Strategies of Health Promotion Unit 6 Article Review

Health buzz at school: Evaluations of a statewide teen health campaign

Ming Wang, and Amy Struthers

College of Journalism & Mass Communications, University of Nebraska-Lincoln, Lincoln, NE, USA

ABSTRACT Drawing upon data from the first two years of a statewide school-based buzz-centered health communication campaign that encouraged high school students to adopt healthy behavior, this article finds that the buzz marketing component increased campaign awareness among students in participat- ing schools compared to those in the comparison schools, but there was no significant difference between their health atti- tudes. Furthermore, attitude toward the campaign mediated the effect of buzz exposure on health attitudes.

KEYWORDS buzz campaign; social marketing; obesity; teen wellness

Obesity has become a true epidemic (King, 2013) or pandemic (Swinburn et al., 2011) in the United States. The statistics of obesity among teens is alarmingly unsettling. In 2011–2012, almost 17% of youth were found to be obese (Ogden, Carroll, Kit, & Flegal, 2014). Obesity has immediate and long-term adverse health consequences.

Obese adolescents have been shown to be more prone to prediabetes (Li, Ford, Zhao, & Mokdad, 2009), bone and joint ailments, and a myriad other physical and psychological problems (Daniels et al., 2005; Dietz, 2004). It is no wonder that obesity usually leads to a lower weight-related quality of life (Zeller et al., 2015). In light of such dire consequences, public health professionals are work-

ing to curb this trend. Health agencies and nonprofit organizations in many states have waged campaigns to battle teen obesity, such as Hawaii’s “Rethink Your Drink” campaign and Georgia’s Strong4Life campaign. Notably, First Lady Michelle Obama has been a devout advocate who pro- motes healthy lifestyles for kids with her “Let’s Move!” campaign, bringing the issue of childhood obesity and adolescent health to the attention of the public (Batchelder & Matusitz, 2014). Given these changes, we partnered with the state’s Department of Health

and Human Services (DHHS) in 2007 to launch a school-based buzz-

CONTACT Ming Wang [email protected] 330 Andersen Hall, Lincoln, NE, USA. Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/whmq. � 2018 Taylor & Francis

HEALTH MARKETING QUARTERLY 2018, VOL. 35, NO. 2, 151–166 https://doi.org/10.1080/07359683.2018.1490544

centered marketing campaign that tackled the obesity issue by targeting high school students. We chose this group because high school students start to develop some life-long health habits as they claim more individual agency at this late adolescence stage (Taylor et al., 2012). Instead of adopt- ing an information-based knowledge-focused strategy, the campaign employed a fun, hands-on, and interactive theme. In addition to the use of traditional media, this campaign relied heavily on student buzz agents to engage their peers through a multitude of communication tactics at schools. The campaign started in 2007 and ended in 2013. Surveys with buzz

agents in this campaign have shown that their attitudes toward the cam- paign were positively associated with improvements in health attitudes and behavior (Struthers & Wang, 2016). This study extends this assessment of buzz agents to evaluations of the general student body by analyzing data from the first two years of the campaign to assess if the buzz marketing strategy increased awareness of the campaign and improved health attitudes among students in intervention high schools compared to those in com- parison schools who only received campaign messages through mass media. Moreover, this article tests whether exposure to buzz marketing tactics increased positive attitude toward the campaign, which in turn led to more favorable health attitudes.

School-based health campaigns

Common strategies to promote health messages to teens include campaign- ing through family members (Andrews, Silk, & Eneli, 2010; Blom-Hoffman, Wilcox, Dunn, Leff, & Power, 2008), on mass media (Paek, Oh, & Hove, 2012; Randolph & Viswanath, 2004), in communities (Chomitz et al., 2010; Economos & Irish-Hauser, 2007), and at schools (Baranowski, Cullen, Nicklas, Thompson, & Baranowski, 2002; Story, Kaphingst, & French, 2006). At the early adolescent stage, parental influence is declining (Austin, 1995) and peer norms start to determine whether a behavior is hip, safe, or desirable (Maxwell, 2002). Therefore, school-based interventions are par- ticularly important for high school teens. School-based obesity prevention programs have been found to be quite

