RECOGNIZE: a social norms campaign to reduce rumor spreading in a junior high school.

This article studied changes in rumor spreading and perceptions of peers' rumor spreading among students at one public junior high school following a social norms marketing campaign. Results of the study show that perceptions of peer rumor spreading fell following the campaign, but self-reports of rumor spreading did not decrease. Results suggest that a social norms marketing campaign conducted by a professional school counselor and delivered to students in a junior high can reduce misperceptions of negative social behaviors.

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While most school counselors would agree that rumor spreading is part of the adolescent experience, a review of the literature reveals that gossip or rumor spreading is connected to bullying behavior and is thus detrimental to students and academic achievement (Beale, 2001; Eisenberg & Aalsma, 2005; Hall, 2006; Unnever & Cornell, 2003). Bullying is defined as negative actions and behaviors intended to inflict psychological harm, physical injury, or discomfort upon another who does not have equal social status or power (Olweus, 1993; Smith, 1991; Smith & Sharp, 1994). Bullying behaviors include overt aggression such as teasing, name calling, and physical pushing or hitting, as well as indirect or relational bullying such as social exclusion and rumor spreading (Crick & Grotpeter, 1995; Dennis, 1999; Janssen, Craig, Boyce, & Pickett, 2004; Nansel et al., 2001; Shapiro, Baumeister, & Kessler, 1991).

All types of bullying behavior are of critical importance to school counselors for a number of reasons. It is estimated that up to three-quarters of young adolescents experience some type of bullying (Eisenberg & Aalsma, 2005; Hoover, Oliver, & Hazier, 1992). Bullying behaviors, from teasing and rumor spreading to physical fights, tend to peak in early adolescence and to decrease in frequency as adolescence progresses (Eisenberg & Aalsma; Nansel et al., 2001; Whitney & Smith, 1993). In particular, indirect aggression such as gossiping, rumors, and social exclusion increases with age and cognitive skills, making this form of bullying more prevalent among 12- to 15-year-olds than among younger children (Bjorkqvist, Lagerspetz, & Kaukiainen, 1992; Nansel et al.; Rivers & Smith, 1994).

Bullying prevention and intervention are crucial concerns for middle school and junior high counselors because these behaviors peak during these years and they are associated with a variety of negative consequences. Victims of overt verbal harassment and psychological bullying (teasing, ridicule, exclusion, rumors, and name calling) experience a variety of negative psychological consequences, including anxiety, anger, embarrassment, loneliness, depression, low self-esteem, and relational deterioration (Boivin & Hymel, 1997; Juvonen, Nishina, & Graham, 2000; Nansel et al., 2001). In addition, bullying is also associated with increased substance use and decreased academic performance (Furlong, Sharma, & Rhee, 2000; Nansel et al.).

Rumor spreading may have similar negative consequences as other forms of verbal harassment, and its impact extends beyond the individual being targeted because of the involvement of peers in the harassment. With indirect aggression, the perpetrator does not insult, tease, or attack the victim directly; rather he or she harasses the victim through the peer group by spreading false rumors, gossiping, or excluding the victim (Bjorkqvist et al., 1992; Garandeau & Cillessen, 2006; Owens, Shute, & Slee, 2004). The very nature of rumor spreading touches many students, whose sense of security in the school may be threatened by seeing and hearing other students being teased or insulted (Beale, 2001; Hall, 2006; Jeffrey, 2004; Nansel et al., 2001; Slaby, 2005). In order to prevent the negative consequences of rumor spreading and bullying among early adolescents, school counselors "are encouraged to assess the unique needs of their schools and work collaboratively to design and implement programs that will help create and reinforce safe environments for all students" (Milsom & Gallo, 2006, p. 19).

SOCIAL NORMS PROGRAMS FOR SECONDARY STUDENTS

One prevention approach that can address the unique concerns of a school is the social norms approach. Social norms approaches promote healthy behaviors through identifying a particular behavior (e.g., rumor spreading) among a population (a junior high, a school district), and then using a variety of media to communicate the true behavioral norm for that behavior among that population (Perkins, 2003c). Social norms theory "predicts that overestimations of problem behavior will increase these problem behaviors while underestimations of healthy behaviors will discourage individuals from engaging in them" (Berkowitz, 2004, p. 5). Research on adolescents and young adults has found that perceptions of social norms and peer expectations can have a more significant impact on individual behaviors and self-perceptions than other influences such as physiology, personality, family, or culture (Berkowitz & Perkins, 1986; Borsari & Carey, 2001; Casey-Cannon, Hayward, & Gowen, 2001; Kandel, 1985; Roberto, Meyer, Boster, & Roberto, 2003).

Perceptions of norms within a peer group take two unique forms, descriptive norms and injunctive norms, which have different influences on behavior (Cialdini, Reno, & Kallgren, 1990). Descriptive norms refer to an individual's belief about how widespread or common a behavior or attitude is among his or her peers, whereas injunctive norms refer to the social approval or disapproval expected when engaging in that behavior (Cialdini et al.). Researchers examining alcohol use among adolescents have found that injunctive norms are a greater predictor of behavior than the descriptive norm, yet reducing the perception of the descriptive norm has reduced alcohol consumption (Berkowitz, 2004; Borsari & Carey, 2003). When examining the influence of social norms on behaviors, it is important to distinguish between these two conceptions of norms and to examine them separately (Borsari & Carey, 2003; Cialdini et al.).

