Running head: Social marketing Physical Activity Campaigns in Adults
Effectiveness of Social Marketing Campaigns to Promote Physical Activity in Adults:
A Systematic Review
Yuan Xia
A Thesis Proposal
Submitted to the School of Graduate Studies of the University of Lethbridge
In Partial Fulfillment of the Requirements for the Degree
Master of Science (MSc) in Management
Faculty of Management
University of Lethbridge
© Yuan Xia, 2013
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Running head: Social marketing Physical Activity Campaigns in Adults
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Abstract
Obesity has become a severe public health issue and its consequences lead to severe
health disorders and economic hardships. Reduced levels of physical activity is a major
contributor to the epidemic and as a result promoting physical activity is an important
strategy in the battle to prevent obesity and promote public health. Social marketing
framework as a behavior change tool is compatible with the psychological states of the
target audience (adults, in our case) and what managers of a physical activity intervention
want to achieve. However, it is not known whether social marketing strategy promotes
physical activity. The present study will perform a systematic review of published studies
to assess effectiveness of physical activity interventions that employed a social marketing
framework and provide recommendations to social change managers to improve future
interventions.
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Table of Contents
Introduction .............................................................................................................. 4
Literature Review ..................................................................................................... 6
Increasing Prevalence and Trends of Adult Obesity in the World .....................................6
Impacts of Obesity ............................................................................................................9
Causes of Obesity ............................................................................................................ 11
The Role of Physical Activity in Obesity Prevention and Long-term Weight Loss
Maintenance ................................................................................................................... 17
How Much Physical Activity Is Enough for Body-Weight Regulation? ........................... 21
Target Audience of Physical Activity Interventions ........................................................ 23
Why Social Marketing .................................................................................................... 25
Social Marketing Benchmarks ........................................................................................ 29
Behavior. ................................................................................................................................ 29
Customer Orientation. ............................................................................................................ 31
Theory. ................................................................................................................................... 32
Insight. ................................................................................................................................... 33
Exchange. ............................................................................................................................... 34
Competition............................................................................................................................ 35
Segmentation.......................................................................................................................... 36
Marketing Mix. ...................................................................................................................... 38
Funding and Partnership ........................................................................................................ 40
Evaluating Effectiveness of A Physical Activity Intervention .......................................... 40
Objectives of the Study ........................................................................................... 42
Method .................................................................................................................... 42
Key Words and Inclusion Criteria .................................................................................. 43
Article Data Extraction ................................................................................................... 44
Data Analysis .................................................................................................................. 44
Contributions .......................................................................................................... 45
Timeline .................................................................................................................. 45
Budget ..................................................................................................................... 45
References ............................................................................................................... 47
Appendix 1 Data Extraction Form .......................................................................... 57
Appendix 2 Data Extraction Codebook ................................................................... 59
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Introduction
Obesity epidemic has become a worldwide health issue that needs attention from
governments and nongovernmental organizations. The prevalence of adult obesity has
reached an alarming level in the world (Flegal et al., 2012; Tjepkema, 2005; Berghofer et
al., 2008; Ma et al., 2005). Obesity not only leads to other severe health disorders, such
as resistance and hyperinsulinemia, type-2 diabetes, hypertension, dyslipidemia, coronary
heart disease, gallbladder disease, cancer, and early mortality (Pi-Sunyer, 2002), but also
creates enormous economic burden for both government health systems and individuals
(Withrow and Alter, 2010).
Existing literature suggests that physical activity has a significant role in reversing
obesity epidemic and maintaining general health. Researchers observed that motorized
transportation (Bassett, et al., 2008; Bell et al., 2002), low level of leisure-time physical
activity (Abu-Omar and Rutten, 2008), and high level of “screen time” (Banks et al.,
2010) are associated with obesity. A dose-response effect of physical activity on weight
loss and long-term weight maintenance is found through randomized, controlled trials
(Jeffery et al., 2003; Wing and Phelan, 2005). Because of the decreasing level of physical
activity (Brownson, 2004) and the significant role of physical activity in weight loss,
weight control, and general health, it is recommended that adults should practice 30
minutes of moderate exercise 5 times per week to maintain general health (World Health
Organization), 60-90 minutes of moderate exercise per day to prevent weight regain
(Saris et al., 2003), and 45-60 minutes of moderate exercise per day to prevent transition
from overweight to obese (Saris et al., 2003).
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Social marketing is “a process that applies marketing principles and techniques to
create, communicate, and deliver value in order to influence target audience behaviors
that benefit society (public health, safety, the environment, and communities) as well as
the target audience” (Kotler and Lee, 2008, p. 7). Since social marketing frame is
compatible with what managers in a physical activity campaign want to achieve, it seems
reasonable to put social marketing efforts to promote physical activity. While some
amount of research has been conducted to review effectiveness of social marketing
programs promoting health behaviors (Stead et al., 2007; McDermott et al., 2005), past
studies have not assessed effectiveness of social marketing efforts independently, so the
field remains generally under-researched.
The purpose of the present study is to systematically review evidence on efforts to
promote physical activity among adults and to assess these studies within a social
marketing framework. We believe that the present study will provide recommendations to
improve future physical activity campaigns and to contribute to social marketing theory.
The rest of the proposal report is presented as follows. The report will first discuss
the extent of obesity epidemic around the world, and later consequences and causes of
obesity. Among causes of obesity, physical activity plays a central role. As a result, the
report will focus on efforts to understand the role of physical activity in obesity
prevention and weight control and discuss recommendations by health experts to observe
adequate levels of physical activity. Later the report will discuss levels of audience
members to target, argue why social marketing should be employed as a social change
tool to promote physical activity, and what social marketing principles should be
employed to conduct an effective social marketing campaign. In the final pages, the
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report delves into methodological issues and ends by discussing activities to be carried
out after proposal defense.
Literature Review
Increasing Prevalence and Trends of Adult Obesity in the World
Body mass index, an index to detect weight balance, is calculated as weight in
kilograms divided by height in meters squared (kg/m2). Usually, people whose BMI is
between 25.0 and 29.9 are categorized as overweight, and people whose BMI is more
than 30.0 are categorized as obese (Flegal et al., 2012).
Adult obesity is a public health challenge in Canada and the United States. In the
United States, obesity in adult population has been significantly increasing since 1980s
and reached an alarming level by 2010. To get the idea of prevalence and trends of
obesity at the population level, we used data from a series of National Health and
Nutrition Examination Surveys (NHNES) carried out by the National Center for Health
Statistics (NCHS). Figure 1 shows time trends in age-adjusted prevalence (%) of obesity
(BMI≥30.0 kg/m2 and 35.0≤BMI≤39.9 kg/m2) in adults (age 20-74 years old for
NHANES I-III and age≥20 years old for NHANES 2009-2010) from 1971-2010. There is
no significant change of prevalence in obesity among American adults in the first ten
years. At some time between NHANES II (1976-1980) and NHANES III (1988-1994),
American adult obesity population started to increase sharply from 13.2% to 19.6%. By
2010 when the latest NHANES was released, more than 44% of American adult
population was obese. Obesity prevalence in 2010 is more than twice as high as the
number in 1994. Furthermore, those numbers do not include data from pre-obesity group
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Running head: Social marketing Physical Activity Campaigns in Adults
(25.0≤BMI≤30.0 kg/m2). According to the latest NHANES, by 2010, at least 68.8% of
American adults aged 20 or older was overweight and obese (Flegal et al., 2012).
Prevalence (%) of Obesity
USA
50
45
40
35
30
25
20
15
10
5
0
All Adults
Men
Women
NHANES I (1971-1974)
12.9
11.2
14.3
NHANES II (1976-1980)
13.2
11.9
14.4
NHANES III (1988-1994)
19.6
18.2
21
NHANES (2009-2010)
44.8
43.6
45.8
Figure 1. The data are from NHANES (1971-1974, 1976-1980, 1988-1994, 19992010) (Flegal et al., 1998; Flegal et al., 2012)
In Canada, although the absolute prevalence of obesity among adults is lower than
that of the U.S., the trend is upwards since 1978. We used data from Canada Health
Survey (1978-1979), Canadian Heart Health Surveys (1986-1992), and Canadian
Community Health Survey (2004). Figure 2 shows the trend in adults (aged 18 to 74
years old) in Canada from 1978 to 2004. During the first 15 years of the time span, the
rate in adult obesity slightly increased from 13.7% to 14.6%. By 2004 when the Canadian
Community Health Survey was released, the obesity rate among adults in Canada had
reached 23.1%, almost 10% higher than the number in 1978-1979. Compared to the
trends of adult obesity in the U.S., rates of obesity among adults in Canada are
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Running head: Social marketing Physical Activity Campaigns in Adults
significantly lower, and the increase in adult obesity in Canada is much slower. However,
it is a worrying trend that the graph continues to show upward trend.
Canada
25
Obesity Rates
20
15
10
5
0
Canada
1978-1989
1986-1992
2004
13.7
14.6
23.1
Figure 2. The data are from Canada Health Survey (1978-1979), Canadian Heart
Health Surveys (1986-1992), and Canadian Community Health Survey (2004)
(Tjepkema, 2005)
The same upward trend of obesity is also observed in other countries in the world
such as European cities and China. In Europe, the prevalence of obesity in male adults
