate and discourage negative behaviors like bullying.

Purpose of the Study

The purpose of this study was to determine the effectiveness of the SSS classroom program (Brigman & Webb, 2010) on fifth-grade students’ prosocial behavior, bullying behavior, engagement in school success skills and perceptions of classroom climate. The problem addressed is significant for two reasons. First, a wide range of negative consequences can result from ineffectively dealing with bullying (Bernstein & Watson, 1997; Carney, 2008; Catalano et al., 2004; Deluty, 1985; Gini & Pozzoli, 2009; Olweus, 1993; Reijntjes et al., 2010; Swearer et al., 2010). Second, further research is needed to demonstrate the positive impact that school counselors have in schools. It has been stated that the school counselor’s role in addressing bullying in schools is crucial (Crothers & Levinson, 2004; Hanish & Guerra, 2000; Hazler & Carney, 2000; Hermann & Finn, 2002).

Research Questions

The following research questions were addressed: (a) Is there an increase in the prosocial behaviors of fifth-grade students after participating in the SSS classroom program? (b) Is there a decrease in the bullying behaviors of fifth-grade students after participating in the SSS classroom program? (c) Is there an increase in levels of engagement in student success skills (cognitive and learning, social, and self-management) of fifth-grade students after participating in the SSS classroom program? (d) Is there an improvement in classroom climate after fifth-grade students participate in the SSS classroom program?

Method

Participants and Sampling Procedures

Fifth-grade students (N = 336, 181 females and 155 males) from five public elementary schools in central Florida volunteered to participate in this study. The eligibility criteria included the following: (a) participating schools had to employ a certified school counselor, (b) school counselors had to agree to implement the manualized SSS classroom program (Brigman & Webb, 2010), and (c) in an attempt to create a whole-school culture, the school had to have more than one fifth-grade classroom participating. On average, each school contained 4–6 general education fifth-grade classrooms; 21 of these 22 classrooms in the five participating elementary schools were included in the study. All students in general education fifth-grade classrooms were invited to participate. Blended classrooms (e.g., multiple grade levels in one classroom) were not included so that generalizations among age levels could be made between schools. The volunteer sample (N = 336) mean age was 10 years old. Racial identifications included 7 (2%) Asian, 52 (15%) African American, 221 (66%) Caucasian, 43 (13%) Latino/a, 12 (3.6%) Multiracial and 1 (.4%) American Indian. Thirty-one percent of the sample (n = 104) received free lunch and 7.1% (n = 24) were on reduced-lunch status.

The study followed a pre-post quasi-experimental cohort group design (Cook & Campbell, 1979). Random assignment of individual students was not conducive to preserving the nature of a whole-school culture, so schools were assigned to either the treatment or comparison group based on the order in which they volunteered to participate. The first three schools to volunteer were assigned to the treatment group (schools A, B and C) while the last two schools (schools D and E) were assigned to the comparison group.

Procedures

Following approval from the university’s Institutional Review Board, consent for research was obtained from the participating school district, school administrators, parents, teachers and students. In September, five certified school counselors from the participating schools received a 1-day training in the manualized use of the SSS classroom guidance program as well as other study-related procedures including instrument administration and electronic summary report instructions. The SSS program, consisting of five consecutive 45-minute lessons spaced a week apart, was then implemented in all fifth-grade classrooms in the treatment schools beginning in October. Monthly booster lessons followed beginning in January. Only students with parent permission completed the required instruments: the Peer Relations Questionnaire (PRQ), the Student Engagement in School Success Skills (SESSS) survey and the My Class Inventory-Short Form Revised (MCI-SFR). Students were ensured of the anonymity of their reporting by using generic school, classroom and student numbers. For a classroom to remain eligible to participate, a minimum of 80% of the students in the classroom had to return a signed parent consent form.

     Treatment group. Schools A, B and C served as the treatment group (n = 209) and participating fifth-grade students in this group received the SSS classroom intervention. These students completed the following pretests in September 2010: the PRQ, MCI-SFR and SESSS. Implementation of the SSS classroom program began in October. Following the completion of the first five SSS lessons, treatment students completed the SESSS instrument (posttest). Booster lessons were delivered in January, February and March, and treatment students were then asked to complete the PRQ, MCI-SFR and SESSS following the final booster lesson (post-posttest).

     Comparison group. Schools D and E served as the comparison group (n = 127) and did not receive the SSS intervention during the study. Students in these schools experienced business as usual, including any regularly scheduled school counseling programming. Comparison schools were eligible to receive the SSS curriculum after the study was completed. Participating students in the comparison schools completed the three instruments at the same time intervals (pretest, posttest and post-posttest) as students in the treatment group.