Social norms programs can be effective for encouraging healthy behaviors that are influenced by incorrect perceptions of peer norms. With secondary students, social norms approaches have been used primarily to reduce tobacco and alcohol use (Agostinelli & Grube, 2005; Haines, Barker, & Rice, 2003; Linkenbach & Perkins, 2003; Ott & Doyle, 2005). The key feature of every social norms campaign is to present truthful information on the percentage of students engaging in healthy positive behaviors in order to encourage those healthy behaviors (Perkins, 2003c). Social norms campaigns can take the form of a mass media campaign (billboards, television ads, radio announcements) across an entire state or a multimedia campaign (posters, banners, stickers, T-shirts, screen-savers, video announcements) in a single school. In the past several years, prevention practitioners across the country have begun using social norms approaches to address issues of peer violence and health issues beyond alcohol and tobacco (Berkowitz, 2003; Craig & Perkins, 2008; Perkins, 2003b). More recently, researchers have begun to use social norms approaches to address bullying among junior high and middle school students (Craig & Perkins).

PURPOSE OF THE STUDY

Rumor spreading, one aspect of bullying, is of concern to school counselors because it can impact the social well-being and academic performance of individual students. The purpose of this study was to investigate if a social norms multimedia campaign could be used to reduce rumor spreading among students at one public school. Social norms theory predicts that unhealthy behaviors such as rumor spreading can be reduced by reducing misperceptions following exposure to believable messages describing the true norm (Berkowitz, 2004). Five primary research questions were examined: (a) How do campaign recognition and believability influence the perception that other students at the school are spreading rumors? (b) How do campaign recognition and believability influence self-reported rumor-spreading behavior? (c) Can a social norms campaign reduce misperceptions of the descriptive rumor-spreading norm? (d) What are the greatest predictors of self-reported rumor spreading? (e) Can a social norms campaign reduce self-reported rumor spreading?

METHODS

"RECOGNIZE": Campaign Development

A focus group facilitated by the school counselor and the school district's prevention coordinator motivated this prevention project. Students were asked to identify the top issues at their school and they identified rumor spreading as a top concern. The campaign was developed following the seven-step Montana Model of Social Norms Marketing (Linkenbach, 2003).

This social norms project was initiated and directed by the school counselor who developed the campaign in cooperation with others knowledgeable in the social norms approach, including the school district's prevention coordinator, a youth marketing specialist, and a university researcher. The campaign was funded by a local educational grant aimed at supporting prevention projects. The primary costs included the services of the youth marketing specialist, the university researcher, and the production of campaign materials, which cost about $1,800.

The school counselor implemented the campaign with help from the school faculty and a student "street team" that acted as a focus group for campaign materials and messages and helped to disseminate materials. Six students, one boy and one girl from each grade, were recruited to the street team each year from a leadership class. Seeking a balance of interests, peer groups, genders, and grades, the school counselor selected students based on a letter they wrote about why they would like to be on the team. These students are referred to as a "street team" because they are the first students to carry the social norms message to their peers and they provide essential feedback on the student perceptions of the campaign materials (Smith & Reynolds, 2008; Wong et al., 2004). The school faculty provided support for this prevention method by communicating campaign messages in their classes and explaining the validity of the data when questioned by students, rather than sabotaging the campaign or supporting students' doubts. In the campaign implementation stage, the students helped the school counselor to distribute campaign materials and convey the campaign message to their peers.

Program planning began when the school counselor held the initial focus group with students in fall 2003, then worked with the school district's research and development center during that school year to develop a questionnaire for the evaluation of social norms prevention campaigns. Baseline data were collected in May 2004 and message development occurred the following summer and early fall. Students were selected for the street team at the beginning of the school year and the school counselor facilitated a few focus group sessions where students reviewed campaign materials and messages and made suggestions for revision. Then, these same students acted as a street team to help disseminate campaign materials and provide ongoing feedback to the school counselor.

The campaign included dual messages related to the theme "RECOGNIZE Respect." Each campaign poster and message included messages about respecting your body by not doing substances (alcohol and tobacco) and respecting others by not spreading rumors. This study reports on only the rumor-spreading behaviors. The marketing plan began with introducing and spreading the brand message "RECOGNIZE" as the campaign tagline that would identify the campaign as the specific messages changed over the coming years. After the introduction of the campaign tagline, specific messages were introduced with statistics related to rumor spreading.