effective at least in the short run (Dobbins, De Corby, Roberson, Husson, & Tirillis et al., 2009; Khambalia, Dickinson, Hardy, Gill, & Baur, 2012; Story et al., 2006), boosting physical activity (Melnyk et al., 2013) and pro- ducing a moderate increase in fruit and vegetable consumption (Howerton et al., 2007). The impact of such programs has not been consistent, however. One

school-based health intervention program targeted at adolescent girls in

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Minnesota, for instance, found few significant differences in a host of health-related outcomes between intervention and control schools (Neumark-Sztainer, Story, Hannan, & Rex, 2003).

Buzz marketing

Buzz marketing is not a new idea. In communication science, this concept is rooted in the personal influence paradigm or the two-step flow of infor- mation framework (Lazarsfeld, Berelson, & Gaudet, 1948) where interper- sonal communication is deemed a strong complement to mass media information (Chaffee & Mutz, 1988) and sometimes can overpower the role of mass communication in bringing about attitude and behavioral change (Katz, 1972). Buzz instigated by a small group of highly involved people can bring

about health attitude change among the lowly involved (Gosselt, Van Rompay, & Tolhuis, 2012). For teens, messages from authority figures, such as teachers and government agencies, can be perceived as preaching whereas their peers tend to be viewed as more credible sources of informa- tion (Thomas, 2004). Indeed, peer exposure was found to be positively associated with one’s own physical activity at school, physical activity out- side of school, and fruit and vegetable intake, all of which contribute to the prevention of obesity (de la Haye, Robins, Mohr, & Wilson, 2011; Salvy et al., 2008; Shin et al., 2014). Many public health campaigns, such as the “Students Against Drunk Driving” campaign, the “Above the Influence” campaign, and “The Truth” campaign, have relied upon peer influence to motivate teens toward adaptive and healthy behavior. A comprehensive review of peer-to-peer health promotion interventions for the youth has found the strategy to be quite effective (Harden, Weston, & Oakley, 1999). Buzz marketing levering peer influence can be effective for a host of rea-

sons. Social cognitive theory (Bandura, 2009) suggests that individuals model behavior that they have observed to be desirable and rewarding. This type of modeling has been reported in school children who are influ- enced by how much food their peers eat and how physically active their peers are (Efrat, 2009; Romero, Epstein, & Salvy, 2009). Social facilitation theory, which maintains that people change their behavior simply because of the presence of others, also explains how peers can influence health behavior (Salvy, de la Haye, Bowker, & Hermans, 2012). Impression man- agement theory, suggesting that individuals change behavior to maintain a certain image, has been applied to the study of health behavior as well (Salvy et al., 2012). Overall, Brechwald and Prinstein (2011) posit that peer influence works for adolescents because they engage in high-status behav- ior, because they engage in behaviors that match the social norms of a

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valued group, because they engage in behaviors that are reinforced by peers, and because they engage in behaviors that contribute to a favorable self-identity. Buzz marketing campaigns often build a reservoir of buzz agents, peers

who are typically employed to talk about or advocate for a particular prod- uct or service (Freeman & Chapman, 2008). These agents play multi- faceted roles, such as endorsers, distributors, researchers, consumers as well as influencers (Ahuja, Michels, Walker, & Weissbuch, 2007). The buzz component of our campaign therefore relied on a team of buzz agents we have assembled.