Instruments

     Peer Relations Questionnaire – For Children – Short Form. The PRQ (Rigby & Slee, 1993a) was designed to reveal student experiences with bullying at school. The questionnaire takes approximately 5–7 minutes to complete and is comprised of 20 items in which students are asked to circle how often the statements are true for them. The answers range on a 4-point scale from never = 1, once in a while = 2, pretty often = 3, to very often = 4. The PRQ consists of three scales and several filler items: a Bully Scale, a Victim Scale and a Prosocial Scale; students in the present study took all three scales. Scoring is determined by the items contained in each of the scales, with higher scores corresponding to a propensity for bully, victim and/or prosocial behaviors (Rigby & Slee, 1993b). Rigby and Slee (1993b) reported the reliability of the PRQ using the following alpha coefficients: bully scale (.75–.78), victim scale (.78–.86) and prosocial scale (.71–.74), indicating more than adequate internal consistency. Recent evaluation of the PRQ’s psychometric properties by Tabaeian, Amiri, and Molavi (2012) supported it as a highly reliable and valid instrument that should continue to be used in research.

     Student Engagement in School Success Skills Survey. The SESSS is a 33-item student self-report of cognitive engagement in SSS program skills and strategies, using language specific to the SSS curriculum, and takes approximately 15 minutes to complete (Carey, Brigman, Webb, Villares, & Harrington, 2013). Students are asked to circle how often they have engaged in a list of behaviors within the last 2 weeks (e.g., “I tried to encourage a classmate who was having a hard time doing something,” “I noticed when another student was having a bad day,” “I listened to music so that I would feel less stressed”). Possible responses include I didn’t do this at all, I did this once, I did this two times or I did this three or more times. The SESSS is intended for use with students in grades 3–12. Though a four-factor model was first revealed in an exploratory factor analysis conducted by Carey et al. (2013), a subsequent confirmatory factor analysis revealed the following three factors: self-direction of learning (which represents the combination of two original factors—management of learning and application of learning strategies), support of classmates’ learning and self-regulation of arousal, which correspond to the three subscales of the SESSS (Brigman et al., 2014). Coefficient alphas for the three SESSS subscales were as follows: self-direction of learning: 0.89, support of classmates’ learning: 0.79 self-regulation of arousal: 0.68, and 0.90 for the SESSS as a whole (Villares et al., 2014), indicating good internal consistency.

     My Class Inventory-Short Form-Revised. The MCI-SFR is a 20-item instrument that intends to measure the perceptions of students in grades 4–6 of four areas related to classroom climate (satisfaction, friction, competitiveness and cohesiveness). The instrument takes approximately 10–15 minutes to complete and respondents are asked to select either “yes” (3 points) or “no” (1 point). Omitted or invalidly scored items receive two points. Reports on the psychometric properties for both the MCI-SF and MCI-SFR have indicated strong concurrent validity when comparing long and short versions across each of the scales (.91–.97). Additionally, some degree of internal consistency (largely adequate coefficient alphas) has been reported for class means with Australian children (.58–.81). The MCI-SF yielded more acceptable alpha coefficients for each of the scales (.84–.93) than did the long version, the MCI. Modifications to the revised MCI-SFR produced a better overall instrument, improving factor interpretability and reliability (Fraser, 1982; Sink & Spencer, 2005). Sink and Spencer (2005) reported that interpreting students’ responses from pretest to posttest on the MCI-SFR should be straightforward, with higher scores on the satisfaction and cohesion scales providing positive indicators of a healthy classroom environment, and higher scores on the competitiveness and friction scales suggesting needed improvement in this area.

Data Analysis

Individual students were the units of analysis in the study. An alpha level of .05 and one-way analysis of variance (ANOVA) tests were used to analyze differences in prosocial behaviors, bullying behaviors, school engagement skills and perceptions of classroom climate between students who participated in the SSS program (treatment group) and students who did not (comparison group). A post hoc Bonferroni correction was used to lessen the chance of a Type I error. Prior to the analyses, all the variables of interest were examined for accuracy of data entry, missing values, outliers and the normality of distributions. In addition, effect sizes (ES) were calculated to determine the practical significance of the SSS classroom program for the various student outcomes.