Over the course of two school years, from fall 2004 to spring 2006, the campaign delivered the general message "RECOGNIZE--Most [School Name] Junior High School Students Do Not Spread Rumors." The message was delivered in a variety of media including stickers, T-shirts, screen-savers, flyers, and banners. Each semester a new round of materials was developed and distributed in order to keep the messages fresh and the data up to date. Specific messages included statistics from the questionnaire such as, "In a typical week 86% of students reported not spreading rumors." The school counselor along with the participating teachers and student street team were responsible for the creative distribution of the marketing items. Stickers were slipped into lockers through the slots in the doors. The school counselor and teachers randomly recognized students for engaging in positive behaviors (e.g., turning in money found in the lunchroom) with T-shirts, water bottles, or stickers from the campaign. The media specialist posted screen-savers in the media lab, and the street teams hung posters in places where students would be most likely to see and read them.

Participants

The school at which the campaign was implemented had a student population of approximately 300 students enrolled in the seventh, eighth, and ninth grades. The school is located in a suburban school district with more than 23,000 students. The student population, like that of the town, is predominantly White (82%), 15% Hispanic, with a small minority (3%) of American Indians, Asians, and Blacks. About 52% of the school population is male and 48% is female.

The sample was selected each semester by surveying all students enrolled in selected required courses (e.g., science, social studies). We used this method because we hoped to obtain a representative sample as all students are required to take these courses. The baseline data were collected in spring 2004 from approximately half of the student body, 122 students, 79% (n = 96) of whom were eighth graders, 16% (n = 20) were ninth graders, and the remainder were seventh graders. In subsequent years the school agreed to allow the administration of the survey to all students, and the subsequent samples are larger, including 85% to 90% of all students currently enrolled.

Posttests were administered in spring 2005, fall 2005, and spring 2006. These questionnaires included 258, 275, and 233 students, respectively. Again, administration was conducted in required courses in an effort to easily target each student. Students enrolled in the school participated in the survey each semester that it was administered, so the eighth-grade students in the spring 2004 data are the ninth-grade students in the spring 2005 data.

Of all the participating students, 30% (n = 254) were in the seventh grade, 42% (n = 360) were in the eighth grade, and 27% (n = 241) were in the ninth grade. The ethnic and gender makeup of the sample matched the enrollment figures for the school at that time, with 47% (n = 390) female, 14% (n = 119) Hispanic, and 81% White (n = 710) students. The baseline sample overrepresented eighth graders (79% in the sample vs. 42% in the school) because of the classes chosen for surveying. However, we found no significant grade-level differences in the variables of interest (see Table 1), so the baseline sample's lack of representativeness with respect to grade should not bias the results of the study.

Procedures

Consent for the questionnaire was garnered using established district policy for voluntary questionnaires. Parents were notified that their students would be completing the questionnaire, given a description of the content of the questionnaire, and given the opportunity to opt their child out of participating. The questionnaire was administered to students in the computer lab at the school where the school counselor or classroom teacher read a standardized set of instructions to each class of students before administering the questionnaire. The questionnaire was anonymous and voluntary. Any student who wanted to opt out was given the opportunity to sit quietly instead of participating. Following the administration of the questionnaire, the data were cleaned and filtered for suspect responses (Cross & Newman-Gonchar, 2004; Rosenblatt & Furlong, 1997). Fewer than 3% (N = 22) of all questionnaires were excluded from analysis, resulting in a total of 866 responses used in the analyses.

Instrumentation

The Student Perception Survey is a self-report, Web-based questionnaire developed by a research center that is a collaborative between the school district and the local university's School of Education. The Web-based questionnaire contained 86 items and was developed to include both the behavioral questions that the school district regularly monitors and normative questions needed for the evaluation and development of social norms prevention programs addressing substance use and bullying behaviors. The questions on rumor spreading were developed with input from student focus groups, and then the potential questions were piloted twice with students from the school to ensure that the questions measured the concepts intended by the researchers. In fall 2005, additional items were added to the Student Perception Survey to measure campaign recognition and believability.

Only eight items from the Student Perception Survey were analyzed for this study, as the remainder focused on other behaviors. Self-reported rumor spreading was measured with two questions, "How often do you typically spread rumors?" and, "In the past 30 days, how often have you spread a rumor?" Students also were asked, "In the past 30 days, how often have you heard a rumor spread about another person?" The descriptive norm was measured by asking students their perception of others: "How often do you think other students in your school typically spread rumors?" All items were scored on a 4-point, ordinal scale with responses of never, less than once a month, once a week, and daily.

Two questions measured the injunctive norm regarding rumor spreading. Students were asked to agree or disagree with the following statement: "I will be seen positively if I spread rumors or say negative things about another student." They also were asked how much they thought most other students in their school would agree with that same question. These questions have four responses: strongly agree, agree, disagree, and strongly disagree.

During the first year of the campaign, campaign recognition and believability were assessed in focus groups with students. During these focus groups students talked about their perceptions of the messages, where they noticed them the most, and what images and phrasing they found to be the most believable. Measures of recognition and believability were added to the online survey in fall 2005. Questionnaire items asked students how often they had seen RECOGNIZE messages, with a 6-point scale where 1 = never and 6 = several times a day. Campaign believability was reported on a 7-point scale where 1 = not believable and 7 = believable. For logistic regression analysis, the campaign believability scale was condensed into three categories. Numbers 1-3 were recoded to not believable, 4 was coded neutral, and 5-7 were recoded to believable.