ranged from 4.0% to 28.3% and in female adults from 6.2% to 36.5% (Berghofer et al.,
2008). Generally speaking, the adult obesity rates of western or northern regions are
lower than the rates of central, eastern, and southern regions (Berghofer et al., 2008). The
rates of male adult obesity (BMI≥25.0) are high in Spain, Italy, Cyprus, Czech R., and
Poland, and the rates of female adult obesity (BMI≥25.0) are high in Spain, Italy,
Romania, Czech R., and Poland (Berghofer et al., 2008). In central, eastern, and southern
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Europe, the prevalence of adult obesity has reached a concerning level. Since Chinese
tend to have a higher percentage of body fat than westerners under the same BMI value
(Deurenberg-Yap and Deurenberg, 2003), people with BMI≥24.0 and BMI≥28.0 are
categorized as overweight and obesity for Chinese population (Chen, 2008). Under this
classification of overweight and obesity, in 2002, the prevalence of overweight and
obesity of Chinese adults is 7.1% and 22.8%, respectively (Chen, 2008). From 1992 to
2002, prevalence of obesity and overweight in Chinese adults aged 18 year old and over
has increased by 40.7% and 97.2%, respectively (Ma et al., 2005). In summary, obesity
has become a public health issue in many parts of the world. As a global health and
clinical issue, obesity, as well as its consequences, has reached a level that deserves
attention from governments and nongovernmental organizations.
Impacts of Obesity
Obesity leads to several health risks (Pi-Sunyer, 2002; Thompson et al., 1999).
From a pathophysiological perspective, Pi-Sunyer (2002) proposed several disorders
associated with obesity that lead to higher mortality and morbidity, including insulin
resistance and hyperinsulinemia, type-2 diabetes, hypertension, dyslipidemia, coronary
heart disease, gallbladder disease, cancer, and early mortality. Thompson and colleagues
(1999) employed a dynamic model to analyze relationship between BMI and five obesityrelated diseases: hypertension, hypercholesterolemia, type-2 diabetes mellitus, coronary
heart disease, and stoke. Their findings show that the estimated risk (%) of all the five
diseases has a positive association with BMI for both men and women aged 35-64 years
old. That is, obese individuals have a greater chance to have the five diseases than their
leaner peers. For example, among women aged 55 to 64 years old, obese individuals
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(18.4%) have three times higher chance to suffer from type-2 diabetes mellitus than their
leaner peers (5.6%). Furthermore, Thompson and colleagues (1999) suggested that this
estimate of risk of related diseases tend to be conservative because other diseases
associated with obesity, such as gallbladder disease, were not included in the model. In
other words, obesity may have more influential power on health issues in reality than
what is reported in the literature.
Obesity also results in economic hardships for both society and individuals. Other
than the direct costs of healthcare and treatment, obesity is also responsible for indirect
costs such as significant productivity loss, transportation costs and human capital
accumulation costs (Hammond and Levine, 2010). By studying articles published
between 1990 and 2009, Withrow and Alter (2010) found that the direct costs of obesity
impose a heavy burden for both health systems and obese individuals. According to their
estimate, obesity is responsible for between 0.7% and 2.8% of a country’s total healthcare
expenditures. Obese individuals spend approximately 30% more in medical costs than
individuals with a normal body weight (Withrow and Alter’s, 2010).
Further, developing countries might suffer the obesity burden more than developed
countries in the future. Kelly and colleagues (2008) pointed out that although obesity and
overweight is more common in economically developed countries than in economically
developing countries (prevalence of overweight and obesity is 35.2% versus 19.6% and
20.3% versus 6.7%, respectively), developing countries may result in more absolute
numbers of overweight and obese population because of their large population. Given the
underdeveloped status of economy of those countries, obesity might place an even
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heavier burden on the government and health system of economically developing
countries in the future.
Causes of Obesity
From an energy balance perspective, body-weight regulation is achieved by
systems that adjust or match energy balance (energy intake versus energy expenditure)
(Martinez, 2000; Hill, 2006; Dietz, 2004). When energy intake exceeds energy
expenditure, it results in a positive energy balance and unhealthy body-weight gain.
Researchers (Martinez, 2000; Hill, 2006; Dietz, 2004) believe that the interaction
between genetic factors, dietary patterns, physical activity, and environment factors
influence energy balance and body-weight maintenance.
The biological and genetic factors have played a significant role in global obesity
epidemic. According to Hill (2006), our biological system strongly favors weight gain
over weight loss. Furthermore, humans prefer sweet-tasting foods and perhaps highenergy dense foods (Drewnowski, 1998), and humans do not seem to have a strong
biological drive to promote energy expenditure (Hill & Peters, 1998). Martinez (2000)
also suggested that some people are more genetically susceptible to obesity than others.
However, genetic and biological factors should not be solely held responsible for the
increasing prevalence of obesity. According to Martinez (2000), the worldwide increase
of obesity is also triggered by the presence of other factors such as unfavorable
environment (e.g. easy access to energy-, fat-dense, and high-sugar foods) and behavioral
changes in physical activity.
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According to Martinez (2000), a low level of activity-related energy expenditure
plays a major role in the increasing prevalence of obesity. By studying U.S. national
surveys, such as Behavioral Risk Factor Surveillance System, from 1950s to 2000s,
Brownson (2004) and colleagues concluded that the overall levels of physical activity of
Americans have been decreasing due to a host of factors such as technological advances
(motorized transportation, conveniently available services, and digital entertaining
products), urban sprawl and sedentary activities. Of the total time that people are awake,
the time spent carrying out all the activities (work-related activity, transportation, and
those carried out at home) are declining. Brownson et al.’s estimation of levels of
physical activity of Americans tends to be conservative because they only studied
sedentary activities during leisure time. Sedentary behaviors are also work- and
transportation-related. Due to technological advances, many occupations do not require
much physical activity anymore. More and more people rely heavily on motorized
transportation instead of walking and cycling. Despite this limitation, Brownson et al.’s
study gives us a general idea of Americans’ decreasing level of physical activity.
In general, researchers (Sturm, 2004; Brownson et al., 2004; Sallis and Glanz,
2009) categorize physical activity into four domains: leisure-time/recreation activity,
occupation-related activity, transportation activity, and home production/domestic
activity. Of those domain-specific activities, transportation and leisure-time/recreation are
found to have strong association with obesity prevalence while occupation and domestic
activity is remotely associated (Ball et al., 2001; Abu-Omar & Rutten, 2008).
Active transportation is a predictor of low rates of obesity. To study the relationship
between the transportation behavior and rates of obesity, Bassett and colleagues (2008)
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analyzed data on transportation and rates of obesity from national surveys and published
studies released between 1994 and 2006 and based on European, North American, and
Australian populations. In their study, active transportation was defined as the percentage
of trips taken by walking, bicycling, and public transit, and obesity was defined as
BMI≥30 kg*m-2. They observed much lower levels of active transportation in North
America (12% and 19% in America and Canada, respectively) and Australia (14%) than
the levels in European cities. The most transportation-active countries are Latvia (67%),
Switzerland (62%), and Netherlands (52%). On the other hand, the prevalence of obesity
based on measured weight and height in North America (34.3% and 22.7% for America
and Canada, respectively) and Australia (20.8%) is much higher than the rates of
European countries except for Great Britain. Based on Bassett et al.’s (2008) analysis,
one deduces a relationship between active transportation and the prevalence of obesity
based on energy expenditure.
Bassett and colleagues (2008) suggested that the observed trend between active
transportation and obesity rates could be explained by the contribution of active
transportation in energy expenditure. Bassett and colleagues (2008) calculated and
compiled data on walking and bicycling distance and calories burnt by Europeans and
Americans in 2000. Europeans walked and bicycled a total average of 569 kilometer per
year, three times as much as the Americans’ total average of 180 kilometer. In 2000,
Europeans burnt between 48 and 83 calories per person per day on active transportation,
comparing to Americans burning 20 calories per person per day.
Bell et al.’s study (2002) supports the influence of active transportation on low
prevalence of obesity using longitudinal data of Chinese population. Bell and colleagues
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(2002) used cross-sectional data (1997) from Chinese adults aged 20 to 55 years to
explore relationship between current obesity status and vehicle ownership and cohort data
(1989 to 1997) from adults aged from 20 to 45 years to study the impact of vehicle
acquisition on the potential odds of becoming obese. In Bell et al.’s (2002) study, obesity
was defined as BMI≥25 kg/m2 based on body weight status adjusted for Asian
populations as proposed by World Health Organization (2000). Non-motorized
transportation included bicycles and tricycles, and motorized transportation included
motorcycles and cars. Bell and colleagues (2002) found a positive relationship between
ownership of motorized transportation and prevalence of obesity.
Specially, obesity rates of people who owned motorized vehicles were 70% higher
among men and 85% higher among women than those who did not own a motorized
vehicle. To further substantiate the effect of transportation shift from non-motorized ones
to motorized ones on the odds of becoming obese, Bell and colleagues (2002) studied the
link between motorized vehicle acquisition and weight gain. Their findings suggest that
acquiring motorized transportation is associated with body-weight gain among men. Men
with a motorized vehicle during 1989 to 1997 attained 1.82 kg weight while those
without lost 0.57 kg. Bell et al. (2002) concluded that ownership and acquisition of
motorized transportation is a significant predictor of obesity for Chinese population.
Low level of leisure-time physical activity (LTPA) is associated with body-weight
gain and adult obesity (Abu-Omar and Rutten, 2008), although gender and ethnic
differences exist (Seo & Li, 2010; Ball et al., 2001; Li et al., 2010). Abu-Omar and
Rutten (2008) conducted a study to learn relationship between leisure-time physical
activity and obesity in a national population level. They recruited participants from 27
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member states of the European Union and from Croatia, Turkey, and Cyprus North in
2005. In their study, obesity was defined as BMI≥30.0 kg/m2, and total volumes of
physical activity were calculated with metabolic equivalents (MET-min/week). The
participants were 15 years older and were recruited from a face-to-face interview. The
findings suggest that the level of LTPA is inversely associated with the risk of being
obese for both males and females in European countries. Other studies recruiting national
or state level of samples also observed the inverse association between LTPA and adult
obesity, although the results favor women and Caucasian population (Seo & Li, 2010;
Ball et al., 2001; Li et al., 2010).
According to Wagner et al. (2001), regular moderate levels of leisure-time physical
activity is negatively associated with BMI and waist circumference independent of high
intensity physical activity. Wagner and colleagues (2001) conducted multiple regression
analysis on a 5-year longitudinal study among middle-aged European men aged between
50 and 59 years old, free of coronary heart disease. Wagner and colleagues (2001)
observed a significant inverse association between regular moderate level of LTPA and
BMI and waist circumference. Compared to participants in sedentary group, participants