In this study, a partial eta-squared (ES; hp²) calculation was computed by SPSS (Field, 2009; Howell, 2008; Sink & Mvududu, 2010). The ES addresses the magnitude of the difference between groups or relationships between variables. The following benchmarks were used to determine small, medium, and large or strong ES strengths regarding hp² calculations: (a) .01 small, (b) .06 medium, and (c) .14 large or strong (Green & Salkind, 2008; Sink & Mvududu, 2010).

Results

Preliminary ANOVAs were conducted on the students’ PRQ, SESSS and MCI-SFR pretest scores to determine whether statistically significant differences existed among the treatment and comparison groups prior to the implementation of the SSS intervention. No statistically significant differences were found on pretest scores; therefore, no covariates were used in subsequent analyses of students’ PRQ, SESSS and MCI-SFR posttest scores. Table 1 provides a summary of the study’s main findings.

Prosocial Behaviors

Research question 1 examined whether fifth-grade students who participated in the SSS classroom program would experience an increase in prosocial behaviors as compared to their peer counterparts who did not receive the intervention. Prosocial behaviors were assessed using the prosocial scale of the PRQ. A total of 188 students from the treatment group (schools A, B and C) and 123 students from the comparison group (schools D and E) were included in this analysis (n = 311). Findings from an ANOVA showed a statistically significant difference between groups, F(1, 308) = 18.708, p = .000 and h_p²  = .06, a medium effect size. Participants in the treatment group (n = 188, M = 12.61, SD = 2.47) reported higher scores for prosocial behaviors at posttest as opposed to participants in the comparison group (n = 123, M = 11.27, SD = 2.81). Results indicated that students in the treatment schools reported engaging in prosocial behaviors more often at posttest than students in the comparison schools, highlighting the practical significance of using this intervention to positively influence student behavior.

Table 1

Summary Table of P Values, Effect Size Estimates, and Confidence Intervals for All Measures

Note. PRQ = Peer Relations Questionnaire; SESSS = Student Engagement in School Success Skills;
MCI-SFR = My Class Inventory-Short Form-Revised; p = significance at posttest; hp² = partial eta-squared
effect size; CI = confidence interval;

* p < .05.

Bullying Behaviors

The second research question asked whether fifth-grade students who received SSS would experience a decrease in bullying behaviors, assessed by the bully scale of the PRQ, compared to their peers in the comparison group. Results from a one-way ANOVA showed a statistically significant difference between the participants’ (n = 311) posttest scores, F(1, 308) = 5.708, p = .017 and a small effect size, h_p² = .02. These findings confirmed that students in the treatment group evidenced a decrease in mean change scores on the PRQ bully scale after SSS implementation, whereas students in the comparison schools reported an increase. Thus, students in the treatment group who received the SSS classroom intervention reported less bullying behavior at posttest than students in the comparison group.

Engagement in School Success Skills

Research question 3 investigated whether participating fifth-grade students who received the SSS classroom program would experience an increase in levels of engagement in student success skills (cognitive and learning, social, self-management) as compared to their peer counterparts. Results from the SESSS instrument were used in this analysis. A total of 115 students in the treatment group (schools A, B and C) and 85 students in the comparison group (schools D and E) were included in the SESSS analysis (n = 200). Table 2 displays the treatment and comparison group means, standard deviations, and change scores for the SESSS by school at the following three data collection periods: pretest (prior to SSS implementation), posttest (immediately following implementation of the five weekly SSS lessons) and post-posttest (at the end of the study).

Table 2

Treatment and Comparison Group Means, Standard Deviations and Change Scores for the SESSS by School

Note. SESSS = Student Engagement in School Success Skills; n = number; M = mean; SD = standard deviation;

T = treatment group; C = comparison group; * = treatment school; +/- = mean change score.

   SESSS posttest score analysis. Findings from an ANOVA on the posttest scores on the SESSS (from the pretest in October to the posttest in December) showed a statistically significant difference between schools, F(1, 197) = 69.295, p = .000 and h_p² = .26, a large effect size. Students in the treatment group (n = 115, M = 2.50, SD = .642) evidenced higher levels of engagement in school success skills from pretest to posttest than their counterparts in the comparison group (n = 85, M = 1.73, SD = .617).

SESSS post-posttest score analysis. A second one-way ANOVA showed no statistically significant differences between the treatment and comparison groups scores from pretest (October) to post-posttest (March), F(1, 197) = .820, p = .366 and h_p² = .004, a small effect size.

