Abstract
This study examined school staff reported behavioral responses to bullying, general likelihood of intervening and perceived self-efficacy for intervening with student bullying. We explored if the existence of school bullying-related policies and/or policy trainings was associated with the ways in which school staff responded to bullying. Data came from 8,668 school staff from 156 elementary, middle and high schools in the U.S. Results suggested that while the existence of anti-bullying policies was an important contributor to increased staff self-efficacy for intervening with bullying, it was not associated with self-reports of increased responses to bullying. However, being trained on their schools’ anti-bullying policy was associated with higher odds of intervening with the involved students, discussing the incident with other school staff (e.g., administrators, counselors), and referring the students involved to the school counselor/psychologist. Moreover, there were clear role and grade level differences in staff responses, such as being less likely to respond to bullying in high school, as compared to middle and elementary school. The results suggested that the existence of a school policy is not likely sufficient to shift behavior. Additional training and professional development are necessary across all school staff, especially in upper grades.
Keywords: School staff, bullying, responses, intervention, policies and training
All states in the U.S. have required that school districts create anti-bullying policies. A large-scale study suggested a positive impact of anti-bullying policies (Hatzenbuehler et al., 2015), with other studies finding little support for the link between anti-bullying policies and school safety outcomes (Sabia & Bass, 2017). It is clear that additional studies are necessary that specifically examine the impact of policies on school staff interventions because when school staff fail to intervene, bullying levels tend to increase, as does student distrust in school staff (Campaert et al., 2017). This distrust hinders the development of positive, nurturing teacher-student relationships which have proven to be beneficial for both academic functioning and social and emotional behaviors (e.g., Ferráns & Selman, 2014).
There are several factors associated with how comfortable staff feel intervening with bullying including availability of bullying prevention resources, participation in trainings on the school’s bullying policy, involvement in bullying prevention efforts as well as one’s role in the school (Bradshaw et al., 2013; O’Brennan et al., 2014), staff connectedness and perceived self-efficacy (O’Brennan et al., 2014). Some studies have found that teachers with high self-efficacy intervene more often in bullying (e.g., Duong & Bradshaw, 2013; Yoon & Bauman, 2014), whereas others have found that teachers’ self-efficacy was not associated with more effective handling of bullying (e.g., Dedousis-Wallace et al., 2014). Taken together, these findings highlight the importance of understanding what individual strategies school staff use when they witness bullying and the relation with self-efficacy which can help in identifying targets for training and support.
Current Study
While many agencies and researchers contend that anti-bullying policies are a critical element of an effective bullying prevention strategy (e.g., National Academies of Science, 2014), the empirical findings have been mixed regarding the extent to which these policies actually impact staff responses to bullying. We aimed to address gaps in the anti-bullying policy literature by better understanding how those policies relate to staff responses to bullying, with particular interest in developmental and contextual differences, including the role various staff play in the school. Specifically, we examined differences in staff responses to bullying based on grade level (elementary, middle and high school) and role (e.g., general education, special education, administrator). We also explored whether staff members’ responses were associated with their school’s bullying-related policy and/or their own training on their school’s policy. Finally, we examined whether policies and/or trainings were associated with staff’s likelihood of intervening with bullying and their self-efficacy in addressing bullying. This line of work may provide further insights into staff training and professional development to optimize the impact of policies on bullying-related outcomes.
Method
Participants
The current study drew upon data from 8,668 school staff (156 schools), of which 62.2% (N = 5392) witnessed bullying in the past 30 days. The subsample of those who witnessed bullying were included in Aim 1 and Aim 2 (see measures for more detail), the full sample was used for Aim 3.
Procedure
Districts were approached for participation in the Maryland Safe and Supportive Schools Project (MDS3), which focused on the use of a self-report school climate measure. All schools approached agreed to participate. Participation was voluntary for schools and for staff, with participation rates exceeding 80% across schools. The self-report MDS3 School Climate Survey (see Bradshaw et al., 2014 for details regarding the survey) was administered online in the spring of 2018, all responses were anonymous. IRB approval was granted by the University of Virginia, #2015-0049-00, Maryland Safe and Supportive Schools (MDS3) Project.
Measures
School Staff Demographics.
The MDS3 Survey included a series of self-reported demographic questions: Staff were requested to report their gender (coded as male versus female); race/ethnicity (coded as White versus all other categories); years of working (with higher numbers representing more years in schools); grade level (elementary, middle and high); and, their role in the school (administrator, general education teacher, special education teacher, school counselor/psychologist (labeled SC/P); office staff, and other supporting staff).
