week 5 and6 - Biology
G E N E R A L A R T I C L E
The Role of Social Cognitive Theory
in Farm-to-School-Related Activities:
Implications for Child Nutrition*
LINDA BERLIN, PhDa,b KIMBERLY NORRIS, PhDc JANE KOLODINSKY, PhDd,e ABBIE NELSON, MSf
ABSTRACT
BACKGROUND: Farm-to-school (FTS) programs are gaining attention for many reasons, one of which is the recognition that
they could help stem the increase in childhood overweight and obesity. Most FTS programs that have been evaluated have
increased students’ selection or intake of fruits and vegetables following the incorporation of FTS components. However, the
wide range of activities that are typically part of FTS programs make it difficult to pinpoint which components have the greatest
potential to improve students’ health behaviors. Within the field of nutrition education, theory-based interventions that target
the key underlying factors influencing health behavior offer the most promise.
METHODS: We review existing research on dietary health impacts and implications of 3 key FTS-related activities and explore
the component activities of FTS in terms of their potential to address the key constructs of social cognitive theory (SCT) — which
is a current best practice in the field of nutrition — suggesting that FTS programs incorporating a diverse set of activities appear
to be most promising.
RESULTS: We find that components of FTS programs incorporate many of the key theoretical constructs in SCT, and show that
FTS programs have great potential to facilitate movement toward desired dietary changes. However, it is unlikely that a set of
activities in any one current FTS program addresses multiple constructs of the theory in a systematic manner.
CONCLUSION: More intentional inclusion of diverse activities would likely be beneficial. Future research can test these
assertions.
Keywords: nutrition and diet; school food services; health educators; school health instruction.
Citation: Berlin L, Norris K, Kolodinsky J, Nelson A. The role of social cognitive theory in farm-to-school-related activities:
implications for child nutrition. J Sch Health. 2013; 83: 589-595.
Received on April 3, 2012
Accepted on August 12, 2012
The farm-to-school (FTS) movement gained tractionduring the 1990s, and then flourished over
the next decade, resulting in an estimated 2,000
programs in nearly 9,000 schools across the country
by 2008.1 Lacking a precise definition, FTS programs
are characterized as linking farmers and K-12 schools
with the primary purposes of contributing to nutritious
meals and education for youth and better incomes
for farmers who market locally. Additional goals
include enhancing youth’s appreciation and awareness
aExtension Assistant Professor, ([email protected]), Department of Nutrition and Food Sciences, University of Vermont, 109 Carrigan Drive, Burlington, VT 05405-0086.
bDirector, ([email protected]), Center for Sustainable Agriculture, University of Vermont, 109 Carrigan Drive, Burlington, VT 05405-0086.
cAssociate Agent, ([email protected]), Food Supplement Nutrition Education, University of Maryland, 10632 Little Patuxent Parkway, Suite 435, Columbia, MD 21044.
dProfessor and Chair, ([email protected]), Community Development and Applied Economics, University of Vermont, 109 Carrigan Drive, Burlington, VT 05405.
eDirector, ([email protected]), Center for Rural Studies, University of Vermont, Morrill Hall Rm. 202, Burlington, VT 05405.
f Director, ([email protected]), Vermont Food Education Every Day, NOFA-Vermont, PO Box 697, 14 Pleasant Street, Richmond, VT 05477.
Address correspondence to: Linda Berlin, Extension Assistant Professor, ([email protected]), Department of Nutrition and Food Sciences, University of Vermont, 109 Carrigan
Drive, Burlington, VT 05405-0086.
*Indicates CHES continuing education hours are available. Also available at http://www.ashaweb.org/continuing_education.html
of agriculture, food, and nutrition, strengthening
local economies, and furthering youth’s sense of
connectedness to the community.2,3
As a result of FTS programs’ diverse purposes and
grassroots nature, the types of activities they encom-
pass vary considerably from program to program. This
variety may be due to a view that FTS efforts appear
to be best designed from the ground up. Despite this
diversity, most FTS programs serve locally produced
foods in the school cafeteria,4,5 often highlighting
fresh or processed fruits and vegetables (eg, kale,
Journal of School Health • August 2013, Vol. 83, No. 8 • © 2013, American School Health Association • 589
squash, tomato sauce), dairy and meat products,
eggs, beans, and other value-added items (eg, pesto,
granola, cider). In addition to locally sourced food
served in the cafeteria, components of FTS activities
common to many programs include taste tests, lessons
on healthful food choices, farm visits, school gardens,
recycling activities, and composting systems.
The rapid expansion of FTS has been part of a
broader food system relocalization movement in the
United States. Other facets of this movement, which
may or may not happen in communities with FTS
programs, have included the revival of farmers’ mar-
kets, development of direct marketing relationships
between farmers and restaurant operators, forma-
tion of CSAs or ‘‘community supported agriculture,’’
and numerous other connections among producers,
processors, distributors, and consumers of food.2 Pro-
ponents of the food relocalization movement often
cite improved food quality and safety, small-scale food
production, biodiversity, resource protection, commu-
nity well-being, democratic participation, and regional
palates.6 Despite their long list of attributes, the con-
cepts of ‘‘local’’ and ‘‘regional,’’ as they apply to food
systems, are no more precisely defined than is the term
‘‘farm-to-school.’’
FTS programs are gaining attention for their
potential to help stem the increasingly prevalent trend
of childhood overweight and obesity. A comparison
of National Health and Nutrition Examination Survey
(NHANES) data over more than 30 years (1976-1980
and 2009-2010) shows that the prevalence of obesity
has increased for children aged 6-11 years, from 6.5\%
to 18.0\%; and for those aged 12-19 years from 5.0\%
to 18.4\%.7,8 Increased consumption of fruits and veg-
etables has been recognized as a successful strategy for
reducing overweight and obesity,9 and is of particular
interest here because greater access to produce is
often a core component of FTS efforts.10 In fact, the
Centers for Disease Control and Prevention (CDC)
has identified FTS programs as an effective approach
to improving student health through healthier school
meals as well as nutrition and eco-literacy involving
hands-on and out-of-doors experiences.11
Many FTS programs that have been evaluated have
increased students’ selection or intake of fruits and veg-
etables following the incorporation of FTS components
such as including locally grown produce into school
meal selections, creating school gardens, and provid-
ing classroom-based nutrition education.10 Of 5 studies
that also examined FTS participants’ dietary behavior
outside of school, 4 found increases in the selection or
intake of fruits and vegetables by the children. Another
study of primary data from 7 school-based nutrition
intervention studies — not necessarily incorporating
components of FTS programs — showed a net increase
of 0.45 servings of fruits and vegetables per student.12
While there are few specific FTS program
evaluations, many of the individual activities that
are sometimes part of FTS programs such as school
gardens have been researched outside of the FTS
context. These identify public health implications,
including impacts on nutrition knowledge, food
preference, and dietary behaviors. The following
sections review existing research on the dietary health
impacts and implications of three key FTS-related
activities. Then, we explore the component activities
of FTS in terms of their potential to address the
key constructs of social cognitive theory (SCT) — a
health behavior change theory on which nutrition
interventions are commonly based — suggesting that
FTS programs incorporating a diverse set of activities
appear to be most promising in this regard.13
LITERATURE REVIEW
Research and evaluations that examined the
impacts of food-related activities in the school setting
are included in this review if they are typical of
the types of activities that are conducted within a
FTS context. Because FTS does not have a precise
definition, not all activities reviewed here were
necessarily linked in the school setting to a defined
FTS program. Much of the research cited here was
identified through a 2009 review by Joshi et al,1
and augmented with additional research published
after that report. The 3 broad areas of focus include
classroom-based nutrition education activities, school
gardens, and food interventions such as school lunch
menu changes and taste tests.
Component One: Nutrition Education Interventions
for Children
One of the most explicit goals of FTS is to improve
childhood nutrition. Programs may attempt to increase
knowledge and awareness, change attitudes, improve
skills, or alter behaviors, to positively impact health
measures. Despite great interest in this goal, research
specifically designed to identify how FTS nutrition
education components influence child nutrition
has been limited. Furthermore, it is challenging to
compare results across the few studies that have been
done, due to the diverse array of approaches that fall
under the broad definition of FTS.10
Studies show benefits of combining experiential
nutrition education with that based in the class-
room. Classroom-based nutrition education programs
yielded increases in fruit and vegetable consumption
among students, from 0.20 to 0.99 servings.14,15 A
study of classroom-based nutrition education and
hands-on gardening activities for fourth grade students
showed that compared with a control group, both
these activities ‘‘significantly improved the nutrition
590 • Journal of School Health • August 2013, Vol. 83, No. 8 • © 2013, American School Health Association
knowledge of the students,’’ as long as 6 months after
the intervention. Furthermore, while both activities
increased students’ preferences for certain vegetables,
the garden-based nutrition education did so for a
greater number of vegetables.16
Component Two: School Gardens
A review of 11 studies showed that garden-
based nutrition interventions have varying impacts on
youth’s produce consumption. Of the featured studies,
conducted between 1990 and 2007, 5 were school-
based, involving children ages 5-15. Of the 4 studies
that looked at actual changes in fruit and vegetable
intake, 3 found evidence of increased intake. Of the 6
studies that considered fruit and vegetable preferences,
2 showed increased preferences. Of the 3 studies that
examined willingness to taste fruits and vegetables, 2
reported increased willingness to taste.17
More recent research has provided clearer evidence
that garden-based education improves youth’s appre-
ciation of fresh produce. Garden education programs
have been shown to improve attitudes toward fruits
and vegetables for second to fifth graders.18 In addi-
tion, a 12-week pilot intervention for fourth to sixth
graders through a summer YMCA program showed
increases in the variety of fruits and vegetables ‘‘ever
eaten,’’ as well as improvements in vegetable prefer-
ences and requests for fruits and vegetables at home.19
A 28-week study of second graders in a school setting
showed that youths involved in gardening in addi-
tion to classroom-based nutrition education were more
likely to choose and consume vegetables in the cafe-
teria, as compared with a control group and another
group who only received classroom-based nutrition
education. The group that participated in gardening
activities also showed improved nutrition knowledge
and taste ratings compared with the control group.20
Although these studies’ results are promising,
their limitations — including small sample sizes, lack
of long-term follow-up, convenience samples, and
frequent absence of control groups — prevent firm
overall conclusions about school gardens’ impacts
on youth’s consumption of and preferences for fresh
fruits and vegetables.
Component Three: School Lunch Option, Taste Tests,
and Farm Connections
School-based interventions to improve nutrition
often incorporate some combination of taste tests
in the classroom or cafeteria, more healthful food
choices available in the cafeteria, and connections
between children and local farmers. Given prominent
goals to improve children’s suboptimal intake of fruits
and vegetables, such as those put forth in the most
recent Child Nutrition Reauthorization Act, much
of the recent research on the impact of school food
interventions focuses on produce consumption.
Seven studies featured in a review of FTS program
evaluations showed that participation in FTS programs
increased cafeteria offerings of fruits and vegetables.
