Assignment: Marketing and Communication Techniques for Health Care Products

When selecting marketing and communication techniques, health care organizations must carefully examine their consumer populations, as not all techniques are effective for all consumers. Depending on the product, organizations might even choose two or three different techniques in an effort to reach multiple consumer segments. For this Assignment, you examine the consumer populations of your organization and create an advertisement using marketing and communication techniques appropriate for your consumers.

To prepare:

We can write
your paper for you
100% original
24/7 service
50+ subjects

Select a health care product to market within your organization.

  • Identify the consumer population of your organization, including general and business consumer.
  • Consider traditional and/or contemporary marketing techniques that may be appropriate for your consumer population (i.e., brochure, flyer, video commercial, audio commercial, billboard, social media, etc.). Reflect on why you might select this technique and how you might use it to market the product.
  • With the marketing technique you select in mind, consider how you might create an advertisement to market the health care product and what communication techniques might be appropriate for your population.
  • The Assignment

    Write a 2-page brief that addresses the following:

  • Describe the health care product you selected.
  • Analyze the consumer population of your health care organization.
  • Recommend a marketing technique that is appropriate for your consumer population (i.e., brochure, flyer, video commercial, audio commercial, billboard, social media, etc.). Include why you selected this technique and how you will use it to market the product you selected.
  • Recommend one or two communication techniques that are appropriate for the consumer population.
  • Then, create an advertisement using the marketing technique you selected. Be sure to utilize communication techniques that would be appropriate for the consumer population you identified