RESULTS

Descriptive Statistics

Differences in rumor-spreading behaviors and perceptions are summarized by year, gender, and grade in Table 1. No substantial differences in rumor-spreading behaviors or perceptions were found between the grades in this school, but there were some differences between boys and girls. A slightly higher percentage of boys (61%) than girls (54%) thought that their peers believed they would be seen positively if they spread rumors. In contrast, girls were more likely than boys to report hearing rumors in the past 30 days, to perceive that others spread rumors once a week or more, and to report that they typically spread rumors once a week or more (see Table 1).

Baseline Misperceptions

As predicted by social norms theory, students reported pervasive misperceptions about the degree to which their peers engage in rumor spreading. In spring 2004, the pre-intervention, baseline data indicated that 60% of students reported that they typically never spread rumors and only 13% reported spreading rumors once a week or more frequently (see Table 1). In contrast, only 3% of students estimated that never spreading rumors was the norm; instead the majority of students (55%) reported that they thought that other students at their school typically spread rumors daily and another 22% reported thinking that most students spread rumors once a week. Although a great majority (77%) of students thought that most students in their school spread rumors every day or every week, only 43% reported having heard rumors that frequently (see Table 1). In addition, the majority (58%) of students reported that they believed other students thought they would be perceived positively, or receive social approval, if they engaged in rumor spreading.

Campaign Recognition and Believability

In order for a social norms campaign to reduce the targeted behavior, students must be exposed to the normative messages. During the second year of the campaign, the great majority of students at this junior high reported recognizing the campaign in both fall 2005 (83%) and spring 2006 (85%). Over the course of the school year, the median frequency of reported exposure increased from seeing the campaign messages "a few times a month" to "a few times a week," while the proportion of students who reported seeing the campaign on a daily basis increased from 21% in the fall to 36% in the spring. We used Somers' d to test the association between two ordinal variables, campaign recognition (independent) and campaign believability (dependent). The more frequently students reported having seen the campaign messages, the more believable they rated the campaign messages (Somers' d = .274, p < .001). Across the school year, ratings of campaign believability fell slightly; the mean rating was 4.1 in fall 2005, but only 3.7 by the spring.

How do campaign recognition and believability influence the perception that other students at the school are spreading rumors? Because campaign believability was only assessed in fall 2005 and spring 2006, the influence of campaign recognition and campaign believability on perceptions of the peer norm and self-reports of typical rumor spreading was examined for those semesters only. The N in Table 2 includes all the students in the school, who responded in one semester or the other to all items examined in the equations in Table 2. The results of logistic regression examining factors that affect the perception of the descriptive norm that "Other students typically spread rumors" once a week or daily are presented in Table 2. Hearing rumors once a week or daily in the past 30 days is the greatest predictor of the perception that other students spread rumors once a week or more. As compared to students who heard rumors infrequently, once a month or less, students who heard rumors frequently were 4.5 times more likely to perceive that the descriptive norm is frequent rumor spreading (Exp 13 = 4.54, p < .001). Campaign believability is the only other predictor of the descriptive norm. Students who did not believe the campaign messages were nearly twice as likely (Exp [beta] = 1.92, p < .05) as those who did believe the messages to overestimate the frequency of rumor spreading. The null effect of campaign recognition in both equations illustrates that campaign exposure alone is not enough to influence perceptions of peer norms.

How do campaign recognition and believability influence self-reported rumor-spreading behavior? We also analyzed results for the logistic regression examining factors that predict self-reported rumor spreading: "I typically spread rumors" once a week or daily. The descriptive norm is by far the greatest predictor of self-reported typical rumor-spreading behavior. Students who reported that they thought that other students typically spread rumors more than once a week were six times more likely to report that they spread rumors once a week or more (Exp [beta] = 6.23, p < .001). In addition, hearing rumors and campaign believability also substantially increased the odds that a student reported spreading rumors once a week or more often. Hearing others spread rumors in the past 30 days nearly quadrupled (Exp [beta] = 3.98, p < .001) the probability of reporting typically spreading rumors frequently. Students who did not believe the campaign messages were three times more likely (Exp [beta] = 3.29, p < .01) to report frequent rumor spreading. This same regression equation also was used to examine self-reported rumor spreading in the past 30 days, and the results are substantially similar with the descriptive norm and hearing rumors being the greatest predictors of spreading rumors in the past 30 days. Because these results are so similar, they are not included in Table 2, but are available upon request from the first author.

Pre/Post Intervention Comparison

Table 3 shows data comparing baseline data from spring 2004 to two posttests in spring 2005 and spring 2006. The analyses in this table excluded data from fall 2005 because rates of rumor spreading in the fall and spring semesters follow different patterns; spring rates are usually significantly higher than fail rates. Including fall data might falsely inflate the impact of the campaign; therefore comparing only spring data over time is a more conservative method for examining the impact of the campaign. Can a social norms campaign reduce misperceptions of the descriptive rumor-spreading norm? Table 3 presents the results of logistic regression examining factors that predict for the perception that "other students spread rumors" once a week or daily, comparing the predicted probabilities for spring 2005 and spring 2006 to the baseline data in spring 2004. As in the previous analysis, the strongest predictor of the descriptive norm is hearing rumors in the past 30 days. Students who heard rumors once a week or more in the past 30 days were five times more likely (Exp [beta] = 5.29, p < .001) than their peers who heard rumors infrequently or not at all to perceive that the normative behavior is to spread rumors once a week or more often.