Subsequently, participating students chose more fruits
and vegetables than they did before their participation
in the programs.1 One study in this review reported
that on days when the salad bar was available, approx-
imately 85\% of students selected fruits and vegetables,
compared to 35\% choosing fruits and vegetables when
only hot lunch was available. Between 80\% and 90\%
of the salad bar produce that students selected was
unprocessed, compared to only 10\% to 20\% of the
hot lunch fruits and vegetables they chose.21 Similar
studies in Compton, California, showed that students
choosing foods from FTS salad bar lunches selected
between 90\% and 140\% of United States Department
of Agriculture (USDA)-recommended daily servings
of fruits and vegetables, while students choosing hot
lunch selected just 40\% to 60\% of the recommended
servings. For comparison, both groups took close to
the recommended amounts of proteins and grains; this
suggests that gains in fruit and vegetable consumption
may be a unique contribution of school lunch salad
bars.22
Across the nation, salad bar lunches consistently
offer nearly twice the servings of fruits and vegetables
that hot lunches provide.21 In Oregon, FTS salad bar
programs raised the average servings of fruits and
vegetables taken by students from 1.24 to 2.26.23 In
Los Angeles schools, students self-reported eating an
average 4.09 daily servings of fruits and vegetables
when participating in salad bar lunch programs, com-
pared to 2.97 daily servings prior to the introduction
of the salad bar. Students selecting the salad bar
also reported consuming fewer total daily calories,
cholesterol and fats.24 Pennsylvania parents reported
that their children opted for healthier foods at home
when participating in FTS interventions, specifically
noting that they ate fewer foods high in fats and salt.25
FTS programs can be a boon to school lunch
programs’ revenue, as studies show that they typically
increase school meal participation rates between 4\%
and 16\%.26-28 This is an important part of school
food services’ budgets, because they must cover part
of their operating costs through sales of full-price
meals. They are also reimbursed by the USDA per
meal served for purchases of commodity foods, as well
as for serving free and reduced-price meals to eligible
students.29 One California school meal cost analysis
showed that participation rate increases of as little as
8\% can offset additional costs of labor related to an
FTS salad bar program.27
Little research was identified describing how taste
tests within FTS programs affect actual student dietary
behavior. Practitioners use taste tests to introduce
Journal of School Health • August 2013, Vol. 83, No. 8 • © 2013, American School Health Association • 591
students to nutritious food choices, to educate students
about what makes food healthy, and to allow food
service providers to assess the feasibility of serving
new foods.30 The link between taste tests and actual
food choice and intake has yet to be made.
Clinical research conducted in the United Kingdom
demonstrates that exposure to a vegetable through 8
daily taste tests increased children’s preferences for
that vegetable more effectively than reward methods,
when compared with control groups.31 Taste tests held
in a school setting in Burlington, Vermont, facilitated
the integration of new, healthy food items into the
school lunch menus, including pesto pasta and pesto
pizza, chicken caesar salads, minestrone soup, and
granola-yogurt parfaits.32
School food service professionals interviewed in a
set of case studies observed that students are more
willing to eat fresh fruits and vegetables if they
have interacted with the farmer who grew them,
through activities such as field trips to the farm or
visits by the farmer to the school.33 These qualitative
observations warrant further research into the effects
that educational interactions with farmers have on
students’ consumption of fresh fruits and vegetables.
Overall, research has shown these are positive gains
from the implementation of FTS programs. However,
given the variety of interventions across FTS programs
and the grassroots efforts by communities to imple-
ment them, FTS programs consist of interventions in
search of a theory that provides a conceptual frame-
work upon which to build testable hypotheses. Given
that FTS programs require resources to implement,
having impact research to show the efficacy is an
important next step toward policy changes that may
help stem the rising tide of childhood obesity.
Farm-to-School and Behavior Change Theory
Theory-based interventions that target key factors
influencing health behavior are a current best practice
in the field of nutrition education. The social ecological
model is one relevant theory that describes 5 levels
on which health-related behaviors and conditions are
influenced: intrapersonal, interpersonal, institutional,
community, and public policy.34,35 There are multiple
theories that address how change might happen at
each of these levels of influence, some of which are
particularly suited for certain types of interventions.
Social cognitive theory, although primarily focused
on the interpersonal sphere of influence, also
encompasses factors linked to the intrapersonal,
institutional, and community levels. This theory is
frequently the framework around which youth-related
food and nutrition interventions are designed because
of its: (1) emphasis on approaches that are important
to youth, such as positive reinforcement and (2)
applicability to public health issues, as evidenced by its
recent applications in these fields.36-38 It is, therefore,
a good fit for considering the factors associated with
FTS impacting students’ food-related decision-making
and behaviors.
SCT addresses the relationship among 3 factors that
have to do with how people acquire and maintain
health-related behaviors: the environment, personal
characteristics, and personal experience. These 3
factors operate in a reciprocal manner with each
influencing the others, and are translated into a
number of specific constructs which can help shape
the components of an intervention. For example,
an intervention built on SCT might incorporate a
changed environment (institutional and community
level), positive reinforcements for new behaviors
(intrapersonal level), and opportunities to build or
enhance behavioral capability (intrapersonal level),
self-control (intrapersonal level), and self-efficacy,
such as through modeling (interpersonal level).13,39
To understand how the key constructs of SCT
relate to FTS activities, the following list provides a
basic outline of the constructs 39 and indicates how
they might apply to dietary behavior change that
incorporates more local, healthful foods:
• Behavioral capability: youth having the knowledge
and skills that are necessary to choose and consume
a diet that incorporates local, healthful foods.
• Expectations: youth having beliefs about the likely
outcomes of consuming a healthful diet that includes
local foods.
• Expectancies: youth valuing the results of eating a diet
consisting of healthful, local foods.
• Locus of control: youth’s perception of who reinforces
continued consumption of local, healthful foods.
• Reciprocal determinism: interaction between a youth
and his or her environment that results in
consumption of more healthful, local foods.
• Reinforcement: a youth’s response related to the con-
sumption of local, healthful foods that increase the
chance of the behavior being repeated; reinforce-
ment can be provided internally (by oneself) or
externally (by another);
• Self-control or self-regulation: youth gaining control
by monitoring and adjusting personal behaviors
(consumption of local, healthful foods).
• Self-efficacy: youths’ confidence in their ability to
consume local, healthful foods.
• Emotional coping response: how youth deal with the
sources of anxiety that surround their consumption
of local, healthful foods.
DISCUSSION
Vermont Food Education Every Day (VT FEED)
provides a concrete example of how SCT can be incor-
porated into FTS programs. Many FTS programs in
592 • Journal of School Health • August 2013, Vol. 83, No. 8 • © 2013, American School Health Association
Vermont have been initiated or supported by VT FEED,
which encourages and provides technical assistance to
schools through its ‘‘3 Cs’’ model: classroom, cafeteria,
and community. Schools with the most comprehen-
sive programs — those that incorporate all 3 Cs in their
efforts to improve their food environments — would
likely touch upon the intrapersonal, interpersonal,
and community spheres of influence addressed in the
social ecological model and SCT. Although VT FEED
did not intentionally design its interventions around
health behavior-change theory, and no peer-reviewed
research yet considers FTS programs in this light, the
rest of this paper explores how components of FTS
programs in Vermont do (or do not) address key con-
structs of SCT, and discusses these programs’ likelihood
of influencing long-term health behavior change.
Table 1 provides a description of the types
of activities that are often incorporated into FTS
programs. It then describes whether each activity takes
place in the classroom, cafeteria, or community, and
which, if any, of the constructs of SCT are addressed
when the activity is carried out.
As noted previously, the activities incorporated into
each FTS program are not consistent across programs,
making it impossible to draw a conclusion about the
extent to which the constructs of SCT are addressed
through FTS. However, some generalizations can be
made from the content of Table 1.
First, the activities that are commonly part of FTS
do touch upon many of the theoretical constructs
in SCT, and often an activity has the potential to
address a number of constructs. Second, and most
importantly, FTS programs are likely to modify the
students’ food environment while simultaneously
providing opportunities for them to learn through
observation of others (modeling) during activities
such as taste tests, eating in the cafeteria, gardening,
and cooking.30 Together these approaches have great
potential to facilitate movement toward desired dietary
change. However, more research is needed to test these
assertions.
Another question to guide further research is
whether there are any approaches covered in SCT
that could be integrated more consistently into FTS
programs. Specific questions to ask toward this end
include: Is parental involvement in FTS programs
adequate to reinforce key messages at home, and
thereby help establish a stronger sense of control
(‘‘locus of control’’) in students? How can empirical
evidence be used to assess the value of local foods
in nutrition education to justify use of the classroom
setting to develop expectations and expectancies? and
Are students provided with positive reinforcement
when they make nutritionally beneficial choices in
the cafeteria? Further research that explores the links
between FTS and behavior change theory will enable
a closer examination of some of these questions. Ta
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Journal of School Health • August 2013, Vol. 83, No. 8 • © 2013, American School Health Association • 593
FTS programs that incorporate a number of diverse
activities are apt to lead to positive dietary behavior
change, in part because of their capacity to address
multiple constructs of SCT. However, because most
FTS programs are locally driven and differ from place
to place,5 they do not necessarily combine multiple
activities using SCT or …
SCT and SEM
Social Cognitive Theory
&
Socio ecological model
1
Social Cognitive Theory
2
What is the Social Cognitive Theory?
Theoretical perspective focusing on:
- individual characteristics (i.e., self-efficacy);
- how people learn by observing others;
- how the environment influences behavior.
Created by Albert Bandura
(Ormrod, 2008)
(http://webspace.ship.edu/cgboer/bandura.html)
3
Changing behavior
According to the (SCT), changing a behavior depends on two factors:
Individual Characteristics (internal)
Environmental Factors (external)
Within each of these factors there
are several constructs
(Edberg, 2007 )
4
SCT Categories & Concepts
Reciprocal determinism
Psychological determinants of behavior
Outcome Expectations
Self-efficacy
Collective efficacy
Observational Learning
Environmental determinants of behavior
Incentive motivation
Facilitation
Self-regulation (Excellent example from Cookie Monster)
Moral disengagement
5
Reciprocal determinism
“Social Cognitive Theory (SCT) describes learning in terms of the interrelationship between behavior, environmental factors, and personal factors.”
(IDEA , 2009)
6
the Reciprocal effect to change
(PB) a persons thoughts and beliefs, can affect a person’s behavior. For example, one’s personal self efficacy beliefs about writing an essay can influence one’s writing behaviors, such as choice of literary topics, effort, and persistence.
(PE) Self-efficacy beliefs also can affect a person’s environment; for example, efficacious students who are trying to write in a noisy social or physical environment may increase their personal concentration to avoid distractions.
(EP) Conversely, one’s social environment can affect personal variables and behaviors. Students who receive encouraging feedback from teachers may feel more personally efficacious and work harder to succeed. Teachers can inspire students to write by creating a favorable classroom environment, such as by giving children adequate time to write and revise.
(BP)The influence of behavior on personal variables can be seen in the student who succeeds in reading a moderately difficult book and then experiences higher self-efficacy and motivation to try reading another book of comparable difficulty.
(BE) Behaviors also can affect the environment, as when students eliminate distractions from their environments (e.g., turn off the television so they can read better).
7
Incentive Motivation
The use of rewards and punishment to modify behavior.
Reinforcements
Specify behaviors you will reinforce.
Provide people with clear feedback.
Punishments
Rules and consequences posted
Consistency (e.g., zero tolerance policy)
Reinforcements: I really like the way Kevin is working quietly.
Feedback: Explain why student received full credit so they can repeat this behavior.
Consistency: Students are less likely to break a rule when seeing classmate reprimanded.
8
Self-regulatIon
“Controlling oneself though self-monitoring, goal setting, feedback, self reward, self-instruction and enlistment of social support.”
Examples
Set goals
Monitor progress toward the goals
Assess the extent to which goals are met
Behavior change assessment
Food diary
Health assessment
Problem solving
Self-management
(Edberg, 2007 p.54)
some programs that aid in Self-regulation
AA/NA, Weight Watchers, Big Brothers/Big Sisters
9
Outcome Expectations
Beliefs about the likelihood (expectations) and value (expectancies) of the consequences of behavioral choices.
Expectations: what someone thinks will happen if they make a change.
Expectancies: whether the person thinks the expected outcome is good or likely to be rewarded.
Do the Expectations and Expectancies sub-constructs look familiar?