Perceptions of Classroom Climate

Finally, research question 4 investigated whether fifth-grade treatment group students would perceive an improvement in classroom climate as compared to students in the comparison group. Due to attrition, 308 fifth-grade students completed the four scales (satisfaction, cohesion, competitiveness and friction) of the MCI-SFR. Findings from an ANOVA using the MCI-SFR satisfaction scale posttest scores revealed a statistically significant difference between the treatment and comparison groups, F(1, 305) = 5.523, p = .019 and h_p² = .02, a small effect size. In particular, students in the treatment group (n = 187, M = 10.96, SD = 2.86) reported higher scores on the satisfaction scale at posttest than did students in the comparison group (n = 121, M = 10.39, SD = 2.74). The ANOVA tests on the other three scales of the MCI-SFR did not result in statistically significant differences between the treatment and comparison groups.

Discussion

The findings of this study reflect the connection between prosocial skills and reduced aggression, a finding which has been well documented in previous literature (Endresen & Olweus, 2001; Feshbach, 1997; McMahon & Washburn, 2003). School counselor interventions that focus on teaching prosocial behaviors have been successful in reducing aggressive behaviors such as bullying (Frey, Hirschstein, & Guzzo, 2000); these types of interventions also have been tied to improved academic achievement (Wentzel, 2003; Wentzel & Caldwell, 1997). The American School Counselor Association (ASCA; 2012) recommends that counselors cover academic, personal and social, and career domains as part of a comprehensive school counseling program. Results of this study support the delivery of interventions that incorporate the teaching of cognitive, social and self-management skills as a means to increase prosocial skills, reduce bullying behavior and promote a positive classroom climate. The design of the current study attempted to create a whole-school approach by implementing the SSS classroom program across an entire grade level (grade 5) in the treatment schools. Given that bullying peaks in the transition years, addressing the fifth-grade population was viewed as a proactive approach. SSS implementation resulted in some positive outcomes for those students, indicating that even a modified whole-school approach can be beneficial.

Previous SSS studies have documented the intervention’s positive impact on student academic performance as measured by standardized test scores in math and reading (Villares et al., 2012). Professionals in the field of counseling have identified a need to evaluate the link between the SSS program and intermediate variables related to student learning such as engagement in school success skills, prosocial behavior and perceptions of classroom climate (Carey, Dimmitt, Hatch, Lapan, & Whiston, 2008). Findings from the current study indicate that students who received the SSS intervention engaged significantly more in behaviors indicative of school success at posttest. These results are encouraging, since a body of research cites the negative impact that bullying can have on student academic achievement (Beale & Scott, 2001; Boulton et al., 2008; Nansel et al., 2001; Olweus, 1993).

The quality of a classroom climate also can impact students’ success. Although improved perceptions of classroom climate were predicted across all areas in the current study, statistically significant differences were only noted on perceptions related to satisfaction. The researchers postulate that treatment students were more likely to tune into questions pertaining to satisfaction, as this is a focus of the SSS program (noticing small improvements, focusing on the positives, and creating a safe, caring, supportive, encouraging classroom). The maintenance of a positive school and classroom climate directly affects whether or not students feel accepted and happy among their peers (Greenberg et al., 2003; Millings, Buck, Montgomery, Spears, & Stallard, 2012; Shochet, Dadds, Ham, & Montague, 2006). The literature indicates that the effectiveness of school counseling interventions can be greatly impacted by the school’s climate (Greenberg et al., 2003). Specifically, factors such as teacher adherence to the curriculum and staff buy-in can affect a program’s success (Biggs, Vernberg, Twemlow, Fonagy, & Dill, 2008; Yoon, 2004). Teachers should be involved in program implementation so that they become invested in its success. The current study addressed this area in that the classroom teachers were collaborators in SSS implementation. The program asks that classroom teachers be present during the counselor-led sessions so that they can cue students to use the skills taught throughout the regular school day. Thus, evidence-based interventions like the SSS program that emphasize school connectedness can be of benefit to students (Millings et al., 2012).

Implications for Practice and Future Research

The findings of this study support the use of the school counselor-led SSS classroom program as a practical means of impacting students’ prosocial skills, bullying behavior, engagement in school success skills and some perceptions of classroom climate, as indicated by various student self-report measures. Since the bullying literature calls for the use of multiple measures when attempting to link interventions to improvements, we recommend that additional studies track attendance rates, disciplinary referrals, bullying incident reports, and peer and teacher nominations, in addition to student instruments. Future researchers in this area also should gather data from teacher participants and vary the type of measurements specifically tied to prosocial and bullying behaviors (Pellegrini & Bartini, 2000; Van Schoiack-Edstrom, Frey, & Beland, 2002), as well as academic outcomes (Carey et al., 2008; Hall, 2006). This study sought to create a whole-school culture by incorporating the intervention across an entire grade level at each school. Future researchers might consider implementing SSS across several grade levels or throughout the entire school, as students across various grades often come in contact with one another throughout the school day.