Whatcha doin? campaign

Our approach toward the campaign revolved around illustrating the fun, and even unexpected lifestyle that could come from increased fruit and vegetable consumption and more physical activity. The campaign tagline, “Whatcha doin? How you do it is up to you,” lets teenagers know that they could make their own choices. After extensive planning, we launched the campaign in the fall of 2007 at

six local high schools—four intervention and two comparison schools—in one school district. The campaign was promoted on local media including billboards and television stations to which students from all local schools were exposed. The buzz strategy was implemented in four select high schools only in the first year. We worked with the principal of each of these four intervention schools

to identify a teacher–coordinator who would serve as an on-the-ground recruiter for buzz agents. Diverse student groups were proposed as buzz agent teams, including a student council, a nutrition class, a DECA club and a physical education class. This effort resulted in 32 buzz agents the first year. Each school could customize the campaign in its own unique way work-

ing with a pool of tactical materials we provided. Buzz agents received tools to help promote the campaign within their schools, from information pack- ets to collateral materials such as stability balls, T-shirts, static clings, stick- ers, and campaign signs. These students first slowly rolled out the campaign using stealth tactics, followed by frequent branded “random acts” involving fruits, vegetables, and physical activity. Buzz agents were encour- aged to use their own imaginations and stage many small low-cost but unexpected activities. By utilizing the Whatcha doin? signs, stickers, and T- shirts to properly brand the random acts, students could link the random- ness with the campaign and effectively kept both the buzz and the cam- paign alive.

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These same four intervention schools participated in the campaign again in the second year, joined by eight more high schools in other school dis- tricts across the state. A total of 165 buzz agents and an estimated number of 8,057 students were involved. The campaign theme was retained and the tactical materials were used again, but we introduced some new ones, such as a carrot man costume and some word magnets, based on the evaluations we received from the pilot year. We also started a website promoting the campaign in our second year. To evaluate campaign effectiveness, we only surveyed students in intervention schools and did not collect responses from those in schools that did not participate in the buzz program. Given the literature on the effectiveness of school-based buzz marketing

health campaign strategy, students in intervention schools should be more aware of our campaign and hold more positive attitudes toward being physically active and eating more fruit and vegetables. Therefore, we expect that during the first year:

H1: Students in schools that implemented a buzz strategy were more aware of the Whatcha doin? campaign than those in comparison schools.

H2: Students in schools that implemented a buzz strategy showed more favorable health attitudes toward (a) being physically active, (b) eating fruit and (c) eating vegetables than those in comparison schools.

In addition to knowing whether there were any differences between intervention and comparison schools, we are also interested in learning how the buzz strategy worked in intervention schools. In a successful per- suasion process, awareness of and attitude toward a subject are usually highly correlated (McGuire, 1985). Therefore, it is hypothesized that in intervention schools:

H3: Exposure to the buzz strategy of the Whatcha doin? campaign was positively associated with attitude toward the campaign.

Affect-referral theory

How can attitude toward the campaign affect attitude toward health issues that are highlighted by the campaign? Affect-referral theory offers some insight. Sometimes people may form attitudes based on affect for an alter- native instead of processing through a cognitive route and examining beliefs and arguments (Wright, 1975). People sometimes transfer their feel- ings for one object to a related objective, a core argument in the attitude toward the ad theory (Batra & Ray, 1986; MacKenzie, Lutz, & Belch, 1986; Shimp, 1981), which posits that in product advertising, liking of an ad leads to more favorable attitudes toward the brand, resulting in higher purchase intentions. This theory has received strong empirical support over the past

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few decades. As Fishbein and Ajzen (1975) put it, “At the most general level, we learn to like (or have) favorable attitudes toward objectives we associate with ‘good’ things, and we acquire unfavorable feelings toward objectives we associate with ‘bad’ things” (p. 217). Some posit that affect-referral is possible due to a classic conditioning

mechanism (Shimp, 1981), while others contend that attitude toward the ad (or campaign) is a heuristic on the peripheral route to persuasion in the classic elaboration likelihood model framework (Petty, Brinol, & Priester, 2009). Based on the affect-referral theory, it is expected that individuals who

like an ad would also develop positive attitudes toward the product, service, or issue portrayed in the ad. Some empirical studies support this claim. One’s attitude toward a public service announcement, for instance, has been shown to exert significant positive influence on their attitude toward the advocated issue (Dillard & Peck, 2000; Nan, 2008). Most of the research on attitude toward the ad is tested at the micro-,

psychological level. This theoretical framework can also be applied to a macrolevel that tests the impact of health campaigns. Moreover, surveys of buzz agents have shown that campaign attitude was positively associated with health attitudes (Struthers & Wang, 2016). Based on this line of rea- soning, the study predicts the same relationship for the general stu- dent population:

H4: Attitude toward the buzz strategy of the Whatcha doin? campaign was positively associated with health attitudes such as (a) being physically active, (b) eating fruit, and (c) eating vegetables.

Putting H3 and H4 together, we have developed an attitude toward the campaign mediation model. In essence, the effect of campaign exposure on issue attitude is expected to be channeled through attitude toward the campaign.

Method

Data

The Whatcha doin? buzz campaign was implemented each year in partici- pating high schools in [authors’ state] from 2007 to 2013. We were only able to test the hypotheses with the first two waves of the project because a survey instrument was distributed to the general student population in the buzz schools only in W1 (2007–2008) and W2 (2008–2009). Students in two comparison schools, who only received the local media exposure but not the school-based buzz program, were also assessed in W1.

156 M. WANG AND A. STRUTHERS

A different questionnaire was developed each year, but the questions asked in the first two waves were largely the same. The populations were somewhat different, however. The same four buzz intervention schools par- ticipated in both waves; eight new schools joined the second wave. Campaign tactics also differed slightly. We introduced three new tactical materials in the second wave—a carrot man costume, word magnets, and a website.

Measures

Test of H1 and H2: Intervention and comparison schools in W1 H1 and H2 were tested on the W1 data that included 351 respondents in four schools that participated in the buzz intervention and 457 respondents in two comparison schools who did not receive the buzz treatment but who were nonetheless exposed to the overall campaign through local media channels such as billboards, movie theaters, and TV. We did not survey students in comparison schools in W2. To measure campaign awareness, students were asked to pick what the cam-

paign was about from a list of topics. Selecting each of the three campaign topics was coded as 1; not selecting a given topic was coded as 0. Of the entire sample, 36.6% were aware that the campaign was about being physically active, 29.2% knew it was about eating fruit and 27% knew it was about eating vege- tables. In terms of health attitudes, of all the students, 92.9% liked being phys- ically active, 95.3% liked eating fruit and 65.9% liked eating vegetables.

Test of H3 and H4: Intervention schools in W1 and W2 H3 and H4 set out to explore the relationships between buzz exposure, campaign attitude, and health attitudes, so we only focused on the students in the schools who received the buzz campaign treatment in W1 and W2. Since these were two waves of cross-sectional data, we estimated two separ- ate path models for each wave to see if the hypothesized relationships held in both waves.

Exogenous variables Our key exogenous variable of interest is campaign exposure, but we also controlled for a host of demographic and mass media campaign expos- ure variables. Demographic variables. Three demographic variables were controlled for:

grade, sex, and race. For W1, students came quite evenly from each grade (Grade 9: 22.3%; Grade 10: 24.3%; Grade 11: 28.6%; Grade 12: 24.9%). There were more female (55.2%) and White (74.6%) students. For W2,

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fewer students were from Grade 12 (Grade 9: 37.1%; Grade 10: 31.5%; Grade 11: 22.2%; Grade 12: 9.3%). Similar to W1, there were also more female (54.5%) and White (62%) students. Campaign exposure through mass media. We controlled for potential

exposure to the Whatcha doin? campaign on local mass media. In W1, three media channels were measured: billboards, movie theater and TV. Students indicated whether they had noticed Whatcha doin? through each of these channels; “yes” was coded as 1 and “no” as 0. Descriptive statistics shows that 56.8% noticed the campaign on billboards, 9.3% in the movie theater, and 58.1% on TV. In W2, the following three media channels were measured: billboards, Internet/website, and TV. The same coding procedure was followed. Data show that 48.3% noticed the campaign on billboards, 24.7% on Internet/website, and 37.1% on TV. Campaign exposure through buzz marketing. Students in intervention

schools were asked a battery of questions about whether they noticed the tac- tics used by the Whatcha doin? campaign; this battery is a unique list of tac- tics that were used by buzz agents in each school. In Wave 1, the options were: cardboard cutouts, green stability balls, random acts, sings, stickers, sur- vey booth, T-shirts, video contest, and window clings. The answer “yes” was coded as 1 and “no” as 0. These items were summed to create a W1 buzz exposure index (a ¼ .67, M ¼ 5.34, SD ¼ 2.06). In Wave 2, the tactics employed were: word magnets, green stability balls, random acts, signs, stick- ers, costume character, T-shirts, video contest, and window clings. These items were summed to create a W2 buzz exposure index (a ¼ .74, M ¼ 5.33, SD ¼ 2.33).

Endogenous variables Campaign attitude. Students were asked, “Overall, what is your attitude toward Whatcha doin? materials, promotion, and activities?” They were given five options: loved it, liked it, no opinion, didn’t like it, and hated it. The answers were reverse coded from 1 to 5 so that higher values indicated more favorable attitudes (W1: M ¼ 3.30, SD ¼ .76; W2: M ¼ 3.50, SD ¼ .96). Health attitudes. Students were asked about their attitudes toward being

physically active, eating fruit and eating vegetables. In W1, the options were like it or don’t like it. Like it was coded as 1 and don’t like it as 0. Most liked eating fruit (95.7%); physical activity was close behind (92.3%); substantially fewer liked eating vegetables (67.5%). In W2, a 5-point scale was employed ranging from love it to hate it. The answers were reverse coded so that higher values indicated more favorable health attitudes. The mean was highest for attitude toward eating fruit (M ¼ 4.37, SD ¼ .79), fol- lowed by physical activity (M ¼ 4.31, SD ¼ .87) and eating vegetables (M ¼ 3.58, SD ¼ 1.13).

158 M. WANG AND A. STRUTHERS

Results

Differences between intervention and comparison schools

To test H1 and H2, we conducted a series of v2 tests comparing the per- centage of respondents who correctly identified what Whatcha doin? was about and the percentage of respondents who liked three health issues in schools who received a buzz strategy treatment compared to the compari- son schools who did not. Consistent with H1, students from intervention schools were more likely

than those from comparison schools to have correctly identified what the campaign was about. As we can see in Table 1, a higher percentage of stu- dents from intervention schools knew Whatcha doin? was about being physically active (comparison schools: 14.7%, intervention schools: 63.8%, v2[1] ¼ 208.17, p < .000), knew Whatcha doin? was about eating fruit (com- parison schools: 6.6%, intervention schools: 58.7%, v2[1] ¼ 260.87, p < .000), and knew Whatcha doin? was about eating vegetables (compari- son schools: 5.3%, intervention schools: 55.3%, v2[1] ¼ 252.11, p < .000). Next, we turn to health attitudes. Intervention schools and comparison

schools did not differ in their attitudes toward being physically active, v2(1) ¼ .29, n.s., toward eating fruit, v2(1) ¼ .232, n.s., or toward eating veg- etables, v2(1) ¼ .601, n.s. Hence, H2 is not supported. Incidentally, in terms of the overall attitude toward the campaign, inter-

vention and comparison schools did not differ significantly either: Mintervention ¼ 3.145, Mcomparison ¼ 3.303, t(412) ¼ �1.903, n.s. Taken together, the buzz component of the Whatcha doin? campaign achieved its awareness goals, but failed to bring out health attitudinal changes in inter- vention schools compared to the comparison schools.

Campaign attitude mediation model

To test H3 and H4 specified in the mediation model, we performed path analyses in Mplus 7 (Muthen & Muthen, 2012). The W1 analysis was con- ducted on the four intervention schools only.

Table 1. Differences in campaign awareness and health attitudes between comparison and intervention schools.

%

Variable Comparison schools Intervention schools v2 (1)

Whatcha doin? is about being physically active 14.7 63.8 208.170��� Whatcha doin? is about eating fruit 6.6 58.7 260.866��� Whatcha doin? is about eating vegetables 5.3 55.3 252.114��� Attitude toward being physically active 93.3 92.3 .286 Attitude toward eating fruit 94.9 95.7 .232 Attitude toward eating vegetables 64.8 67.5 .601 �p < .05; ��p < .01; ���p < .001.

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For each wave, we regressed campaign attitude on buzz exposure while simultaneously regressing three health attitudes (being physically active, eating fruit, and eating vegetables) on campaign attitude. Additionally, we also controlled for demographics and exposure to the campaign on trad- itional media by regressing them on each of the endogenous variables. The mediation model in W1 (n ¼ 222) was estimated with WLSMV that

adjusted for means and variances of diagonally weighted least squares because the three health attitude variables were dichotomous. A review of the model fit statistics reveals the hypothesized model to exhibit a good fit to the data. For instance, v2(3) ¼ 3.361, p > .05; RMSEA ¼ .023, CFI ¼ .991, all meeting conventional cutoff criteria (Hu & Bentler, 1999). In terms of demographic and mass media campaign exposure, noticing

Whatcha doin? on TV was positively associated with attitude toward the campaign (B ¼ .24, SE ¼ .11, p < .05) and school grade, a proxy for age, was positively associated with attitude toward eating vegetables (B ¼ .21, SE ¼ .09, p < .05). Figure 1 shows a path diagram based on the results from estimating the

theoretical model with W1 data. As expected, buzz exposure was positively associated with attitude toward the campaign (B ¼ .10, SE ¼ .03, p < .01), which in turn was positively associated with attitude toward being physic- ally active (B ¼ .44, SE ¼ .15, p < .01), attitude toward eating fruit (B ¼ .37, SE ¼ .11, p < .001) and attitude toward eating vegetables (B ¼ .34, SE ¼ .11, p < .01), lending strong support for H3 and H4. Now, we turn to W2 data, which surveyed all intervention schools and

no comparison schools, to see if we can replicate the results in a new sam- ple. The path diagram based on the results is reported in Figure 2. The mediation model in W2 (n ¼ 467) was estimated with MLR that was

robust to nonnormality. Chi-square test of model fit is statistically signifi- cant in this sample, v2(3) ¼ 9.224, p < .05. However, this statistic is more likely to be significant when the sample size is large. The other model fit statistics demonstrate that the model fit the data reasonably well:

Figure 1. Mediation model for experimental schools in W1. �p < .05; ��p < .01; ���p < .001.

160 M. WANG AND A. STRUTHERS

RMSEA ¼ .067, CFI ¼ .976, SRMR ¼ .016. Note that RMSEA is slightly larger than the recommended threshold (Hu & Bentler, 1999). Having established overall model fit, we then turn to a review of the

effects of demographic and mass media campaign exposure variables. Grade in school was negatively associated with attitude toward the cam- paign (B ¼ �.10, SE ¼ .04, p < .05). Being male was also negatively associ- ated with attitude toward the campaign (B ¼ �.30, SE ¼ .08, p < .001), attitude toward eating fruit (B ¼ -.26, S.E. ¼ .08, p < .001) and attitude toward eating vegetables (B ¼ �.21, SE ¼ .10, p < .05), but positively associ- ated with attitude toward being physically active (B ¼ .31, SE ¼ .08, p < .001). Noticing the campaign website was positively associated with atti- tude toward being physically active (B ¼ .24, SE ¼ .09, p < .01). Figure 2 shows a diagram based on the results from estimating the theor-

etical model. Congruent with our theoretical propositions, buzz exposure was positively associated with attitude toward the campaign (B ¼ .10, SE ¼ .02, p < .001), which in turn was positively associated with attitude toward being physically active (B ¼ .23, SE ¼ .06, p < .001), attitude toward eating fruit (B ¼ .20, SE ¼ .06, p < .01), and attitude toward eating vegeta- bles (B ¼ .14, SE ¼ .07, p < .05). Hence, H3 and H4 were both supported by the W2 data as well. In sum, two cross-sectional datasets from two waves both buttressed our

campaign attitude mediation model.

Discussion

The unique design of the Whatcha doin? campaign during its first two years of implementation allowed us to assess the potential of peer-to-peer buzz marketing to effect health attitude change. Comparing campaign awareness between students who were exposed to

our buzz marketing intervention versus those who were not, we found modest success of our strategy. Having buzz agents embedded in schools to

Figure 2. Mediation model for W2. �p < .05; ��p < .01; ���p < .001.

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initiate different kinds of fun activities indeed made more students aware of the campaign. The effect size was quite substantial for awareness of the three issue topics. This demonstrates that school-based interventions, espe- cially coupled with a peer-to-peer buzz marketing strategy, can be quite effective in breaking through the information clutter that plagues commu- nication through mass media channels. This heightened awareness did not lead to significant differences in atti-

tudes toward any of the three health issues, however. In a classic persuasion process from awareness to attitudinal to behavioral change (Ajzen, 1991), our campaign was only able to penetrate the first level. Moreover, the per- centage of liking vegetables for each group significantly lagged behind the other two health issues. Given the disparity of agreement attitudes toward eating vegetables and doing the other two activities, we need to better understand how we can motivate teens to consume more vegetables. Future health campaigns targeting high school students are encouraged to focus on the issue of vegetable consumption since the acceptance level of the other two issues is already quite high. Its promise notwithstanding, school-based health programs are not always

successful. In another school-based trial study for obesity prevention, Living 4 Life, we also failed to find any significant differences in anthropometry and behavioral changes between intervention and comparison schools (Utter et al., 2011). The literature indicates that it is indeed hard to bring about health atti- tude and behavioral changes. A meta-analysis of 57 randomized controlled tri- als of obesity prevention programs targeting children and adolescents merely identified four primary studies reporting both statistically and clinically sig- nificant differences in health outcomes between intervention and comparison groups (Thomas, 2006). Hence, our results are largely consistent with the modest-effects results from other health campaigns (Utter et al., 2011). Consistent with our theorization, the campaign attitude mediation model

fit both waves of data nicely. As our model specifies, exposure to the buzz strategy led to more positive attitude toward the campaign, resulting in more favorable health attitudes toward the three campaign issues. This the- oretical model is significant in at least two ways. To begin with, it brings a macro dimension to the attitude toward the ad research. The majority of empirical studies testing this theory are micro-level research where the larg- est unit is usually an ad. By applying this theory in a campaign context, we show that the affect transfer process can be more pervasive and general. Moreover, our model lends further support to previous studies that showed liking for an ad can be transferred to not just brands, but also issues por- trayed in the ad (Nan, 2008). Our Whatcha doin? program has demonstrated that peer-to-peer buzz

marketing can break through the clutter and potentially affect health

162 M. WANG AND A. STRUTHERS

attitudes. Yet, some limitations still warrant attention. For instance, even though Whatcha doin? later became a statewide campaign up until 2013, we only surveyed the general student population in the very first two years of the program. Hence, the number of participating schools was not large, rendering the results susceptible to sample peculiarities. Absent panel data, we also were not able to test causality. In addition, even though attitude toward the ad theory (Shimp, 1981) and the theory of planned behavior (Ajzen, 1991) would suggest improved health attitudes lead to health behavioral changes, we were not able to extend our theoretical model to the behavioral dimension. Obesity as a public health issue is likely going to stay for years to come.

As students spend more time on social media and on their mobile devices, peer influence is not delimited by the school setting any more. Testing and extending the lessons from this study to the new information environment therefore is a promising and worthy agenda for health communication researchers to pursue.

Disclosure statement

No potential conflict of interest was reported by the author(s).

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