    Journal of Health Communication, 18:20–40, 2013
    Copyright # Taylor & Francis Group, LLC
    ISSN: 1081-0730 print=1087-0415 online
    DOI: 10.1080/10810730.2012.688243
    Theory and Model Use in Social Marketing
    Health Interventions
    Nottingham University Business School, Nottingham, United Kingdom
    Institute of Public Communication and Education, Faculty of
    Communication Sciences, University of Lugano, Lugano, Switzerland
    The existing literature suggests that theories and models can serve as valuable
    frameworks for the design and evaluation of health interventions. However, evidence
    on the use of theories and models in social marketing interventions is sparse. The
    purpose of this systematic review is to identify to what extent papers about social
    marketing health interventions report using theory, which theories are most
    commonly used, and how theory was used. A systematic search was conducted for
    articles that reported social marketing interventions for the prevention or management of cancer, diabetes, heart disease, HIV, STDs, and tobacco use, and behaviors
    related to reproductive health, physical activity, nutrition, and smoking cessation.
    Articles were published in English, after 1990, reported an evaluation, and met the
    6 social marketing benchmarks criteria (behavior change, consumer research, segmentation and targeting, exchange, competition and marketing mix). Twenty-four
    articles, describing 17 interventions, met the inclusion criteria. Of these 17 interventions, 8 reported using theory and 7 stated how it was used. The transtheoretical
    model=stages of change was used more often than other theories. Findings highlight
    an ongoing lack of use or underreporting of the use of theory in social marketing
    campaigns and reinforce the call to action for applying and reporting theory to guide
    and evaluate interventions.
    Social and behavioral research on the role of theory in health campaigns suggests
    that it provides valuable frameworks to design and evaluate interventions (Glanz
    & Rimer, 2005; Hastings, 2007) and that effective campaigns tend to use theory
    (Lombardo & Léger, 2007; Thackeray & Neiger, 2000; Weinreich, 1999). ‘‘Theory’’
    was added to the Social Marketing Benchmark Criteria in 2006, a set of best practice
    guidelines for social marketing (French & Blair-Stevens, 2006). To date, reviews of
    social marketing initiatives have not addressed how or the extent to which theory
    is used in developing or evaluating social marketing campaigns (Evans, Blitstein,
    Hersey, Renaud, & Yaroch, 2008; Grilli, Ramsay, & Minozzi, 2002; Snyder et al.,
    2004; Stead, Gordon, Angus, & McDermott, 2007). Evidence on theory and model
    use in social marketing interventions is sparse (Lefebvre, 2000).
    Address correspondence to Nadina Raluca Luca, Nottingham University Business
    School, Jubilee Campus, Nottingham, United Kingdom NG8 1BB. E-mail: nadina_luca@
    Social Marketing Theory
    Social marketing is an approach to developing health, environment, and social
    change campaigns that aim to influence target audiences to voluntarily accept, reject,
    modify, or abandon a behavior for the benefit of individuals, groups, or society
    (Andreasen, 1995; Kotler & Lee, 2008). The social marketing process includes formative research, audience segmentation, development of a marketing mix (product,
    price, place, promotion), and an evaluation (Pirani & Reizes, 2005). The marketing
    mix is a key component that differentiates social marketing from other planning
    models and frameworks for health communication, education, or promotion initiatives aimed to facilitate change. The social marketing approach also relies on the
    appropriate use of behavioral theory to provide frameworks for developing initiatives by specifying the determinants of health behavior. By understanding these factors, intervention strategies can be developed that specifically address important
    theoretical constructs.
    One of the fundamental theories required in social marketing initiatives is the
    economic exchange theory. It postulates that human relationships are formed by
    the use of a subjective cost-benefit analysis and the comparison of alternatives.
    It is considered a core component in social marketing, is included in both published versions of the social marketing benchmark criteria (Andreasen, 2002;
    French & Blair-Stevens, 2006), and has considerable importance in developing
    the price and the product mix components (Hastings, 2007; Kotler & Lee, 2008).
    Exchange theory suggests that social marketers provide strong incentives emphasizing that the benefits of the product outweigh the costs (Kotler & Lee, 2008).
    Although it is fundamental in social marketing, a cost-benefit analysis alone does
    not create behavior change. Thus, social marketing also relies on the use of health
    behavior theory.
    In the most recent publication about the use of theory in social marketing, the
    most frequently cited include diffusion theory, the stages of change=transtheoretical
    model, social cognitive theory, theory of reasoned action, theory of planned behavior, health belief model, and protection and motivation theory (Lefebvre, 2000).
    Researchers have commonly reported using theory to develop the ‘‘promotion’’
    element of the marketing mix, although theory and models can provide useful insight
    to other elements of the social marketing mix with implications on the intervention
    design and measuring outcomes (Winett, 1995). The use of theory in social marketing health interventions should help social marketers identify whether a particular
    behavior is determined primarily by attitudinal, normative, self-efficacy, environmental or other social considerations, or a combination of these (Fishbein & Yzer,
    2003) and then to design the marketing mix to address these determinants.
    Lefebvre’s (2000) chapter published over a decade ago called for better reporting
    of the use of theory in social marketing activities. This systematic review seeks to
    learn if social marketers have answered that call by reporting the use of theories
    and models in social marketing health interventions. Thus, the purpose of this study
    is to review social marketing interventions aimed to change behaviors related to
    nutrition, physical activity, smoking, STDs=HIV=AIDS, heart disease, diabetes,
    and cancer, examining whether theses interventions reported the use of theory, which
    theory or theories they used, and how they used theory to design or evaluate the
    N. R. Luca and L. S. Suggs
    Data Source and Search Strategy
    We conducted a systematic search of peer-reviewed articles from March 1, 2009, to
    April 30, 2009. Bibliographic databases included the following: Cochrane Library;
    Wiley Interscience; Science Direct; PsycINFO; PubMed; Psychology and Behavioral
    Sciences Collection; Communication & Mass Media Complete; Library, Information
    Science & Technology Abstracts Publications; Communication Studies: A SAGE
    Full-Text Collection; Social Services Abstracts; Sociological Abstracts; ABI=Inform;
    Emerald Management Xtra; JSTOR.
    Search terms included the following: social marketing, systematic review, metaanalysis, intervention, strategy, marketing mix, campaign, theory, health communication, health promotion, model, nutrition, physical activity, reproductive health,
    STDs, tobacco, cancer, diabetes, heart disease, smoking, HIV, and AIDS.
    Inclusion/Exclusion Criteria
    Included articles were peer-reviewed English-language articles published between
    1990 and 2009 that described social marketing health interventions for the prevention or management of cancer, diabetes, heart disease, HIV, STDs and tobacco
    use, behaviors related to reproductive health, physical activity, nutrition, and smoking cessation. Included interventions met the 2002 social marketing benchmark criteria: behavior change, consumer research, segmentation and targeting, exchange,
    competition, and marketing mix (Andreasen, 2002). The studies reported at least
    three of the marketing mix components, or made them possible to clearly identify,
    and reported an evaluation. Two reviewers evaluated each article and coded them
    independently. Agreement of 100% was established before analyzing the data.
    Outcome Measures
    To synthesize the findings, the health issue addressed, setting, target audience, theory=
    model used, how theory was used, and reported outcomes for each initiative were coded.