Perceptions of Bullying and Policy.
Consistent with prior research (e.g., Gladden et al., 2014; Olweus, 1993), participants read a definition of bullying (see Waasdorp & Bradshaw, 2015 for definition), and then were asked “How often have you seen students being bullied within the past 30 days?” (not at all-1 to several times a week-5; labeled frequency). They were also asked “Has a parent told you that their child has been bullied within the past 30 days?” (yes = 1 and no = 0). School staff were also asked: “This school has an anti-bullying or bullying prevention policy” (yes/no); “I have received training this year on this school’s anti-bullying or bullying prevention policy” (yes/no); “I have received training this year on how to complete A Bullying, Harassment, or Intimidation Form” (yes/no; herein “the Form”); “If you saw bullying, how likely is it that you would intervene?” (not likely-1, somewhat, likely, very likely-4); and “I have effective strategies for handling a bullying situation” (strongly disagree-1 to strongly agree-4).
Response to Bullying.
School staff responded to a single question “When you have seen bullying in the past 30 days, how did you respond?” by endorsing up to 10 possible response options (see Table 1 for all options). Staff responded to each question by indicating whether they utilized each response (yes = 1 and no = 0). They were also provided the option of indicating, “I did not see bullying in the past 30 days”. Those who chose this option (n = 3,276, 37.8%) were not presented with the list of possible responses to bullying and due to this, did not have any data for Aims 1 and 2.
Table 1.
Individual-level Descriptive Data by Grade
| Elementary school | Middle school | High school | Percent Endorsed Across All School Types | |
|---|---|---|---|---|
| Response (%) | ||||
| Intervened with the bully | 68.98 | 71.16 | 60.04 | 68.34 |
| Intervened with the victim | 63.50 | 66.16 | 53.83 | 62.95 |
| Talked to other staff about it | 45.89 | 44.84 | 30.23 | 42.62 |
| Talked to an administrator about it | 34.88 | 39.55 | 30.23 | 36.11 |
| Talked to bully’s parent about it | 25.29 | 16.50 | 9.42 | 18.56 |
| Talked to victim’s parent about it | 23.14 | 15.32 | 10.77 | 17.47 |
| Referred student to a guidance counselor or school psychologist (SC/P) | 27.64 | 35.60 | 19.15 | 29.64 |
| Ignored it/did nothing | .78 | 2.85 | 2.80 | 2.06 |
| Talked to a SC/P | 37.13 | 42.23 | 22.88 | 36.83 |
| Completed the Form | 3.23 | 6.00 | 4.14 | 4.62 |
| Frequency of witnessing victimization | 2.99 (1.14) | 3.77 (1.12) | 3.38 (1.12) | |
| Perceived existence of school-level policy (%) | 56.56 | 63.60 | 56.83 | |
| Received training on policy (%) | 40.17 | 50.38 | 44.72 | |
| Received training on Form (%) | 30.63 | 41.65 | 32.09 | |
| Parents reporting victimization (%) | 25.24 | 25.69 | 14.70 |
School-Level Covariates.
At the school-level, demographic variables in each model included student-teacher ratio, suspension rate, and percent of students receiving free and reduced priced meals (FARMS).
Analytical Strategies
For Aim 1, to account for the nested nature of the data where staff were nested in schools, multilevel logistic regression modeling was used to examine differences by grade level (37.9% elementary school, 17.9% high school, with 44.2% middle school staff as the reference group) and role (first with 63.6% general education teacher as the reference group) in staff binary responses to student bullying. The following variables were controlled for in the models: staff’s frequencies of witnessing bullying (M = 3.68, SD = 1.28), years working at this school (10.5% had 1 year of work experience, 18% had 1–3 years, 27.2% had 4–8 years, and 44.3% had 9 years or more), gender (81.5% female), and White (66.7% white) at level-1; student-teacher ratio (M = 7.73:1, SD = 5.52), suspension rate (M = .15, SD = .49), and percentage of students receiving FARMS (M = .43, SD = .24) at level-2.