Limitations

The participants were derived from one suburban school district and randomization procedures were not possible, thereby limiting the sample size and generalizability of the results. Likewise, due to one school dropping out of the study at the onset, the numbers between the treatment and comparison groups were not equivalent. The high level of attrition also was a limitation, specifically regarding the SESSS instrument. Though 336 students were in the original sample, only 200 of these were included in the analysis on the SESSS due to dropping out or not adequately completing the instrument in its totality at all three intervals.

The self-report nature of all three of the instruments was an added limitation, particularly with the problem of bullying. Students involved in bullying incidents, whether they were bullies, victims or bystanders, might be hesitant to report or indicate negative behaviors. This reluctance could have resulted in respondent bias and decreased reliability in the results.

Finally, the current study used only one component of the SSS curriculum (classroom program). Future studies might involve additional modalities, including individual and small group counseling as well as parent involvement. This study did not examine the impact of the SSS program over time. Follow-up studies are needed to support the long-term effectiveness of school counselor-led interventions that increase prosocial behaviors, reduce bullying behaviors and promote a positive school climate.

Conclusion

Results of the study provide support that students who receive the SSS classroom intervention led by school counselors (Brigman & Webb, 2010) evidence statistically significant differences in prosocial behaviors, bullying behaviors, engagement in school success skills and perceptions related to satisfaction with their classroom climate, as compared to students who do not receive the program. The findings provide empirical support for the notion that when students are taught skills in key areas (personal and social, self-management, and cognitive and academic) they benefit across social, emotional and behavioral outcomes. The study also suggests that aggressive behaviors such as bullying can be influenced by programs that do not specifically target these behaviors. Finally, this research points to the positive impact school counselors can have on student success, particularly when they deliver interventions that promote social competence among students. Providing school counselors with an evidence-based program that impacts students across several domains is of great value for school counseling practice.

Conflict of Interest and Funding Disclosure

The authors reported no conflict of interest

or funding contributions for the development

of this manuscript.

References

American School Counselor Association. (2012). The ASCA national model: A framework for school counseling programs (3rd ed.). Alexandria, VA: Author.

Beale, A. V., & Scott, P. C. (2001). “Bullybusters”: Using drama to empower students to take a stand against bullying behavior. Professional School Counseling, 4, 300–305.

Bernstein, J. Y., & Watson, M. W. (1997). Children who are targets of bullying: A victim pattern. Journal of Interpersonal Violence, 12, 483–498. doi:10.1177/088626097012004001

Biggs, B. K., Vernberg, E. M., Twemlow, S. W., Fonagy, P., & Dill, E. J. (2008). Teacher adherence and its relation to teacher attitudes and student outcomes in an elementary school-based violence prevention program. School Psychology Review, 37, 533–549.

Boulton, M. J., Trueman, M., & Murray, L. (2008). Associations between peer victimization, fear of future victimization and disrupted concentration on class work among junior school pupils. British Journal of Educational Psychology, 78, 473–489. doi:10.1348/000709908X320471

Bradshaw, C. P., O’Brennan, L. M., & Sawyer, A. L. (2008). Examining variation in attitudes toward aggressive retaliation and perceptions of safety among bullies, victims, and bully/victims. Professional School Counseling, 12, 10–21. doi:10.5330/PSC.n.2010-12.10

Brigman, G., & Campbell, C. (2003). Helping students improve academic achievement and school success behavior. Professional School Counseling, 7, 91–98.

Brigman, G., & Webb, L. (2010). Student success skills: Classroom manual (3rd ed.). Boca Raton, FL: Atlantic Education Consultants.

Brigman, G. A., Webb, L. D., & Campbell, C. (2007). Building skills for school success: Improving the academic and social competence of students. Professional School Counseling, 10, 279–288.