    Characteristics of interventions and the use of theory are summarized and discussed.
    We initially retrieved 271 articles. After we removed ineligible and duplicate articles for
    this review, we identified 24 qualifying studies reporting 17 interventions (see Table 1).
    Health Topics and Target Audiences
    The most common behavioral focus of the 17 initiatives was nutrition (n ¼ 4), followed by diabetes (n ¼ 3) and STDs (n ¼ 3). Two initiatives focused on physical
    activity, two on HIV testing and prevention, and two on smoking behavior (one
    prevention and one cessation). One campaign focused on heart disease prevention.
    Nutrition interventions targeted community college students who were 24–32
    years old (Shive & Neyman Morris, 2006), school board members (McDermott
    et al., 2005), low-income students of public elementary schools (Wechsler, Basch,
    Social Marketing Theory
    Table 1. Interventions
    Energize Your Life!
    Intervention to promote
    low-fat milk selection
    in schools
    Food Friends
    Get Up and Do Something
    Control Your Diabetes.
    For Life
    Thunder and Lightning
    and Rain
    Move More Diabetes
    Heart Truth
    Style: Doing the Right
    The Healthy Talk
    The Healthy Penis
    HIV. Live With It. Get
    Think Again
    Listening to Reason
    I Am the Owner of Me
    Heart disease
    Shive and Neyman Morris
    McDermott et al. (2005)
    Wechsler et al. (1998)
    Young et al. (2004)
    Johnson et al. (2007)
    Wong et al. (2004)
    Huhman et al. (2007)
    Berkowitz et al. (2008)
    Berkowitz, Huhman, and
    Nolin (2008)
    Price et al. (2008)
    Heitzler et al. (2008)
    Peterson, Abraham, and
    Waterfield (2005)
    Gallivan et al. (2007)
    Almendarez, Boysun, and
    Clark (2004)
    Richert et al. (2007)
    Long et al. (2008)
    Wackett (1998)
    Cho et al. (2004)
    Montoya et al. (2005)
    Ahrens et al. (2006)
    Futterman et al. (2001)
    Lombardo and Léger (2007)
    De Gruchy and Coppel
    Schmidt, Kiss, and
    Lokanc-Diluzio (2009)
    Zyber, & Shea, 1998), and preschool children 3 to 5 years of age and their parents
    (Johnson, Bellows, Beckstrom, & Anderson, 2007; Young, Anderson, Beckstrom,
    Bellows, & Johnson, 2004). Diabetes initiatives targeted people with type 2 diabetes
    (Richert, Webb, Morse, O’Toole, & Brownson, 2007), older Latino=Hispanic men
    and women with uncontrolled diabetes (Almendarez, Boysun, & Clark, 2004), and
    adults with diabetes (Gallivan, Lising, Ammary, & Greenberg, 2007). STD
    N. R. Luca and L. S. Suggs
    interventions targeted toward 15–29-year-olds (Wackett, 1998), young Hispanic
    adults (Cho, Oehlkers, Mandelbaum, Edlund, & Zurek, 2004), and gay and bisexual
    individuals (Ahrens et al., 2006; Montoya et al., 2005). The two physical activity programs targeted children 9 to 13 years of age, parents, teachers, youth program leaders (Berkowitz et al., 2008; Berkowitz, Huhman, & Nolin, 2008; Heitzler, Asbury,
    & Kusner, 2008; Huhman et al., 2007; Price, Huhman, & Potter, 2008; Wong et al.,
    2004) and young adults 18–30 years of age (Peterson, Abraham, & Waterfield,
    2005). HIV=AIDS prevention and=or testing programs targeted HIV-positive and
    HIV-negative gay men who engage in unsafe sex practices (Lombardo & Léger,
    2007) and youth of color in high seroprevalence communities (Futterman et al.,
    2001). The smoking prevention intervention targeted youth 12–18 years of age
    (Schmidt, Kiss, & Lokanc-Diluzio, 2009) and the smoking cessation intervention targeted adults older than 40 years of age (De Gruchy & Coppel, 2008). The heart disease
    campaign targeted women 40–60 years of age with special focus on African American
    and Hispanic women (Long, Taubenheim, Wayman, Temple, & Ruoff, 2008).
    Theories and Models
    Eight initiatives mentioned using 10 theories and models (Berkowitz et al., 2008;
    Berkowitz, Huhman, & Nolin, 2008; De Gruchy & Coppel, 2008; Gallivan et al.,
    2007; Heitzler et al., 2008; Huhman et al., 2007; Johnson et al., 2007; Long et al.,
    2008; Peterson et al., 2005; Price et al., 2008; Richert et al., 2007; Wackett, 1998;
    Wong et al., 2004; Young et al., 2004; see Table 2). Some initiatives used more than
    one theory and some were not clear about how theory was used. For example, the
    heart disease awareness campaign (Long et al., 2008) reported using seven theories
    and models with no specifications on how they guided, informed, or were used to
    design and evaluate the campaign.
    The most frequently mentioned theories and models were stages of change
    (n ¼ 4) and the theory of planned behavior (n ¼ 3). The stages of change model
    was used for segmentation (Gallivan et al., 2007; Richert et al., 2007), evaluation
    (De Gruchy & Coppel, 2008), and message design (Gallivan et al., 2007), and
    reported as the transtheoretical model used to guide intervention development in
    two campaigns (Long et al., 2008; Richert et al., 2007). The theory of reasoned
    action and theory of planned behavior were reported together as guiding the design
    of physical activity and heart disease interventions (Long et al., 2008; Peterson et al.,
    2005). The theory of planned behavior, information processing theory, and social
    cognitive theory were reported to have guided the development and evaluation of
    VERB, a physical activity for youth, campaign (Berkowitz et al., 2008; Huhman
    et al., 2007; Price et al., 2008; Wong et al., 2004). Social network theory was used
    for promotion in a STD campaign (Wackett, 1998) and mentioned as basis for the
    heart disease intervention (Long et al., 2008). The health belief model was used
    for message design in a diabetes initiative (Gallivan et al., 2007) and as a basis for
    the heart disease awareness campaign (Long et al., 2008). Social learning theory
    was mentioned as basis for the message design in a nutrition intervention (Johnson
    et al., 2007; Young et al., 2004) and for guiding the intervention development in the
    heart disease initiative (Long et al., 2008). Information motivation and behavioral
    skills model was used in the development of promotion and message design in one
    STD intervention (Wackett, 1998). The use of diffusion of innovations theory was
    reported in the heart disease intervention (Long et al., 2008).
    Social network theory
    Social learning theory
    Social cognitive theory
    Diffusion of innovations
    Information motivation
    and behavioral skills model
    Information processing theory
    Theory of reasoned action
    Theory of planned behavior
    Health belief model
    Number of
    Stages of change model=
    transtheoretical model
    Theory or model
    Table 2. Frequency of theory=model use
    5: VERB (physical activity)
    11: Style: Do the Right Thing (sexually
    transmitted diseases)
    10: Heart Truth (heart disease)
    5: VERB (physical activity)
    4: Food Friends (nutrition)
    10: Heart Truth (heart disease)
    11: Style: Do the Right Thing (sexually
    transmitted diseases)
    10: Heart Truth (heart disease)
    7: Control Your Diabetes for Life (diabetes)
    10: Heart Truth (heart disease)
    6: Get Up and Do Something (physical
    10: Heart Truth (heart disease)
    5: VERB (physical activity)
    6: Get Up and Do Something (physical
    10: Heart Truth (heart disease)
    16: Listening to Reason (smoking cessation)
    7: Control Your Diabetes for Life (diabetes)
    9: Move More Diabetes (diabetes)
    10: Heart Truth (heart disease)
    Campaign design; evaluation
    Promotion, message, campaign design
    Campaign design
    Campaign design; segmentation evaluation
    Promotion, message design
    Campaign design
    Campaign design
    Message design
    Campaign design
    Campaign design; evaluation
    Campaign design
    Campaign design; segmentation, evaluation
    Campaign design; evaluation
    Campaign design
    Segmentation and evaluation
    Campaign design, segmentation and messages
    Campaign design
    How used
    N. R. Luca and L. S. Suggs
    Interventions used a variety of study designs and outcome measures (see Table 3).
    Campaign awareness was high (more than 50%) for the majority of interventions
    with some exceptions: 11% for a diabetes program (Richert et al., 2007) and
    23.2% for a smoking cessation program (De Gruchy & Coppel, 2008).
    Nutrition interventions reported positive outcomes including a statistically significant improvement of school board members’ support for four of seven proposed
