Investigating the Role of Brand Equity in Predicting the Relationship Between Message Exposure and Parental Support for Their Child’s Physical Activity

Abstract

Social marketing researchers have identified brand equity as a potential mediator of the relationship between campaign message exposure and resulting behavior. This study examined whether message exposure and components of brand equity contribute to overall brand equity changes over the course of a 12-month campaign evaluation. In addition, we examine whether brand equity consistently accounts for covariance (i.e., mediation) in the relationship between message exposure and parental support (PS). Data were drawn from ParticipACTION’s “Think Again” campaign evaluations that targeted parents, specifically moms, with children between the ages of 5 and 11 years (three independent samples: March 2011, N = 702 [T1]; September 2011, N = 706 [T2]; March 2012, N = 670 [T3]). Univariate analyses of variance were used to examine changes in message exposure and components of brand equity over time, while structural equation modeling was used to examine the brand equity model relationship. Findings revealed that message exposure was greatest at T3 (ps < .01) and that brand equity was greatest at T2 (ps < .05). Model fit statistics revealed modest to good fit. Results demonstrated that Think Again message exposure was related to brand equity (standardized effects .10–.28) and that brand equity was related to PS (standardized effects .30–.40; (ps < .01). Importantly, an indirect effect of message exposure on PS through brand equity (standardized effects .03–.09) emerged in all models (ps < .05). This study demonstrates the utility of branding social marketing campaigns to increase campaign effectiveness.

Keywords

brand equity public health branding parental support health messaging health promotion

Introduction

Public health branding can add value to the product, service, or lifestyle being promoted by building a relationship between consumers and the branded objects (Evans & Hastings, 2008). A key outcome of branding is brand equity, a set of associations that consumers form with a brand that can either add to, or subtract from, the value of a brand (Aaker, 1996; Evans & Hastings, 2008; Keller, 1993). ParticipACTION, a nonprofit organization dedicated to promoting and supporting active living, recently executed a branded social marketing campaign targeting parents to promote children meeting the physical activity guidelines. It is unknown whether parents’ ParticipACTION brand equity was important in determining whether or not they engaged in parental support (PS) for child physical activity as a result of seeing the campaign ads. As such, parents’ ParticipACTION brand equity, as well as their exposure to campaign ads, was assessed at different time points across the life of the campaign. In addition, how ParticipACTION brand equity relates to parents’ complying with campaign messages was evaluated.

Background and Literature

Physical activity participation is associated with physical and mental health benefits for children (Janssen & LeBlanc, 2010). Unfortunately, only a small proportion of children are meeting the guidelines of 60 min of moderate-to-vigorous physical activity each day (Colley et al., 2011; Janssen & LeBlanc, 2010). Parents have a critical role in helping increase child physical activity, given that PS is positively related to child physical activity (Gustafson & Rhodes, 2006; Yao & Rhodes, 2013). PS refers to parent behaviors that may facilitate or enable children to engage in physical activity (e.g., offering encouragement, facilitating participation by providing transportation, and access to equipment). It is necessary to find ways to effectively persuade parents to engage in such support behaviors as a means of increasing child physical activity.

Recognizing the important role of parents in promoting child physical activity, national physical activity promotion agencies in Canada and the United States have started targeting parents with their campaigns. In Canada, ParticipACTION challenged parents to Think Again in their campaign aiming to raise awareness of child inactivity. Similarly in the United States, the Center for Disease Control targeted parents and children in the VERB campaign and demonstrated an increase in children’s free-time physical activity after 1 year (Huhman et al., 2005; Huhman et al., 2010). Parental awareness of VERB was associated with positive attitudes, beliefs toward physical activity, and social support behaviors (Price, Huhman, & Potter, 2008). Thus, mass media can be effective when targeting parents to engage in PS behaviors. As child inactivity continues to be a public health concern, discovering how to make these messages more effective is of interest and importance.

Brand equity has emerged as a worthy concept to investigate when considering audience behavior change. In product marketing, brand equity has been related to greater brand preferences, brand purchase intentions (Cobb-Walgren, Ruble, & Donthu, 1995), and brand loyalty (Taylor, Celuch, & Goodwin, 2004). In the case of health and social marketing, people may be more likely to act in line with campaign goals, for example, when they perceive the organization behind the campaign as credible and trustworthy.