Over the course of the intervention, the probability of overestimating the frequency of rumor spreading among other students fell by over half. Following one year of the campaign, the odds of overestimating the frequency of rumor spreading decreased by a factor of .51 (p < .05), and after two years of the campaign, spring 2006, the odds decreased even further by a factor of .41 (p < .01). This means that after the first year of the campaign, students were hall as likely to overestimate the frequency of rumor spreading, and by the end of the second year of the campaign, students were only 40 percent as likely to overestimate the actual norm as they had been prior to the campaign.

What are the greatest predictors of self-reported rumor spreading? We also analyzed the results of the logistic regression examining factors that affect self-reported rumor spreading via the response "I typically spread rumors" once a week or daily, comparing spring 2005 and spring 2006 to the baseline year 2004. In this analysis, the perception of the descriptive norm is by far the greatest predictor of self-reports of spreading rumors once a week or daily. Overestimating the frequency with which other students spread rumors increases the odds over 10 times that a student will report spreading rumors frequently (Exp [beta] = 10.98, p < .001). Hearing rumors frequently in the past 30 days is also a substantial predictor, though not as large as the perception of the descriptive norm (Exp [beta] = 4.95, p < .001).

Can a social norms campaign reduce self-reported rumor spreading? Given that campaign recognition was high and misperceptions significantly improved over the course of the campaign, social norms theory would predict that reports of rumor spreading also would decline. While misperceptions of the rumor-spreading norm seem to have declined following the intervention, self-reports of rumor spreading actually increased. In the spring of 2005 students were more likely (Exp [beta] = 1.81, p =.14) to report typically spreading rumors once a week of more often than in spring 2004, though this change is not statistically significant; however, this increase grew by the spring of 2006. The odds of students reporting that they spread rumors once a week or more increased three times (Exp [beta] = 3.17, p < .001) by spring 2006. Individual response category analysis shows that students were less than half as likely to report never spreading rumors (Exp [beta] = .43, p = .003) and over three times more likely to report spreading rumors once a week or daily (Exp [beta] = 3.35, p = .003) by the end of the campaign. This is the opposite of what social norms theory predicts, and opposite the trend for misperceptions of the descriptive norm. In addition, self-reported rumor spreading in the past 30 days was analyzed using the same regression equation and the results show the same pattern of predictors with the descriptive norm and hearing rumors being the greatest predictors of spreading rumors in the past 30 days. The increase in reported rumor spreading over time is similar in this variable as in the measure used in Table 3, typical rumor spreading.

DISCUSSION

Most of the results of this social norms campaign are consistent with social norms theory and previous research. The results show that girls are more likely than boys to hear others spreading rumors, which is consistent with past research on verbal bullying in which girls were more likely to experience rumor spreading (Fekkes, Pijpers, & Verloove-Vanhorick, 2005; Nansel et al., 2001; Owens et al., 2004). Although girls in this sample were more likely to report hearing and spreading rumors, gender was not a significant predictor of either the perception of norms or rumor-spreading behavior in the regression analyses. Among girls, hearing rumors more frequently accounts for greater misperceptions of the norms and slightly higher rates of self-reported rumor spreading than reported by boys. Analysis of the importance of descriptive and injunctive norms revealed that among these junior high students, descriptive norms were by far the biggest predictor of their own behavior. In this sample, junior high students spread rumors because they thought other kids were doing it, not because they believed spreading rumors would be viewed positively or garner social approval.

Results of this campaign are largely consistent with social norms theory. Social norms approaches attempt to change student behavior through correcting misperceptions of norms related to that behavior. Successful campaigns must have high recognition and believability in order to change misperceptions (Clapp, Lange, Russell, Shillington, & Voas, 2003; Granfield, 2002; Perkins, 2003b). The strategies employed in this campaign resulted in high campaign recognition in which the majority of students noticed campaign messages a few times a week by the end of the campaign. In addition, campaign believability increased with campaign recognition, and believing campaign messages predicted more accurate perceptions of peers' rumor spreading and lower rates of reported rumor spreading.

While perceptions of rumor spreading norms became more accurate over the course of the campaign, one result is inconsistent with social norms theory. Reports of typical rumor spreading increased over the course of the campaign. The modal response and the median for typically spread rumors both moved from "never" to "once a week." In this school, perception of the descriptive norm was the biggest predictor of reported rumor-spreading behavior and misperceptions decreased substantially following exposure to the campaign. Based on social norms theory, we would therefore expect reports of typical rumor spreading to go down as the misperceptions decreased (Berkowitz, 2004; Perkins, 2003b). Why then were students more likely to report spreading rumors once a month or more after the campaign? One possibility is that because the campaign focused on reducing substance use as well as rumor spreading, students did not get enough exposure to rumor-spreading messages to result in behavior change. In one study of social norms approaches to reduce bullying behaviors, including rumor spreading, some school sites took more than a year to result in substantial behavior change because of inadequate exposure to normative messages (Craig & Perkins, 2008).