    nutrition policy options (12%, 14.2%, 14.7%, 11.8%, p < .5; McDermott et al., 2005), and a significant change from pre- to postintervention in typical fruit intake (t ¼ 3.4, p < .01; Shive & Neyman Morris, 2006). Another found a significant change in low-fat milk consumption of inner-city elementary students in the intervention group (25% preintervention vs. 57% postintervention; F(1) ¼ 48.02, p < .01; Wechsler et al., 1998). A nutrition program based on social learning theory found a significant decrease in preschool-aged children’s dislike of new foods from preintervention to postintervention (p < .08) in the intervention group, whereas the control group showed statistically significant increase in their dislike of new foods at follow-up (p < .10; Johnson et al., 2007). The outcomes reported by diabetes interventions indicate positive changes, although none were statistically significant. One intervention that used the transtheoretical model and health belief model showed an increase of blood glucose tests from 39% at baseline to 55% postintervention (Gallivan et al., 2007). One program that did not mention using theory suggested that 27% of those who saw the campaign reported having taken some type of action to control their diabetes and that 54 of 750 targeted Latinos with uncontrolled diabetes made calls to a toll-free line (Almendarez et al., 2004). The third diabetes program, which used stages of change for segmentation purposes, reported making contact with 750 people living with diabetes and 176 referrals to diabetes self-management services (Richert et al., 2007). The heart disease intervention, based on seven theories and models (Long et al., 2008), found that 45% would talk to their doctor and=or get a check-up, but did not measure behavior change. The Get Up and Do Something physical activity intervention (Peterson et al., 2005) discussed that although they did not measure behavior change, they did evaluate the effect of the campaign on attitudes, perceptions, and intention to be more active. Attitudes and intention, both constructs in the theory of planned behavior and theory of reasoned action, were claimed to be positive (27.7% intended to be more active). However, no data regarding attitudes were reported nor were preintervention intention data reported. The VERB campaign reported a statistically significant dose-response effect of tweens exposure to VERB (c ¼ 0.19, CI [0.11, 0.26]; d ¼ 15.4, CI [8.1, 22.8], p < .05) regarding physical activity (Huhman et al., 2007). The tobacco control intervention, Listening to Reason, used stages of change for segmentation and evaluation and indicated no significant behavior change (De Gruchy & Coppel, 2008). The smoking prevention campaign, I Am the Owner of Me, did not report having used theory and reported no significant behavior change (Schmidt, Kiss, & Lokanc-Diluzio, 2009). A statistically significant decrease in knowledge about condoms being a preventive action against STDs was reported in one intervention developed on two theories (Wackett, 1998; 63.1% preintervention, 51.5% postintervention, p < .01), but this intervention also found a statistically significant increase in knowledge that one 27 1 ID Pilot study, school-based 2-month intervention to promote fruit intake Type of intervention Students 24–32 years of age at two California community colleges Target audience N=A Theories= models and how used Table 3. Interventions, theories=models, and outcomes Quasi-experimental (intervention group and control group) preintervention= postintervention Evaluation design Campaign awareness: 72.3% Behavior change: (a) Typical fruit intake: intervention group ¼ 1.7= 2.1 (preintervention= postintervention), t ¼ 3.4 ; control group ¼ 1.8=2.0 (preintervention= postintervention), t ¼ 0.90; intervention versus control postintervention t ¼ 0.4; (b) Previous day fruit intake: intervention group ¼ 1.5=1.8 (preintervention= postintervention), t ¼ 2.0 ; control group ¼ 1.6=1.9 (preintervention= postintervention), t ¼ 1.0; intervention group versus control group postintervention t ¼ 0.1 Outcomes (Continued ) N=A Notes about theories and outcomes 28 Regional campaign, communitywide intervention aimed to place school nutrition policies on policy agenda and change beliefs of school board members toward need for good nutrition policy School-based (six schools in one city [three 2 3 ID Type of intervention Table 3. Continued Low-income, inner-city students of School board members Target audience N=A N=A Theories= models and how used Preintervention= postintervention; (intervention Preintervention= postintervention Evaluation design Behavior change: Low-fat milk consumption: intervention group ¼ 25% Statistically significant change in board support for the following: banning fast food in elementary school, a-la-carte food sales in elementary schools, banning fast food sales in all schools, banning a-la-carte sales in
    all schools
    No significant changes in
    the following: providing
    healthy food options,
    establishing minimum
    nutritional standards,
    limiting food and soda
    ads, locating soda
    machines in lightly trafficked areas, banning fast
    food sales, banning ads,
    increasing cost of vending
    machine foods and sodas
    Notes about
    theories and
    Pilot study,
    intervention to
    promote eating
    new fruits and
    groups; three
    aimed to
    increase uptake
    of low-fat milk
    versus whole
    milk during
    children 3–5
    years of age
    Theory of planned
    Social learning
    longitudinal study
    group vs. control
    Campaign awareness:
    children ¼ 81%, in 2004;
    Attitude change: Refusals
    to try new food:
    intervention group ¼ 28
    (preintervention), 1
    (postintervention) ;
    control group ¼ 6
    (preintervention) versus
    10 (postintervention)
    Decrease in dislike
    of new foods from
    preintervention to
    postintervention: intervention group (p < .08) Increase in dislike of new foods at follow-up: control group (p < .10) (preintervention), 57% (postintervention), F(1) ¼ 48.02 ; control group ¼ 28% (preintervention), 28% (postintervention) (Continued ) Campaign developed on a Social learning theory supported developmental learning skills 30 Regional, 13-week media campaign aimed at encouraging physical activity National campaign aimed at 7 communitywide intervention to promote daily physical activity 6 ID Type of intervention Table 3. Continued Adults with diabetes Young adults 18–30 years of age children (9–13 years of age) Secondary audience: parents, teachers, youth program leaders Target audience Transtheoretical model (messages, segmentation, Theory of reasoned action (campaign design and evaluation); theory of planned behavior (campaign design and evaluation) (campaign design, segmentation, evaluation); social cognitive theory (campaign design, segmentation, evaluation); information processing theory (campaign design and evaluation) Theories= models and how used Longitudinal postinterventions Postintervention Evaluation design Campaign awareness: 58% in 2001; 50% in 2002 A1C test awareness: 31% Campaign awareness: 62.5% (5%) Behavior change: 27.7% intended to be more active, 22.9% talked with someone about it parents ¼ 34% in 2003, 55% in 2005 ; effect size ¼ 0.02 to 0.07 Behavior change: dose-response effect of exposure to VERB and physical activity (c ¼ 0.19, CI [0.11, 0.26]) Outcomes Segmentation of priority populations, Favorable cognitive impact on attitudes, perceptions, and intent to be more active (theory of reasoned action=theory of planned behavior) logic model based on theory Notes about theories and outcomes 31 Regional (one U.S. state), communitywide campaign aimed to increase awareness of diabetes Regional in one U.S. state, communitywide campaign 8 9 raising awareness about controlling diabetes People with type 2 diabetes who engaged in some physical Latino adults 40–65 years of age with uncontrolled diabetes The transtheoretical model (segmentation) N=A campaign design); health belief model (messages) Longitudinal (lay health educators network) and postintervention Postintervention Longitudinal: over 3 years established lay health educators network of 35 people; 750 contacts with Respondents: 54 members of the target population (TA) and 447 without diabetes (other) Campaign message recall: all ¼ 29.2% Campaign slogan name awareness: TA ¼ 7 5%, other ¼ 50% Behavior change: Took any action as a result of the ads: 27% of all who saw ads on TV, 32.7% of all who heard ads on radio; 32.5% of all who saw or heard ads on radio, TV, or print (1998), 59% (2003) Behavior change: Daily blood glucose testing: 39% (1997), 55% (2002); A1C testing (of those aware of it): 61% (1999), 69% (2000), 71% (2001) N=A N=A (Continued ) consistent messages 32 10 ID National, communitywide