Brand equity has been evaluated in public health brands in the contexts of antismoking (Evans, Price, & Blahut, 2005), substance use prevention (Lee & Hecht, 2011), condom use for HIV/AIDS prevention (Evans, Taruberekera, Longfield, & Snider, 2011), and physical activity, respectively (Price, Potter, Das, Wang & Huhman, 2009). In general, greater brand equity was related to greater intentions to engage, or engagement, in the behaviors promoted by the campaigns (Evans et al., 2005; Evans et al., 2011; Lee & Hecht, 2011; Price et al., 2009). The analysis of the VERB brand demonstrated that increased brand equity in tweens (age 9–13 years) was associated with increased positive attitudes toward physical activity and greater participation in free-time physical activity (Price et al., 2009). This suggests that brand equity may be important when considering the promotion of physical activity to a target audience. To our knowledge, what role brand equity may play in promoting PS for child physical activity has not been investigated.

When investigating the role of brand equity in a social marketing campaign, it is important to consider and evaluate the core components of brand equity: brand loyalty, perceived quality (PQ)/leadership, association/differentiation, awareness, and market behavior (Aaker, 1996). Aaker (1996) emphasizes that the components that will provide the best indicator of brand equity should be considered based on the context. The components of brand equity relevant to public health branding assessed in the current investigation include (1) brand awareness: the presence of the brand’s product (behavior) in the audience’s mind, (2) PQ: envisioning the functional brand benefits, (3) leadership and popularity (L&P): rating the brand compared to others for promoting that public health initiative, (4) organizational associations (OA): how the audience links the brand with the behavior, and (5) brand personality (BP): the associations the audience has with the brand (Evans & Hastings, 2008). By evaluating a variety of the components of brand equity, the current study will conceptualize a clear vision of brand equity in the context of physical activity promotion branding.

Evans and Hastings (2008) suggest that brand equity may act as a mediator between campaign message exposure and the outcome behavior advocated by the campaign. This relationship was observed in the evaluation of the truth^® campaign for antismoking (Evans et al., 2005); however, a similar relationship has not been examined in the context of physical activity social marketing campaigns targeting parents directly. Testing this proposed framework for brand equity may provide more insight on how brand equity works, and whether it is relevant, in public health campaigns encouraging parents to engage in behaviors supporting child physical activity. Situated in the context of the ParticipACTION Think Again campaign, the purpose of the current investigation was 2-fold. One objective was to observe whether message exposure and brand equity components that contribute to overall brand equity changed over the course of a 12-month campaign evaluation. We hypothesize that as the life of the campaign progresses, these would have increased. In addition, we examined whether brand equity consistently accounts for covariance (i.e., mediation) in the relationship between campaign message exposure and PS behavior at three different time points across the campaign. We hypothesized that this relationship would emerge at each evaluation time point. We did not examine change in PS behavior because these data are reported elsewhere (Gainforth et al., in preparation).

Method

Study Design

This was a cross-sectional study with different cohorts of participants being surveyed at three different time points of the Think Again campaign.

Participants

Data were collected by Angus Reid Public Opinion, a hired vendor, at three different time points; March 2011 (T1), September 2011 (T2), and March 2012 (T3). At each time point, a new nationally representative cohort of participants was recruited (T1, n = 712; T2, n = 706; T3, n = 694) from a panel of consumers (N = 120,000 Canadian adults) who agreed to answer research surveys in return for small compensation. The eligibility criterion for the current investigation included being a parent of at least one child between the ages of 5 and 11 years. The ages of the children used to determine participants’ eligibility for parents relate to the information requested by ParticipACTION regarding their target consumers for the campaign.

Measures

Demographics

Parents reported their province of residence, gender, employment status, household income, and education.

Message exposure

Message exposure was indicated for two ads from the Think Again campaign shown in the evaluation process. After viewing each ad, participants were asked, “Approximately how many times have you seen this ad on television” followed by an open-ended response option for each ad.

Brand equity

Aaker (1996) suggests the “Brand Equity Ten” which is a framework comprised of 10 measures that together can be used to assess the components of brand equity. Individual ParticipACTION brand equity measures were developed based on the communication, messaging, and behavioral goals of the Think Again campaign. These items are similar to those recommended by Evans and Hastings (2008) for public health brands and similar to the types of questions used to assess brand equity for the truth^® and VERB campaigns (Evans et al., 2005; Price et al., 2009). Ten items in total were used to assess these components of brand equity. The component measures are described.