who performed more than 9 MET hour/week of low-to-moderate-intensity recreational
activity had 0.33kg/m2 and 0.90 cm lower levels in mean BMIs and waist circumference,
respectively (Wagner et al., 2001).
Environmental factors influence obesity issue by influencing behavioral factors,
such as levels of physical activity. Sallis and Glanz (2009) groups environments into a)
physical activity environments that support people to be physically active, such as parks,
sidewalks, trails, schools, workplaces, playgrounds, child care settings, and private
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recreation facilities, and b) common settings for sedentary behaviors, such as homes,
workplaces, sports venues, schools, and driver-friendly roadways. In Bauman and Bull’s
(2007) review, several studies found that people who live in a neighborhood with easy
access to various recreation facilities are more physically active.
In Saelens and Handy’s review (2008), they found a trend that recreation walking is
positively related to pedestrian infrastructure and aesthetics. Kaczynski and Henderson
(2007) reviewed studies on relationship between physical activity levels and built
environment, such as parks and recreation facilities. The review found that increased
physical activity is associated with proximity to parks or recreation settings. Past
literature thus suggests that easy access to recreation facilities and better pedestrian
infrastructures motivates recreational physical activity and activity-related energy
expenditure.
Sedentary behaviors, such as “screen time” watching TV and using computer, are a
major contributor to total energy expenditure and thus obesity (Brownson et al., 2004;
Banks et al., 2010). Banks and colleagues (2010) conducted a cross-sectional analysis in
adults aged 45 years and older to study the relationship between sedentary behaviors and
obesity. In their study, Banks and colleagues (2010) combined TV and computer usage
into “screen time”, and calculated “total daily time spent sitting”. Banks et al.’s findings
suggest that sedentary behavior has positive association with the risk of obesity. The risk
of being obese grows with increase in screen time. That is, people whose screen time was
less than 1 hour had 15% risk of being obese while people whose screen time was more
than 8 hours had 27.6% risk of being obese.
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For other sedentary behaviors, the association between total sitting time and obesity
is less dramatic than the trend between screen time and obesity. However, the positive
association between total sitting time and the risk of being obese is clear. That is, people
who sat for less than an hour had 18.3% risk of obesity while people who sat more than 8
hours had 24.6% risk of obesity. Furthermore, sedentary behaviors have an independent
effect on obesity, which means the effect of physical activity on reducing risk of obesity
may be compromised by a sedentary lifestyle. The findings of Banks et al.’s study (2010)
show that the association of physical activity and risk of obesity is influenced by screen
time. Interestingly, within high-level physical activity group, individuals whose screen
time was more than 8 hours had a much higher risk of being obese than those whose
screen time was less than one hour did. Also, the most active individuals who had highest
level of screen time had almost the same risk of obesity (1.72, 95% CI 1.46, 2.03) as the
least active ones with lowest level of screen time (2.05, 95% CI 1.71, 2.45).
Although genetic and environmental factors influence obesity epidemic, evidence
of association between physical activity and obesity highlights the need to change
people’s behavior (e.g. active transportation, regular leisure-time physical activity and
less sedentary behaviors) and make them more physically active.
The Role of Physical Activity in Obesity Prevention and Long-term Weight Loss
Maintenance
According to Catenacci and Wyatt (2007), physical activity that produces energy
deficit of 500-1,000 kcal per day will initiate substantial weight loss. With cross-sectional
data and longitudinal data, previous studies have observed a trend that low risk of obesity
is accompanied by increasing levels of physical activity (See Causes of Obesity).
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However, observational studies cannot provide causality of the association between
physical activity and obesity. Randomized, controlled trials (RCTs) give us a more clear
idea of the dose-response effect of physical activity on obesity than observational studies
do.
Catenacci and Wyatt (2007) reviewed prospective, randomized, controlled trials
with an intervention of at least more than 4 months. All the studies identified in their
review were published after 1997. The Centers for Disease Control and Prevention and
the American College of Sports Medicine issued a public health recommendation in 1995
(Pate et al., 1995). Reviewing studies building on the updated guideline gives us new
insights on physical activity. Catenacci and Wyatt (2007) identified 16 randomized,
controlled trials, which compared participants’ weight loss in a group prescribed physical
activity with weight loss in a control group prescribed no physical activity intervention.
By reviewing the findings of RCTs, they found that in most of the trials (11 out of 16),
there was significant weight loss in physical activity groups as compared to the control
groups. However, the amount of weight loss was modest. Most of the trials reported
weight loss of 1-3 kg in exercise groups.
In Klem and colleagues’ (1997) long-term weight loss maintenance study,
participants reported a 30.00 (±15.49) kg of weight loss and 10.57 (±5.23) kg/m2 of BMI
decrease. Compared to the data from Klem et al.’s study, weight loss reported in the
RCTs in Catenacci and Wyatt’s review is not substantial. However, Catenacci and Wyatt
(2007) pointed out that the prescribed level of physical activity in those trials was not
enough to result in an energy deficit. Of the 16 randomized, controlled trials, 11 trials
prescribed physical activity of 60-180 minutes per week. Compared to caloric restriction
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programs that usually produce an energy deficit of 500-1,000 kcal per day, the prescribed
level of physical activity in those trials cannot burn enough calories to result in a large
energy deficit to initiate substantial weight loss (Catenacci and Wyatt, 2007).
Catenacci and Wyatt’s argument on the dose-response effect of high levels of
physical activity on substantial weight loss is supported by Jeffery et al.’s (2003) study.
The study compared weight loss in two treatment groups with prescribed physical activity
of 1000 kcal/week energy expenditure (standard behavior therapy) and 2500 kcal/week
(high physical activity) energy expenditure during 18 months. The energy expenditure
was not significantly different between the two treatment groups at the baseline.
Participants in high physical activity group gradually increased their energy expenditure
to 2500 kcal/week at the end of the sixth month and maintained this level of energy
expenditure till the end of the trial.
Jeffery and colleagues (2003) reported that mean cumulative weight loss in high
physical activity groups were 9.0 ± 7.1, 8.5 ± 7.9, and 6.7 ± 8.1kg, respectively at 6, 12,
and 18 month while the corresponding weight losses in standard behavior therapy were
8.1 ± 7.4, 6.1 ± 8.8, and 4.1 ± 7.3 kg, respectively. Of the results, weight losses in 12
month and 18 month between the two treatment groups were significantly different.
Weight loss in high physical activity group reported in Jeffery et al.’s (2003) is greater
than the results of trials reviewed in Catenacci and Wyatt’s (2007) study (0.1 kg to 5.2 kg
in the exercise groups) and the result from previous review (Wing, 1999). It seems that a
higher prescribed level of physical activity contributes to more weight loss.
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High level of physical activity is a predictor of long-term weight loss maintenance
(Wing & Phelan, 2005; Baak et al., 2003). Losing body-weight is not the end of
combatting obesity epidemic; on the contrary, long-term weight regulation is also
important to reversing the prevalence of obesity, especially for the people who were
obese and have lost substantial body-weight lately. To learn how to successfully maintain
long-term weight loss, Wing and Hill (Klem et al., 1997) established the National Weight
Control Registry in 1994. The registry included more than 4,000 adults (aged 18 or above)
who had lost at least13.6 kg and kept it off for at least one year. Wing and Phelan (2005)
documented registered members’ behaviors related to long-term maintenance of weight
loss. Engaging in high levels of physical activity was one of the most commonly reported
strategies to maintain weight loss (The other strategies were low-calorie and low-fat diet,
regular breakfast, regular self-monitoring of weight, maintaining a consistent eating
pattern, and catching signs of weight regain before it gets out of control). Women in the
registry reported an average of 2,545 kcal/week in physical activity, and men reported an
average of 3,293 kcal/week. According to Wing and Phelan (2005), those levels of
physical activity equal to about 1 hour/day of moderate-intensity activity, such as brisk
walking. Other reported activities included weight lifting, cycling, and aerobics.
The association between physical activity and long-term weight loss maintenance is
also supported by Baak et al.’s (2003) prospective study with European samples. Baak et
al. (2003) found that leisure-time physical activity is one of the three most important
determinants of long-term maintenance of weight loss. Their study included two phases.
The first phase focused on losing weight for the first six months. Participants who were
aged 17-53 and had a BMI of 30-45 were treated for obesity with combination of
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sibutramine, dietary restriction and advice on exercise and behavior in the first phase.
According to James et al. (2000), sibutramine is “a tertiary amine that has been shown to
induce dose-dependent weight loss and to enhance the effects of a low-calorie diet for up
to a year” (p. 2119). The next 18 months were the second phase to evaluate long-term
weight loss maintenance. Variables of body weight, dietary intake, and physical activity
were measured at baseline, 6, 12, 18 (except physical activity), and 24 months. The
results of multiple regression analysis showed that LTPS is one of the three factors that
significantly influences weight maintenance. Higher levels of LTPA, along with
sibutramine treatment and greater initial body weight, explained 20% of the variation in
weight maintenance. Interestingly, dietary factors, age, and sex did not significantly
influence weight maintenance in their case.
How Much Physical Activity Is Enough for Body-Weight Regulation?
Before we discuss how to promote physical activity, a central question that needs
to be addressed is how much physical activity is enough to manage healthy weight.
According to Saris and colleagues (2003), two factors determine its answer: whom to
target to and what physical activity goals are. Past literature has identified three groups:
people who have been obese (BMI≥30.0 kg/m2), people who have lost substantial bodyweight, and people who have a normal (BMI≤25.0 kg/m2) or overweight body-weight
(25.0≤BMI≤30.0). The corresponding PA goals should be treatment of obesity aiming by
achieving substantial weight loss, long-term weight maintenance to prevent weight regain,
and obesity prevention.
Most nations base their PA guidelines with the goal to improve and maintain
general health and cardiorespiratory fitness. Warburton and colleagues (2007) reviewed
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15 physical activity national guidelines for adults since 1975 and 22 consensus statements
about health outcomes of physical activity in different countries and regions, including
the United States, Canada, Australia, Switzerland, Philippines, New Zealand, UK, and
European Union. Almost all the consensus statements and guidelines identified in their
review converge on the fact that adults should accumulate at least 30 minutes of
moderate-intensity physical activity per day, on at least 5 days, preferable all days, of a
week. According to World Health Organization’s recommendation on levels of physical
activity for adults aged 18 - 64 years, this amount and intensity of physical activity
recommended in most national guidelines helps reduce the risk of cardiovascular disease,
diabetes, colon cancer and breast cancer.
Saris et al. (2003) suggested that 60-90 minutes of moderate intensity activity or
lesser amounts of intensive activity per day would help formerly obese individuals
prevent weight regain and that 45-60 minutes of moderate intensity activity per day are