campaign aimed at increasing awareness of heart disease in women and to encourage women to talk with their doctor, learn their risk, and take action to lower it aimed at promoting physical activity and improving selfmanagement for people with type 2 diabetes and to establish a lay health educator network Type of intervention Table 3. Continued All women 40–60 years of age, special focus on African Americans and Hispanics activity but wanted to do more; community members to serve as lay health educators Target audience Health belief model, theory of reasoned action= planned behavior, social learning theory, transtheoretical model, diffusion of innovations theory, social network theory (all: campaign design) Theories= models and how used The 1997, 2000, 2003, 2005, 2006 longitudinal national surveys (campaign launched in 2002) (people with type 2 diabetes) Evaluation design Campaign awareness: of red dress ¼ 25% (2005); saw, heard, or read information about heart disease: 81% (2005); that heart disease is the number one killer of women: all women: 1997 ¼ 30%, 2000 ¼ 34%, 2003 ¼ 46%, 2006 ¼ 57%; African Americans: 1997 ¼ 15%, 2006 ¼ 31%; Hispanics: 1997 ¼ 20%, 2006 ¼ 29%; Caucasians: 1997 ¼ 33%, 2006 ¼ 68% diabetics; 176 referrals to self-management services Postintervention: 11% campaign awareness Outcomes N=A Notes about theories and outcomes 33 Regional 3-month campaign to reduce rates of chlamydia infection in the Yukon Statewide media campaign aimed at reducing 11 12 Young adults 18–24 years of age; young Hispanic adults Young adults 15–29 years of age N=A Information motivation behavioral skills model (campaign design, promotion, message); social network theory (campaign design, promotion) Postintervention pilot evaluation Preintervention= postintervention No specific data available; positive association between campaign exposure and Hispanic Campaign awareness: 53% Awareness of chlamydia symptoms: 29% (preintervention), 49.5% (postintervention) Knowledge of preventive actions: use condoms: 63.1% (preintervention), 51.5% (postintervention) ; abstinence: 18.3 (preintervention), 14.9% (postintervention); get tested before sex: 20.5% (preintervention), 28.4% (postintervention) Behavior change: screening tests increased by 15% from previous year Engagement: 45% would talk to their doctor and= or get a check-up Behavior change: concluded awareness leads to self-reported behavior change yet reported no behavior change data N=A (Continued ) A theory-based intervention: better knowledge outcomes (data also show that knowledge about protective practices decreased after campaign) 34 City, communitywide campaign aimed at changing the community norm about testing for syphilis and increasing awareness and knowledge about syphilis Six cities, communitywide campaign aimed to promote HIV testing 14 unintended pregnancy and STDs 13 ID Type of intervention Table 3. Continued Adolescents of color Gay and bisexual individuals 18–24 years of age Target audience N=A N=A Theories= models and how used Before, during, and after campaign test, cross-sectional Two longitudinal postinterventions (6 months and 2.5 years after campaign) Evaluation design Campaign awareness: 90% Behavior change: calls to hotline: 2,774; HIV tests: 3,737 Campaign awareness: 80% (6 months), 85% (2.5 years) Behavior change: 6 months: campaign awareness associated with 90% increase in likelihood for having tested for syphilis in the past 6 months: OR ¼ 1.9 (95% CI [1.3– 2.9]) 2.5 years: campaign awareness associated with 76% increase in likelihood for testing: OR ¼ 2.1 (95% CI [0.9–5.2], p ¼ .10) adults’ belief in importance of talking with partner, intention to speak with partner and to have talked with partner Outcomes N=A N=A Notes about theories and outcomes 35 City campaign aimed at reducing smoking Citywide 12-week campaign aimed at denormalizing tobacco use 16 17  p < .05.  p < .01. N=A ¼ not available. National, 6-week campaign aimed at decreasing new HIV infections 15 Youth 12–18 years of age who had experimented with tobacco products Smokers older than 40 years of age in contemplation and preparation stage who lived in most deprived areas of city HIV-positive and HIV-negative gay men who engage in unsafe sex practices N=A Stages of change model (segmentation, evaluation) N=A Preintervention= postintervention evaluation of first 6 weeks of campaign Postintervention Postintervention Campaign awareness: campaign slogan ¼ 60%; saw or heard ads on TV or radio: 52% Behavior change: no significant behavior change Campaign awareness: 27 of 116 (23.2%) clients at stop smoking service had seen campaign; 12 of 116 clients tried quitting as a result of campaign Campaign awareness: 79% Behavior change: 76% reported rethinking sexual practice; 48% changed something about their sex practices N=A Evaluation only with those in the action stage excluded people in other stages that might have been influenced by the campaign No indication of the explicit use of any theory to develop campaign; Suggested the use of theory to design the campaign might have improved outcomes 36 N. R. Luca and L. S. Suggs should be tested for STDs before having intercourse (20.5% preintervention, 28.4% postintervention, p < .05). Neither of the two HIV campaigns reported using theory. The HIV testing campaign (Futterman et al., 2001) implemented in six cities reported 2,774 calls to their hotline and administering 3,737 HIV tests, which peaked during the ‘‘get tested week’’ part of the campaign at 462 tests, up from 93 in the first week of the campaign. Results of an intervention aimed to decrease new HIV infections that did not use theory (Lombardo & Léger, 2007) showed that 76% of those surveyed reported they would rethink their sexual practices and 48% suggested that they had changed something about their sexual behaviors. The Healthy Penis syphilis campaign reported a significant (p ¼ .10) increase in likelihood for testing (OR ¼ 2.1; 95% CI [0.9–5.2]) 2.5 years after the campaign (Ahrens et al., 2006; Montoya et al., 2005). Six interventions discussed the association of the use of theory and the campaign outcomes. A nutrition intervention (Johnson et al., 2007; Young et al., 2004) credited the use of social learning theory with the development of learning new skills in their target population. A physical activity intervention (Berkowitz et al., 2008; Berkowitz, Huhman, & Nolin, 2008; Huhman et al., 2007; Price et al., 2008; Wong et al., 2004) emphasized the positive role of theory of planned behavior, social cognitive theory, and information processing theory in developing intervention strategies and designing the evaluation. A diabetes control intervention using the stages of change model and the health belief model (Gallivan et al., 2007) indicated the segmentation of priority populations and consistent messages as contributing to the intervention success (an increase of blood glucose tests from 39% at baseline to 55% during intervention). A STD intervention using the information motivation behavioral skills model and the social network theory to guide the design of the intervention targeting youth (Wackett, 1998) reported that the use of theory was related to knowledge outcomes. However, for the three knowledge outcomes reported, only one was positive. Two articles described possible limitations related to theory use. The authors of one of the HIV=AIDS articles suggest that based on evidence of effective, theory-driven campaigns, it was unfortunate that theory was not used (Lombardo & Léger, 2007). They provide several examples of how the health belief model, theory of planned behavior, and the transtheoretical model could have helped the campaign developers to design a stronger campaign that better addressed the determinants of unsafe sex practices of HIV-positive individuals. The smoking cessation intervention (De Gruchy & Coppel, 2008) did not report significant behavior change and suggested that choosing groups from specific stages of change for the evaluation might have resulted in the omission of relevant outcomes in individuals in other stages. Discussion This study adds updated evidence regarding the acknowledged gap in social marketers’ use of theory. Of the 17 interventions included, 8 reported using theory and 7 stated how it was used, with varied levels of specificity. Since Lefebvre (2000) called for better reporting of the use of theory in social marketing activities, we have progressed very little. The frequency of stages of change or the transtheoretical model (n ¼ 4) in guiding the intervention and=or, more specifically the message or evaluation design, is Social Marketing Theory 37 consistent with the literature that supports the popularity of this