Brand awareness

One item assessing brand recognition, B_recognition, and one assessing brand recall, B_recall, were used to determine whether parents were aware of the ParticipACTION brand. The B_recognition item asked participants to indicate their familiarity with ParticipACTION as an organization on a 3-point scale; 1 = never heard of it, 2 = know little about it, or 3 = know a lot about it. For B_recall, participants were asked to name up to 10 organizations that promote physical activity. Participants who listed ParticipACTION received a score of 1; participants who did not name ParticipACTION received a score of 0. B_recognition and B_recall were assessed prior to viewing campaign ads.

Perceived Quality (PQ)

Participants rated their agreement (1 = strongly disagree to 4 = strongly agree) with the following statements: (a) “ParticipACTION is the best organization to represent the importance of physical activity” and (b) “ParticipACTION does an excellent job of raising awareness about issues related to physical inactivity.”

Leadership and popularity (L&P)

Participants rated their agreement (1 = strongly disagree to 4 = strongly agree) with the following statements: (a) “ParticipACTION is the national voice of physical activity and sport participation in Canada” and (b) “ParticipACTION is providing national leadership to move people to move more.”

Organizational associations (OA)

Participants rated their agreement (1 = strongly disagree to 4 = strongly agree) with the following statements: (a) “ParticipACTION is trustworthy,” (b) “ParticipACTION has an impact that matters,” and (c) “ParticipACTION is making a difference.” Cronbach’s αs were .85, .86, and .84 for T1, T2, and T3, respectively.

Brand personality (BP)

Participants rated their agreement (1 = strongly disagree to 4 = strongly agree) with the following statement: “ParticipACTION is bold in its approach.”

Parental support (PS) for child physical activity

Eight items were used to assess PS for child physical activity. Participants were asked to complete the phrase, “As a result of seeing these ads on television have you done any of the following? Please check all that apply.” The options presented were (a) set goals for how much activity my child/children will get each day of the week, (b) planned a time when my child/children can be active, (c) enrolled my child/children in an organized physical activity or sport, (d) made stricter rules for my child/children with regard to time spent on sedentary activities (e.g., watching TV, playing video games, etc.), (e) talked to my child/children about being more active, (f) looked for opportunities to be active as a family, (g) talked to my spouse or partner about encouraging my child/children to be more active, and (h) started doing more physical activity myself and/or as a family. Responses were made by checking yes (1) or no (0). A composite score was created using the sum of the 8 behavioral items. This measure reflects methods of PS in the literature as well as the behavioral outcome goals of the social marketing campaign (Biddle & Goudas, 1996; Gustafson & Rhodes, 2006; Trost et al., 2003).

Think Again Campaign Messages

The advertisements used in this study to determine message exposure were the “soccer” and “swimming” 15-s versions from ParticipACTION Canada’s Think Again campaign (see http://www.participaction.com/about/our-campaigns/ to view the advertisements). The advertisements are targeted to moms with children between the ages of 5 and 11 years and feature the same take-home message, “Fact is, kids need at least 60 minutes of physical activity per day. Every day” (see Berry et al., 2014, for more detail). When viewed on television, the ParticipACTION brand logo appears with the take-home message at the end. When shown to participants in this study, the advertisements were unbranded.

Procedure

The Think Again campaign was launched in January 2011 and the television ads used in the current study were aired on television in three waves (January–March 2011; June–August 2011; January–March 2012). At the end of each wave, members of an Angus Reid consumer panel were recruited to view unbranded examples of two advertisements from the campaign and to complete a survey. The research team was not involved in the data collection or selecting the study sample of participants. Data collection was completed online. This study was approved by the Queen’s University General Research Ethics Board.