Another possible explanation for perception change without behavior change is that the campaign increased students' awareness of their own rumor spreading. The campaign messages explicitly focused students' attention on their own behavior, encouraging them to "RECOGNIZE" what they said about other students. It is plausible to think that this then caused students to recognize that they sometimes spread rumors, increasing the odds that students reported spreading rumors once a week or once a month. Many social norms campaigns address behaviors that are relatively infrequent and notable occurrences, such as consuming alcohol of driving under the influence (Berkowitz, 2004). In contrast, rumor spreading is a regular and ordinary occurrence, which may make students less aware of their own routine rumor-spreading behavior. If, indeed, students became more aware of their behavior, the results of this campaign may actually document increased self-awareness or decreased misperception of one's own behavior, and not an actual increase in rumor-spreading behavior. In fact, examination of the measure "heard rumors in the past 30 days" shows little change from baseline to post-campaign. The lack of change on this measure suggests that actual rumor-spreading behavior may have not increased over the course of the campaign, but rather that students' awareness of their own behavior accounts for the changes in self-reports of typical rumor spreading.

Limitations

While the results of this study show significant changes in perceptions over the course of the social norms campaign, the study is limited by the lack of a control site and the demographics of the sample. Having data to compare from another junior high school in the district would add greater validity to our assessment of the impact of the social norms campaign. The demographics of this school are representative of the local school district and the local community, but do not represent the demographics of larger populations and therefore have limited generalizability. In addition, the use of self-report data to measure rumor spreading has the potential to be biased by the students' capacity to accurately perceive their own behavior. While the use of self-report data is common to measure bullying behaviors among youth, it may be less reliable for some behaviors than others (Elliott, Huizinga, & Menard, 1989; Huizinga & Elliott, 1986; Kandel, 1996). If, as we suggested above, the lack of change in reported rumor spreading is the result of students becoming more aware of their own behaviors, then the validity and reliability of this measure must be questioned.

Implications for School Counselors

School counselors often are tasked with primary responsibility for promoting and supporting positive healthy behaviors and climates for their students, which is the explicit mission of social norms approaches, to promote healthy behaviors (Berkowitz, 2004; Perkins, 2003a). However, it is important to note that school counselors cannot run a successful social norms campaign in isolation. While school counselors can take the lead, it is critical that educational stakeholders--school faculty, administration, research professionals, and students--come together to provide additional support and assistance to ensure a campaign's success (Orpinas, Horne, & Staniszewski, 2003).

One of the advantages of using a social norms approach to prevention is that it can be adopted by a school as a framework for all prevention activities in the school, rather than a new program targeting only one behavior. Many issues can be addressed under this framework, including substance use, violence prevention, and sexual harassment (Berkowitz, 2003; Perkins, 2003c). When this approach is adopted as an overarching framework, it then makes it easier for school counselors to work with teachers and other school staff to support a particular campaign. Once school staff learns how to communicate normative messages to students, they can simply change the content of messages to address particular behaviors. School counselors can utilize their knowledge of existing school statistics (e.g., attendance, grades) to craft positive messages on a variety of behaviors. For example, in a school where attendance is a concern, the school counselor could draw on existing attendance records to craft a normative message such as "90% of students miss school less than one day a quarter." Adopting a social norms approach to encouraging healthy behaviors can begin at many schools without any new data collection; it only requires utilizing existing data in new ways.

School counselors will find it easier to adopt the social norms approach if they take advantage of professional development opportunities to learn about this approach. We recommend that school counselors attend conferences or workshops on the social norms approach as well as other workshops such as facilitating focus groups. After attending conferences and workshops, school counselors then can use their knowledge of the approach to train parents, teachers, and other school staff about the power of positive messages in setting norms and behavioral expectations (DeJong, 2003; Perkins, 2003b). This can be done though presentations at staff meetings, school improvement committees, and parent groups. For example, a school counselor can present the basic theory, show a few graphs of the differences between perceptions and behaviors among students at the school, and then speak with others about how they can talk to students about the true norms in conjunction with the posters and other media materials that have been developed for a campaign.

Social norms campaigns are the most effective when each site, or school, has a dedicated campaign coordinator who understands the culture of the school and can observe student reactions to the campaign materials. We recommend utilizing the experience of professional marketing agencies only if they understand the premise of social norms campaigns and are committed to being responsive to student feedback in the development of campaign materials (Perkins, 2003b). In larger school districts, the district's own media and communications staff may be able to help develop posters and other materials for the campaign. Because social norms campaigns are research based, it is important to enlist the support of an evaluator who is familiar with the social norms approach so that he of she can assist not only in the analysis of posttest data, but also in the accurate use of data in campaign messages (Berkowitz, 2004).