model among social marketers. The model was applied to design messages for people in different stages of change in diabetes (Gallivan et al., 2007; Richert et al., 2007) and smoking cessation (De Gruchy & Coppel, 2008) interventions, as well as to guide the development of the heart disease initiative. Although social cognitive theory is considered an updated version of social learning theory, two interventions reported using social learning theory and one used social cognitive theory. The authors of the two articles reporting the use of social learning theory suggested that it provided useful insight in developing a nutrition intervention (Johnson et al., 2007; Young et al., 2004) that targeted preschool children in order to help them learn to experience new foods. In addition, a theoretical framework consisting of the theory of planned behavior, social cognitive theory, and information processing theory was mentioned for a physical activity intervention (Berkowitz et al., 2008; Berkowitz, Huhman, & Nolin, 2008; Huhman et al., 2007; Price et al., 2008; Wong et al., 2004) with a possible effect on the positive outcomes reported. The information motivation behavioral skills model was used for promotion and message design in a STD intervention addressing chlamydia (Wackett, 1998) that reported positive and negative knowledge outcomes. Overall, the findings illustrate that the available information on if, and then how, theory and models are used to develop social marketing campaigns is not reported with adequate details. The data suggest that theory was rarely used to guide the development of campaigns, and when campaigns did use theory, they often did not clearly describe how theory was used. One article discusses the lack of theory, highlighting that the campaign (Lombardo & Léger, 2007) was atheoretical despite the evidence showing that ‘‘effective campaigns tend to utilize the principles of health behavior change theories in all phases of campaign design, including formative research, message design, and evaluation’’ and provide numerous citations to support this claim (Lombardo & Léger, 2007, p. 387). Conclusion The purpose of this systematic review was to investigate the extent to which articles about social marketing health interventions report using theory, which theories are used, and how theory guided the development and evaluation of initiatives. The findings highlight a lack of use and sufficient reporting of health behavior theory in social marketing campaigns. This could be a result of an absence of theoretically driven initiatives or a lack of reporting on how theory and models are used. This review found similar results as one conducted a decade ago (Lefebvre, 2000) and thus reinforces the call to action for better reporting and=or the use of theory to guide interventions. In 2006, behavioral theory was established as a social marketing benchmark criterion in an updated version of Andreasen’s 2002 benchmarks (French & Blair-Stevens, 2006). Hence, theory is officially integrated as a core component of the social marketing process and existing evidence supports the use of theory and its connection with well-design effective initiatives (Thackeray & Neiger, 2000; see also Lombardo & Léger, 2007). Thus, it is perplexing that the majority of initiatives in this review did not use or clearly report the use of theory. Perhaps using a social marketing approach to change this behavior among social marketers is warranted. This means making use of the field concepts and tools in order to encourage social marketers to incorporate theories and models in their interventions and thoroughly report on the process. Better marketing of the need 38 N. R. Luca and L. S. Suggs for using behavior theories and models in social marketing would emphasize the contribution that their use can bring to a social marketing intervention. The benefits include resourceful instruments for intervention design and evaluation that can be applied to various settings, target audiences, and health topics. This article serves as an initial step in that direction by highlighting the lack of current use of theory and calling for more appropriate use and thorough reporting of the use of behavioral theory in social marketing activities. Developing interventions that use theory and report its implications would help answer this call and contribute to the evidence-based progress of the field. References Ahrens, K., Kent, C. K., Montoya, J. A., Rotblatt, H., McCright, J., Kerndt, P., & Klausner, J. D. (2006). Healthy penis: San Francisco’s social marketing campaign to increase syphilis testing among gay and bisexual men. PLoS Medicine, 3, e474. doi: 10.1371= journal.pmed.0030474 Almendarez, I., Boysun, M., & Clark, K. (2004). Thunder and lightning and rain: A Latino= Hispanic diabetes media awareness campaign. Family & Community Health, 27, 114–122. Andreasen, A. R. (1995). Marketing social change: Changing behavior to promote health, social development, and the environment. San Francisco, CA: Jossey-Bass. Andreasen, A. R. (2002). Marketing social marketing in the social change market place. Journal of Public Policy and Marketing, 21(1), 3–13. Berkowitz, J. M., Huhman, M., Heitzler, C. D., Potter, L. D., Nolin, M. J., & Banspach, S. W. (2008). Overview of formative, process, and outcome evaluation methods used in the VERBTM Campaign. American Journal of Preventive Medicine, 34(6 Suppl), S222–S229. Berkowitz, J. M., Huhman, M., & Nolin, M. J. (2008). Did augmenting the VERBTM Campaign advertising in select communities have an effect on awareness, attitudes, and physical activity? American Journal of Preventive Medicine, 34(6 Suppl), S257–S266. Cho, H., Oehlkers, P., Mandelbaum, J., Edlund, K., & Zurek, M. (2004). The Healthy Talk family planning campaign of Massachusetts: A communication-centered approach. Health Education, 104, 314–325. De Gruchy, J., & Coppel, D. (2008). Listening to reason: A social marketing stop-smoking campaign in Nottingham. Social Marketing Quarterly, 14(1), 5–17. Evans, D., Blitstein, J., Hersey, J. C., Renaud, J., & Yaroch, A. L. (2008). Systematic review of public health branding. Journal of Health Communication, 13, 721–741. Fishbein, M., & Yzer, M. C. (2003). Using theory to design effective health behavior interventions. Communication Theory, 32, 164–183. French, J., & Blair-Stevens, C. (2006). Social marketing national benchmark criteria. London, United Kingdom: UK National Social Marketing Centre. Futterman, D. C., Peralta, L., Rudy, B. J., Wolfson, S., Guttmacher, S., Smith Rogers, A., & the Project Access Team of the Adolescent Medicine HIV=AIDS Research Network (2001). The ACCESS (Adolescents Connected to Care, Evaluation, and Special Services) project: Social marketing to promote HIV testing to adolescents, methods and first year results from a six city campaign. Journal of Adolescent Health, 29(Suppl), 19–29. Gallivan, J., Lising, M., Ammary, N. J., & Greenberg, R. (2007). The National Diabetes Education Program’s ‘‘Control Your Diabetes. For Life.’’ campaign: Design, implementation, and lessons learned. Social Marketing Quarterly, 13, 65–82. Glanz, K., & Rimer, B. K. (2005). Theory at a glance. A guide for health promotion practice (2nd ed.). Bethesda, MD: National Institutes of Health, The National Cancer Institute. Grilli, R., Ramsay, C., & Minozzi, S. (2002). Mass media interventions: Effects on health services utilization. Cochrane Database of Systematic Reviews, 1, CD000389. doi: 10.1002=14651858.CD000389 Social Marketing Theory 39 Hastings, G. (2007). Social marketing: Why should the Devil have all the best tunes? Oxford, United Kingdom: Butterworth Heinemann. Heitzler, C. D., Asbury, L. D., & Kusner, S. L. (2008). Bringing ‘‘play’’ to life: The use of experiential marketing in the VERBTM Campaign. American Journal of Preventive Medicine, 34(6 Suppl 1), S188–S193. Huhman, M. E., Potter, L. D., Duke, J. C., Judkins, D. R., Heitzler, C. D., & Wong, F. L. (2007). Evaluation of a national physical activity intervention for children: VERBTM Campaign, 2002–2004. American Journal of Preventive Medicine, 32(1), 38–43. Johnson, S. L., Bellows, L., Beckstrom, L., & Anderson, J. (2007). Evaluation of a social marketing campaign targeting preschool children. American Journal of Health Behavior, 31(1), 44–55. Kotler, P., & Lee, N. (2008). Social marketing influencing behaviors for good. Los Angeles, CA: Sage. Lefebvre, R. C. (2000). Theories and models in social marketing. In P. N. Bloom & G. T. Gundlach (Eds.), Handbook of marketing and society (pp. 506–519). Newbury Park, CA: Sage. Lombardo, A. P., & Léger, Y. A. (2007). Thinking about ‘‘Think Again’’ in Canada: Assessing a social marketing HIV=AIDS prevention