Data Analysis

Data analysis was completed using Statistical Package for the Social Sciences (SPSS) Software Version 20 (IBM, Armonk, NY) and linear structural relations (LISREL) 8.71 Software (Scientific Software International, Lincolnwood, IL). Participants who indicated they had technical difficulties with at least one of the videos were excluded from the analysis. Due to the large sample size, skewness and kurtosis values were not estimated to assess normality (Field, 2009). Outliers, defined as having z-scores where z = ±3.29, were sought out for each continuous variable. Outliers were replaced to one unit above or below the cutoff (Tabachnick, Fidell, & Osterlind, 2001). Multiple imputation was employed to account for missing data (Allison, 2002). Univariate analyses of variance (ANOVAs) with Bonferroni post hoc testing were used to analyze the study objective of changes in model indicators of brand equity and message exposure across the three campaign evaluations. Structural equation modeling with maximum likelihood estimation and a variance/covariance matrix was used to examine the indirect effect of brand equity on PS in the model across the three independent data sets. As described in the Measures section, two factors (viewed Video 1, viewed Video 2) loaded into message exposure, six factors (B_recall, B_recognition, PQ, L&P, OA, and BP) composed of 10 items loaded into brand equity, and for PS, the single factor (PS) loaded with a fixed error estimate of 1 α to provide a conservative estimate of measurement error. The first indicator of all concepts in the model was also fixed to 1.0 in order to create a metric scale. The structural model depicts message exposure predicting brand equity, which has an indirect effect on PS. See Figure 1 for this structural equation model that was tested at each of the evaluation time points.

Results

Participants

Of the parents recruited for T1 (n = 712), T2 (n = 706), and T3 (n = 694), 1.4% (n = 10), 6.9% (n = 49), and 3.5% (n = 24) were, respectively, excluded because they indicated they could not see or hear at least one of the campaign advertisements. The remaining parents for T1 (n = 702), T2 (n = 657), and T3 (n = 670) were included in the analyses. Demographic information is presented in Table 1.

Table 1.

Participant Characteristics.

Demographic Characteristic	March 2011	September 2011	March 2012
Gender, % (n)
Male	7.1 (50)	5.8 (38)	9.3 (62)
Female	92.9 (652)	94.2 (619)	90.7 (608)
Province, % (n)
Ontario	42.9 (301)	42.0 (276)	38.8 (260)
Quebec	14.7 (103)	22.4 (147)	24.8 (166)
British Columbia	15.0 (105)	11.7 (77)	13.6 (91)
Other	27.4 (193)	23.9 (157)	24.7 (185)
Education, % (n)
Completed high school	10.3 (72)	7.5 (49)	11.8 (79)
Completed college	25.9 (182)	28.0 (184)	27.0 (181)
Completed university	25.2 (177)	25.6 (158)	24.9 (167)
Employment status, % (n)
Employed full time	42.3 (297)	44.0 (289)	48.4 (324)
Employed part time	17.4 (122)	17.2 (113)	14.0 (94)
Other	40.3 (283)	38.8 (255)	37.6 (252)
Household income, % (n)
Less than US$100,000	61.4 (431)	63.9 (420)	60.9 (409)

ANOVA Results

Results from the ANOVAs indicated that there were significant differences in message exposure and brand equity over time. Levene’s test statistic was significant in several of the ANOVAs, thus violating the assumption of homogeneity of variance. However, in large sample sizes, this often occurs even with small differences in group variances (Field, 2009). The variance ratio was used to assess homogeneity of variance and it was deemed acceptable in each case.

Message exposure

Significant differences in message exposure were seen across time points for both ads, F(2, 2026) = 18.39, p < .01 and F(2, 2026) = 15.18, p < .001, respectively. Pairwise comparisons revealed that for both ads participants in the T3 cohort had greater message exposure than participants at T2 (ps < .01, ds > .15) and at T1 (ps < .001, ds > .29). No other differences were observed. See Table 2 for descriptive statistics.

Table 2.

Factor Loadings for the Three Brand Equity Models.

	Mean (SD)			Factor Loading
	T1	T2	T3	T1	T2	T3
Message exposure
Seen Video 1	3.47 (4.07)	4.39 (7.37)	5.91 (10.02)	1.00	.97	1.00
Seen Video 2	2.88 (3.95)	3.70 (7.02)	4.95 (9.18)	0.89	.84	0.87
Brand equity
PQ	2.96 (.64)	3.15 (.61)	2.99 (.61)	.93	.90	.91
L&P	3.07 (.63)	3.22 (.62)	3.09 (.60)	.89	.91	.91
BP	2.76 (.77)	3.04 (.74)	2.79 (.71)	.90	.71	.79
OA	3.07 (.60)	3.23 (.57)	3.09 (.56)	.92	.91	.90
B_recognition	2.21 (.57)	2.23 (.53)	2.14 (.56)	.40	.34	.34
B_recall	0.23 (.42)	0.35 (.48)	0.23 (.42)	.22	.13	.15

Note. SD = standard deviation; PQ = perceived quality; L&P = leadership and popularity; BP = brand personality; OA = organizational associations.