Expectations
Analogous to:
Behavioral Beliefs
Expectancies
Analogous to:
Evaluations of Behavioral Outcomes
These are the constricts that influence attitude towards behavior in the TRA.
10
Self-Efficacy
“A person’s confidence that he or she can perform a behavior.”
Self-Efficacy vs. Self-Esteem
Confidence to perform a skill vs. how one feels about him/herself.
A child first learning to ride a bike may not feel very confident.
A child with high self-efficacy in physical activity would attempt to ride a bike, even when feeling unsure, because they have mastered other difficult tasks in the past.
With low self-efficacy, the child may be hesitant to pedal a bike for fear that he or she may fall.
(Edberg, 2007, p. 53)
Mastery Experience
Practice
Social Modeling
Others can do it and so can you!
Example?
Saw a friend do a half-marathon…
11
Collective Efficacy
“Beliefs about the ability of a group to perform concerted actions that bring desired outcomes.”
Example:
MADD’s ability to create new alcohol related laws
12
Vicarious learning
A person learns by observing the behavior of others and the consequences of that behavior.
Watch the Bobo the clown experiment in blackboard content
BoBo Doll Experiment
http://www.youtube.com/watch?v=Pr0OTCVtHbU
(Edberg, 2007)
1:22
Observational Learning
Learning behaviors by exposure to interpersonal or media displays of them, particularly through peer modeling.
14
Facilitation
Providing tools, resources, or environmental changes that make new behaviors easier to perform.
Example: greenways to facilitate walking/bike riding
15
Moral disengagement
Ways of thinking about harmful behaviors and the people who are harmed that make infliction of suffering acceptable by disengaging self-regulatory moral standards.
Rationalize, justify, or permit conditions which compromise health.
Example: allowing vape companies to market towards youth. Business rights vs. health of children
Euphemistic labeling
Consider homophobia, racism, sexism, etc. Examples?
Dehumanization and attribution of blame
Drug testing welfare recipients?
Diffusion and displacement of responsibility
Fault of the leader, not the individual?
Perceived moral justification
Ends justify the means?
16
Limitations
“SCT can’t explain why learners can reproduce some behaviors they observe but can’t reproduce others.”
(Eggen & Kauchak, 2010, p.188)
17
Limitations
“SCT cannot explain the role of context and social interaction in complex learning environments.”
“For example, student interaction in small groups facilitates learning. The process involved in these settings extend beyond simple modeling and imitation.”
(Eggen & Kauchak, 2010 p.188)
18
So What?
You personally, your behavior, and your environment all affect each other.
People may have trouble changing their health behavior because of what is going on around them so look at the “big” picture.
Be careful what you do because you never know who is watching.
Children see, children do video
19
Socio ecological model
History: Ecological Model
Until the late 1970s/early 1980s, health promotion professionals focused primarily on the knowledge, and attitudes of individuals.
There was an overall lack of attention devoted to the social, cultural, and economic circumstances which influence behavior.
(Edberg, 2007)
21
Why the Ecological Model is different?
Assumed that multiple factors influences peoples’ behaviors rather than one cause.
i.e., Lack of knowledge
It is a complex interaction between individuals and environment, a process that together influences behavior
The Ecological Model takes into consideration community, society, and relationships as potential contributors to the behavior of individuals
22
Ecological Model
Explain Behavior
Different Levels:
Environmental
Political
Socioeconomic
Cultural
You!
23
Ecological Model
Guide Interventions
24
1st Level: Individual Factors
Intrapersonal
Awareness and knowledge about health risks, ways to prevent health problems, etc.
Biophysical characteristics
Genetics
Personal attitudes and motivations
Developmental stage
Adolescent, adult
Habits
(Edberg, 2007)
25
2nd Level: Interpersonal
The extent to which relationships and social networks influence behavior.
Social/peer groups impact lifestyle patterns
Attitudes/beliefs/behaviors of people the individual interacts with
Consider college student behavior…
26
3rd Level: Organizational
Organizations and social institutions impact health.
Campuses, class schedules, workplace, childcare, etc.
(Edberg, 2007)
27
4th Level: Community
The effect the community has on health behavior.
Walkability, businesses, transportation, etc.
28
5th Level: Public Policy
How state and federal laws affect people’s health behaviors
Policies and funding for HPP
Health insurance (policies, costs, availability)
Regulations that impact health risk (such as age regulations)
Smoking, drinking, driving laws, etc.
(Edberg, 2007)
29
Limitations
How easy it is to address each stage of the Ecological Model?
What about resources ($$) needed? Time?
Compare it to, say, the Health Belief Model…
references
Anderson, E., Winett, R., & Wojcik, J. (2007, November). Self-Regulation, Self-Efficacy, Outcome Expectations, and Social Support: Social Cognitive Theory and Nutrition Behavior. Annals of Behavioral Medicine, 34(3), 304-312. Retrieved September 29, 2009, doi:10.1080/08836610701677659
Edberg Mark, (2007) Essentials of Health Behavior. “Social Cognitive Theory” Chapter 5 p. 51-56, Jones and Bartlett Publishers. Washington, DC.
Eggen, P. & Kauchak, D. (2010) Educational Psychology. “Social Cognitive Theory” Chapter 6 p. 179-188, Merrill. Columbus, OH.
Institute for Dynamic Educational Advancement (IDEA). Journal of Interaction Recipes, (2009) “Social Cognitive Theory” Retrieved: Sep. 29, 2009. http://www.idea.org/page110.html
Schunk, D., & Zimmerman, B. (2007). Influencing Childrens Self-Efficacy and Self-Regulation of Reading and Writing Through Modeling. Reading & Writing Quarterly, 23(1), 7-25. Retrieved September 29, 2009, doi:10.1080/10573560600837578
Glanz, Karen; Rimer, Barbara K.; Lewis, Frances Marcus. Health Behavior and Health Education theory, research, and practice. Chapter 8 pgs. 168-181. San-Francisco: Jossey-Bass 2002. Print
Martin, J.J. (2008). Using Social Cognitive Theory to Predict Physical Activity in Inner- City African American School Children. Journal of Sport and Exercise Physiology, 30 (4), 378-391.
Ormrod, Jeanne Ellis (2008). Educational Psychology. Chapter 10 pg. 343. Pearson Education Inc. New Jersey.
31
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Journal of Agromedicine
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Using the Socio-Ecological Model to Frame
Agricultural Safety and Health Interventions
Barbara C. Lee, Casper Bendixsen, Amy K. Liebman & Susan S. Gallagher
To cite this article: Barbara C. Lee, Casper Bendixsen, Amy K. Liebman & Susan S. Gallagher
(2017) Using the Socio-Ecological Model to Frame Agricultural Safety and Health Interventions,
Journal of Agromedicine, 22:4, 298-303, DOI: 10.1080/1059924X.2017.1356780
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COMMENTARIES
Using the Socio-Ecological Model to Frame Agricultural Safety and Health
Interventions
Barbara C. Leea, Casper Bendixsena, Amy K. Liebmanb, and Susan S. Gallagherc
aNational Children’s Center for Rural and Agricultural Health and Safety, Marshfield Clinic, Marshfield, Wisconsin, USA; bEnvironmental and
Occupational Health, Migrant Clinicians Network, Salisbury, Maryland, USA; cPublic Health and Community Medicine, Tufts University School
of Medicine, Boston, Massachusetts, USA
ABSTRACT
The Socio-Ecological Model (SEM) is a conceptual framework depicting spheres of influence over
human behavior that has been applied in public health settings for nearly five decades. Core
principles of all variations of the SEM are the multiple influences over an individual’s behaviors,
the interactions of those influences, and the multilevel approaches that can be applied to
interventions intended to modify behaviors. A project team modified the standard SEM to address
interventions for protecting children from agricultural disease and injury. The modified SEM
placed the “child in the farm environment” at the core with five interrelated levels (spheres) of
influence over the child. This framework provides guidance on how a multifaceted, multilevel
intervention can maximize the potential for impact on behaviors and decisions made by parents/
adults responsible for the safety of children on farms. An example of how this model could work
to safeguard youth operating tractors is provided.
KEYWORDS
Agriculture; safety; socio-
ecological model; theory
Background
Occupational safety and health advocates are con-
stantly searching for strategies that offer sustain-
able interventions that reduce risks of injury and
disease. These strategies are often based on educa-
tion, engineering, environmental, and/or enforce-
ment approaches. To strengthen and potentially
measure their impact, they can be based on prin-
ciples of safety and hygiene, past experience, and
sometimes a theoretical model. Agricultural safety
and health interventions have lagged behind other
occupational safety and public health approaches
but increasingly are adopting evidence-based stra-
tegies guided by theories and models that have
demonstrated success in changing unsafe tradi-
tions into safe behaviors. This paper describes
how a well-known public health model has been
modified for agricultural safety and health to mul-
tiply and maximize the impact of agricultural
safety interventions.
Introduced in the 1970s, the Socio-Ecological
Model (SEM) is a broad-based conceptual model
depicting basic ecological principles of human
behavior.1 The SEM has undergone numerous
updates and modifications for different
applications.2 The World Health Organization and
U.S. Centers for Disease Control and Prevention
are among the many users of this model, which
illustrates multiple dimensions and complex
human interactions that influence behaviors.3,4 At
the core of the model is an individual whose beha-
vior is the primary interest. A figure of enlarging
circles added above the core individual demon-
strates how spheres of increasing influence have
higher degrees of impact on individual behavior
(Figure 1). The next level of influence is his/her
interpersonal relationships such as relatives, peer
groups, or healthcare providers. Following this is
the organizational level, which includes organiza-
tions, schools, churches, and workplaces. Next is
the community level, which represents relationships
between organizations. Finally, at the outer sphere
of the figure, is the public policy level that includes
federal/state regulations with enforcement options.
Terminology for the middle levels of the model is
CONTACT Barbara C. Lee [email protected] National Children’s Center for Rural and Agricultural Health and Safety, Marshfield Clinic,
1000 N. Oak Avenue, Marshfield, WI 54449, USA.
Color versions of one or more of the figures in the article can be found online at www.tandfonline.com/wagr.
JOURNAL OF AGROMEDICINE
2017, VOL. 22, NO. 4, 298–303
https://doi.org/10.1080/1059924X.2017.1356780
© 2017 Taylor & Francis
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typically altered depending on the user’s needs and
the model’s application.
In an extensive review of various ecological
models of health behaviors published in 2008,
authors explain that the core principles of an eco-
logical model are: (1) there are multiple influences
on an individual’s behaviors, including factors at
the intrapersonal level, interpersonal level, with
increasing influence at levels of organization, com-
munity, and public policy; (2) influences interact
across these different levels or spheres of influence;
(3) use of this model should be applied to specific
behaviors; and (4) multilevel approaches can be
the most effective interventions for changing
behaviors.5 The evolution of the SEM is based in
part on five different theories explaining human
behavior, dating from 1951 to 2006, as well as
eight different theories used to guide behavior
change, dating from 1953 to 2005. The influence
of different theorists and their applications of con-
ceptual models over time can explain both the
strength and the various visual depictions of the
SEM for different audiences.
Modified model
In 1996, the National Institute for Occupational
Safety and Health (NIOSH) launched its National
Childhood Agricultural Injury Prevention
Initiative.6 As a component of that initiative, the
National Children’s Center for Rural and
Agricultural Health and Safety (NCCRAHS) was
established to link public and private sector initia-
tives based upon a national plan of action.7 In
2014, with two decades of experience, the
NCCRAHS wanted to base its current and future
endeavors on a theoretical model that would max-
imize potential impacts. The SEM was chosen as a
logical fit for the center’s theme of strengthening
public-private partnerships to address childhood
agricultural injury prevention.8 The model has
long-standing acceptance by public health agen-
cies, and it has applications in multiple settings
on topics ranging from adding positive nutritional
habits and physical activity to avoiding risky prac-
tices such as smoking and unsafe sex. To the best
of our knowledge, the SEM had not specifically
and proactively been applied in agricultural safety
and health interventions or program evaluations,
nor has it been modified in any specific way to
address the well-being of children.