campaign. Journal of Health Communication, 12, 377–397. Long, T., Taubenheim, A. M., Wayman, J., Temple, S., & Ruoff, B. A. (2008). The Heart Truth: Using the power of branding and social marketing to increase awareness of heart disease in women. Social Marketing Quarterly, 14(3), 3–29. McDermott, R. J., Berends, V., McCormack Brown, K., Agron, P., Black, K. M., & Pitt Barnes, S. (2005). Impact of the California Project LEAN school board member social marketing campaign. Social Marketing Quarterly, 11(2), 18–40. Montoya, J. A., Kent, C. K., Rotblatt, H., McCright, J., Kerndt, P. R., & Klausner, J. D. (2005). Social marketing campaign significantly associated with increases in syphilis testing among gay and bisexual men in San Francisco. Sexually Transmitted Diseases, 32, 395–399. Peterson, M., Abraham, A., & Waterfield, A. (2005). Marketing physical activity: Lessons learned from a statewide media campaign. Health Promotion Practice, 6, 437–446. Pirani, S., & Reizes, T. (2005). The Turning Point Social Marketing National Excellence Collaborative: Integrating social marketing into routine public health practice. Journal of Public Health Management Practice, 11, 131–138. Price, S. M., Huhman, M., & Potter, L. D. (2008). Influencing the parents of children aged 9–13 years: Findings from the VERBTM Campaign. American Journal of Preventive Medicine, 34(6 Suppl 1), S267–S274. Richert, M. L., Webb, A. J., Morse, N. A., O’Toole, M. L., & Brownson, C. A. (2007). Move more diabetes: Using lay health educators to support physical activity in a communitybased chronic disease self-management program. The Diabetes Educator, 33(Suppl 16), 179S–184S. Schmidt, E., Kiss, S. M., & Lokanc-Diluzio, W. (2009). Changing social norms: A mass media campaign for youth ages 12–18. Canadian Journal of Public Health, 100(1), 41–45. Shive, S. E., & Neyman Morris, M. (2006). Evaluation of the Energize Your Life! social marketing campaign pilot study to increase fruit intake among community college students. Journal of American College Health, 55(1), 33–39. Snyder, L. B., Hamilton, M. A., Mitchell, E. W., Kiwanuka-Tondo, J., Fleming-Milici, F., & Proctor, D. (2004). A meta-analysis of the effect of mediated health communication campaigns on behavior change in the United States. Journal of Health Communication, 9(Suppl 1), 71–96. Stead, M., Gordon, R., Angus, K., & McDermott, L. (2007). A systematic review of social marketing effectiveness. Health Education, 107, 126–191. 40 N. R. Luca and L. S. Suggs Thackeray, R., & Neiger, B. L. (2000). Establishing a relationship between behavior change theory and social marketing: Implications for health education. Journal of Health Education, 31, 331–335. Wackett, J. (1998). A theory based initiative to reduce the rates of chlamydia trachomatis infection among young adults in Yukon. The Canadian Journal of Human Sexuality, 7, 347–356. Wechsler, H., Basch, C. E., Zyber, P., & Shea, S. (1998). Promoting the selection of low-fat milk in elementary school cafeterias in an inner-city Latino community: Evaluation of an intervention. American Journal of Public Health, 88, 427–433. Weinreich, N. K. (1999). Hands-on social marketing: A step-by-step guide. Thousand Oaks, CA: Sage. Winett, R. A. (1995). A framework for health promotion and disease prevention programs. American Psychologist, 50, 341–350. Wong, F., Huhman, M., Heitzler, C., Asbury, L., Bretthauer-Mueller, R., McCarthy, S., & Londe, P. (2004). VERBTM—A social marketing campaign to increase physical activity among youth. Preventive Chronic Disease, 1(3), 1–7. Young, L., Anderson, J., Beckstrom, L., Bellows, L., & Johnson, S. (2004). Using social marketing principles to guide the development of a nutrition education initiative for preschool-aged children. Journal of Nutrition Education and Behavior, 36, 250–257. Copyright of Journal of Health Communication is the property of Routledge and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. Curr Obes Rep (2015) 4:37–45 DOI 10.1007/s13679-014-0128-5 ETIOLOGY OF OBESITY (T GILL, SECTION EDITOR) New Media but Same Old Tricks: Food Marketing to Children in the Digital Age Bridget Kelly & Stefanie Vandevijvere & Becky Freeman & Gabrielle Jenkin Published online: 10 January 2015 # Springer Science+Business Media New York 2015 Abstract ‘New media’ refers to digital technologies, which offer unmatched opportunities for food companies to engage with young people. This paper explores the emergence of food marketing using new media, the potential impact of this marketing on young people, and current and potential policy responses to limit exposure to these promotions. Foremost in any informed policy discussion is the need for robust evidence to demonstrate the need for intervention. In this case, such evidence relates to the extent of children’s exposures to commercial food promotions via new media, and the nature of these promotions. Approaches to, and challenges of, collecting and assessing these data are discussed. There is accumulating evidence that food marketing on new media is increasing and influences children’s food preferences and choices. The impact of integrated campaigns, which reinforce commercial messages across multiple platforms, and of new media, which engage personally with potential consumers, is likely to be greater than that of traditional marketing. This article is part of the Topical Collection on Etiology of Obesity B. Kelly (*) Early Start Research Institute, School of Health and Society, University of Wollongong, Wollongong, Australia e-mail: S. Vandevijvere Department of Epidemiology and Biostatistics, School of Population Health, University of Auckland, Auckland, New Zealand e-mail: B. Freeman School of Public Health, The University of Sydney, Sydney, Australia e-mail: G. Jenkin Social Psychiatry and Population Mental Health Research Unit, University of Otago, Wellington, New Zealand e-mail: Keywords Food . Beverage . Marketing . Digital media . New media Introduction ‘New media’ is by definition an ever-changing paradigm, although in current marketing contexts it refers to digital technologies, including the Internet and mobile devices. These technologies are characterised by interactivity, virtuality, globalisation and many-to-many communication [1]. The use of this media for marketing purposes has allowed companies to share unprecedented volumes of product information, enabled highly segmented target markets and customisation of messages, and redesigned advertising to encompass communication, education, and entertainment [2]; blurring the line between commercial and non-commercial content. The advancement of the web from static sites to a social and participatory space has further provided opportunities to engage potential consumers with personal communications, and enabled the co-creation of brand messages through user-generated content (e.g. comments, blogs, videos) [3]. New media marketing includes promotions on company-owned and third-party websites (not owned by the company), social media, email, and marketing via mobile devices through text messages, applications (apps), and branded games. Mobile devices also allow advertising messages to be context-aware, by linking with location tracking software [4]. Contemporary media environments are characterised by these rapidly evolving interactive digital platforms, which are integrated with more traditional forms of advertising, including television, radio and print media [5]. This creates a plethora of media opportunities and a saturation of marketing messages, particularly 38 when these channels are used concurrently by users as part of media ‘multi-tasking’ (moving between and across platforms simultaneously). The use and reach of new media is vast. Data on 12-17 year olds in the USA from 2012 estimated that 95 % used the Internet, and 81 % used some form of social media, and most commonly Facebook [6]. A survey of 25,142 9—16 year olds from 25 European countries in 2010 found that 59 % of Internet users had their own social network site profile [7]. The rise in use of social media is not confined to young people. Almost three-quarters of online US adults used social networking in 2014 [8]. Mobile phone ownership is also substantial, with 91 % of people globally owning a mobile phone, half of which are ‘smart’ or Internet-enabled [9]. The rapid spread of social media and mobile technology into society has been paralleled by the use of these platforms for commercial marketing purposes [10]. Industry data from the US clearly demonstrate this changing emphasis on new media for food and beverage marketing, particularly in communications directed at young people. In a comparison of industry marketing expenditure using data