For Aim 2, we leveraged multilevel logistic regression modeling to examine the contributions of level-1 policy-related variables and level-2 school characteristics in predicting staff responses to bullying, controlling for the same demographic variables as for Aim 1. Level-1 policy-related variables were staff’s perceived existence of school policies on bullying, received training on, how to complete the Form, and parents reporting their child being victimized. Descriptive statistics for level-1 policy-related variables are reported in Table 1 and those for other level-1 variables and for level-2 school characteristics were virtually identical as in Aim 1 and are thus not presented. For Aim 3, a multilevel regression model was utilized to explore the contributions of level-1 policy-related variables and level-2 school characteristics, controlling for the demographic staff variables (same as in the models for Aims 1 and 2) in predicting school staff’s likelihood of intervening with bullying and their self-efficacy in addressing bullying.
Results
Multiple regression analyses were conducted to compare staff who witnessed bullying in the past month to those who did not. Relatedly, staff who did not witness bullying were more likely to be affiliated with elementary and high schools than with middle schools, OR = 1.48 and 1.24, B = .40 and .22, SEs = .03, t = 14.17 and 6.90, ps < .001; had more years of working, B = .20, SE = .02, t = 8.23, p < .001; were more likely to be an office staff member than a general education teacher, OR = 1.53, B = .43, SE = .04, t = 11.53, ps < .001. No differences were found on gender (OR = .96, B = −.04, SE = .03, t = −1.14, p > .05), race/ethnicity (OR = 1.07, B = .07, SE = .04, t = 1.82, p > .05), and other roles relative to a general education teacher (OR = .94 to 1.07, B = −.07 to .07, SE = .05 to .06, t = −1.33 to 1.17, ps > .05) between the staff who witnessed bullying in the past month and those who did not.
Characteristics of Staff Responses to Bullying
Of staff who endorsed any response to bullying, on average, they reported two responses; specifically, 7.76% of staff endorsed one response and 43.75% endorsed four responses. The percent of staff endorsing each of the 10 responses by grade are presented in Table 1.
Role and Grade Differences in Staff Responses
The results show that there were differences by role regarding their response (see Table 2). Additionally, as shown in Table 2, compared to middle school staff, elementary school staff showed higher odds and high school staff showed lower odds of responding directly (e.g., actively intervening with involved students) to bullying incidents among students, including intervening with students involved, talking to other staff and to the bully’s parent. Further, relative to middle school staff, elementary school staff showed higher odds of contacting the victim’s parents whereas high school staff were less likely to contact the counselor and refer the involved students to them.
Table 2.
Multilevel Logistic Regression Results Examining Grade and Staff Role Differences on Their Responses to Student Bullying
| Bully | Victim | Other staff | Administrator | Bully’s parent | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Predictors | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR |
| Level-1 | ||||||||||
| Administratorb | 1.79(.76)* | 5.98 | 1.37(.48)** | 3.94 | .21(.31) | 1.24 | .11(.28) | 1.07 | 3.52(.32)*** | 33.91 |
| Special Ed. teacherb | .01(.11) | 1.01 | .08(.17) | 1.08 | .60(.14)*** | 1.83 | .05(.14) | .93 | .03(.19) | 1.03 |
| SC/Pb | −.39(.24) | .68 | .01(.21) | 1.01 | .08(.19) | 1.08 | 1.28(.18)*** | 2.76 | 1.01(.20)*** | 2.74 |
| Office Staffb | −1.24(.17)*** | .29 | −.78(.15)*** | .46 | −.21(.14) | .81 | .38(.17)* | .75 | −.76(.29)** | .47 |