A comprehensive review of childhood agricul-
tural safety interventions conducted by Gallagher
in 20129 assessed 26 peer-reviewed studies that
reported the effectiveness of childhood farm safety
interventions. It was determined that most inter-
ventions focused on the individual level of the
SEM and typically used education as the primary
strategy to increase knowledge and influence beha-
vior change. Based upon these findings, the author
provided eight recommendations for the future,
framed around the principles of the SEM, such as
multilevel partnerships; repeated interventions;
approaches beyond education (e.g., engineering,
policy); diversity in funding; and sustained, wide-
spread dissemination.9
A planning team at the NCCRAHS reviewed
literature and versions of the SEM and discussed
the impact of the spheres of influence relevant to
the political, social, and individual environment
affiliated with agricultural communities. The
team incorporated concepts from non-agricultural
projects including experiences using the model for
low-income workers.
Our modified version of the SEM (Figure 2)
placed the “child in the farm environment” at the
core of the figure, with the knowledge that a child
(up to 18 years) who lives, visits, or works on a
farm is not in a position to change safety practices
Figure 1. Socio-ecological model: framework for prevention,
centers for disease control. Available from the Centers for
Disease Control and Prevention (CDC). http://www.cdc.gov/vio
lenceprevention/overview/social-ecologicalmodel.html.4
JOURNAL OF AGROMEDICINE 299
http://www.cdc.gov/violenceprevention/overview/social-ecologicalmodel.html
http://www.cdc.gov/violenceprevention/overview/social-ecologicalmodel.html
him/herself. Rather, the focus of interventions is to
influence the behaviors of those adults who have
the authority and knowledge to reduce the risk of
injury and disease affecting children. We believe
that all children deserve equal protection from
preventable disease and injury, and adults hold
full responsibility for safeguarding children under
their care.
At the model’s core is the child under the
influence and protection of the adult(s). There
are five spheres with interrelated-levels of influ-
ence over the child. The adult sphere includes
parents, guardian, farm owners, employers, and
any other individual(s) who may have responsi-
bility for youth in the agricultural production site
or a farm homestead. The next level of influence
is interpersonal—this includes persons with close
relationship to the immediate family such as rela-
tives, friends, and peer groups. It can also include
health care providers and child care providers
who regularly interact with the family. At the
third sphere above the child is the community
level, which can include local businesses such as
farm cooperatives and community-based organi-
zations such as FFA chapters, schools, faith-based
groups/churches, and child care centers. At a
higher level of influence are institutions and orga-
nizations that span beyond the local region. This
includes agricultural companies such as property/
casualty insurance providers, trade associations,
agribusinesses that set standards and guidelines
for purchasing agricultural products, national/
international trade agreements, bankers and lend-
ing agencies, and national media that influence
public opinion. The highest level of influence is
policy. For the most part, this represents federal
and state regulations regarding the role of youth
in agricultural work. It can also represent issues
such as immigration, federal/state workers com-
pensation laws, and Occupational Safety and
Health Administration (OSHA) enforcement
standards.
Degrees of influence of the various spheres are
subject to many factors. Each superordinate level
influences the subordinate level. For example, a
public policy may influence a community program
that influences an adult to make responsible deci-
sions regarding work assigned to a child living on
a farm.
When applying this modified SEM concept to
agricultural safety and health interventions, the
ideal approach is to have an interrelational link
that crosses through as many spheres as possible.
We have solid evidence from interventions in non-
agricultural settings that a multilevel approach
with repeated interventions has the greatest like-
lihood of achieving the desired outcome. For
example, a 2014 report described how the SEM
was used in a multilevel intervention to reduce
health inequities among low-income workers.10
Another example is an assessment to propose
community outreach interventions to improve
Figure 2. Socio-ecological model modified to address agricultural safety and health interventions.
300 B. C. LEE ET AL.
fruit and vegetable intake among inner-city
African Americans. Literature was reviewed on
past interventions addressing this topic. Relevant
interventions were categorized by SEM level then,
based upon intervention effectiveness, and recom-
mendations for a multifaceted community-based
approach became the basis and rationale for “Best
Practices” ecological nutritional programs for
African Americans.11
Applying the SEM for agricultural safety
What would an ideal intervention based on this
SEM concept look like? For explanatory purposes,
consider an unsafe practice that puts youth at high
risk of an agriculture-related injury. What is the
desired behavior change? And what approach
could be used at multiple levels to influence the
adults that bear primary responsibility for youth
involved in that unsafe practice?
Agricultural safety
Equipment manufacturers and safety professionals
recommend that all tractors used for production
activities include basic safety principles of seatbelts
and Rollover Protection Structures (ROPS). It has
been shown that this safety standard of a tractor
being equipped with a seatbelt and ROPS (or
enclosed cab) can virtually eliminate tractor-
related fatalities when the operator appropriately
uses these safety features.12,13
Burden
For youth working in agriculture, tractors are the
leading cause of death. An analysis of occupational
fatality cases from 2001 to 2013 among U.S. work-
ers under the age of 18 revealed that of the 406
recorded fatalities across all occupations, about
50\% of deaths occurred in agricultural jobs, of
which nearly all were associated with transporta-
tion and equipment.14 Young workers are often
asked to operate tractors that do not meet safety
standards, because the older unsafe tractors may
be smaller, less expensive, and less complicated to
operate, and farm owners do not want young
people operating their high-powered, expensive
equipment. There are no child labor regulations
that mandate safety standards of tractors operated
by youth. Further, in the United States, family
farms are exempt from child labor in agriculture
regulations. In occupational settings, the parent or
work supervisor bears responsibility for ensuring
that a young worker is safeguarded. However,
agricultural work activities can be complicated,
making close supervision and oversight difficult
to maintain, especially when workers are doing
field operations with tractors and trailed
implements.
Solution
To minimize the toll of serious injuries and deaths
among young workers in agriculture, a solution
would be to ensure that youth (14–18 years) who
are assigned agricultural work involving tractor
operations be allowed only to operate tractors
equipped with ROPS, and that these youth be
required to wear the tractor seatbelt at all times.
Implementing this solution would entail a multi-
level, integrated approach that alters long-standing
practices and might challenge family and/or cul-
tural traditions. Applying the SEM to a multilevel,
integrated intervention would involve each sphere
of influence approaching the problem from a dif-
ferent angle, but all with the same desired outcome
of improving safety.
The scenario below (Table 1) describes an inter-
vention, based on the SEM, of a national-level
campaign to “Safeguard youth operating tractors.”
The scenario above is an idealistic picture of how
the SEM could work, involving entities at all levels
of the SEM, and proposing they would agree and
engage in a unified way. Realistically, this would be
time and resource intensive and difficult to exe-
cute. But undoubtedly, if this scenario were set
into operation, there could be a profound change
that would drastically reduce the toll of injuries
and deaths to youth operating tractors.
Implications
Putting the SEM into practice in agriculture is
possible. Over the past five decades, much has
been learned about the etiology of farm injuries
through data on the incidence of injuries and
details on changing trends in types of injuries.
JOURNAL OF AGROMEDICINE 301
Our biggest challenge moving forward is
improving safety interventions and taking
approaches that will have the biggest impact on
reducing the toll of injuries. These multilevel
and interrelated interventions have the potential
of shifting the “culture” of agriculture to have a
greater emphasis on and respect for a “safety
culture” in agriculture. It also broadens the gen-
eral public’s perspective on the issue, rather than
solely relying on direct interventions by parents
or policy-level changes. The diversity of indivi-
duals and organizations involved strengthens the
capacity to change practices, resulting in lives
saved.
Conclusions
Public health demonstration programs have shown
us the SEM is a strong and effective way to change
individual behaviors by influencing those beha-
viors at multiple levels. We propose to modify
the SEM for application in agricultural safety and
health promotion programs. As this model is
applied, evaluated, and improved over time, our
hope is to have a measurable and sustained
improvement in safe practices that create a true
culture of safety in agriculture.
Funding
Efforts toward developing this dedicated issue of the Journal
of Agromedicine with a focus on the Socio-Ecological Model
were funded in part by the National Institute for
Occupational Safety and Health via the National Children’s
Center for Rural and Agricultural Health and Safety (NIOSH
2U54OH009568) and the National Farm Medicine Center.
References
1. Brofenbreener U. The Ecology of Human Development:
Experiments by Nature and Design. Cambridge, MA:
Harvard University Press; 1979.
2. Images of Socio-ecological model. https://www.google.
com/search?q=socio-ecologic+models+cdc+ima
ges&tbm=isch&tbo=u&source=univ&sa=X&ved=
0ahUKEwiL67r4mobUAhXp6oMKHYSUCuEQsAQIM
g&biw=1152&bih=616. Accessed May 22, 2017.
Table 1. An intervention, based on the SEM, of a national-level campaign to “Safeguard youth operating tractors.”
Policy Federal child labor laws in agriculture would be changed to set a minimum age of 16 years to operate tractors on
public roads and 14 years to operate tractors on private land. The family farm exemption would be eliminated.
Federal and state OSHA would establish minimum age limits for all safety standards and would require workers
younger than 18 years to wear seatbelts and operate only tractors with ROPS. OSHA standards regarding tractor
operations would be enforceable on all farms regardless of number of employees.
Institution/organization Tractor manufacturers (e.g., via Association of Equipment Manufacturers [AEM] trade association) would publicly
announce a position statement that supports the OSHA standard. Agribusinesses would require compliance with
federal/state laws and OSHA standards as an expectation of entities from whom they purchase products. National
FFA would set a national standard that their Student Agricultural Experience (SAE) ensure youth are in settings
where they comply with this safety standard and announce their position via National FFA communication
mechanisms that reach advisors, members, and alumni. Other organizations such as the American Academy of
Pediatrics would post a position on this safety standard. The national media would publish stories about this
national campaign to protect young tractor operators. Media stories of lives saved would begin to shift traditional
thinking about guidelines for young people operating tractors.
Community A comprehensive social marketing campaign would be launched to “Safeguard Youth Operating Tractors.” The
campaign would be crafted with messages and dissemination strategies based on stakeholder input. Using targeted
campaign messages, including social media outlets at the regional and local level, FFA Chapters, schools, and faith-
based groups would facilitate efforts of farm owners to ensure any tractors operated by youth are safely equipped.
Incentives would be provided by local insurers and bankers, offering economic aid for farmers needing financial
assistance to upgrade their tractors operated by youth. These community groups would promulgate the campaign
messages and, where appropriate, the position statements issued by national-level organizations. School-based
activities would no longer promote “ride your tractor to school” events but would emphasize campaign messages
and facilitate tractor safety certification programs. Community-level advocates for the campaign would be trained to
deal with controversies surrounding the tractor topic.
Interpersonal Peer groups, friends, and relatives would share “Safeguard youth operating tractors” campaign materials and openly
encourage farm owners and parents to adopt the recommended practices and OSHA standards. These people would
reach out to underserved, hard-to-reach farm owners (e.g., niche farms, special populations) with the same
information and expectations regarding youth involved in agricultural work.
Adult Farm parents, farm owners, and employers would acknowledge the multilevel pressure being exerted to change
farm practices and comply with the new OSHA standard by not allowing youth to operate tractors unsafely.
Child/youth Young tractor operators would have strict safety standards set, having access only to ROPS tractors as well as
knowing and understanding they are required to wear seatbelts.