Brigman, G., Wells, C., Webb, L., Villares, E., Carey, J. C., & Harrington, K. (2014). Psychometric properties and confirmatory factor analysis of the student engagement in school success skills survey. Measurement and Evaluation in Counseling and Development. doi:10.1177/0748175614544545

Campbell, C. A., & Brigman, G. (2005). Closing the achievement gap: A structured approach to group counseling. Journal for Specialists in Group Work, 30, 67–82. doi:10.1080/01933920590908705

Carey, J., Brigman, G., Webb, L., Villares, E., & Harrington, K. (2013). Development of an instrument to measure student use of academic success skills: An exploratory factor analysis. Measurement and Evaluation in Counseling and Development, 47, 171–180. doi:10.1177/0748175613505622

Carey, J. C., Dimmitt, C., Hatch, T. A., Lapan, R. T., & Whiston, S. C. (2008). Report of the national panel for evidence-based school counseling: Outcome research coding protocol and evaluation of student success skills and second step. Professional School Counseling, 11, 197–206.

Carney, J. V. (2008). Perceptions of bullying and associated trauma during adolescence. Professional School Counseling, 11, 179–188.

Catalano, R. F., Haggerty, K. P., Oesterle, S., Fleming, C. B., & Hawkins, J. D. (2004). The importance of bonding to school for healthy development: Findings from the social development research group. Journal of School Health, 74, 252–261. doi:10.1111/j.1746-1561.2004.tb08281.x

Cook, T. D., & Campbell, D. T. (1979). Quasi-Experimentation: Design and analysis issues for field settings. Boston, MA: Houghton Mifflin.

Crothers, L. M., & Levinson, E. M. (2004). Assessment of bullying: A review of methods and instruments. Journal of Counseling & Development, 82, 496–503. doi:10.1002/j.1556-6678.2004.tb00338.x

Daly, E. J., III, Duhon, G. J., & Witt, J. C. (2002). Proactive approaches for identifying and treating children at risk for academic failure. In K. L. Lane, F. M. Gresham, & T. E. O’Shaughnessy (Eds.), Interventions for children with or at risk for emotional and behavioral disorders (pp. 18–32). Boston, MA: Allyn & Bacon.

Deluty, R. H. (1985). Cognitive mediation of aggressive, assertive, and submissive behavior in children. International Journal of Behavioral Development, 8, 355–369. doi:10.1177/016502548500800309

DeVoe, J. F., Peter, K., Kaufman, P., Miller, A., Noonan, M., Snyder, T. D., & Baum, K. (2004). Indicators of school crime and safety: 2004. Retrieved from http://nces.ed.gov/pubs2005/2005002.pdf

Durlak, J. A., Weissberg, R. P., Dymnicki, A. B., Taylor, R. D., & Schellinger, K. B. (2011). The impact of enhancing students’ social and emotional learning: A meta-analysis of school-based universal interventions. Child Development, 82, 405–32. doi:10.1111/j.1467-8624.2010.01564.x

Endresen, I. M., & Olweus, D. (2001). Self-reported empathy in Norwegian adolescents: Sex differences, age trends, and relationship to bullying. In A. C. Bohart & D. J. Stipek (Eds.), Constructive & destructive behavior: Implications for family, school, and society (pp.147–165). Washington, DC: American Psychological Association.

Feshbach, N. D. (1997). Empathy: The formative years—implications for clinical practice. In A. C. Bohart & L. S. Greenberg (Eds.), Empathy reconsidered: New directions in psychotherapy (pp. 33–59). Washington, D.C.: American Psychological Association.

Field, A. (2009). Discovering statistics using SPSS (3rd ed.). Thousand Oaks, CA: Sage.

Fraser, B. J. (1982). Development of short forms of several classroom environment scales. Journal of Educational Measurement, 19, 221–227.

Frey, K. S., Hirschstein, M. K., & Guzzo, B. A. (2000). Second step: Preventing aggression by promoting social competence. Journal of Emotional and Behavioral Disorders, 8, 102–113. doi:10.1177/106342660000800206

Gini, G., & Pozzoli, T. (2009). Association between bullying and psychosomatic problems: A meta-analysis. Pediatrics, 123, 1059–1065. doi:10.1542/peds.2008-1215

Green, S. B., & Salkind, S. J. (2008). Using SPSS for Windows and Macintosh: Analyzing and understanding data (5th ed.). Upper Saddle River, NJ: Prentice-Hall.

Greenberg, M. T., Weissberg, R. P., O’Brien, M. U., Zins, J. E., Fredericks, L., Resnik, H., & Elias, M. J. (2003). Enhancing school-based prevention and youth development through coordinated social, emotional, and academic learning. American Psychologist, 58, 466–474. doi:10.1037/0003-066X.58.6-7.466

Hall, K. R. (2006). Using problem-based learning with victims of bullying behavior. Professional School Counseling, 9, 231–237.