required to prevent the transition to overweight or obesity. Despite lack of details, it
seems that the amounts and intensity of physical activity for general health recommended
in most national guidelines in Warburton et al.’s (2007) review is not enough for obesity
prevention and long-term weight maintenance. Of the 15 national physical activity
guidelines in Warburton et al.’s review, only two guidelines (UK and World Health
Organization) mentioned obesity prevention or weight control. Of the 22 consensus
statements about health benefits of physical activity identified in Warburton et al.’s (2007)
review, only one consensus specifically addresses obesity issue, but it did not specify
details on how much physical activity is enough to deal with obesity. International
recommendation for physical activity released from World Health Organization suggests
Running head: Social marketing Physical Activity Campaigns in Adults
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that more activity is required for more health benefits, but it does not give details on how
much more on weight loss and control. National physical activity guideline released in
UK suggested that 45-60 minutes of moderate intensity exercise per day are required for
obesity prevention (Department of Health, 2004).
A meeting was held in Bangkok in 2002 to specifically address the issue of
physical activity level that can potentially prevent weight gain and regain. All the
participants at the meeting agreed that for formerly obese adults, 60 minutes of moderate
intensity of activity, such as walking and cycling, is necessary to prevent weight regain,
and 80-90 minutes are preferable (Saris et al., 2003). Also, it seems that 45-60 minutes of
moderate intensity activity per day is likely to help prevent the transition from
overweight or obesity (Saris et al., 2003).
In short, to answer the question raised at the beginning of the sector, there is
consensus in the literature that at least 30 minutes of moderate-intensity physical activity
5 days, preferably on all days, of a week is recommended to maintain general health.
More physical activity will bring more health benefits. Forty-five to sixty minutes of
moderate intensity activity per day is likely to prevent becoming overweight or obese.
For individuals who were obese and have lost substantial weight lately, at least 60
minutes of moderate intensity of activity, preferably 80-90 minutes, is recommended to
prevent weight regain.
Target Audience of Physical Activity Interventions
Selecting target audience is a key step in the social marketing planning process. In
social marketing, all decisions are audience-centric. In other words, campaign strategy
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and evaluation is influenced by the selection and understanding of the audience group. In
the present study, we choose to target adults aged between 18 and 60 years old. This
group includes college population (18-24 years old), young adults (25-35 years old),
middle age adults (35-50 years old), and adults (50-60 years old) before their early senior
life. However, this audience group is just one of the many groups one could target in the
physical activity promotion efforts.
“Downstream” individuals refer to the ones who are physically inactive, and who
are at risk of certain consequences (e.g. obesity and related health issues) because of the
undesired behavior. Social marketers target downstream individuals because downstream
individuals can make the issue go away by adopting a desired behavior. Campaigns with
a downstream approach target individuals such as residents in a neighborhood, students
in a university, associates in a workplace, and so on. In the present study, we choose
studies targeting downstream individuals because interventions can bring direct benefits
by attempting to influence people who are having the issue.
Three age groups are identified from the existing literature to whom physical
activity is usually promoted: children, adults, and seniors. We believe that adult
population fits the present study the best. Here is why. Adult exercise pattern has an
important influence on quality of people’s senior life. Although physical activity prevents
people from severe health disorders, it might be too late to promote PA to people who
have already suffered the disorders. We believe that by targeting adults, social marketing
campaigns can influence not only adults but also future seniors. On the other hand,
childhood obesity requires incorporation of multiple parties, such as schools, parents, and
policy makers (Andreasen, 2006). For example, parents’ exercise habit may play an
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important role in children’s beliefs of physical activity and physical activity pattern. It is
logical for social marketers to target upstream or midstream members instead of children
(e.g. participACTION campaign) (Craig et al., 2009) when promoting physical activity
among children. To be brief, we believe that promoting PA to adults will be an efficient
way of promoting physical activity among the broadest sections of the society. Thus, we
will review studies targeting adults.
Why Social Marketing
Social change managers can employ several approaches to influence individual
health behavior. Social marketing is one of them. We will briefly discuss the various
behavior change options and argue in this section how social marketing is an appropriate
tool to promote physical activity among adults.
According to Rothschild (1999), social change managers can employ three
strategies to influence individual behavior: education, marketing, and law. Education
relies on sending messages to inform or/and persuade target audience to adopt desired
behavior voluntarily but does not provide direct or and immediate benefits (Rothschild,
1999). Marketing offers benefits and reduces barriers toward the desired behavior by
providing opportunity in the environment and incentives (Rothschild, 1999). Law
promotes desired behavior in a non-voluntary by using coercion or by threatening to be
punished for noncompliance (Rothschild, 1999).
To explain why and when to apply social marketing, Rothschild (1999) proposed a
model to manage health behavior in terms of target audience’s motivation, opportunity,
and ability. Rothschild (1999) suggests that individuals will be motivated to behave when
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they can discern that the desired behavior will serve their self-interest. In the MOA model,
law is appropriate when targets lack motivation (e.g. college students have to attain a
certain amount of credits from physical education classes to apply for graduation).
Opportunity is environmental mechanism that facilitates individuals to act (Rothschild,
1999). Rothschild (1999) suggests that opportunity can be created through social
marketing programs or indirectly through law. Social marketers provide opportunity by
delivering products or service. For example, to motivate individuals to use stairs, a social
marketing campaign can persuade university to close elevators for certain period of a day
so that people have to use stairs.
Law imposes behaviors and penalizes individuals if they do not practice them. For
instance, government can withhold funding to the schools that do not provide students
enough time to be physically active. In the MOA model, ability is defined as perceived
individual skill or proficiency to carry out desired behavior, such as overcoming a wellformed or addictive habit or confronting peer pressure. Rothschild (1999) suggests that
ability can be taught through educational programs and imparted through marketing by
reinforcing a newly developed skill. Rothschild’s (1999) MOA model suggests that
marketing is a powerful tool to develop opportunity or/and ability when individuals are
motivated and that marketing is helpful to develop motivation in combination with law.
The stages of change model (Prochaska & DiClemente, 1983) suggests that
awareness is also an important factor for individuals to adopt health behaviors. Within
stages of change model, there are five phases for individuals to complete a behavioral
change: pre-contemplation, contemplation, preparation, action and maintenance.
According to Ronda and colleagues (2001), people in pre-contemplation are not
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considering increasing their physical activity within six months, and people in
contemplation are. A significant factor that proceeds people from pre-contemplation to
contemplation is awareness of personal risk behavior (Ronda et al., 2001; van Sluijs et al.,
2007). Ronda et al.’s study shows that participants who were not aware of their physical
inactivity had less intention to increase their level of physical activity than those who
rated their physical activity as low. Rothschild (1999) also suggests that people who
perceive benefits of a desired behavior are more motivated to behave. The previous
literature suggests that when individuals are premature to adopt a desired behavior,
increasing their awareness of benefits of a desired behavior or/and consequences of the
corresponding unhealthy behavior may help them increase intention to behave.
Other than motivation, opportunity, ability, and awareness, current usage and level
of competitions is strong indicator of which tool(s) (education, marketing, and law) to
apply (Rothschild, 1999). Current usage may involve breaking a well-formed habit that is
addictive. In such situations, education is not sufficient. More powerful tools such as
marketing can help individual develop ability to break a problematic behavior pattern.
The more competitive the current behaviors are, the more powerful tools should be
applied to manage health behaviors. Sedentary behaviors are a strong competing behavior
for being physically active. For example, many people prefer elevator than stairs even for
a short distance. Many of them might have known the benefits of taking stairs and being
active, but they continue to use elevator. In this case, the competing behavior is so strong
that educational programs are less likely to influence individuals’ behavior. Marketing
should be applied to help people be physically activity.
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Perceived barrier has been identified as a reliable predictor of physical activity
from the existing literature, and consistent evidence shows that barriers are negatively
correlated with physical activity behavior (Schwetschenau et al., 2008). Lack of time,
care-giving duties, lack of motivation, and lack of energy are identified as the major
barriers to physical activity for adults from existing literature (Toscos, Consolvo, and
McDonald, 2011). Lack of time is the top reported barrier (Toscos, Consolvo, and
McDonald, 2011). It is highly correlated to women who have heavy care-giving duties of
children, aged parents, or other family members (Toscos, Consolvo, and McDonald,
2011). Lack of time is also a most cited barrier to follow healthy dietary and exercise
habits for college students (Silliman et al., 2004).
Fear of potential injury or poor health is most reported in the studies targeting
older populations (Costell et al., 2011; Moschny et al., 2011). For employees who are
provided on-site corporate fitness center, internal barriers (e.g. embarrassment to workout
around colleagues) and external barriers (e.g. inadequate equipment) are found to be
negatively associated with physical activity (Silliman et al., 2004). To be brief, perceived
barriers to physical activity can be grouped into environmental factors (e.g. inadequate
recreational facilities in the neighborhood or equipment provided by gyms), motional
factors (e.g. lack of motion and lack of willpower), health issue (e.g. fear of potential
exercise injury), personal factors (e.g. embarrassment to exercise around people), and
other priorities (e.g. lack of time or other duties). To overcome such barriers, marketing is
necessary.
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Social Marketing Benchmarks
Since the present study proposes assessing effectiveness of social marketing
framework to promote physical activity, we will delve deeper into the social marketing
concepts. We will utilize these concepts, especially the social marketing benchmarks
proposed by UK’s National Social Marketing Centre (NSMC, 2006), to identify studies
during literature search. These benchmarks will help us identify social marketing
programs in the literature search and distinguish them from other behavior management
efforts (e.g. communication interventions). Social marketing benchmarks also provide a
consistent approach to reviewing and evaluating studies and campaigns (NSMC, 2006).
According to NSMC (NSMC, 2006), a social marketing interventions aiming to influence
individuals’ behavior should possess eight elements: behavior, customer orientation,
theory, insight, exchange, competition, segmentation, and marketing mix. Each
component is described below.
Behavior.