| Other supporting teacherb | −.91(.20)*** | .40 | −.55(.20)** | .58 | .21(.17) | 1.23 | −.01(.18) | .85 | −.71(.27)** | .49 |
| Frequency | .47(.05)*** | 1.60 | .36(.05)*** | 1.43 | .36(.04)*** | 1.43 | .29(.04)*** | 2.34 | .30(.06)*** | 1.35 |
| Years of working | .03(.06) | 1.03 | .05(.05) | 1.05 | −.01(.04) | .99 | .14(.04)*** | 1.10 | −.11(.05)* | .90 |
| Male | .31(.15)* | 1.36 | .04(.11) | 1.04 | −.06(.08) | .94 | .01(.10) | .93 | .09(.13) | 1.10 |
| White | .28(.14)* | 1.33 | .28(.12)* | 1.32 | .25(.11)* | 1.28 | .09(.10) | 1.14 | −.06(.12) | .94 |
| Elementary schoola | .51(.11)*** | 1.67 | .64(.32)* | 1.90 | .92(.22)*** | 2.50 | .42(.25) | 1.26 | .86(.20)*** | 2.35 |
| High schoola | −.38(.14)** | .68 | −.37(.10)*** | .69 | −.41(.08)*** | .67 | −.14(.12) | .75 | −.49(.19)* | .61 |
| Level-2 | ||||||||||
| FARMS | −.48(.27) | .24(.26) | −.31(.18) | −.01(.24) | −.19(.31) | |||||
| Suspension rate | .10(.03)** | −.11(.03)*** | .19(.02)*** | .12(.06)* | −.07(.03)* | |||||
| Student-Teacher ratio | 1.63(1.01) | 1.16(1.06) | 1.43(.82) | 3.48(1.40)* | .50(.99) | |||||
| Victim’s parent | Referral | Ignore/Nothing | Counselor | Form | ||||||
| Predictors | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR |
| Level-1 | ||||||||||
| Administratorb | 3.50(.37)*** | 33.17 | .91(.28)** | 2.49 | −.14(.77) | .87 | 1.56(.31)*** | 4.74 | 2.93(.31)*** | 18.75 |
| Special Ed. teacherb | .19(.21) | 1.21 | .22(.15) | 1.25 | −1.67(.73)* | .19 | .17(.15) | 1.18 | .52(.22)* | 1.68 |
| SC/Pb | 1.71(.24)*** | 5.53 | −.33(.20) | .72 | −.51(.58) | .60 | −.31(.17) | .74 | 2.18(.29)*** | 8.88 |
| Office Staffb | −.21(.22) | .81 | −.21(.17) | .81 | −.23(.42) | .80 | −.20(.16) | .82 | .24(.42) | 1.27 |
| Other supporting teacherb | −.56(.28)* | .57 | −.01(.19) | .99 | −.52(.47) | .60 | −.24(.18) | .79 | .32(.26) | 1.38 |
| Frequency | .29(.05)*** | 1.33 | .38(.04)*** | 1.46 | .59(.13)*** | 1.81 | .28(.04)*** | 1.33 | .16(.08)* | 1.18 |
| Years of working | −.04(.05) | .97 | .07(.05) | 1.07 | −.13(.11) | .88 | .04(.04) | 1.04 | .05(.07) | 1.05 |
| Male | .02(.13) | 1.02 | −.40(.12)** | .67 | .38(.27) | 1.46 | −.33(.11)** | .72 | .15(.20) | 1.16 |
| White | −.05(.13) | .95 | .24(.10)* | 1.27 | −.05(.23) | .95 | .26(.11)* | 1.29 | −.07(.18) | .93 |
| Elementary schoola | .70(.23)** | 2.02 | −.31(.26) | .74 | −.50(1.23) | .61 | .18(.19) | 1.20 | −.20(.87) | .82 |
| High schoola | −.22(.15) | .81 | −.61(.08)*** | .54 | .34(.27) | 1.41 | −.77(.11)*** | .46 | −.19(.19) | .83 |
| Level-2 | ||||||||||
| FARMS | −.10(.25) | .78(.21)*** | .55(.56) | .39(.25) | .64(.38) | |||||
| Suspension rate | −.12(.03)*** | −.05(.04) | −.97(1.04) | .04(.03) | .03(.05) | |||||
| Student-Teacher ratio | .54(.79) | 1.76(.94) | 2.31(1.39) | .04(1.09) | 1.69(1.58) | |||||
Note. Frequency = Frequency of witness victimization. FARMS = percent of students receiving free and reduced priced meals within school.
Middle School is the reference group
General Education Teacher is the reference group.
p < .05
p < .01
p < .001.
Regarding the contributions of other covariates in predicting staff responses, we found that the more frequently staff witnessed bullying incidents, the more likely they were to endorse any response to bullying (including ignore). In addition, the number of years working was positively associated with their odds of talking to an administrator and negatively associated with their odds of contacting the bully’s parents. Compared to female staff, male staff were more likely to talk to the bully as well as less likely to contact and refer involved students to a counselor. In addition, White staff showed higher odds of intervening with students involved, talking to other staff, and contacting a counselor and referring involved students to a counselor than non-white staff.