Brand equity

Significant differences in all components of brand equity were observed across time points for PQ, F(2, 2026) = 17.64, p < .001; L&P, F(2, 2026) = 10.72, p < .001; OA, F(2, 2026) = 15.71, p < .001; BP, F(2, 2026) = 28.77, p < .001; brand recall, F(2, 2026) = 17.31, p < .001; and brand recognition, F(2, 2026) = 4.83, p < .01. Pairwise comparisons revealed that participants in the T2 cohort had significantly greater PQ, L&P, OA, BP, and brand recall than participant cohorts at T1 (ps = .001; ds = .30, .24, .27, .37, and .27, respectively) or at T3 (ps = .001; ds = .41, .21, .25, .35, and .27, respectively). Participants in the T3 cohort had significantly lower brand recognition than participants at T1 (p = .03; d = .12) or T2 (p = .01; d = .17). No other differences were observed.

Prediction Model Testing

Model fit statistics reflect reasonable to good data fit for each of the models at T1, χ²(25, N = 702) = 272.57; p < .01. Comparative fit index (CFI) = .89; root mean square error of approximation (RMSEA) = .16, T2, χ²(25, N = 657) = 127.79; p < .01. CFI = .97; RMSEA = .08, and T3, χ²(25, N = 670) = 254.10; p < .01. CFI = .93; RMSEA = .12, respectively (Hu & Bentler, 1999). Of concern are the high RMSEA values at T1 and T3, which traditionally indicate reasonable errors of approximation (Hu & Bentler, 1999). However, it has been suggested that this cutoff is based largely on intuition and has little statistical reasoning (Marsh, Hau, & Wen, 2004; McDonald & Marsh, 1990). Any improvements in model fit would have to come from adjustments to the brand awareness measures (brand recognition and brand recall). Observation of the standardized residuals suggested that no simple and sensible modifications to the model would improve fit. Most of the misfit was from a series of small correlated error and structural disturbance terms or cross-loadings.

The measurement estimations of the three models are presented in Table 2 with depictions of the individual models in Figures 2 –4. Overall factor loadings at all three time points were found to be significant (ps < .01). Factor loadings ranged from .22 to 1.00, .13 to .97, and .15 to 1.00 for T1, T2, and T3, respectively. All factors loading into brand equity aside from the brand awareness measures (B_recall and B_recognition) had standardized effects ranging from .89 to .93, .71 to .91, and .78 to .91 for T1, T2, and T3, respectively.

Message exposure was found to significantly predict brand equity with standardized effects of .28, .16, and .10 at T1, T2, and T3 respectively (ps < .01). Brand equity was found to significantly predict PS with standardized effects of .32, .40, and .30 at T1, T2, and T3 respectively. All models demonstrated a significant indirect path from message exposure to PS through brand equity. The standardized indirect effect of message exposure on PS through brand equity was .09 (p < .01), .06 (p < .05), and .03 (p < .05) for T1, T2, and T3, respectively. Models at T1 and T2 also showed a significant direct pathway from message exposure to PS with standardized effects of .17 and .25, respectively (ps < .01). The models accounted for 8%, 3%, and 1% of the variance in brand equity and 16%, 25%, and 9% of the variance in PS at T1, T2, and T3, respectively.

Discussion

The first objective of this study was to observe whether there were any changes in message exposure or brand equity over the life of the Think Again campaign. It should be reiterated that the same participants were not observed at the three time points and as a result, these trends are population wide. Significant differences in all indicators across time points were observed. Specifically, message exposure was significantly lower at T1 and T2 than at T3. All brand equity components were significantly lower at T1 than at T2 and were significantly higher in T2 than in T3. This suggests brand equity was highest at T2 approximately 9 months after the campaign launch allowing adequate time for parents to be exposed to the campaign. The discordance between high message exposure and lower brand equity at T3 versus T2 may be indicative of ad overexposure at T3. Ad “wearout,” which occurs when exposure to an ad no longer has a significant effect or has a negative effect, has been documented in the literature (Pechmann & Stewart, 1988). Although the relationship between message exposure and brand equity remained significant and positive at T3, the standardized effects indicate a smaller association between these variables than at T1 and T2. As such, at T3, the ads may have been approaching “wearout” leaving message exposure to be less influential on brand equity. Research examining optimal ad exposure is needed.