“The intervention is focused on influencing specific behaviors, not just
knowledge, attitudes and beliefs

Clear, specific, measurable and time-bound behavioral goals have been set, with
baselines and key indicators established” (NSMC, 2006)
Behavioral change is the key objective of a social marketing campaign, although
social marketers use education to influence targets’ knowledge, attitudes and beliefs to
support the behavioral change. According to Kotler and Lee (2008), there are three types
of objectives that are associated with a social marketing campaign: behavior objective
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(something marketers want target audience to act), knowledge objectives (something
marketers want target audience to know), and belief objectives (something that marketers
want target audience to feel or believe). However, a social marketing campaign always
has a behavior objective, although sometimes a social marketing campaign has
knowledge or/and belief objectives to support a behavior objective.
When the targets are not aware of an issue or don’t possess the requisite knowledge
or skill to perform a desired behavior, combined efforts of educational programs and
marketing programs should be applied. In Rothschild’s (1999) MOA model, there are two
situations that marketers need to bring education before they launch marketing campaign:
lack of ability and lack of motivation. Education can deliver facts on attractive
alternatives, information on how to perform the desired behavior, information on location
of goods or services and so on (Kotler & Lee, 2008). The other situation is that the targets
might not realize or not think they have a problem, so they do not have a motivation to
behave. Education programs can provide information on benefits of a desired behavior,
on consequences of an undesired behavior and so on (Kotler & Lee, 2008). In this case,
education may raise awareness of an issue, change targets’ belief of the issue, and
provide educational information on how to perform a desired behavior. However,
changes in knowledge, attitudes and beliefs will not necessarily lead to behavior change.
Social marketing goals establish a desired level of behavioral change in percentage
or numbers as a result of social marketing program efforts (Kotler & Lee, 2008). To
establish a proper social marketing goal, marketers need to know the current level of a
behavior engagement (baseline data). Social marketing goals, especially behavior goals,
should be doable so that target audience feels they can make progress step by step and
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will not be frustrated. Also, social marketing goals should be measurable so that target
audience can determine if they have performed the desired behavior.
Customer Orientation.