For the associations between school-level characteristics and staff responses, we found that the higher the student suspension rate, the more likely staff were to talk to the bully, administrators and other staff, but less likely to talk to the victim, or the parents of involved students. Similarly, the higher the FARMS, the more likely staff were to refer the involved students to a counselor. Also, a higher student-teacher ratio was associated with school staff being more likely to contact the school administrator. See Table 2.
Contributions of Policy-related Variables in Predicting Staff Responses
As reported in Table 3, staff who had been trained on their schools’ anti-bullying policy had significantly higher odds of responding directly (e.g., actively intervening with involved students) than untrained staff. Staff who had been trained on completing the Form were more likely to do so and less likely to ignore bullying than those who had not been trained. When parents contacted the teacher about their child being bullied, teachers were more likely to respond directly to student bullying (e.g., intervening with the victim). In addition, staff reported existence of bullying policies did not predict their responses to bullying accounting for its correlation with whether staff received training. The associations between other level-1 covariates and level-2 school characteristics and staff responses were similar to the results in Aim 1 and therefore not reported in Table 3.
Table 3.
Multilevel Logistic Regression Results Examining the Associations Between Policy-Related Variables and Staff Responses to Student Bullying
| Bully | Victim | Other staff | Administrator | Bully’s parent | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| Predictors | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR |
| Perceived existence of school-level policy | .11(.18) | 1.12 | −.10(.15) | .90 | −.03(.11) | .97 | .05(.10) | 1.05 | .02(.15) | 1.00 |
| Received training on policy | .42(.19)* | 1.52 | .21(.10)* | 1.23 | .22(.11)* | 1.12 | .20(.10)* | 1.18 | −.02(.17) | .98 |
| Received training on Form | .06(.15) | 1.06 | .05(.14) | 1.05 | .02(.09) | 1.02 | .08(.12) | 1.09 | .18(.14) | 1.20 |
| Parents reporting victimization | −.07(.17) | .94 | .37(.12)** | 1.45 | .53(.11)*** | 1.70 | .95(.10)*** | 2.60 | 1.18(.12)*** | 3.27 |
| Victim’s parent | Referral | Ignore/Nothing | Counselor | Form | ||||||
| Predictors | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR | B (SE) | OR |
| Perceived existence of school-level policy | −.06(.17) | .94 | −.22(.14) | .80 | −.13(.30) | .88 | −.07(.13) | .93 | .14(.23) | 1.15 |
| Received training on policy | .22(.18) | 1.25 | .51(.10)*** | 1.67 | .06(.27) | 1.06 | .27(.13)* | 1.20 | −.07(.19) | .93 |
| Received training on Form | .19(.15) | 1.21 | −.12(.10) | .89 | −.91(.24)*** | .41 | .13(.08) | 1.14 | .35(.13)** | 1.42 |
| Parents reporting victimization | 1.72(.13)*** | 5.60 | .56(.10)*** | 1.75 | .08(.25) | 1.08 | .76(.12)*** | 2.13 | 1.34(.17)*** | 3.82 |
p < .05
p <.01
p <.001.
Contributions of Policy-related Variables in Predicting Staff’s Likelihood of and Self-Efficacy in Addressing Bullying
As reported in Table 4, staff members’ perceived existence of school-wide anti-bullying policies, receiving trainings on the policy and on Form completion were positively associated with their likelihood of and self-efficacy in addressing bullying. Regarding the level-1 predictors, the more frequently staff witnessed bullying, the less likely they were to intervene and the less confidence they perceived in addressing bullying. Elementary school staff reported higher likelihood of intervening and self-efficacy whereas high school staff showed lower likelihood of intervening and self-efficacy than middle school staff. See Table 4 for differences by role. At the school level, a higher FARMS rate and lower student suspension rate were associated with lower likelihood of intervening and less efficacy in addressing bullying.
Table 4.