302 B. C. LEE ET AL.
https://www.google.com/search?q=socio-ecologic+models+cdc+images\%26tbm=isch\%26tbo=u\%26source=univ\%26sa=X\%26ved=0ahUKEwiL67r4mobUAhXp6oMKHYSUCuEQsAQIMg\%26biw=1152\%26bih=616
https://www.google.com/search?q=socio-ecologic+models+cdc+images\%26tbm=isch\%26tbo=u\%26source=univ\%26sa=X\%26ved=0ahUKEwiL67r4mobUAhXp6oMKHYSUCuEQsAQIMg\%26biw=1152\%26bih=616
https://www.google.com/search?q=socio-ecologic+models+cdc+images\%26tbm=isch\%26tbo=u\%26source=univ\%26sa=X\%26ved=0ahUKEwiL67r4mobUAhXp6oMKHYSUCuEQsAQIMg\%26biw=1152\%26bih=616
https://www.google.com/search?q=socio-ecologic+models+cdc+images\%26tbm=isch\%26tbo=u\%26source=univ\%26sa=X\%26ved=0ahUKEwiL67r4mobUAhXp6oMKHYSUCuEQsAQIMg\%26biw=1152\%26bih=616
https://www.google.com/search?q=socio-ecologic+models+cdc+images\%26tbm=isch\%26tbo=u\%26source=univ\%26sa=X\%26ved=0ahUKEwiL67r4mobUAhXp6oMKHYSUCuEQsAQIMg\%26biw=1152\%26bih=616
3. World Health Organization. The ecological framework.
2017. http://www.who.int/violenceprevention/
approach/ecology/en/. Accessed May 22, 2017.
4. Centers for Disease Control and Prevention. 2015. The
social-ecological model: a framework for prevention.
https://www.cdc.gov/violenceprevention/overview/
social-ecologicalmodel.html. Accessed July 3, 2017.
5. Sallis JF, Owen N, Fisher EB. Ecological models of
health behavior. In: Glanz K, Rimer BK, Viswanath
K, eds. Health Behavior and Health Education:
Theory, Research, and Practice. 4th ed. San Francisco:
Jossey-Bass; 2008:465–485.
6. Castillo D, Hard D, Myers J, Pizatella T, Stout N. A
national childhood agricultural injury prevention
initiative. J Agric Saf Health. 1998;4:183–191.
doi:10.13031/2013.15368.
7. National Committee for Childhood Agricultural Injury
Prevention. Children and Agriculture: Opportunities for
Safety and Heatlh. Marshfield, WI: Marshfield Clinic;
1996.
8. National Center of Excellence for the Prevention of
Childhood Agricultural Injury (RFA: OH-14-005);
Grant Application Submitted to National Institute for
Occupational Safety and Health. Marshfield, WI:
Marshfield Clinic Research Foundation; 2014.
9. Gallagher SS. Characteristics of evaluated childhood
agricultural safety interventions. J Agromedicine.
2012;17:109–126. doi:10.1080/1059924X.2012.664033.
10. Baron SL, Beard S, Davis LK, et al. Promoting integrated
approaches to reducing health inequities among low-
income workers: applying a social ecological framework.
Am J Ind Med. 2014;57:539–556. doi:10.1002/ajim.v57.5.
11. Robinson T. Applying the socio-ecological model to
improving fruit and vegetable intake among low-
income African American. J Community Health.
2008;33:395–406. doi:10.1007/s10900-008-9109-5.
12. Springfeldt B, Thorson J, Lee B. Sweden’s thirty-year
experience with tractor rollovers. J Agric Saf Health.
1998;4:173–180. doi:10.13031/2013.15355.
13. Reynolds SJ, Goves W. Effectiveness of roll-over pro-
tective structure in reducing farm tractor fatalities. Am
J Prev Med. 2000;18:63–69. doi:10.1016/S0749-3797(00)
00142-2.
14. Rauscher KJ, Myers DJ. Occupational fatalities among
young workers in the United States: 2001-2012. Am J
Ind Med. 2016;59:445–452. doi:10.1002/ajim.v59.6.
JOURNAL OF AGROMEDICINE 303
http://www.who.int/violenceprevention/approach/ecology/en/
http://www.who.int/violenceprevention/approach/ecology/en/
https://www.cdc.gov/violenceprevention/overview/social-ecologicalmodel.html
https://www.cdc.gov/violenceprevention/overview/social-ecologicalmodel.html
http://dx.doi.org/10.13031/2013.15368
http://dx.doi.org/10.1080/1059924X.2012.664033
http://dx.doi.org/10.1002/ajim.v57.5
http://dx.doi.org/10.1007/s10900-008-9109-5
http://dx.doi.org/10.13031/2013.15355
http://dx.doi.org/10.1016/S0749-3797(00)00142-2
http://dx.doi.org/10.1016/S0749-3797(00)00142-2
http://dx.doi.org/10.1002/ajim.v59.6
Abstract
Background
Modified model
Applying the SEM for agricultural safety
Agricultural safety
Burden
Solution
Implications
Conclusions
Funding
References
NIH Publication No. 05-3896
Printed September 2005
2931-NCI Theory cvr.f 11/17/05 3:18 PM Page 1
Theor y
at a Gl ance
U.S. DEPARTMENT
OF HEALTH AND
HUMAN SERVICES
National Institutes
of Health
A G u i d e F o r H e a l t h P ro m o t i o n P ra c t i ce
Theory
at a
Glance
A Guide For Health Promotion Practice
(Second Edition)
U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
National Institutes of Health
Foreword
A
decade ago, the first edition of Theory at a Glance was published. The guide was
a welcome resource for public health practitioners seeking a single, concise
summary of health behavior theories that was neither overwhelming nor superficial.
As a government publication in the public domain, it also provided cash-strapped
health departments with access to a seminal integration of scholarly work that was useful to
program staff, interns, and directors alike. Although they were not the primary target audience,
members of the public health research community also utilized Theory at a Glance, both as
a quick desk reference and as a primer for their students.
The National Cancer Institute is pleased to sponsor the publication of this guide, but its
relevance is by no means limited to cancer prevention and control. The principles described
herein can serve as frameworks for many domains of public health intervention,
complementing focused evidence reviews such as Centers for Disease Control and
Prevention’s Guide to Community Preventive Services. This report also complements a
number of other efforts by NCI and our federal partners to facilitate more rigorous testing
and application of health behavior theories through training workshops and the development
of new Web-based resources.
One reason theory is so useful is that it helps us articulate assumptions and hypotheses
concerning our strategies and targets of intervention. Debates among policymakers
concerning public health programs are often complicated by unspoken assumptions or
confusion about which data are relevant. Theory can inform these debates by clarifying key
constructs and their presumed relationships. Especially when the evidence base is small,
advocates of one approach or another can be challenged to address the mechanisms by
which a program is expected to have an impact. By specifying these alternative pathways to
change, program evaluations can be designed to ensure that regardless of the outcome,
improvements in knowledge, program design, and implementation will occur.
I am pleased to introduce this second edition of Theory at a Glance. I am especially
impressed that the lead authors, Dr. Barbara K. Rimer and Dr. Karen Glanz, have enhanced
and updated it throughout without diminishing the clarity and efficiency of the original. We
hope that this new edition will empower another generation of public health practitioners to
apply the same conceptual rigor to program planning and design that these authors exemplify
in their own research and practice.
Robert T. Croyle, Ph.D.
Director
Division of Cancer Control and Population Sciences
National Cancer Institute
Spring 2005
Acknowledgements
The National Cancer Institute would like to thank Barbara Rimer Dr.P.H. and
Karen Glanz Ph.D., M.P.H., authors of the original monograph, whose knowledge of
healthcommunications theory and practice have molded a generation of health promotion
practitioners. Both have provided hours of review and consultation, and we are grateful to
them for their contributions.
Thanks to the staffs of the Office of Communications, particularly Margaret Farrell,
and the Division of Cancer Control and Population Sciences and Kelly Blake, who guided
this monograph to completion. We appreciate in particular the work of Karen Harris,
whose attention to detail and commitment to excellence enhanced the monograph’s
content and quality.
Table of Contents
Introduction viii
Audience and Purpose 1
Contents 1
Part 1: Foundations of Theory in Health Promotion and Health Behavior 3
Why Is Theory Important to Health Promotion and Health Behavior Practice? 4
What Is Theory? 4
How Can Theory Help Plan Effective Programs? 4
Explanatory Theory and Change Theory 5
Fitting Theory to the Field of Practice 5
Using Theory to Address Health Issues in Diverse Populations 7
Part 2: Theories and Applications 9
The Ecological Perspective: A Multilevel, Interactive Approach 10
Theoretical Explanations of Three Levels of Influence 12
Individual or Intrapersonal Level 12
Health Belief Model 13
Stages of Change Model 15
Theory of Planned Behavior 16
Precaution Adoption Process Model 18
Interpersonal Level 19
Social Cognitive Theory 19
Community Level 22
Community Organization and Other Participatory Models 23
Diffusion of Innovations 27
Communication Theory 29
Media Effects 30
Agenda Setting 30
New Communication Technologies 31
Part 3: Putting Theory and Practice Together 35
Planning Models 36
Social Marketing 36
PRECEDE-PROCEED 39
Where to Begin: Choosing the Right Theories 43
A Few Final Words 44
Sources 48
References 49
Tables and Figures
Tables
Table 1 An Ecological Perspective: Levels of Influence 11
Table 2 Health Belief Model 14
Table 3 Stages of Change Model 15
Table 4 Theory of Planned Behavior 17
Table 5 Social Cognitive Theory 20
Table 6 Community Organization 24
Table 7 Concepts in Diffusion of Innovations 27
Table 8 Key Attributes Affecting the Speed and Extent of an Innovation’s Diffusion 28
Table 9 Agenda Setting, Concepts, Definitions, and Applications 31
Table 10 Diagnostic Elements of PRECEDE-PROCEED 42
Table 11 Summary of Theories: Focus and Key Concepts 45
Figures
Figure 1 Using Explanatory Theory and Change Theory to Plan and Evaluate Programs 6
Figure 2 A Multilevel Approach to Epidemiology 10
Figure 3 Theory of Reasoned Action and Theory of Planned Behavior 18
Figure 4 Stages of the Precaution Adoption Process Model 19
Figure 5 An Integrative Model 21
Figure 6 Sociocultural Environment Logic Framework 26
Figure 7 An Asthma Self-Management Video Game for Children 33
Figure 8 Social Marketing Wheel 38
Figure 9 The PRECEDE-PROCEED Model 40
Figure 10 Using Theory to Plan Multilevel Interventions 46
Introduction
viii
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his monograph, Theory at a Glance: Application to Health Promotion and Health
Behavior (Second Edition), describes influential theories of health-related behaviors,
processes of shaping behavior, and the effects of community and environmental
factors on behavior. It complements existing resources that offer tools, techniques,
and model programs for practice, such as Making Health Communication Programs Work:
A Planner’s Guide,i and the Web portal, Cancer Control PLANET (Plan, Link, Act, Network
with Evidence-based Tools).ii Theory at a Glance makes health behavior theory accessible
and provides tools to solve problems and assess the effectiveness of health promotion
programs. (For the purposes of this monograph, health promotion is broadly defined as the
process of enabling people to increase control over, and to improve, their health. Thus, the
focus goes beyond traditional primary and secondary prevention programs.)
For nearly a decade, public health and health care practitioners have consulted the original
version of Theory at a Glance for guidance on using theories about human behavior to inform
program planning, implementation, and evaluation. We have received many testimonials
about the First Edition’s usefulness, and requests for additional copies. This updated edition
includes information from recent health behavior research and suggests theoretical
approaches to developing programs for diverse populations. Theory at a Glance can be
used as a stand-alone handbook, as part of in-house staff development programs, or in
conjunction with theory texts and continuing education workshops.
For easy reference, the monograph includes only a small number of current and applicable
health behavior theories. The theories reviewed here are widely used for the purposes of
cancer control, defining risk, and segmenting populations. Much of the content for this
publication has been adapted from the third edition of Glanz, Rimer, and Lewis’ Health
Behavior and Health Education: Theory, Research, and Practice,1 published by Jossey-Bass
in San Francisco. Readers who want to learn more about useful theories for health behavior
change and health education practice can consult this and other sources that are
recommended in the References section at the end of the monograph.
i Making Health Communication Programs Work (http://www.nci.nih.gov/pinkbook/) describes a practical
approach for planning and implementing health communication efforts.
ii Cancer Control PLANET (http://cancercontrolplanet.cancer.gov) provides access to data and resources
that can help planners, program staff, and researchers to design, implement, and evaluate evidence-based
cancer control programs.
(http://www.nci.nih.gov/pinkbook/)
(http://cancercontrolplanet.cancer.gov)
Audience and Purpose
This monograph is written primarily for public health workers in state and local health
agencies; it is also valuable for health promotion practitioners and volunteers who work in
voluntary health agencies, community organizations, health care settings, schools, and the
private sector.
Interventions based on health behavior theory are not guaranteed to succeed, but they are
much more likely to produce desired outcomes. Theory at a Glance is designed to help users
understand how individuals, groups, and organizations behave and change—knowledge they
can use to design effective programs. For information about specific, evidence-based
interventions to promote health and prevent disease, readers may also wish to consult the
Guide to Community Preventive Services, published by the Centers for Disease Control and
Prevention (CDC) at www.thecommunityguide.org.
Contents
This monograph consists of three parts. For each theory, the text highlights key concepts
and their applications. These summaries may be used as “checklists” of important issues to
consider when planning or evaluating programs or to prompt project teams to think about the
range of factors that influence health behavior.
Part 1. Foundations of Theory in Health Promotion and Health Behavior describes ways that
theories and models can be useful in health behavior/health promotion practice and
provides basic definitions.
Part 2. Theories and Applications presents an ecological perspective on health
behavior/health promotion programs. It describes eight theories and models that
explain individual, interpersonal, and community behavior and offers approaches to
solving problems. A brief description of each theory is followed by definitions of key
concepts and examples or case studies. The section also explores the use of new
communication technologies.
Part 3. Putting Theory and Practice Together explains how theory can be used in health
behavior/health promotion program planning, implementation, and evaluation.
Two comprehensive planning models, PRECEDE-PROCEED and social marketing,
are reviewed.
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Part 1
Foundations of Theory
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Why Is Theory Important to
Health Promotion and Health
Behavior Practice?
Effective public health, health promotion,
and chronic disease management programs
help people maintain and improve health,
reduce disease risks, and manage chronic
illness. They can improve the well-being
and self-sufficiency of individuals, families,
organizations, and communities. Usually,
such successes require behavior change at
many levels, (e.g., individual, organizational,
and community).
Not all health programs and initiatives are
equally successful, however. Those most
likely to achieve desired outcomes are
based on a clear understanding of targeted
health behaviors, and the environmental
context in which they occur. Practitioners
use strategic planning models to develop
and manage these programs, and
continually improve them through
meaningful evaluation. Health behavior
theory can play a critical role throughout
the program planning process.
What Is Theory?
A theory presents a systematic way of
understanding events or situations. It is a
set of concepts, definitions, and propositions
that explain or predict these events or
situations by illustrating the relationships
between variables. Theories must be
applicable to a broad variety of situations.
They are, by nature, abstract, and don’t
have a specified content or topic area.
Like empty coffee cups, theories have
shapes and boundaries, but nothing inside.
They become useful when filled with
practical topics, goals, and problems.
• Concepts are the building blocks—the
primary elements—of a theory.
• Constructs are concepts developed or
adopted for use in a particular theory.
The key concepts of a given theory are
its constructs.
• Variables are the operational forms of
constructs. They define the way a
construct is to be measured in a specific
situation. Match variables to constructs
when identifying what needs to be
assessed during evaluation of a theory-
driven program.
• Models may draw on a number of theories
to help understand a particular problem in
a certain setting or context. They are not
always as specified as theory.
Most health behavior and health promotion
theories were adapted from the social and
behavioral sciences, but applying them to
health issues often requires that one be
familiar with epidemiology and the biological
sciences. Health behavior and health
promotion theories draw upon various
disciplines, such as psychology, sociology,
anthropology, consumer behavior, and
marketing. Many are not highly developed
or have not been rigorously tested. Because
of this, they often are called conceptual
frameworks or theoretical frameworks; here
the terms are used interchangeably.
How Can Theory Help Plan
Effective Programs?
Theory gives planners tools for moving
beyond intuition to design and evaluate
health behavior and health promotion
interventions based on understanding of
behavior. It helps them to step back and
consider the larger picture. Like an artist,
a program planner who grounds health
interventions in theory creates innovative
ways to address specific circumstances.
He or she does not depend on a “paint-by
numbers” approach, re-hashing stale ideas,
but uses a palette of behavior theories,
skillfully applying them to develop unique,
tailored solutions to problems.
Using theory as a foundation for program
planning and development is consistent with
the current emphasis on using evidence-
based interventions in public health,
behavioral medicine, and medicine. Theory
provides a road map for studying problems,
developing appropriate interventions, and
evaluating their successes. It can inform the
planner’s thinking during all of these stages,
offering insights that translate into stronger
programs. Theory can also help to explain
the dynamics of health behaviors, including
processes for changing them, and the
influences of the many forces that affect
health behaviors, including social and
physical environments. Theory can also help
planners identify the most suitable target
audiences, methods for fostering change,
and outcomes for evaluation.
Researchers and practitioners use theory
to investigate answers to the questions of
“why,” “what,” and “how” health problems
should be addressed. By seeking answers
to these questions, they clarify the nature
of targeted health behaviors. That is, theory
guides the search for reasons why people
do or do not engage in certain health
behaviors; it helps pinpoint what planners
need to know before they develop public
health programs; and it suggests how to
devise program strategies that reach target
audiences and have an impact. Theory also
helps to identify which indicators should be
monitored and measured during program
evaluation. For these reasons, program
planning, implementation, and monitoring
processes based in theory are more likely
to succeed than those developed without
the benefit of a theoretical perspective.
Explanatory Theory and
Change Theory
Explanatory theory describes the reasons
why a problem exists. It guides the search
for factors that contribute to a problem (e.g.,
a lack of knowledge, self-efficacy, social
support, or resources), and can be changed.
Examples of explanatory theories include
the Health Belief Model, the Theory of
Planned Behavior, and the Precaution
Adoption Process Model.
Change theory guides the development of
health interventions. It spells out concepts
that can be translated into program
messages and strategies, and offers a basis
for program evaluation. Change theory
helps program planners to be explicit about
their assumptions for why a program will
work. Examples of change theories include
Community Organization and Diffusion of
Innovations. Figure 1. illustrates how
explanatory theory and change theory can
be used to plan and evaluate programs.
Fitting Theory to the Field of Practice
This monograph includes descriptions and
applications of some theories that are
central to health behavior and health
promotion practice today. No single theory
dominates health education and promotion,
nor should it; the problems, behaviors,
populations, cultures, and contexts of public
health practice are broad and varied. Some
theories focus on individuals as the unit of
change. Others examine change within
families, institutions, communities, or
cultures. Adequately addressing an issue
may require more than one theory, and no
one theory is suitable for all cases.
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Figure 1. Using Explanatory Theory and Change Theory to Plan and Evaluate Programs
Problem
Behavior
or
Situation
ChangeTheory
Which strategies?
Which messages?
Assumptions about
how a program
should work
Evaluation
Planning
Explanatory
Theory
Why?
What can
be changed?
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Because the social context in which
behavior occurs is always evolving, theories
that were important in public health
education a generation ago may be of
limited use today. At the same time, new
social science research allows theorists to
refine and adapt existing theories. A recent
Institute of Medicine report2 observed that
several theorists have converged in their
views, identifying several variables as
central to behavior change. As a result,
some constructs, such as self-efficacy, are
central to multiple theories.
Effective practice depends on using
theories and strategies that are appropriate
to a situation.
One of the greatest challenges for those
concerned with behavior change is learning
to analyze how well a theory or model “fits”
a particular issue. A working knowledge of
specific theories, and familiarity with how
they have been applied in the past,
improves skills in this area. Selecting an
appropriate theory or combination of
theories helps take into account the multiple
factors that influence health behaviors.
The practitioner who uses theory develops a
nuanced understanding of realistic program
outcomes that drives the planning process.
Choosing a theory that will bring a useful
perspective to the problem at hand does not
begin with a theory (e.g., the most familiar
theory, the theory mentioned in a recent
journal article, etc.). Instead, this process
starts with a thorough assessment of the
situation: the units of analysis or change,
the topic, and the type of behavior to be
addressed. Because different theoretical
frameworks are appropriate and practical for
different situations, selecting a theory that
“fits” should be a careful, deliberate process.
Start with the steps in the box at the top of
the next page.
A Good Fit:
Characteristics of a Useful Theory
A useful theory makes assumptions about
a behavior, health problem, target
population, or environment that are:
• Logical;
• Consistent with everyday observations;
• Similar to those used in previous
successful programs; and
• Supported by past research in the same
area or related ideas.
Using Theory to Address Health
Issues in Diverse Populations
The U.S. population is growing more
culturally and ethnically diverse. An
increasing body of research shows health
disparities exist among various ethnic and
socio-economic groups. These findings
highlight the importance of understanding
the cultural backgrounds and life
experiences of community members, though
research has not yet established when and
under what circumstances targeted or
tailored health communications are more
effective than generic ones. (Targeting
involves using information about shared
characteristics of a population subgroup to
create a single intervention approach for
that group. In contrast, tailoring is a process
that uses an assessment to derive
information about one specific person, and
then offers change or information strategies
for an outcome of interest based on that
person’s unique characteristics.)3
Most health behavior theories can be
applied to diverse cultural and ethnic
groups, but health practitioners must
understand the characteristics of target
populations (e.g., ethnicity, socioeconomic
status, gender, age, and geographical
location) to use these theories correctly.
There are several reasons why culture and
ethnicity are critical to consider when
applying theory to a health problem. First,
morbidity and mortality rates for different
diseases vary by race and ethnicity; second,
there are differences in the prevalence of
risk behaviors among these groups; and
third, the determinants of health behaviors
vary across racial and ethnic groups.
What People in the Field Say About Theory
“Theory is different from most of the tools
I use in my work. It’s more abstract, but
that can be a plus too. A solid grounding
in a handful of theories goes a long way
toward helping me think through why I
approach a health problem the way I do.”
— County Health Educator
“I used to think theory was just for
students and researchers. But now I have
a better grasp of it; I appreciate how
practical it can be.”
— State Chronic Disease Administrator
“By translating concepts from theory
into real-world terms, I can get my staff
and community volunteers to take a closer
look at why we’re conducting programs
the way we do, and how they can succeed
or fail.”
— City Tobacco Control Coordinator
“A good grasp of theory is essential for
leadership. It gives you a broader way
of viewing your work. And it helps create
a vision for the future. But, of course, it’s
only worthwhile if I can translate it clearly
and simply to my co-workers.”
— Regional Health Promotion Chief
“It’s not as hard as I thought it would be
to keep up with current theories. More
than ever these days, there are tools and
workshops to update us often.”
— Patient Education Coordinator
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Part 2
Theories and Applications
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The Ecological Perspective: A
Multilevel, Interactive Approach
Contemporary health promotion involves
more than simply educating individuals
about healthy practices. It includes efforts
to change organizational behavior, as well
as the physical and social environment of
communities. It is also about developing and
advocating for policies that support health,
such as economic incentives. Health
promotion programs that seek to address
health problems across this spectrum
employ a range of strategies, and operate
on multiple levels.
The ecological perspective emphasizes the
interaction between, and interdependence
of, factors within and across all levels of a
health problem. It highlights people’s
interactions with their physical and socio
cultural environments. Two key concepts
of the ecological perspective help to identify
intervention points for promoting health:
first, behavior both affects, and is affected
by, multiple levels of influence; second,
individual behavior both shapes, and is
shaped by, the social environment
(reciprocal causation).
To explain the first key concept of the
ecological perspective, multiple levels of
influence, McLeroy and colleagues (1988)4
identified five levels of influence for health-
related behaviors and conditions. Defined
in Table 1., these levels include: (1)
intrapersonal or individual factors; (2)
interpersonal factors; (3) institutional or
organizational factors; (4) community
factors; and (5) public policy factors.
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Figure 2. A Multilevel Approach to Epidemiology
Social and Economic Policies
Institutions
Neighborhoods and Communities
Living Conditions
Social Relationships
Individual Risk Factors
Pathophysiological
Pathways
Individual/Population
Health
Genetic/Constitutional
Factors
Envir
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Li
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Source: Smedley BD, Syme SL (eds.), Institute of Medicine. Promoting Health: Strategies from Social and Behavioral
Research. Washington, D.C.:, National Academies Press, 2000.
Table 1. An Ecological Perspective: Levels of Influence
Concept
Intrapersonal Level
Interpersonal Level
Community Level
Institutional Factors
Community Factors
Public Policy
Definition
Individual characteristics that influence behavior, such as
knowledge, attitudes, beliefs, and personality traits
Interpersonal processes and primary groups, including
family, friends, and peers that provide social identity,
support, and role definition
Rules, regulations, policies, and informal structures, which
may constrain or promote recommended behaviors
Social networks and norms, or standards, which exist as
formal or informal among individuals, groups, and
organizations
Local, state, and federal policies and laws that regulate
or support healthy actions and practices for disease
prevention, early detection, control, and management
In practice, addressing the community level
requires taking into consideration
institutional and public policy factors, as well
as social networks and norms. Figure 2.
illustrates how different levels of influence
combine to affect population health.
Each level of influence can affect health
behavior. For example, suppose a woman
delays getting a recommended
mammogram (screening for breast cancer).
At the individual level, her inaction may be
due to fears of finding out she has cancer.
At the interpersonal level, her doctor may
neglect to tell her that she should get the
test, or she may have friends who say they
do not believe it is important to get a
mammogram. At the organizational level,
it may be hard to schedule an appointment,
because there is only a part-time radiologist
at the clinic. At the policy level, she may
lack insurance coverage, and thus be
unable to afford the fee. Thus, the outcome,
the woman’s failure to get a mammogram,
may result from multiple factors.
The second key concept of an ecological
perspective, reciprocal causation, suggests
that people both influence, and are
influenced by, those around them. For
example, a man with high cholesterol may
find it hard to follow the diet his doctor has
prescribed because his company cafeteria
doesn’t offer healthy food choices. To
comply with his doctor’s instructions, he can
try to change the environment by asking the
cafeteria manager to add healthy items to
the menu, or he can dine elsewhere. If he
and enough of his fellow employees decide
to find someplace else to eat, the cafeteria
may change its menu to maintain lunch
business. Thus, the cafeteria environment
may compel this man to change his dining
habits, but his new habits may ultimately
bring about change in the cafeteria as well.
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An ecological perspective shows the
advantages of multilevel interventions that
combine behavioral and environmental
components. For instance, effective
tobacco control programs often use
multiple strategies to discourage smoking.5
Employee smoking cessation clinics have
a stronger impact if the workplace has a
no-smoking policy and the city has a clean
indoor air ordinance. Adolescents are
less likely to begin smoking if their
peers disapprove of the habit and laws
prohibiting tobacco sales to minors
are strictly enforced. Health promotion
programs are more effective when
planners consider multiple levels of
influence on health problems.
Theoretical Explanations of Three
Levels of …
Theory of Reasoned Action, Theory of Planned Behavior,
Background
The Theory of Reasoned Action is used to explain and predict behavior.
Based on attitudes, norms, and intentions
Individual motivational factors influence the likelihood of performing a behavior.
Developed by Icek Ajzen and Martin Fishbein.
(Edberg, 2007)
2
3
3
Behavioral intention is one of the strongest predictors of behavior.
Attitude here focuses on towards the behavior not the object (e.g., disease).
For example, if the goal is to reduce HIV infections, practitioners should focus on addressing attitudes towards condom use as opposed to teaching HIV pathology.
Behavioral Beliefs
Beliefs about the likely consequences of the behavior.
Produce a favorable or unfavorable attitude towards the behavior.
. Example: If I drink too much, then…
(Edberg, 2007)
4
Evaluation of Behavioral Beliefs
Value attached to outcome or attribute.
Produce a favorable or unfavorable attitude towards the behavior.
Example: Missing class because I drank too much would be…
(Edberg, 2007)
5
Subjective Norms
Belief about what is “normal,” and (as defined by the term itself) is subjective (i.e., based on one’s perception)
6
Normative Beliefs
Beliefs about whether referent individuals will approve or disapprove of the behavior.
Example: If I drank too much, my significant other would…
(Edberg, 2007)
Motivation to comply refers to the motivation to do what each referent thinks.
based on the example above, this could be, “it is important for me to make my significant other happy.”
7
But…
Something seemed to be missing.
8
Evolution from TRA to TPB
Fishbein & Ajzen realized the TRA does not address external factors.
TRA doesn’t account for peoples’ perception of the power or control they have over their behaviors.
Perceived Behavioral Control
(Edberg, 2007)
9
10
Perceived Behavioral Control
Perceived Behavioral Control
Control Beliefs
Perceived Power
Perceived behavioral control: The amount of control over a behavior people perceive that they have
11
Control Beliefs
Perceived Behavioral Control
Control Beliefs
Perceived Power
The perceived likelihood of doing the behavior or not.
Example: having sex while intoxicated
12
Perceived Power
Perceived Behavioral Control
Control Beliefs
Perceived Power
Beliefs regarding the presence of factors that could impact doing the behavior.
Example: being intoxicated will make it harder to have sex.
13
General Rule
In most cases:
the more positive the attitude,
the greater the perceived approval (subjective norm),
the stronger the perceived control,
the more likely the person’s intention is to perform the behavior.
14
15
Critiques
The longer the time interval between Behavioral Intention and Behavior, the less likely the behavior will occur.
I will work out today vs.
I will workout in a couple of months
The theory is based on the assumption that human beings are rational and make systematic decisions based on available information. Unconscious motives are not considered.
(Glanz, Rimer, & Viswanath, 2008)
16
Critiques
Factors such as personality and demographic variables are not taken into consideration.
There is much ambiguity regarding how to define Perceived Behavioral Control and this creates measurement problems.
Assumption is made that Perceived Behavioral Control predicts actual behavioral control. This may not always be the case.
(Glanz, Rimer, & Viswanath, 2008)
17
References
Glanz, K., Rimer, B., & Lewis, F. (Eds.). (2002). Health Behavior and Health Education: Theory, Research, and Practice. San Francisco, CA: Jossey-Bass.
Glanz, K., & Rimer, B. K. (1997). Theory at a glance: a guide for health promotion practice. Bethesda, Md.: U.S. Dept. of Health and Human Services, Public Health Service, National Institutes of Health, National Cancer Institute.
THEORY OF REASONED ACTION
Motivation to Comply
Behavioral Beliefs
Behavioral Intention
Behavior
Subjective Norm
Attitude Toward Behavior
Normative Beliefs
Evaluations of Behavioral Outcomes
THEORY OF REASONED ACTION
Behavioral
Beliefs
Evaluations
of
Behavioral
Outcomes
Normative
Beliefs
Motivation
to Comply
Attitude
Toward
Behavior
Subjective
Norm
Behavioral
Intention
Behavior
THEORY OF PLANNED BEHAVIOR
Behavioral Beliefs
Behavior
Subjective Norm
Attitude Toward Behavior
Behavioral Intention
Perceived Behavioral Control
Perceived Power
Control Beliefs
Motivation to Comply
Normative Beliefs
Evaluations of Behavioral Outcomes
THEORY OF PLANNED BEHAVIOR
Behavioral
Beliefs
Evaluations
of
Behavioral
Outcomes
Normative
Beliefs
Motivation
to Comply
Attitude
Toward
Behavior
Subjective
Norm
Behavioral
Intention
Behavior
Control
Beliefs
Perceived
Power
Perceived
Behavioral
Control
*Constructs
Definition
Behavioral intention
Perceived likelihood of performing the behavior
Attitude Behavioral Belief
Belief that behavioral performance is associated with certain attributes or outcomes
Evaluation
Value attached to a behavioral outcome or attribute
Subjective norm
Normative Belief
Belief about whether each referent approves or disapproves of the behavior
Motivation to Comply
Motivation to do what each referent thinks
Perceived behavioral control
Control Belief (TPB)
Perceived likelihood of occurrence of each facilitating or constraining condition
Perceived power (TPB)
Perceived effect of each condition in making behavioral performance difficult or easy
*Constructs Definition
Behavioral intention Perceived likelihood of performing the behavior
Attitude Behavioral
Belief
Belief that behavioral performance is associated
with certain attributes or outcomes
Evaluation
Value attached to a behavioral out come or
attribute
Subjective norm
Normative Belief
Belief about whether each referent approves or
disapproves of the behavior
Motivation to
Comply
Motivation to do what each referent thinks
Perceived
behavioral control
Control Belief (TPB)
Perceived likelihood of occurrence of each
facilitating or constraining condition
Perceived power
(TPB)
Perceived effect of each condition in making
behavioral performance difficult or easy
Reducing Cyberbullying: A Theory of Reasoned
Action-Based Video Prevention Program for
College Students
Ashley N. Doane1*, Michelle L. Kelley2, and Matthew R. Pearson3
1Psychology Department, Chowan University, Murfreesboro, North Carolina
2Psychology Department, Old Dominion University, Norfolk, Virginia
3Center on Alcoholism, Substance Abuse, and Addictions, University of New Mexico, Albuquerque, New Mexico
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Few studies have evaluated the effectiveness of cyberbullying prevention/intervention programs. The goals of the present study
were to develop a Theory of Reasoned Action (TRA)-based video program to increase cyberbullying knowledge (1) and empathy
toward cyberbullying victims (2), reduce favorable attitudes toward cyberbullying (3), decrease positive injunctive (4) and
descriptive norms about cyberbullying (5), and reduce cyberbullying intentions (6) and cyberbullying behavior (7). One hundred
sixty-seven college students were randomly assigned to an online video cyberbullying prevention program or an assessment-only
control group. Immediately following the program, attitudes and injunctive norms for all four types of cyberbullying behavior
(i.e., unwanted contact, malice, deception, and public humiliation), descriptive norms for malice and public humiliation,
empathy toward victims of malice and deception, and cyberbullying knowledge significantly improved in the experimental
group. At one-month follow-up, malice and public humiliation behavior, favorable attitudes toward unwanted contact,
deception, and public humiliation, and injunctive norms for public humiliation were significantly lower in the experimental than
the control group. Cyberbullying knowledge was significantly higher in the experimental than the control group. These findings
demonstrate a brief cyberbullying video is capable of improving, at one-month follow-up, cyberbullying knowledge,
cyberbullying perpetration behavior, and TRA constructs known to predict cyberbullying perpetration. Considering the low
cost and ease with which a video-based prevention/intervention program can be delivered, this type of approach should be
considered to reduce cyberbullying. Aggr. Behav. 42:136–146, 2016. © 2015 Wiley Periodicals, Inc.