Involves the target audience and local community, rather than treating them as
research subjects

Gains key stakeholder understanding and feeds it into strategy

Uses a range of research analyses at every step of strategy development and
delivery process and combines data from different sources (qualitative and
quantitative) (NSMC, 2006)
Formative research is a key element to study target audience in customer
orientation. Formative research can help social marketers understand target audience’s
needs and wants and make effective and efficient marketing strategy to promote desired
behavior to target audience. Kotler and Lee defined formative research as “research used
to help form strategies, especially to select and understand target audiences and develop
draft marketing strategies.”(2008, p. 75).
Other than formative research, pretest and monitor test is also powerful tools to
study target audience (Kotler and Lee, 2008; Andreasen, 2002). Pretest research refers to
a study that test alternative strategies and tactics with target audience before launching
the campaign. It helps campaign managers to ensure that there is no major defect of
potential executions and to fine-tone possible approaches to get to target audiences
effectively (Kotler and Lee, 2008). Monitor research “provides ongoing measurement of
program outputs and outcomes” (Kotler and Lee, 2008, p.76). More importantly, monitor
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research helps campaign managers decide if correction and altering and increased
resources are needed to fulfill campaign objectives (Kotler and Lee, 2008).
Theory.

“The theory, or theories used, are identified after conducting the customer
orientation research

Appropriate behavioral theory is clearly used to inform and guide the methods
mix

Theoretical assumptions are tested as part of the intervention pre-testing” (NSMC,
2006)
Health behavior theories and models help social marketers deepen their
understanding of how their target audience changes behaviors (Kotler and Lee, 2008;
Andreasen, 2002; Dunton et al., 2010). The most widely applied behavior theories and
models in public health include health belief model, theory of reasoned action/theory of
planned behavior, social cognitive theory, transtheoretical model/stages of change model,
and social norms theory. When considered at a broader level, various behavior theories
suggest that a person ought to possess following attributes to perform a desired behavior
(Fishbein, 1995; Kotler & Lee, 2011, pp. 201):

The person intends to carry out the desired behavior;

Few environmental constraints in regards to carrying out the desired
behavior exist in the person’s life;

The person believes he/she ‘can’ perform the desired behavior;
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
33
The person anticipates that the outcome of performing the behavior will be
beneficial;

The person perceives social pressure to behave desirably;

The person has positive emotions to perform the desired behavior;
Insight.

“A deep understanding of what moves and motivates the target audience,
including who and what influence the targeted behavior

Insight is generated from customer orientation work

Identifies emotional barriers (such as fear of testing positive for a disease) as
well as physical barriers (such as service opening hours)

Uses insight to develop an attractive exchange and suitable methods mix”
(NSMC, 2006)
To get deeper understanding of their target audience, social marketers need to know
target audience’s perceived benefits and perceived barriers of the behavior they promote
(Kotler & Lee, 2008). Barriers are something that prevents people from behaving and
what costs for people to behave (Kotler & Lee, 2008). Barriers include internal ones and
external ones (McKenzie-Mohr). Internal barriers refer to individuals lacking the skill or
knowledge needed to perform a behavior, and external barriers refer to the environmental
factors that need to be changed to made individuals perform a behavior more
conveniently. For example, in physical activity context, inactive people may not know
that they are having a problem of being physically inactive. External barriers may include
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34
not having recreational facilities in the neighborhood, not having lanes for bicycles in the
community, or expensive gym membership. Benefits are something that target audience
wants or needs and thus that they value the most (Kotler & Lee, 2008). By offering
benefits that interest target audience, social marketing campaigns are likely to motivate
target audience to adopt a promoted behavior. Numerous health outcomes are a major
benefit to individuals being physically active.
Exchange.

“Clear and comprehensive analyses of the perceived/actual costs versus
perceived/actual benefits

Considers what the target audience values: offers incentives and rewards,
based on customer orientation and insight findings

Replaces benefits the audience derives from the problem behavior and
competition

The exchange offered is clearly linked to “price” in the methods mix” (NSMC,
2006)
Exchange is a key concept of marketing. Traditional concepts of exchange in
economics and commercial marketing also apply in social marketing context: each party
believes that the potential exchange is beneficial (Bagozzi, 1975; Kotler, 1972); there
might be more than two parties involved (Bagozzi, 1978); transactions involve not only
tangible goods and financial payments but also intangible or symbolic products and non
financial payments (e.g. time and efforts) (Kotler & Levy, 1969).
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Peattie and Peattie (2003) gave two specific cases of exchange in social marketing
context. One possibility of exchange is that social marketers provide information,
products, or incentives to audience in exchange for audience adopting desirable behaviors.
The other possibility of exchange in social marketing is that audience changes behaviors
to get psychological benefits of peace of mind or satisfaction in exchange. Kotler and Lee
(2008) suggest there are three factors that need to be considered when an exchange
happens: barriers, benefits, and competition. Voluntary exchange takes place when target
market believes they can get as much or more than they pay (Kotler, 1972). Thus, in
social marketing context, to facilitate a voluntary exchange and, eventually, a behavioral
change, marketers should manage to provide benefits that will help target audience
overcome barriers and benefits offered by competition.
Competition.

“Addresses direct and external factors that compete for the audience’s time
and attention

Develops strategies to minimize the impact of competition, clearly linked to
the exchange offered

Forms alliances with or learns from the competing factors to develop the
methods mix” (NSMC, 2006)
When conducting audience research, social marketers need to identify competition.
According to Kotler and Lee (2008), competition is alternative behaviors that target
audience prefers, may be tempted to do, or is currently doing, rather than adopts the one
that social marketers promote. Competition also refers to organizations or groups who
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36
promote or sell the competing behavior (e.g. video game industry versus physical
activity). In many cases, social marketing programs compete with individual’s lethargy,
habit, and inclination to “do nothing” (Andreasen, 2002; Kotler and Lee, 2008).
Understanding competition is important to form exchange and marketing mix
strategy. McKenzie-Mohr and Smith (1999) proposed a framework to change the ratio of
benefits to barriers so that the desired behavior will be more attractive to target markets:
“a) increase the benefits of the target behavior; b) decrease the barriers (and/ or costs) to
the target behavior; c) decrease the benefits of the competing behavior(s); and d) increase
the barriers (and/or costs) of the competing behaviors”. Kotler and Lee (2008) also
suggested that marketers should make social marketing products and service more
accessible or make access to the competition more difficult and unpleasant.
Segmentation.

“Segmentation is drawn from customer orientation and insight

Does not only rely on traditional demographic, geographic or epidemiological
targeting

Draws on behavioral and psychographic data

Identify the size of your segment or segments

Segments are prioritized and selected based on clear criteria, such as size and
readiness to change

Interventions in the methods mix are directly tailored to specific audience
segments” (NSMC, 2006)
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Segmentation is to divide a broad relevant population into smaller groups that
require unique but similar strategies to change behavior (Kotler & Lee, 2008). There are
three reasons to segment markets. First, audience segmentation can increase campaign
effectiveness. Marketers expect campaign outcomes will be greater by segmenting
markets. For example, a significantly greater percentage of target group is persuaded to
do regular physical activity. Second, audience segmentation can increase campaign
efficiencies. By segmenting markets, marketers expect that a certain amount of outputs
(resources expended) will result in larger outcomes. Finally, audience segmentation will
give marketers input on resource allocation and developing marketing strategies.
Segmentation process can be done through segmentation variables and behavior
models (Kotler & Lee, 2008). The most widely used segmentation variable is
demographic factors (age, gender, family size, income, occupation, education, religion,
and generation) because of their easy availability and predictable power of market needs,
wants, barriers, and behaviors. Other segmentation variables include geographic factors
(world, region, or country, country or region, city or metro size, density, climate, etc.),
psychographic factors (social class, lifestyle, and personality), and behavioral factors
(occasions, benefits, user status, usage rate, loyalty status, readiness stage, and attitude
toward product). Choosing target markets needs to be based on priority of segments
(Kotler & Lee, 2008). Organizations that implement physical activity intervention face
limited resources and efforts, so they need to choose the markets that need the
intervention the most.
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Marketing Mix.