obtained by the Federal Trade Commission (FTC), while television remained the largest source of marketing expenditure between 2006 and 2009, only marketing on new media experienced an increase in expenditure over this time [5]. By 2009, expenditure on new media food marketing had overtaken radio and print advertising, and in-store marketing and packaging [5]. Notably, estimates of the biggest advertising spenders on Facebook in 2013 included Nestle, Coca-Cola, Starbucks and Mondelez/ Kraft [11]. Marketing on many new media platforms is relatively low in cost [7], for example, the cost of maintaining a social media page compared to advertising placement on television. Therefore, comparisons of marketing expenditure do not indicate absolute exposures to these messages on different media. At odds with this increasing use of new media as a platform for marketing communications, most research examining the extent of children’s exposure to food marketing has focused on traditional media, and specifically television. So too, policy discussions and provisions for limiting young people’s exposure to, and the impact of, marketing of unhealthy food has related primarily to reducing the extent and power of television advertising [5]. This narrow approach means that young people’s true exposure to commercial messages for unhealthy food and beverages is sizeably underestimated and public policy arrangements have limited effectiveness. Children are a prime target of commercial marketers because of their independent spending power, influence on household purchases and potential as lifelong brand consumers [12]. Arguments for the protection of children against this marketing have centred on marketing’s contribution to the commercialisation of childhood and the development of unhealthy behaviours, including poor dietary habits in the case Curr Obes Rep (2015) 4:37–45 of food marketing. Children are seen to be particularly vulnerable to marketing’s influences due to their relatively immature cognitive ability to process and interpret commercial messages, and this is particularly the case for those younger than eight years [13]. Even adolescents and young adults, however, are vulnerable to marketing effects, and marketers exploit their susceptibility to social pressures through peer-topeer marketing, such as on social media [14]. This paper aims to explore the potential impact of new media food and beverage marketing on young people’s diets, and to identify current and potential policy responses to limit children’s exposure to these promotions. These media are now embraced for commercial promotions by most food companies and yet are relatively unstudied. Identifying approaches for measuring the extent of young people’s exposure to new media food marketing and the nature of these promotions is necessary to highlight the extent of this issue, and for informing policy development. This review does not extend to the use of new media for good nutrition promotion, although approaches used by commercial marketers could be adopted in social marketing initiatives to promote healthy food choices. Impact of new Media Marketing on Food Preferences and Behaviours Social learning theory is one of the major theories linked to the development of cognitive and behavioural patterns related to consumer behaviour. Social learning theory emphasises the influence of ‘socialisation agents’ in transmitting norms, attitudes, motivations and behaviours to the learner [15, 16]. Such an agent can include the media and also children’s peers [17], through which learning takes place as part of social interaction [15]. In the case of new media, viral communication of commercial messages through social media may contribute to peer-group acceptance and sharing of products, with both media and peers acting synergistically as part of this socialisation model. The effect of commercial food marketing on children has been explained as following a conceptual hierarchy of responses, ranging from impacts on brand awareness, preferences, purchases and ultimately consumption and postconsumption effects, including diet and weight outcomes [18, 19]. When exposure to marketing is sustained over time, and when promoted foods are primarily energy-dense, nutrient poor, this marketing can lead to poor diets, energy imbalance and weight gain. Much of the research to support these responses to food marketing have examined the effect of television advertising on children, as well as of branding generally, such as on packaging [18]. There is less evidence on the impacts of new media food marketing, although it is hypothesised that new media could have a greater impact on Curr Obes Rep (2015) 4:37–45 these outcomes for the following reasons. Firstly, new media facilitates peer endorsement of, and personal communications with, brands [20]. Secondly, children have been found to have much lower recognition of advertisements on webpages than they would for identifying spot advertising on television at the same age [21]. Developmentally, the recognition of advertisements is the first step in understanding the persuasive intent of these messages and in developing a critical response [21]. The lack of explicit advertising cues in some forms of new media, such as for advertising embedded within online games, or whole webpages that are designed to promote a brand, further increase difficulty in recognising advertising content [22••]. Thirdly, some of the more immersive forms of new media, such as branded online gaming, engage children for extended periods of time [23]. The diversification of messages into new media also allows for further integration of commercial messages across multiple media platforms, which independently influence children’s responses, and also reinforce each other to magnify responses [24]. Fourthly, sophisticated web analytics and surveillance now allow marketers to monitor interactions and social relationships online, and to test and precisely refine their messages and approach for maximum impact [25•]. Lastly, parents are likely to be less aware of food marketing on new media [24], thereby reducing the potential for any moderating effects from caregivers, through discussion of marketing intent and messages. Ultimately the persuasive power of food marketing via new media is greater than via traditional marketing because of all these factors. A small number of studies have measured the impact of new media food marketing across a spectrum of attitudinal to behavioural impacts. Most of these studies are experimental trials that have assessed the impacts of branded online gaming (‘advergaming’). In the main, these trials have identified that children’s exposure to advergames positively impacts on perceived traits of products and product preferences [23, 26], and on actual food choice and consumption [27, 28]. In an Australian survey of 5-8 year olds (n=477), older children who were exposed to an advergame promoting Kellogg’s Froot Loops as more rewarding than fruit (earned more points in the arcade-style game) were significantly more likely to report preferring Froot Loops to other cereals, compared with children who did not play the game (65 % vs. 35 %, P

    Place your order
    (550 words)

    Approximate price: $22

    Calculate the price of your order

    550 words
    We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
    Total price:
    The price is based on these factors:
    Academic level
    Number of pages
    Basic features
    • Free title page and bibliography
    • Unlimited revisions
    • Plagiarism-free guarantee
    • Money-back guarantee
    • 24/7 support
    On-demand options
    • Writer’s samples
    • Part-by-part delivery
    • Overnight delivery
    • Copies of used sources
    • Expert Proofreading
    Paper format
    • 275 words per page
    • 12 pt Arial/Times New Roman
    • Double line spacing
    • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

    Our guarantees

    Delivering a high-quality product at a reasonable price is not enough anymore.
    That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

    Money-back guarantee

    You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

    Read more

    Zero-plagiarism guarantee

    Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

    Read more

    Free-revision policy

    Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

    Read more

    Privacy policy

    Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

    Read more

    Fair-cooperation guarantee

    By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

    Read more
    Live Chat+1(978) 822-0999EmailWhatsApp

    Order your essay today and save 20% with the discount code LEMONADE