Multilevel Regression Results Examining the Associations between Policy-Related Variables and Staff’s Likelihood of Intervening with Bullying and Self-Efficacy in Addressing Student Bullying
| Likelihood | Self-efficacy | ||||||
|---|---|---|---|---|---|---|---|
| Predictors | B | SE | t value | B | SE | t value | |
| Level-1 | |||||||
| Perceived existence of school-level policy | .06 | .02 | 2.80** | .14 | .02 | 7.52*** | |
| Received training on policy | .07 | .03 | 2.00* | .12 | .03 | 4.62*** | |
| Received training on Form | .09 | .02 | 5.48*** | .09 | .02 | 4.33*** | |
| Parents reporting victimization | .03 | .02 | 1.31 | .01 | .02 | .00 | |
| Frequency | −.03 | .01 | −3.85*** | −.03 | .01 | −3.82*** | |
| Administratorb | .13 | .03 | 3.81*** | .38 | .06 | 6.86*** | |
| Special Ed. teacherb | −.01 | .02 | −.49 | −.03 | .03 | −.82 | |
| SC/Pb | .05 | .04 | 1.42 | .21 | .05 | 4.67*** | |
| Office Staffb | −.12 | .03 | −4.44*** | −.06 | .03 | −2.22* | |
| Other supporting teacherb | −.05 | .02 | −2.16* | −.03 | .03 | −.92 | |
| Years of Working | .00 | .01 | .50 | .01 | .01 | .68 | |
| Male | −.03 | .02 | −1.48 | .13 | .02 | 6.29*** | |
| White | −.04 | .03 | −1.48 | −.06 | .02 | −2.80** | |
| Elementary schoola | .15 | .02 | 7.24*** | .15 | .02 | 6.15*** | |
| High schoola | −.18 | .04 | −4.43*** | −.06 | .03 | −2.42* | |
| Level-2 | |||||||
| FARMS | −.10 | .03 | −2.93** | −.11 | .04 | −3.07** | |
| Suspension rate | .02 | .00 | 4.59*** | .02 | .01 | 2.63** | |
| Student-Teacher ratio | −.03 | .12 | −.23 | −.21 | .18 | −1.17 | |
Note. Frequency = Frequency of witness victimization. FARMS = percent of students receiving free and reduced priced meals within the school.
Middle School is the reference group
General Education Teacher is the reference group
p < .05
p < .01
p < .001.
Discussion
Despite the mandate for U.S. schools to include anti-bullying policies, few studies have examined the relationship between the existence of a school policy, receiving training and school staff reported responses to bullying. This study filled the gaps in our current research where results suggested clear role and grade level differences in staff responses. In general, as compared to middle school staff, elementary school staff were more likely to report certain responses such as intervening with the students involved (the bullying and the victim), as well as the involved students’ parents. This could be due to differences such as smaller school sizes, fewer students changing classrooms/teachers throughout the day, or more overt forms of bullying that are easier for staff to detect, as well as increased interactions between parents and elementary school staff (Bradshaw & Waasdorp, 2019). Moreover, elementary school staff reported higher self-efficacy for intervening. In contrast, high school staff were significantly less likely than middle school staff to intervene with students or refer them to see a counselor. Notably, our analyses controlled for the frequency of bullying in the school, suggesting that school staff are responding and intervening less with bullying as students get older, regardless of the level of bullying staff witness.
Regarding school staff roles, when compared to general education teachers, there were differences in the types of responses. Specifically, supporting staff reporting significantly lower endorsement of responses, lower likelihood of responding in general, and lower self-efficacy for intervening, over and above the frequency of bullying they witness. While these findings could be related to the limited authority of staff in these roles, they highlight the importance of involving all staff, including both teaching and non-teaching staff in trainings related to bullying intervention, consistent with prior research on education support professionals (Bradshaw et al., 2013). Teachers and special education teachers did not differ in their level of self-efficacy to manage bullying situations, yet their self-efficacy was significantly lower than the self-efficacy of administrators and SC/P. Given students spend a large proportion of their school day with teachers, and students in special education are often at an increased risk for bullying victimization (e.g., Hartley et al., 2015), additional trainings on prevention and intervention of bullying behaviors are needed for general and special education teachers.
Our findings did not suggest that the existence of a school policy was a significant predictor of staff responding directly to bullying, whereas whether staff received training on a policy was, demonstrating the importance of this component in improving staff response to bullying. In theory, implementing an anti-bullying policy is typically intended to serve as an initial recommended step in preventing bullying, but our findings also support that merely having a policy is not sufficient (e.g., see Hall, 2017) and training on how to prevent, recognize and address bullying is crucial (e.g., Bradshaw et al., 2018). Studies have also found that policies can vary, and this variability likely impacts responses, such as the inclusion of a clear definition of bullying and procedures for investigating and responding to bullying (Hatzenbuehler et al., 2015; Haugen et al., 2019; Stuart-Cassel et al., 2011). Future studies need to examine variations in key components of policies and the impacts on bullying interventions (Haugen et al., 2019).
The current results suggested that staff who received training on their schools’ anti-bullying policy were more likely to respond directly to bullying, with a higher odds of intervening with students, discussing the incident with other staff (including administrators and SC/Ps), and referring the students involved to the SC/P. This finding is consistent with prior studies that have touted the importance of providing training to staff on ways to intervene with bullying (Bradshaw et al., 2013; Cornell & Limber, 2015) and demonstrated its impact on student outcomes (Gower et al., 2017; Hall, 2017). Further, receiving training on how to complete a Bullying and Harassment Reporting Form, the state’s process for documenting bullying incidents, was associated with increased likelihood of completing the Form and higher self-efficacy, and decreased odds for ignoring; however, it was not significantly associated with improved responses to bullying. It is clear that policies alone will not be enough to shift behaviors, implementation of the policy through trainings with staff is crucial to increase effectiveness (e.g., Cornell & Limber, 2015).
Regarding the covariates, higher suspensions were associated with higher likelihood of intervening with the bully; they were also associated with lower likelihood of intervening with the victim as well as contacting parents of the children involved. While we did not examine how staff members intervened with the bully, or if their response varied based on the severity of the incident, we know that staff often focus on quickly stopping the behavior through punitive responses (Bradshaw & Waasdorp, 2019) rather than on the systems that maintain bullying cycles. This is consistent with prior research suggesting that staff are more likely to intervene with the perpetrators (Burger et al., 2015). It is important that school staff intervene with all of those involved (Pas et al., 2019), including bystanders (De Luca et al., 2019). Contacting parents is critical because they play a key role in helping to reduce bullying and support their child, whether a victim or perpetrator (e.g., Song et al., 2018). Interestingly, higher rates of suspensions were associated with greater odds of addressing bullying, and feeling more efficacious in doing so; this could reflect a schools robust response to misbehavior. However, a higher FARMS rate, which is a proxy for poverty, was associated with a lower odds that staff would intervene and feel less efficacy to address bullying. These results highlight the need for targeted trainings, especially in schools with a higher FARMS rate, as professional development may be essential for increasing staff responses and decreasing bullying behaviors.
Notably, the data from this study were drawn from self-report quantitative report of perceived behaviors and future studies would benefit from using multiple informants and methods (e.g., observational data) in doing so studies could capture actual behavioral responses. Further, staff responses could vary based on the nature of the bullying incident. For example, if a student was physically injured staff might be more likely to contact an administrator; however, with no physical injury, they might be more likely to discuss with the students involved only. The contextual details regarding the bullying event should be examined in future studies, as this information would be necessary to have a comprehensive understanding of factors related to staff responses.
Conclusions and Implications
These results highlight the need for additional research to examine the specific type of training received that has the most positive impact on both staff responses and student outcomes. It is critical that all school staff receive training on anti-bullying policies with a strong focus on how to handle bullying situations. Our findings illustrate the need for trainings to target staff in the specific roles that reported lower likelihood of intervening and lower self-efficacy in handling bullying situations, namely general education teachers, special education teachers, office staff, and support staff, all of whom witness bullying frequently. These results also underscore the importance of having trainings across all school levels, with more intensive focus on middle and high schools to increase self-efficacy and likelihood for intervening with bullying.
School staff need guidance and training on how to consistently document bullying incidents using approved school forms, and how to communicate about bullying with involved students and their parents. Taken together, these results suggest that having a school bullying policy is associated with staff reporting some type of intervening response to observed bullying and increased self-efficacy for intervening. Future studies would benefit from exploring if self-efficacy is related to actual changes in behaviors. In providing staff trainings on how to identify and handle bullying, schools are likely to see improvements in feelings of safety among students by strengthening the students’ belief that they could get help, from all school-staff, in bullying matters and also decreasing bullying incidents (Bradshaw & Waasdorp, 2019).
Acknowledgement:
The research reported here was supported by the Institute of Education Sciences, U.S. Department of Education, through Grant R305H150027 (PI: C. Bradshaw) and the National Institute of Justice (2014-CK-BX-0005) to the University of Virginia. The writing of the manuscript was supported by the National Institute of Child Health and Human Development (NICHD; 1R01HD094833-01A1). The opinions expressed are those of the authors and do not represent views of either the Institute, the U.S. Department of Education or NICHD. The data that support the findings of this study are available from C.P. Bradshaw, upon reasonable request.
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