Hanish, L. D., & Guerra, N. G. (2000). Children who get victimized at school: What is known? What can be done? Professional School Counseling, 4, 113–119.

Hattie, J., Biggs, J., & Purdie, N. (1996). Effects of learning skills interventions on student learning: A meta-analysis. Review of Educational Research, 66, 99–136. doi:10.3102/00346543066002099

Hazler, R. J., & Carney, J. V. (2000). When victims turn aggressors: Factors in the development of deadly school violence. Professional School Counseling, 4, 105–112.

Hermann, M. A., & Finn, A. (2002). An ethical and legal perspective on the role of school counselors in preventing violence in schools. Professional School Counseling, 6, 46–54.

Howell, D. (2008). Best practices in the analysis of variance. In J. Osborne (Ed.), Best practices in quantitative methods (pp. 341–357). Thousand Oaks, CA: Sage.

León, A., Villares, E., Brigman, G., Webb, L., & Peluso, P. (2011). Closing the achievement gap of Latina/Latino students: A school counseling response. Counseling Outcome Research and Evaluation, 2, 73–86. doi:10.1177/2150137811400731

Masten, A. S., & Coatsworth, J. D. (1998). The development of competence in favorable and unfavorable environments: Lessons from research on successful children. American Psychologist, 53, 205–220.

McMahon, S. D., & Washburn, J. J. (2003). Violence prevention: An evaluation of program effects with urban African American students. The Journal of Primary Prevention, 24, 43–62.

Millings, A., Buck, R., Montgomery, A., Spears, M., & Stallard, P. (2012). School connectedness, peer attachment, and self-esteem as predictors of adolescent depression. Journal of Adolescence, 35, 1061–1067. doi:10.1016/j.adolescence.2012.02.015

Nansel, T. R., Overpeck, M., Pilla, R. S., Ruan, W. J., Simons-Morton, B., & Scheidt, P. (2001). Bullying behaviors among US youth: Prevalence and association with psychosocial adjustment. Journal of the American Medical Association, 285, 2094–2100. doi:10.1001/jama.285.16.2094

Olweus, D. (1993). Bullying at school. Malden, MA: Blackwell.

Ortega, R., & Lera, M.-J. (2000). The Seville anti-bullying in school project. Aggressive Behavior, 26, 113–123. doi:10.1002/(SICI)1098-2337(2000)26:1<113::AID-AB9>3.0.CO;2-E

Payton, J., Weissberg, R. P., Durlak, J. A., Dymnicki, A. B., Taylor, R. D., Schellinger, K. B., & Pachan, M. (2008). The positive impact of social and emotional learning for kindergarten to eighth-grade students: Findings from three scientific reviews—Executive summary. Retrieved from http://www.lpfch.org/sel/PackardES-REV.pdf

Pellegrini, A. D., & Bartini, M. (2000). An empirical comparison of methods of sampling aggression and victimization in school settings. Journal of Educational Psychology, 92, 360–366. doi:10.1037/0022-0663.92.2.360

Reijntjes, A., Kamphuis, J. H., Prinzie, P., & Telch, M. J. (2010). Peer victimization and internalizing problems in children: A meta-analysis of longitudinal studies. Child Abuse & Neglect, 34, 244–252. doi:10.1016/j.chiabu.2009.07.009

Rigby, K., & Slee, P. T. (1993a). Dimensions of interpersonal relation among Australian children and implications for psychological well-being. The Journal of Social Psychology, 133, 33–42. doi:10.1080/00224545.1993.9712116

Rigby, K., & Slee, P. T. (1993b). The Peer Relations Questionnaire (PRQ) [Measurement instrument]. Adelaide, Australia: University of South Australia.

Roth, D. A., Coles, M. E., & Heimberg, R. G. (2002). The relationship between memories for childhood teasing and anxiety and depression in adulthood. Journal of Anxiety Disorders, 16, 149–164. doi: 10.1016/S0887-6185(01)00096-2

Saleebey, D. (2008). Commentary on the strengths perspective and potential applications in school counseling. Professional School Counseling, 12, 68–75.