“Uses all elements of the marketing mix (product, prices, place and promotion)
and/or primary intervention methods (inform, educate, support, design and
control)

Promotion is used to “sell” the product, price, place and benefits to the target
audience, not just to communicate a message

Takes full account of existing interventions in order to avoid duplication

Creates a new brand, or leverages existing brands appropriate to the target
audience

Methods and approaches are financially and practically sustainable” (NSMC,
2006)
Developing a good positioning statement will help form strategy of 4Ps (Kotler &
Lee, 2008). Positioning refers to “the act of designing the organization’s actual and
perceived offering in such a way that it lands on and occupies a distinctive place in the
mind of the target market-where you want it to be” (Kotler & Lee, 2008, p. 185). With
understanding of target market from audience research, positioning statements create an
audience-oriented value proposition, which gives target market a convincing reason why
they should “buy” the product from you instead of your competitors (organization or
groups sell or encourage competing behavior).
Social marketing emphasizes use of all four elements of marketing mix-product,
price, place, and promotion-to form campaign strategy (Kotler & Lee, 2008). Kotler and
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39
Lee (2011) proposed that there are three levels of product in social marketing context:
core product, i.e., benefits of a desired behavior, actual product, i.e., tangible objects and
services provided to facilitate a behavioral change, and augmented product, i.e., any
additional tangible goods or services.
In social marketing context, price management refers to identifying monetary and
nonmonetary costs that target audience associates with adopting a desired behavior
(Kotler & Lee, 2008), and reducing those using various strategies. Monetary costs are the
tangible objects and services related to adopting a desired behavior (e.g. buying sport
gear to be physically active). Nonmonetary costs may include input of time, effort, and
energy to perform a desired behavior, perceived or experienced psychological risks and
losses, and physical discomforts while performing a desired behavior.
Place is “where and when the target market will perform the desired behavior,
acquire any related tangible objects, and receive any associated services.” (Kotler & Lee,
2008, p. 247). Individuals value convenience nowadays. Easy access to the campaign
resources will be an asset for marketers.
Promotion is the persuasive communications tool designed and delivered to
motivate the target audience of a social marketing campaign to take actions (Kotler &
Lee, 2008). Promotion strategy includes making communication strategy and choosing
communication channels. For a communication strategy, marketers need to decide key
message(s) of a campaign (what is expected from target audience to do, know and
believe), messengers, people who deliver campaign message or who endorse the
campaign, and what to say in the campaign and how to say it.
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40
Funding and Partnership
National Social Marketing Centre does not include funding and partnership into
social marketing benchmarks. However, efforts to bring funding and to build partnership
helps bring great resources to a social marketing campaign and positively impacts
campaign strategy. Social marketer can find additional resources and support from
government agencies, nonprofit organizations/foundations, adverting and media partners,
coalitions, and private businesses (Kotler & Lee, 2008).
Evaluating Effectiveness of A Physical Activity Intervention
To review the effectiveness of social marketing campaigns, it is necessary to
conduct evaluation research of social marketing campaigns. According to Kotler and Lee
(2008), depending on different purpose of evaluation, measures of evaluation of social
marketing campaigns fit in one or more of the three categories: output/process measures,
outcomes measures, and impact measures. The present study is to review effectiveness of
social marketing campaigns promoting physical activity, and social marketing
emphasizes behavioral change. Thus, the present study will be focusing on reviewing
outcomes measures and impact measures.
Outcome measures assess target audience response to the efforts of a social
marketing campaign (Kotler & Lee, 2008). These measures are built on the campaign
goals, the specific measurable results that a social marketing program wants its target
audience to achieve. Kotler and Lee (2008) proposed that to evaluate a social marketing
campaign, 9 types of change should be measured:
1. Changes in behavior, including changes in percentage or numbers;
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41
2. Changes in behavior intent;
3. Changes in knowledge, including changes in awareness of important facts,
information, and recommendations;
4. Changes in beliefs, such as changes attitude, opinions, and values;
5. Responses to campaign elements, such as participation rates;
6. Campaign awareness, which provides feedback on the degree to which the
campaign is notices and recalled;
7. Customer satisfaction levels, which will give marketers insight on analyzing
data and future practice;
8. Partnerships and contributions created, which might be associated with
positive responses to the campaign;
9. Policy changes, which may be appropriate for campaigns targeting
“upstream” individuals who are in government agencies.
The most rigorous, costly, and controversial measure of evaluation of social
marketing campaigns is to measure impact that behavioral change a campaign achieves
(Kotler & Lee, 2008). Marketers may need more time to measure impact of a campaign
because target audience needs time to respond. Also, measuring impact of a social
marketing campaign needs rigorous methodology, such as pre-post design, controlexperiment design, control variables, and so on.
It is hard to determine if a social marketing campaign is successful. Many studies
report statistically significant difference of an outcome measure (e.g. levels of
recreational physical activity) between baseline and post-campaign test. If there is a
significant dose-response effect of a campaign on an outcome behavior, most researchers
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42
consider the campaign successful or effective. However, Kotler and Lee (2008) also
pointed out situations without behavior change within changes of stage model. We think
moving target audience from an earlier stage to later stage should also be considered as
successful efforts. Also, behavior adherence should be another factor to determine
effectiveness of a campaign. However, it is hard to determine how long is long enough.
For instance, a person has been physically active for a year. Is one year enough to say
that the person has transferred from maintenance stage to termination? We cannot find
answers to the question from the literature.
Objectives of the Study
As far as we know, no study in the past has systematically reviewed effectiveness
of physical activity promotion efforts using social marketing framework. Although
researchers believe that the more social marketing benchmarks are applied, the more a
campaign will be successful, there is no empirical evidence to support this assertion. To
fill this gap, we present our hypothesis:
The number of social marketing benchmarks applied in a campaign will be
positively associated with success of the campaign outcome.
Method
We will carry out a systematic literature search of studies reporting effectiveness of
social marketing campaigns to promote physical activity in adults listed in five electronic
databases (PubMed, Medline via OVID, Business Complete Source, Web of Science, and
PsycINFO) published between January 1997 and April 2013. In 1995 the Centers for
Running head: Social marketing Physical Activity Campaigns in Adults
43
Disease Control and Prevention (CDC) and the American College of Sports Medicine
(ACSM) issued a physical activity recommendation “Every US adults should accumulate
30 minutes or more of moderate-intensity physical activity on most, preferably all, days
of the week” (Pate et al., 1995), which has an impact on latter studies. Thus, we will
focus on reviewing studies built on the recommendation in 1995.
Key Words and Inclusion Criteria
Combinations of key words include: “physical activity/physical exercise/physical
fitness” AND “social marketing”, “active living/active life” AND “social marketing”,
“physical activity campaign/intervention/promotion”, “physical exercise
campaign/intervention/promotion”, “physical fitness campaign/intervention/promotion”,
“active living campaign/intervention/promotion”, and “active life
campaign/intervention/promotion”.
We will restrict our review to English language published studies, applying the
following inclusion criteria:

Campaigns targeting adults (aged 18 and 60 years old),

Campaigns that the main component or one of the components was aimed
to promote physical activity through behavior change,

Campaigns that employed at least two activity of “marketing mix” (we
will exclude educational campaigns),

Campaigns that reported statistical analyses of an outcome measure
related to physical activity (self-reported or objectively measured), and