The second objective of this study was to establish how brand equity is related to the exposure to campaign advertisements and the desired outcome behavior of increasing PS for child physical activity. The results demonstrated that both message exposure and PS were related to brand equity directly and indirectly. Parents who had higher campaign message exposure reported higher ParticipACTION brand equity. Parents with higher brand equity also reported engaging in more PS behaviors. Importantly, brand equity was found to account for covariance in the relationship between message exposure and PS, suggesting a potential mechanism for brand equity in improving the effectiveness of social marketing campaigns.

The brand equity model findings were consistent with our stated hypothesis, were replicated over the evaluation period, and were similar to other studies (Evans et al., 2005; Evans et al., 2011; Lee & Hecht, 2011; Price et al., 2009). Brand equity accounted for covariance between ad message exposure and PS. As aforementioned, this prediction model was observed in the truth^® campaign where brand equity was seen to mediate the relationship between message exposure and not smoking (Evans et al., 2005). There is an implicit causal hypothesis that accompanies the brand equity mediation finding (Evans & Hastings, 2008). Consumers see branded advertisements and form positive and strong associations with a brand. This brand equity drives the consumer to act in line with the brand’s promotions (Evans & Hastings, 2008). Considering the current investigation, parents who saw the ads may have developed this positive association with ParticipACTION, which in turn made them more likely to act in line with the PS behaviors promoted by ParticipACTION. The current study extends existing findings on public health brand equity, as the targeted outcome behavior does not impact the health outcome of the individual targeted directly by the brand (i.e., the parents’ physical activity). Instead, their behavior may impact the health outcomes of their children. Thus, brand building and brand equity development are important in promoting behaviors to a target segment even when the direct benefits are not involving this group.

The most evident implication of our findings is that branding public health physical activity campaigns and building brand equity with target consumers may in fact increase the effectiveness of the campaign by motivating behavior change. This is emphasized by the medium sized model effects, indicating brand equity may have an observable impact on the outcome behavior. More importantly, this phenomenon may occur when promoting behaviors where the main benefit is indirectly related to that target group. Future research should investigate how public health organizations can effectively invest resources to build brand equity, as it may help make social marketing campaigns more effective. In addition, throughout the life of a campaign, brand equity may peak in the target population after an appropriate viewing time. Brand equity may be highest when all aspects of brand equity are strongest including brand awareness. Ensuring that message exposure is initiated and maintained throughout the campaign life may help aid in keeping brand equity strong to support continued engagement in outcome behaviors.

This study is not without limitations. Because the parents being assessed were not the same at each time point, the ability of data to be compared over time is limited. As such, we are unable to conclude that message exposure and brand equity increased over time, although this was the population trend observed. Future research should aim to replicate this study using a repeated measures design, where the same participants are being tracked over time to accurately gauge behavior change. We also could not account for confounding variables such as seasonal variation—T1 and T3 evaluations were conducted following the winter months, whereas the T2 evaluation was conducted following summer months. Poor weather affects parents’ support of physical activity (Dwyer, Needham, Simpson, & Heeney, 2008) and may have affected the credibility of the Think Again ads at T1 and T3. Additionally, child physical activity was not assessed in this study. The literature supports the link of PS and child physical activity (Gustafson & Rhodes, 2006; Yao & Rhodes, 2013); however, PS was the outcome behavior of interest. Despite these limitations, this study has several strengths. First, the sample was nationally representative and purposefully sampled the target audience of the Think Again campaign. Second, three data sets were analyzed that spanned the duration of the social marketing campaign. As such, changes in key indicators can be observed over time. This study also demonstrates good external validity as the social marketing campaign was real and developed for the purpose of getting parents to engage in PS to increase child physical activity.

Conclusion

This study demonstrated that parents’ ParticipACTION brand equity and exposure to Think Again campaign messages changed over the life of the campaign. Importantly, parents with greater brand equity who were exposed to campaign ads were more likely to engage in PS behaviors. The implication of these findings is that branding public health physical activity campaigns and building brand equity with target consumers may make campaigns more effective in motivating behavior change.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

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