Shochet, I. M., Dadds, M. R., Ham, D., & Montague, R. (2006). School connectedness is an underemphasized parameter in adolescent mental health: Results of a community prediction study. Journal of Clinical Child and Adolescent Psychology, 35, 170–179. doi:10.1207/s15374424jccp3502_1

Sink, C. A., & Mvududu, N. H. (2010). Statistical power, sampling, and effect sizes: Three keys to research relevancy. Counseling Outcome Research and Evaluation, 1, 1–18. doi:10.1177/2150137810373613

Sink, C. A., & Spencer, L. R. (2005). My Class Inventory–Short Form as an accountability tool for elementary school counselors to measure classroom climate. Professional School Counseling, 9, 37–48.

Spriggs, A. L., Iannotti, R. J., Nansel, T. R., & Haynie, D. L. (2007). Adolescent bullying involvement and perceived family, peer, and school relations: Commonalities and differences across race/ethnicity. Journal of Adolescent Health, 41, 283–293. doi:10.1016/j.jadohealth.2007.04.009

Swearer, S. M., Espelage, D. L., Vaillancourt, T., & Hymel, S. (2010). What can be done about school bullying? Linking research to educational practice. Educational Researcher, 39, 38–47.

Tabaeian, S. R., Amiri, S., & Molavi, H. (2012). Factor analysis, reliability, convergent and discriminate [sic] validity of “The Peer Relationships Questionnaire” (PRQ). Studies in Learning & Instruction (Journal of Social Sciences and Humanities of Shiraz University), 3(2), 61–62.

Ttofi, M. M., Farrington, D. P., Lösel, F., & Loeber, R. (2011). Do the victims of school bullies tend to become depressed later in life? A systematic review and meta-analysis of longitudinal studies. Journal of Aggression, Conflict and Peace Research, 3, 63–73. doi:10.1108/17596591111132873

Van Schoiack-Edstrom, L., Frey, K. S., & Beland, K. (2002). Changing adolescents’ attitudes about relational and physical aggression: An early evaluation of a school-based intervention. School Psychology Review, 31, 201–216.

Villares, E., Colvin, K., Carey, J., Webb, L., Brigman, G., & Harrington, K. (2014). Convergent and divergent validity of the student engagement in school success skills survey. The Professional Counselor, 4, 541–552. doi:10.15241/ev.4.5.541

Villares, E., Frain, M., Brigman, G., Webb, L., & Peluso, P. (2012). The impact of student success skills on standardized test scores: A meta-analysis. Counseling Outcome Research and Evaluation, 3, 3–16. doi:10.1177/2150137811434041

Wang, J., Iannotti, R. J., & Nansel, T. R. (2009). School bullying among adolescents in the United States: Physical, verbal, relational, and cyber. Journal of Adolescent Health, 45, 368–375. doi:10.1016/j.jadohealth.2009.03.021

Wang, M. C., Haertel, G. D., & Walberg, H. J. (1994). What helps students learn? Educational Leadership, 51(4), 74–79.

Webb, L. D., & Brigman, G. A. (2006). Student success skills: Tools and strategies for improved academic and social outcomes. Professional School Counseling, 10, 112–120.

Webb, L. D., Brigman, G. A., & Campbell, C. (2005). Linking school counselors and student success: A replication of the student success skills approach targeting the academic and social competence of students. Professional School Counseling, 8, 407–413.

Wentzel, K. R. (2003). Sociometric status and adjustment in middle school: A longitudinal study. Journal of Early Adolescence, 23, 5–28. doi:10.1177/0272431602239128

Wentzel, K. R., & Caldwell, K. (1997). Friendships, peer acceptance, and group membership: Relations to academic achievement in middle school. Child Development, 68, 1198–1209. doi:10.2307/1132301

Winne, P. H., & Nesbit, J. C. (2010). The psychology of academic achievement. Annual Review of Psychology, 61, 653–678.

Yeager, D. S., & Walton, G. M. (2011). Social-psychological interventions in education: They’re not magic. Review of Educational Research, 81, 267–301. doi:10.3102/0034654311405999

Yoon, J. S. (2004). Predicting teacher interventions in bullying situations. Education and Treatment of Children, 27, 37–45.

Zins, J. E., Weissberg, R. P., Wang, M. C., & Walberg, H. J. (Eds.). (2004). Building academic success on social and emotional learning: What does the research say? New York, NY: Teachers College Press.

Melissa Mariani is an Assistant Professor at Florida Atlantic University. Linda Webb is Research Faculty III at Florida State University. Elizabeth Villares is an Associate Professor at Florida Atlantic University. Greg Brigman, NCC, is a Professor at Florida Atlantic University. Correspondence may be addressed to Melissa Mariani, 777 Glades Road, COE 47, 274, Boca Raton, FL 33431, mmarian5@fau.edu.