Articles published between 1997 and 2013.
Running head: Social marketing Physical Activity Campaigns in Adults
44
Article Data Extraction
Data extraction form and codebook are adapted from the ones in Mah et al.’s
(2008). See Appendix 1 and 2 for the extraction form and codebook respectively. Articles
will be analyzed mainly for the presence of social marketing benchmarks. Social
marketing benchmarks were discussed in the literature review section.
Other information extracted from the articles reviewed will include whether the
campaign was self-identified as a marketing campaign; campaign outcome; marketing
strategy (campaign description, behavior positioning, and campaign duration); sampling;
setting; individual characteristics; study design; measures; data analysis methodology;
study results.
Once articles are identified, they will be reviewed by two coders. According to
Lipsey and Wilson (2001), an amount of twenty to fifty studies should be coded
independently between coders to generate coding reliability. In the present study, if the
literature search results in less than fifty studies, coders will code independently all the
studies. Coding discrepancies will be discussed between coders through meetings after
the first round of data extraction. If coders cannot settle the discrepancies, disagreement
will be consulted with the thesis supervisor. The process of discussion will continue until
the coders reach an intercoder reliability of 90%.
Data Analysis
The strategy of data analysis applied in the present study is adapted from Mah et
al.’s study (2008). Campaign outcome will be categorized into either improvement
(statistically significant improvement of outcome measure) or no improvement (no
Running head: Social marketing Physical Activity Campaigns in Adults
45
significant improvement or significantly worsening trend). We will use chi-square test to
assess the statistical significance of association between the number of marketing
benchmarks applied & campaign outcome (improvement & no improvement).
Additionally, we will analyze association of campaign outcomes with each benchmark.
Contributions
The present study will provide evidence of effectiveness and appropriateness of
social marketing campaigns in physical activity context. The result of the study will not
only give a general idea of current social marketing practice in physical activity but also
give insights for improving future efforts to promote physical activity.
Timeline
Proposal Defense
May 2013
Data Extraction and Analysis
May-July 2013
Thesis Write-Up
August-October 2013
Thesis Defense Application
October 2013
Thesis Defense
December 2013
Budget
The study will hire a graduate student as a second coder for data extraction. The
anticipated rate of the second coder is 15 per hour plus benefits. The total cost of the
Running head: Social marketing Physical Activity Campaigns in Adults
46
study depends on the hours spent on data extraction, so it cannot be known at this point.
The expenses of the study would be covered by thesis funds provided by MSc (Mgt)
program at the University of Lethbridge. The remainder would be covered by personal
funds.
Running head: Social marketing Physical Activity Campaigns in Adults
47
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Appendix 1 Data Extraction Form
Paper ID#
Reviewer’s Name
Full Citation
Aims/Objectives
Did this study self-identify as social marketing
interventions?
Yes
__No
Did the author(s) attempt to change physical
__Yes
__No
activity behavior? If yes, describe the behavior.
If yes, what was the behavioral outcome of the Behavioral outcome parameter:
intervention?
Behavioral outcomes and their significance:
__Awareness
__Attitude/Belief
Other outcomes of the intervention
__Behavior Intention
__Other (please specify)
Success rate on other outcomes
Please provide details
Audience Research other than Evaluation Research (Check all that apply):
Primary formative research
Secondary formative research
Pretest research
Monitoring research
__Segmentation
__intentional
list target audiences:
Check presence of the following
__Was the campaign self-funded? If no, list the funding agencies:
social marketing concepts:
__Partners other than the funding agencies (e.g. governor agencies and foundations)
__Exchange of value
__Marketing mix: __product (tangible or intangible)
__price
__place __promotion
__Behavioral Competition
Running head: Social marketing Physical Activity Campaigns in Adults
Behavioral theory (behavior theory or
model explicitly stated)
Marketing Strategy
Sample
Sample Size
City, Country
Individual Characteristics
Setting
Study Design
Data Analysis Methods
Study Results
Measures
Conclusion
Comments
__Yes
__No
Intervention(s)
Behavior Positioning:
Duration:
__Selective
__Representative
Please specify the sampling design:
58
Appendix 2 Data Extraction Codebook
Paper ID#: number every identified paper
Reviewer’s Name: Put this on every form-Yuan Xia/another coder’s name
Full Citation: Follow APA style
Examples: Koren, G., Koren, T., Gladstones, J. (1996). Mild maternal drinking and
pregnancy outcomes: Perceived versus true risks. Clinica Chimica Acta, 246, 155-162
Aims/Objectives: Overall aims and objectives of the paper (see if the paper abstract has
the info), e.g. update and clarify the 1995 recommendation on the types and amounts of
physical activity needed by healthy adults to improve and maintain health.
Did this study self-identify as social marketing interventions?
Did the authors regard the intervention discussed in the paper as a social marketing one?
Did the author(s) attempt to change physical activity behavior? Describe the
behavior.
Did the intervention achieve a change in physical activity behavior, and what was the
behavior, e.g. to urge audience to achieve the recommended level and correct kind of
physical activities.
If yes, what was the behavioral outcome of the intervention?
Behavioral outcomes parameter: e.g. 30% target audience individuals maintained
recommended levels and nature of physical activity for a period of six months after
intervention.
Behavioral outcomes and their significance: success rate and statistical significance of
behavioral outcome variables, e.g. compliance increased from 20% to 30%, and the
difference was significant.
Other outcomes of the intervention
Awareness: A change in knowledge in benefits from recommended levels and nature of
physical activity or consequences of not conducting the recommended levels and nature
of physical activity.
Attitude/Belief: A change in beliefs or perceptions towards physical activity or related
behaviors promoted by the intervention, e.g. self-efficacy towards achieving
recommended level and nature of physical activities.
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Behavior Intention: Future intention to adopt the favorable behavior, e.g. intention to
achieve recommended level and nature of physical activities.
Other: Anything that did not fit above, e.g. media exposure levels.
Success rate on other outcomes
See if the intervention achieved an improved and statistically significant performance of
other outcome variables, e.g. the levels of knowledge of the recommended level of
physical activity intensity increased from 30% to 40%, and improvement was significant.
Social Marketing Concepts (Mah, Tam, & Deshpande, 2008)
Audience Research (Other than evaluation research): Primary formative research,
secondary formative research, pretesting research, or monitoring research. Check all that
apply.
Segmentation: Did the intervention tailor to fit a segment? Was the attempt of
segmenting intentional? If it was, what was the target audience? (e.g. seniors, healthy
adults, etc.)
Funding Source: Was the intervention self-funded? If not, who were the funding
agencies?
Partners: Who were the partners? Were funding agencies part of the partnership team?
Exchange: If the intervention encouraged target group to adopt the favorable behavior by
offering benefits and/or reducing costs (barriers), e.g. offering discount to people who
register in a specific physical activity program.
Marketing mix: If the intervention used a 4P strategy. If it did, which Ps was used? (e.g.
distributing fliers providing knowledge of recommended level and nature of physical
actives)
Behavioral Competition: Did the article acknowledge competing behavior (e.g. watching
TV at home) and competitors (groups and organizations, e.g. commercial companies or
media promoting competing behavior)? Did the strategy make an attempt to achieve
competitive advantage (e.g. promoting unique benefits of doing physical activities, such
as improving mental health and mood)?
Behavioral Theory: If the research stated behavior theory or model explicitly, e.g.
Stages of Change, such as pre-contemplation, contemplation, preparation, action, and
maintenance.
Marketing Strategy:
Running head: Social marketing Physical Activity Campaigns in Adults
61
Intervention(s): describe intervention, e.g. short or intensive motivational interviewing
with or without financial incentive (30 vouchers entitling free access to leisure facilities)
(Harland, Jane, et al. "The Newcastle exercise project: a randomized controlled trial of
methods to promote physical activity in primary care." Bmj 319.7213 (1999): 828-832.).
Behavior positioning: what was the primary platform on which the desired behavior was
promoted? (e.g. positioning moderate physical activities such as taking stairs instead of
taking an elevator as something that is easy to fit in daily routine)
Duration: duration of the intervention
Sample: Was the sample selective or representative? Provide details on the sampling
design: e.g. convenience sampling, judgment sampling, snowball sampling, simple
random, systematic random, cluster, etc.
Sample Size: N=
City, Country: In which city (cities) and country (countries) was (were) the intervention
conducted?
Individual Characteristics: target audience profile and inclusion and exclusion criteria
(e.g. healthy adults who have not been smoking for at least one year)
Setting: Where was the intervention conducted? (e.g. individual, family, or community)
Study Design: e.g. before/after, after-only, RCT, Solomon, between-subject,
basic/factorial, etc.
Data Analysis Methods: Which statistical method (e.g. t-test, ANCOVA, regression,
factor analysis, SEM, etc.) and computer programs (e.g. SPSS, SAS, etc.) was employed
to analyze data?
Study Results: What were the major findings?
Measures: variables that were measured in the study (e.g. amounts of physical activity,
physical activity intensity, etc.)
Conclusion: Overall conclusions of the paper (see if the paper abstract has the info)
Comments: