What limits the effectiveness of antibullying programs? A thematic analysis of the perspective of students
first document is post, and choose two questions to answer is fine
second document is reading
You must provide justification for your opinion/thoughts, show a thorough understanding of the readings, and apply your knowledge; the use of outside examples is encouraged. You must also cite an excerpt from the relevant study for each of your answers.
Week 11 Reading 1: What limits the effectiveness of antibullying programs? A thematic analysis of the perspective of students
Summary
In this study, Cunningham et al., wanted to understand, from the perspective of students, why antibullying programs were ineffective in Canada. They chose to focus on the design and implementation factors as a major factor in their efficacy, explicitly noting the study took place within the confines of a provincially mandated (governmental) antibullying strategy (2016).
They made use of past research they had conducted on the teachers' perpectives to expand their theory and analyze what students didn’t like about these programs and how negative student participation affected the perception of program (Cunningham et al., 2016).
Methods
In this qualitative study, Cunningham et al., used purposeful sampling to recruit 97 students from 5th through 8th from 12 demographically stratified schools in a Canadian of more than 520,000 residents. They stratified schools into sociodemographically diverse quadrants so that the sample would represent schools they classified as low, medium, and high-risk areas (2016).
Their interview team then conducted thirteen 45-minute focus groups where audio recordings were transcribed and coded thematically. They utilized an inductive approach to make sure codes represented the data and organized them using psychological reactance theory. The interview team was comprised of five experienced school social workers who asked a series of questions (Cunningham et al., 2016).
Focus groups allowed them to create an in-depth analysis of design and implementation processes that might influence outcome. They explain that focus groups allowed for a wider range of topics to be discussed, encouraging them to explore areas that might not come up in one-on-one settings. They addressed three major questions from the results:
· What components of school-based antibullying activities do students believe to be ineffective or counterproductive?
· How do students respond to these dimensions of antibullying programs?
· Via what mechanisms might their responses limit the effectiveness of antibullying initiatives?
Findings
Some key findings by Cunningham et al., were that three major factors influenced their sample: presentations, activities, and assets were just not engaging or appealing to them. Many of them were poorly done, overly negative, or pushed by people who lacked credibility. There was also a massive failure on the past of adults in antibullying programs. Teachers were oblivious when bullying was happening, slow to react to it, did not respond with appropriate measures, or responded in a way the students felt was biased or disrespectful. Finally, some students were actively hostile to the program and pushed back on it, skipping presentations, continuing to bully and victimize others (and lying about their participation in it), being disruptive, and discrediting the overall program or presenters (2016).
They presented some statistics (below) on how many students agreed with the statement.
· Presentations and Posters Often Fail to Engage Students
· Boring presentations are of limited effectiveness (69%)
· Repetitive messages lose their influence (38%)
· Students dislike negatively worded antibullying messages (54%)
· Individuals lacking credibility compromise antibullying activities (62%)
· The Organization of Monitoring and Supervision Limits Detection of Bullying
· Teachers fail to detect bullying (54%)
· Delayed responses compromise adult interventions (77%)
· Consequences for perpetrators are ineffective (62%)
· Unfair or disrespectful processes undermine antibullying interventions (62%)
· Some Students Undermine Programs by Disengaging and Pushing Back
· Antibullying activities sometimes elicited student responses which limited the effectiveness of these initiatives (100%)
· Students fail to attend to antibullying activities (77%)
· Denial elicited by antibullying presentations insulates students from their message (31%)
· Students discredit antibullying programs and presenters (54%)
· Students disrupt antibullying activities (38%)
· Some students victimize peers during or immediately after antibullying activities (62%)
Assessment
The study made good use of the literature review, showcasing data about why effective bullying prevention programs were needed. It also devoted significant time to discussing multiple meta-analyses that had previously been published regarding their efficacy and what those findings were.
The study methods seem sound, and Cunningham et al., even address why those chose to do a qualitative study over quantitative. Stratified, purposeful sampling is highly effective, and choosing a larger population representing a more diverse area allowed for them to better generalize their results (as much as you can with a qualitative study). Their use of focus groups and coding protocols also seem to be in line with scientific standards.
The findings are presented clearly, and the graphs are supplemental to the actual statistics. They do also appear to reflect their conclusions that schools need to do better at engaging students, monitoring bullying, and responding appropriately to it.
The largest issue I have with the study is reflected within the limitations. School social workers might not have been the best interviewers, as they could have introduced bias (Cunningham et al., 2016). The study was also done under the auspices of a government mandated antibullying push. They also did not screen out known bullies, who could have actively been working to sabotage the study as their own study results note they work to sabotage antibullying programs within the school.
Reference
Cunningham, C. E., Mapp, C., Rimas, H., Cunningham, L., Mielko, S., Vaillancourt, T., & Marcus, M. (2016). What limits the effectiveness of antibullying programs? A thematic analysis of the perspective of students. Psychology of Violence, 6(4), 596.
Questions
Respond to two of the questions below, citing at least one example in each from the study. Reply to at least two of your classmates throughout the week.
1. The authors chose to ask their questions as a focus group to facilitate a discussion instead of conducting one-on-one interviews. Because bullying such a personal and emotional experience, was this the right decision? Could it have limited in-depth responses and created an echo chamber among peers?
2. Now that Cunningham et al., have created qualitative studies on both the perspectives of teachers (cited multiple times throughout this study) and students, what do you logically expect the design of the next study to look like?
3. The authors chose a sociodemographically diverse population for their sample, but do not appear to have collected any data on race, gender, ethnicity, or family income. Should this have been a part of the study? How do you think it would have an impact on the data?
,
What Limits the Effectiveness of Antibullying Programs? A Thematic Analysis of the Perspective of Students
Charles E. Cunningham, Cailin Mapp, and Heather Rimas McMaster University
Lesley Cunningham Hamilton-Wentworth District School Board, Hamilton,
Ontario, Canada
Stephanie Mielko McMaster University
Tracy Vaillancourt University of Ottawa
Madalyn Marcus Waterstone Clinic, Toronto, Ontario, Canada
Objective: We used qualitative methods to explore the views of students regarding design and imple- mentation factors limiting the effectiveness of the antibullying programs. Method: Using a purposeful strategy, we recruited 97 Grades 5 to 8 students from 12 demographically stratified schools. Interviewers conducted thirteen 45-min focus groups. Audio recordings were transcribed and coded thematically. Results: Three higher order themes emerged. First, students felt that antibullying presentations, posters, and activities sometimes failed to engage students. Antibullying communications that were boring, repetitive, negatively worded, or delivered by presenters lacking credibility were of limited value. Second, students felt that ineffective monitoring and consequences undermined antibullying programs. Students thought teachers failed to detect many bullying episodes, did not respond quickly enough when bullying was reported, adopted ineffective consequences, and failed to sustain helpful programs. Teachers who responded unfairly, were influenced by reputational biases, or dealt with students disrespectfully compromised antibullying interventions. Third, some students disengaged and pushed back by failing to attend to presentations, denying their involvement in bullying, discrediting programs and speakers, disrupting antibullying activities, and defiantly victimizing peers. Conclusions: Poor design and implementation may limit the outcome of antibullying programs. Pushback from a small group of students may have a negative influence on the responses of a wider group of peers. A negative response from students may reduce the commitment of the educators who implement antibullying initiatives. From the perspective of students, schools need to develop more engaging presentations, improve monitoring and supervision, develop more effective responses to bullying, and deal with students in an unbiased and respectful way.
Keywords: bullying, school, prevention programs, psychological reactance, qualitative methods
Epidemiological studies suggest that bullying and victimization remain significant public health concerns (Perlus, Brooks-Russell, Wang, & Iannotti, 2014) with victimization linked to an increase in both health and mental health problems (Due et al., 2005; Fekkes,
Pijpers, Fredriks, Vogels, & Verloove-Vanhorick, 2006; Rudolph, Troop-Gordon, Hessel, & Schmidt, 2011). Systematic reviews and meta-analyses suggest that, on average, prevention programs yield small, though statistically significant, reductions in bullying and
This article was published Online First January 14, 2016. Charles E. Cunningham, Cailin Mapp, and Heather Rimas, Department of
Psychiatry and Behavioural Neurosciences, McMaster University; Lesley Cun- ningham, Hamilton-Wentworth District School Board, Hamilton, Ontario, Can- ada; Stephanie Mielko, Department of Psychiatry and Behavioural Neurosciences, McMaster University; Tracy Vaillancourt, Department of Counseling, Faculty of Education, and School of Psychology, Faculty of Social Sciences, University of Ottawa; Madalyn Marcus, Waterstone Clinic, Toronto, Ontario, Canada.
Lesley Cunningham is now at the Ontario Ministry of Education. Madalyn Marcus is now at the Child and Adolescent Mental Health Department, South Lake Regional Health Centre, Newmarket, Ontario.
This study was supported by the Canadian Institutes of Health Research Grant MOP 123437, the Jack Laidlaw Chair in Patient–Centred Health Care
held by Charles E. Cunningham and a Canada Research Chair from the Canadian Institutes of Health Research held by Tracy Vaillancourt. The authors would like to express their appreciation to the social workers who assisted in the conduct of focus groups: Kelly Duffy-Kariam, Jenny Athana- siou, Carol Jovanovic, and Rose Mary Jankowski. During this study, Lesley Cunningham who is married to Charles E. Cunningham was employed by a participating School Board and the Ontario Ministry of Education. Family members of Stephanie Mielko were employed by a participating School Board.
Correspondence concerning this article should be addressed to Charles E. Cunningham, McMaster Children’s Hospital, Chedoke Site, Evel Build- ing, Room 163, 565 Sanatorium Road, Hamilton, Ontario, Canada L9C 7N4. E-mail: [email protected]
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Psychology of Violence © 2016 American Psychological Association 2016, Vol. 6, No. 4, 596–606 2152-0828/16/$12.00 http://dx.doi.org/10.1037/a0039984
596
victimization (Merrell, Gueldner, Ross, & Isava, 2008; Ttofi & Farrington, 2011; Vreeman & Carroll, 2007). For example, a meta-analysis of 44 evaluations reported that bullying decreased by 20% to 23% while victimization decreased by 17% to 20% (Ttofi & Farrington, 2011). Effect sizes were smaller in North American than in European studies, and smaller for randomized versus nonrandomized designs (Ttofi & Farrington, 2011). In response to these data, Espelage (2013) asked: “Why are bully prevention programs failing in U.S. schools?” A more recent meta-analysis using a three-level hierarchical model examining age as a within-study moderator suggested that, although antibul- lying programs reduce bullying by younger students, programs work poorly beyond Grade 7 (Yeager, Fong, Lee, & Espelage, 2015). Indeed, Yeager and colleagues (2015) concluded that, for students in Grade 8 and above, antibullying programs may produce iatrogenic effects.
This study’s qualitative methods explored the views of students regarding factors that limit the effectiveness of antibullying pro- grams. Students bring a unique perspective to efforts to understand the effectiveness of these initiatives. They may observe bullying incidents that are not detected by adults (Craig, Pepler, & Atlas, 2000), understand contextual contributors (Vaillancourt et al., 2010), and provide valuable suggestions regarding opportunities to improve antibullying efforts (Crothers, Kolbert, & Barker, 2006; Cunningham, Cunningham, Ratcliffe, & Vaillancourt, 2010). Stu- dents are in close touch with the attitudes of their peers and the response of strategically important subgroups to different compo- nents of antibullying programs. In a study using quantitative pref- erence modeling methods, latent class analysis showed that wit- nesses and victims were more likely to be members of a subgroup of Grade 5 to 8 students preferring mandatory uniforms, increased supervision, security cameras, and significant consequences for perpetrators (Cunningham, Vaillancourt, Cunningham, Chen, & Ratcliffe, 2011). Students involved as bullies, in contrast, were more likely to be members of a subgroup that opposed uniforms, preferred more limited supervision, rejected video surveillance, and advocated less severe consequences.
Although educators may be confident in their ability to deal with bullying (Boulton & Boulton, 2012), many students feel that not enough is being done (Bradshaw & Sawyer, 2007; Varjas, Hen- rich, & Meyers, 2009). Middle school students rate most antibul- lying strategies as less useful than do their teachers (Crothers & Kolbert, 2004). Indeed, 61.5% of middle school students believed intervention by educators made bullying incidents worse (Brad- shaw & Sawyer, 2007).
Boulton and Boulton (2012) posed the question: “Are pupils unreceptive to teachers’ anti-bullying initiatives and if so why?” In a qualitative study, participants in Grades 5 to 8 described students who responded to their school’s efforts to prevent bullying by disrupting presentations, destroying materials, and victimizing their peers as a defiant response to antibullying activities (Cun- ningham et al., 2010). There is increasing evidence that prevention initiatives may prompt processes such as psychological reactance (Brehm & Brehm, 1981; Chadee, 2011; Rains, 2013), social con- tagion, or peer deviancy training (Dishion & Tipsord, 2011; Hels- eth et al., 2015) that might limit the effectiveness of antibullying programs. Psychological reactance theory posits that individuals value decision control (Brehm & Brehm, 1981). Accordingly, attempts to influence decisions, change attitudes, or prevent par-
ticipation in high risk activities may elicit a negative emotional response, counterproductive cognitions, attempts to reassert per- sonal control, and, under some circumstances, an increase in behaviors the program is designed to prevent (Brehm & Brehm, 1981; Chadee, 2011; Rains, 2013). Previous studies suggest psy- chological reactance, a response familiar to many parents (Rum- mel, Howard, Swinton, & Seymour, 2000), may have limited the effectiveness of messages designed to reduce racial discrimination (Legault, Gutsell, & Inzlicht, 2011), substance abuse (Dillard & Shen, 2005), and exposure to violent media (Bushman, 2006).
The Current Study
We used qualitative methods to explore the possibility that antibullying programs in Grades 5 to 8 elicit a response interfering with the program’s implementation and effectiveness. Qualitative methods have made an important contribution to studies of bully- ing (Forber-Pratt, Aragon, & Espelage, 2014; Guerra, Williams, & Sadek, 2011; Mishna, Wiener, & Pepler, 2008; Varjas et al., 2009). Although quantitative studies examining the recommendations of students provide clues as to factors limiting the effectiveness of antibullying programs (Cunningham et al., 2011), a qualitative approach allowed an in-depth analysis of design and implementa- tion processes that might influence outcome. The range of ideas discussed in focus groups encouraged exploration of themes that might not emerge in individual interviews. Groups provided a supportive context in which students could exchange ideas, con- sider opposing views, critique existing programs, and suggest alternatives ( Barbour & Kitzinger, 1999). Specifically, we present a thematic analysis (Braun & Clarke, 2006) of focus group narra- tives addressing three questions:
1. What components of school-based antibullying activities do students believe to be ineffective or counterproduc- tive?
2. How do students respond to these dimensions of antibul- lying programs?
3. Via what mechanisms might their responses limit the effectiveness of antibullying initiatives?
Method
Participants
This study was approved by the university/hospital research ethics board, and the review panels of the participating school boards. The study was conducted in a Canadian community of more than 520,000 residents. We adopted a purposeful sampling strategy (Patton, 2002). Members of the research team from the Board of Education advised that the utility of our findings would be enhanced if participating schools reflected the diversity of this region. We stratified schools into sociodemographically diverse quadrants to ensure that the sample included schools from low, medium, and high risk areas. Four Catholic and eight public (Patton, 2002) junior kindergarten to Grade 8 schools were ran- domly selected. We contacted principals, described the project, and determined their willingness to send recruitment consents to
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597WHAT LIMITS ANTIBULLYING PROGRAMS
parents. All schools agreed to participate. School demographics, derived via the methods described by DeLuca and colleagues (DeLuca, Buist, & Johnston, 2012) are described in Table 1.
The reactant student responses noted in a previous study are thought to increase during Grades 5 through 8 (Grandpre, Alvaro, Burgoon, Miller, & Hall, 2003; Rummel et al., 2000). Systematic reviews, moreover, suggest this period marks a transition during which the effectiveness of antibullying programs declines (Yeager et al., 2015). Recruitment, therefore, focused on students in Grades 5 through 8. The 38 boys and 59 girls whose parents returned a signed consent, and who signed a student assent, joined one of six focus groups for boys (two Grade 5, one Grade 6, two Grade 7, and one Grade 8) or seven focus groups for girls (one Grade 5, two Grade 6, one Grade 7, and three Grade 8). Focus groups ranged in size from 5 to 12 students (M � 8).
Context of the Study: Antibullying Programming
Schools conducted antibullying activities according to the Prov- ince of Ontario’s Safe and Accepting Schools Act. This protocol included a series of evidence-informed components developed in collaboration with PREVNet (Ontario Ministry of Education, 2015). A website provided educational resources, videos, a model bullying prevention plan with evidence-informed guidelines, and school climate surveys (Ontario Ministry of Education, Promoting Relationships and Eliminating Violence Network [PREVNet] in collaboration with the Accepting Schools Expert Panel, 2013). Mandated components included a provincial code of conduct, a standard definition of bullying, a school-based bullying prevention policy, and a Bullying Awareness and Prevention week. Schools were required to have a Safe Schools Team that included a prin- cipal, teacher, nonteaching staff, parent, student, and community partner. This team reviewed and planned antibullying activities in response to a biennial School Climate Survey collected by each school. When bullying occurs, students are encouraged to “Tell an adult whom you trust—a teacher, the principal, the school bus driver or the lunchroom supervisor—about what happened or
report it anonymously” (Ontario Ministry of Education, 2013). Bullying was reported to principals using a standardized form, teaching staff were required to respond “immediately” using a standardized protocol (Ontario Ministry of Education, 2009), and incidents were dealt with according to a progressive disciplinary strategy coupled with support for victims and perpetrators (Ontario Ministry of Education, 2012a).
Focus Group Procedures
Focus groups were conducted by five school social workers with formal training in interviewing skills, experience working with students, familiarity with the Ministry of Education’s antibullying protocols, contextual knowledge regarding participating schools and the way in which individual schools dealt with bullying. A member of the research team was present to obtain assent, set up recording equipment, assist with the logistics of the group, and record observations. Focus groups were conducted according to a three-page interview guide. After obtaining signed student assent, the Ministry’s definition of bullying (Ontario Ministry of Educa- tion, 2012b) was presented. The interview guide provided semi- structured questions designed to initiate discussion. As in a previ- ous study, Cunningham et al. (2010) asked, for example, “Can anyone give us an example of something that schools are doing to stop bullying?” Follow-up prompts were designed to encourage discussion (e.g., “Could you tell us a little more about this exam- ple?”) and engage members of the group (e.g., “What do other students think?”). After discussing antibullying activities in their schools, interviewers explored the positive and negative ways students responded to these initiatives: “Sometimes students do things that stop anti-bullying programs from working. Can anyone think of an example of things students do that stop anti-bullying programs from working better?” To create a comfortable setting (Patton, 2002), groups were located in the home schools of par- ticipants. To prevent older students from dominating conversa- tions, and to capture the differing perspective that students in Grades 5 to 8 might provide, we conducted separate groups at each
Table 1 Demographics of Each School’s Neighborhood
School (grade/gender)
Variables
Median income
Percent immigrants
High school dropouts
Single mother families
Children below
poverty line
Psychiatric- related ER
visits Overall rank
RR N R % R N� R % R % R N�
1 (5B) 5 31,575 1 44.7 1 200.0 1 27.6 1 68.5 1 62.0 5 2 (6B) 5 41,427 3 24.9 1 131.6 1 31.8 1 40.6 1 30.1 5 3 (7B) 5 48,221 4 16.9 1 183.3 1 29.4 1 36.2 1 41.5 5 4 (8G) 4 50,904 1 34.5 2 76.0 1 22.1 1 35.3 4 13.2 4 5 (6G) 3 63,491 1 34.6 2 92.7 4 10.1 3 12.5 4 9.9 3 6 (7B) 3 63,564 4 18.0 3 58.1 4 12.2 3 14.4 2 18.7 4 7 (5G) 3 66,539 2 32.6 2 67.9 2 19.8 3 20.1 4 10.6 2 8 (7G) 3 68,872 1 35.4 2 69.0 3 13.1 2 21.4 3 13.6 3 9 (5B) 3 68,872 1 35.4 2 69.0 3 13.1 2 21.4 3 13.6 3
10 (6G) 2 72,092 4 18.7 3 54.2 3 14.3 4 6.5 3 14.4 2 11 (8B) 1 86,826 4 18.9 4 34.6 3 15.5 4 11.9 4 10.4 2 12 (8G) 1 88,843 5 11.4 4 50.0 5 6.8 5 5.6 4 9.7 1
Note. N� � rate per 1,000. R � Quintile ranking of each school (1 � highest, 2 � high, 3 � middle, 4 � low, 5 � lowest); B � boy; G � girl. Overall rank � Quintile ranking on a composite variable based on 24 health, education, and demographic measures.
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598 CUNNINGHAM ET AL.
grade. Because boys and girls may have different views regarding antibullying programs (Cunningham et al., 2010, 2011), we con- ducted separate groups for boys and girls. Consistent with a previous study (Cunningham et al., 2010), students seemed com- fortable talking to peers their own grade and gender.
Analysis of Focus Group Data
We used an approach similar to the thematic analytic procedures described by Braun and Clarke (2006). “Thematic analysis is a method for identifying, analyzing, and reporting patterns (themes) within data,” organizing data, and interpreting the results (Braun & Clarke, 2006). Audio recordings of focus groups were transcribed verbatim and potentially identifying content was removed. Three investigators reviewed the transcripts and identified potential codes (Braun & Clarke, 2006). Rather than imposing a theoretically-based framework, codes, and more general organiz- ing themes, were identified inductively (Braun & Clarke, 2006). Codes were based on the explicit semantic content of the tran- scripts rather than more latent constructions (Braun & Clarke, 2006). This
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