While school counselors are one logical choice for the coordinator of a social norms campaign, there are others in the school who might also head up these efforts. Whether a school counselor is the leader or part of a team, he or she should enlist the support of school stakeholders with the ongoing tasks of a campaign. For example, teachers can assist with survey coordination and administration and other school staff can help to post campaign posters and distribute campaign materials at various school events. Depending on the behavior being targeted, school counselors can provide teachers with the data or other information from a social norms campaign that could be integrated into classroom activities. For example, health teachers can discuss substance use norms while math teachers might utilize data from a social norms survey for a lesson on creating charts and graphs or accurately summarizing statistics. School counselors are ideally positioned to take advantage of regular contact with students to gather feedback from students during campaign development and implementation to find out how the messages are being received. A school counselor is better positioned for this kind of data collection than an outside evaluator, whose services might be better used for data collection and analysis that are outside the counselor's area of expertise.

Most social norms projects typically measure success using self-reported behavior (e.g., alcohol and tobacco use), but rumor spreading is a behavior that can more easily be visible to others in the school. As such, school personnel might notice improvements evidenced by decreased numbers of students seeking the counselor for assistance coping with rumor spreading or decreased numbers of students being sent to the principal to receive disciplinary action due to rumor spreading. In addition to utilizing student surveys to assess rumor spreading and other types of bullying behaviors, school counselors also might want to develop other data sources. They might consider keeping a regular log of visits to the counselor's office including the reason for the visit, in order to use it as a potential data source for bullying concerns before and after intervention activities (Cornell & Brockenbrough, 2004). School counselors also might consider tracking disciplinary referrals related to rumors and bullying and keeping a log of student responses to campaign materials and discussions.

CONCLUSION

The campaign presented is one of the first social norms campaigns to address the issue of rumor spreading as one aspect of bullying. While the results show the campaign reduced misperceptions, the results also pose new questions. In regard to school climate issues, is changing the perception of other's behavior as important as changing the actual behavior? In the case of driving under the influence, a dangerous and potentially lethal behavior, the goal of a social norms campaign is and should be to reduce the high-risk behavior. Changing perceptions of the descriptive norm, other's behavior, is a tool for changing the actual behavior. In regard to rumor spreading and verbal bullying, it could be the case that perception of other's behavior is potentially as harmful as the behavior itself. Researchers have found that perception of risk can create fear for one's personal safety, even without personal experience of risk or danger (Fabiansson, 2007; Giddens, 1991). If misperceptions of the prevalence of rumors in school produce fear and anxiety equal to actually hearing rumors, then a social norms campaign is ideally suited to addressing these issues by promoting the actual norms and reducing the perceived threat of verbal bullying and rumor spreading. Future research could examine the impact of actual rumor spreading on perceived school climate in comparison to the impact of perceived rumor spreading on perceived school climate.

Perhaps the single most important aspect of using social norms as a prevention tool is that social norms theory provides a theoretical umbrella to guide all the prevention work done at the school while at the same time giving school counselors positive, tangible approaches to encouraging students to engage in healthy behaviors. We have learned that with regard to rumor spreading, perception of peer behavior is the greatest predictor of behavior. It appears that communication about true peer group behavior framed in a positive, healthy, and "cool" normative message can reduce the perception that "everyone is doing it."

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Earn CEUs for reading this article. Visit www.schoolcounselor.org, and click on Professional School Counseling to learn how.

Jennifer E. Cross, Ph.D., is an assistant professor in the Department of Sociology, Colorado State University, Fort Collins. E-mail: [e-mail]

William Peisner, M.Ed., is a school counselor in the Poudre School District, Fort Collins, CO.

Table 1. Descriptive Statistics by Time, Gender, and Grade

                              Spring 2004    Spring 2005
                                Prior to     Intervention
                              Intervention     +1 Year

Variables                       %     (n)      %     (n)

Campaign recognition           --     --      --     --
(% have seen the
campaign at least once)

Campaign believability         --     --      --     --
(% think it is believable)

Other students in my          58.1   (117)   61.1   (244)
school think thev will
be seen positively if they
spread rumors (% agree)

Heard rumors once a           42.9   (119)   45.7   (247)
week or more in past
30 days

Other students                77.1   (118)   64.9   (245)
spread rumors once
a week or more

I spread rumors once          12.8   (117)   13.8   (246)
a week or more

                              Fall 2005      Spring 2006
                             Intervention   Intervention
                              1.5 Years      + 2 Years         Total

Variables                      %     (n)      %     (n)      %     (n)

Campaign recognition         82.9   (228)   84.9   (219)   83.9   (447)
(% have seen the
campaign at least once)

Campaign believability       43.2   (257)   33.0   (215)   38.6   (472)
(% think it is believable)

Other students in my         57.4   (265)   55.0   (222)   57.9   (856)
school think thev will
be seen positively if they
spread rumors (% agree)

Heard rumors once a          44.0   (266)   52.4   (225)   46.6   (857)
week or more in past
30 days

Other students               62.5   (264)   62.7   (225)   65.3   (852)
spread rumors once
a week or more

I spread rumors once         13.2   (265)   19.9   (226)   15.1   (854)
a week or more
                                       Gender

                               Male           Female

Variables                     %     (n)      %     (n)

Other students in my        61.3   (431)   53.8   (383)
school think they will be
seen positively if they
spread rumors (% agree)

Heard rumors once           38.6   (440)   54.8   (387)
a week or more in
past 30 days

Other students spread       61.6   (438)   70.3   (384)
rumors once a week
or more

I spread rumors once        11.0   (437)   17.6   (387)
a week or more

                                        Grade

                               Seventh        Eighth          Ninth

Variables                     %     (n)      %     (n)      %     (n)

Other students in my        56.5   (246)   61.4   (355)   54.4   (237)
school think they will be
seen positively if they
spread rumors (% agree)

Heard rumors once           47.6   (254)   46.4   (360)   46.0   (237)
a week or more in
past 30 days

Other students spread       62.3   (252)   66.9   (357)   67.1   (237)
rumors once a week
or more

I spread rumors once        11.5   (253)   16.6   (356)   16.7   (239)
a week or more

Table 2. Logistic Regression Results Predicting Rumor-Spreading
Perceptions and Behaviors as a Function of Campaign Recognition
and Believability

                                Perceptions         Behavior

Variables                    [beta]   Exp (B)    [beta]   Exp (B)

Spring 2006                  -0.14    0.87        0.54    1.73
   (vs. fall 2005)
Male                         -0.34    0.71       -0.30    0.74
Grade (a)
  8                          -0.37    0.69        0.25    1.29
  9                           0.00    0.99        0.21    1.23
Injunctive norm (b)          -0.17    0.85        0.14    1.15
Descriptive norm (c)                              1.86    6.45 ***
Heard rumors once a week
    or more in past 30
    days                      1.00    4.69 ***    1.38    3.85 ***
Campaign recognition (d)     -0.49    0.61       -0.02    0.98
Campaign believability (e)
  Not believable              0.67    1.95 *      1.08    3.93 **
  Neutral                     0.23    1.26        0.55    1.73
Nagelkerke [R.sup.2]              0.20                0.27
Respondents (N) (f)               415                 415

(a) Comparison category = seventh grade.

(b) Comparison category = disagree/strongly disagree with
Other students think I will be perceived positively if
I spread rumors."

(c) Comparison category = "Other students in my school
typically spread rumors once a month or less."

(d) Comparison category = never.

(e) Comparison category = believable.

(f) N refers to all students who responded in one
semester or another. The approximate number of unique
respondents is about half the reported N. For more
information about this, see Note.

* p < .05. ** p < .01. *** p < .001.

Table 3. Logistic Regression Results Predicting Rumor-Spreading
Perceptions and Behaviors as a Function of the Intervention,
Controlling for Individual Characteristics and Normative

Beliefs                       Perceptions           Behaviors

Variables                   [beta]   Exp (B)    [beta]   Exp (B)

Male                        -0.22    0.80       -0.16     0.85
Grade (a)
8                            0.01    1.01        0.88     2.41 *
9                           -0.12    0.89        0.66     1.94
Injunctive norm (b)         -0.09    0.92        0.26     1.30
Descriptive norm (c)          --      --         2.35    10.50 ***
Heard rumors frequently
  in past 30 days            1.66    5.29 ***    1.60     4.98 ***
Time (vs. spring 2004,
  prior to intervention)
Spring 2005, intervention
  + 1 year                  -0.67    0.51        0.60     1.81
Spring 2006, intervention
  + 2 years                 -0.89    0.41        1.15     3.17 *
Nagelkerke [R.sup.2]             0.20                 0.27
Respondents (N) (d)              542                  541

(a) Comparison category = seventh grade.

(b) Comparison category = disagree/strongly disagree with "Other
students think I will be perceived positively if I spread rumors."

(c) Comparison category = "Other students in my school typically
spread rumors once a month or less."

(d) N refers to all students who responded in one semester or
another. The approximate number of unique respondents is
about half the reported N For more information about this, see Note.

* p < .05. ** p < .01. *** p < .001.

Note. The analyses in Tables 2 and 3 are a bit unusual because
we were not able to identify repeated responses by the same
student. It would have been desirable to link a student's response
from one semester to another. This would have given us more power
in the analysis and acknowledge the non-independence of the responses.
Because we could not link individual responses, our analysis cannot
account for individuals being repeated in the sample. On the one hand,
the effect of this may have made our p-values smaller, because the N
is effectively larger; and on the other hand, this would make
our p-values larger because we aren't able to filter out the
individual student variation from the analysis. Therefore, p-values
reported in the table are imperfect, but all the substantial effects
are so small as to alleviate this concern. A related matter that might
be confusing concerning the N in Tables 2 and 3 results from missing
values. The total N in each equation in Tables 2 and 3 does not
match the sum of ns for the included semesters because there are
missing cases for each item in each semester. The ns differ slightly
in each equation because the missing values are different for the
various items used in each equation.