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
Keywords: cyberbullying; prevention; attitudes; norms; college students
INTRODUCTION
Cyberbullying, defined as “willful and repeated harm
inflicted through the use of computers, cell phones, and
other electronic devices” (Hinduja & Patchin, 2009, p. 5),
has been a frequent topic in the media over the past few
years. Reports have shown that youth (e.g., De Nies,
Donaldson, & Netter, 2010; Michels, 2008; Smith-Spark
& Vandoorne, 2013) and a college student (Friedman,
2010) committed suicide after beingcyberbullied.Despite
growing media attention to the issue ofcyberbullying, few
cyberbullying prevention/intervention programs have
been developed and evaluated (e.g., Lee, Zi-Pei,
Svanstr€om, & Dalal, 2013; Menesini, Nocentini, &
Palladino, 2012; Williford et al., 2014; W€olfer et al.,
2014). Furthermore, these prevention programs have been
developed for youth. In the present study, we developed
and tested a cyberbullying prevention program for college
students based on constructs outlined by the Theory of
Reasoned Action (TRA; Ajzen, 1985).
Cyberbullying Prevalence
Although not as extensive as research on youth
(Tokunaga, 2010), a few studies have examined college
students’ experiences of cyberbullying. In three studies
that assessed cyberbullying experiences during college,
approximately 9–11\% of college students reported
having been cyberbullied at their university (Kraft &
Wang, 2010; Schenk & Fremouw, 2012; Walker,
Sockman, & Koehn, 2011). Other studies have found
higher rates of cyberbullying victimization among
�Correspondence to: Ashley N. Doane, Psychology Department, Chowan
University, 1 University Place, Murfreesboro, NC 27855.
E-mail: [email protected]
Received 16 November 2014; Accepted 30 April 2015
DOI: 10.1002/ab.21610
Published online 9 September 2015 in Wiley Online Library
(wileyonlinelibrary.com).
AGGRESSIVE BEHAVIOR
Volume 42, pages 136–146 (2016)
© 2015 Wiley Periodicals, Inc.
college students (54\%, Aricak, 2009; 55\%, DilmaSc,
2009; 22\%, MacDonald & Roberts-Pittman, 2010; 18\%,
Whittaker & Kowalski, 2015). Perpetration rates have
varied from approximately 9–23\% (20\% Aricak, 2009;
23\%, DilmaSc, 2009; 9\%, MacDonald & Roberts-
Pittman, 2010; 12\%, Whittaker & Kowalski, 2015). In
a recent study of college students, Kokkinos, Antonia-
dou, and Markos (2014) identified 11\% of the sample as
cyberbullying victims (only), 14\% as cyberbullying
perpetrators (only), and 33\% as both cyberbullying
victims and perpetrators. However, definitions, regions,
modes of communication included (e.g., cell phones,
email), specific types of behavior assessed, and assess-
ment time frames have varied considerably across these
studies. More recently, the Cyberbullying Experiences
Survey (CES), a comprehensive measure of cyberbully-
ing, was developed. The CES assesses 21 victimization
and 20 perpetration behaviors that reflect four distinct
types of cyberbullying: deception, malice, public
humiliation, and unwanted contact (Doane, Kelley,
Chiang, & Padilla, 2013). Using this multidimensional
assessment of cyberbullying, approximately 78\% of
participants reported experiencing and 53\% reported
perpetrating at least one instance of cyberbullying
involving deception, 88\% experienced and 78\% perpe-
trated cyberbullying involving malice, 73\% experienced
and 38\% perpetrated cyberbullying involving public
humiliation, and 66\% experienced and 29\% perpetrated
cyberbullying involving unwanted contact.
Consequences of Cyberbullying
Research has shown that cyberbullying victims and
perpetrators are at greater risk for mental health and
school problems. Cyberbullying victimization in sam-
ples of youth is associated with school problems (e.g.,
suspension, detention, skipping school, and carrying a
weapon to school; Ybarra, Diener-West, & Leaf, 2007),
emotional problems (e.g., depressive symptoms; Bo-
nanno & Hymel, 2013; Perren, Dooley, Shaw, & Cross,
2010; Ybarra, 2004), suicidal ideation (Bonanno &
Hymel, 2013; Hinduja & Patchin, 2010), and suicide
attempts (Hinduja & Patchin, 2010). In addition,
cyberbullying perpetration is also related to depressive
symptoms (Bonanno & Hymel, 2013), suicidal ideation
(Bonanno & Hymel, 2013; Hinduja & Patchin, 2010),
and suicide attempts (Hinduja & Patchin, 2010).
In a study of college students, Aricak (2009) found
that cyberbullying victims reported higher somatization,
phobic anxiety, paranoid ideation, anxiety, symptoms of
obsessive–compulsive disorder, and depression than
students not involved in cyberbullying. In addition,
those who were both victims and perpetrators of
cyberbullying reported higher somatization, anxiety,
hostility, and paranoid ideation, as well as more
psychotic symptoms than college students not involved
in it. Given the frequency of cyberbullying and the
negative consequences associated with cyberbullying,
low-cost, easily implemented, effective cyberbullying
prevention programs are needed for college students.
Theory of Reasoned Action
The proposed study was guided by the TRA. TRA
posits that attitudes toward a particular behavior (i.e., the
degree to which it is positively or negatively evaluated),
injunctive norms regarding it (i.e., the perception of
others’ approval or disapproval of performing it), and
descriptive norms (i.e., the perception that others
actually engage in it) influence behavioral intentions,
which in turn has a direct effect on the behavior itself
(Fishbein & Ajzen, 2010). Based on this theory,
decreasing positive attitudes toward the behavior and
decreasing positive perceived norms about it are
expected to decrease intentions to perform the behavior;
ultimately, reducing intentions to perform the behavior
should reduce the likelihood of it being carried out.
Violence prevention researchers have argued for the
need to assess attitude change (e.g., Limber, Nation,
Tracy, Melton, & Flerx, 2004; Weisz & Black, 2001).
Bullies tend to have more positive attitudes towards
violence and low empathy toward victims of bullying
(Olweus, 1993a). Therefore, Olweus (1993a, 1993b)
recommends that bullying interventions focus on
changing the attitudes and behavior of bullies and
having students empathize with victims. Recent studies
on children (Elledge et al., 2013) and college students
(Barlett & Gentile, 2012; Boulton, Lloyd, Down, &
Marx, 2012; Doane, Pearson, & Kelley, 2014) have
found positive relationships between favorable attitudes
toward cyberbullying and cyberbullying perpetration.
Using the four-factor cyberbullying perpetration scale
of the CES, Doane et al. (2014) found that attitudes,
descriptive norms, and injunctive norms significantly
predicted cyberbullying intentions, and cyberbullying
intentions predicted cyberbullying behavior. Although
there were some differences between types of cyber-
bullying behavior in terms of which specific TRA
constructs predicted cyberbullying perpetration, positive
attitudes toward cyberbullying was the strongest
predictor of cyberbullying intentions, and cyberbullying
intentions were substantially related to cyberbullying
perpetration. Another study examined the Theory of
Planned Behavior (TPB; Ajzen, 2012), which includes
the TRA constructs as well as perceived behavioral
control, or the degree to which a person believes they are
able to perform a particular behavior (Heirman &
Walrave, 2012). Likewise, they found that attitudes,
subjective norms (i.e., injunctive norms), and perceived
behavioral control were significant predictors of
Aggr. Behav.
Cyberbullying Prevention: Theory of Reasoned Action 137
cyberbullying intentions, which in turn predicted
cyberbullying perpetration. Thus, at least two studies
provide support that modifying TRA constructs may
be an effective means of reducing cyberbullying
perpetration.
Empathy
In addition to TRA constructs, empathy has been
associated with cyberbullying. Studies measuring
empathy in general (Schultze-Krumbholz & Scheitha-
uer, 2009) and empathy specifically related to cyber-
bullying (Doane et al., 2014; Steffgen, K€onig, Pfetsch, &
Melzer, 2011) found higher levels of empathy to be
associated with lower levels of cyberbullying. When
examining affective and cognitive empathy separately,
relationships with cyberbullying perpetration were
inconsistent (Ang & Goh, 2010; Renati, Berrone, &
Zanetti, 2012; Topcu & Erdur-Baker, 2012). Doane et al.
(2014) found the negative associations between empathy
and cyberbullying perpetration to be fully mediated by
TRA constructs such that higher empathy was associated
with less positive attitudes, lower injunctive norms, and
lower descriptive norms for all four types of cyberbully-
ing assessed.
Cyberbullying Prevention Programs for Youth
Several recent multidisciplinary and international
efforts have demonstrated the effectiveness of youth
cyberbullying prevention programs. These programs
vary in length from one-day programs (e.g., W€olfer
et al., 2014) to those that take place over the course of the
school-year (e.g., ViSC Social Competence Program,
Gradinger, Yanagida, Strohmeier, & Spiel, 2015; KiVa
Antibullying Program, Williford et al., 2014). Moreover,
programs also vary in terms of whether they are taught
by trained teachers (Cross, Campbell, Slee, Spears, &
Barnes, 2013; Gradinger et al., 2015; W€olfer et al.,
2014), involve a combination of peer educators and
teacher-led instruction (e.g., Menesini et al., 2012), or
are self-guided but allow interaction with other students
(e.g., Lee et al., 2013). In some instances, they are
delivered in the community (e.g., “Keep it Tame”; Spears
& Zeederberg, 2013) or both in school and the
community (e.g., Cyber Friendly School Project; see
Cross et al., 2013; Campbell, Cross, Spears, & Slee,
2010). Although the results of many of these programs
are preliminary, in general, they have shown benefits in
terms of improved cyberbullying knowledge and
perspective-taking skills and reduced aggressive
behavior.
Prevention Program Characteristics
Although cyberbullying prevention programs have
largely relied on in-person instruction and interactions,
videos have been used in a variety of prevention
programs across other fields, including programs
targeting problems such as workplace violence (e.g.,
Peek-Asa, Casteel, Mineschian, Erickson, & Kraus,
2004), substance abuse or tobacco use (e.g., Ferketich,
Kwong, Shek, & Mae, 2007; Ramirez, Gallion,
Espinoza, & Chalela, 1999), pathological gambling
(e.g., Doiron & Nicki, 2007), and eating disorders (e.g.,
Heinze, Wertheim, & Kashima, 2000; Withers, Twigg,
Wertheim, & Paxton, 2002; Withers & Wertheim,
2004). Prevention programs including videos have been
shown to be effective in increasing empathy toward
victims of rape (e.g., Foubert & Cowell, 2004;
O’Donohue, Yeater, & Fanetti, 2003). Furthermore,
participants in Foubert and Cowell’s study rated the
video aspect of the program as the most powerful part
of the program.
In traditional bullying prevention programs, Olweus
(1993a) recommends using videos of bullying exam-
ples to clarify bullying behavior. The video commonly
used in the school-based Olweus Bullying Prevention
Program is 11 min in length and consists of four
bullying situation vignettes (Olweus, Limber, &
Mihalic, 1999). In addition to providing bullying
information, the bullying video “elicits emotional, ‘gut
feeling’ reactions from the audience” (p. 28). In a study
of Italian youth, Baldry and Farrington (2004)
evaluated a bullying and victimization intervention
program which consisted of three videos, a booklet,
role-playing, and discussions. Youth reported signifi-
cantly less bullying and victimization at post-inter-
vention than pre-intervention.
Internet-based prevention programs have been
used to target many areas, including smoking (see
Walters, Wright, & Shegog, 2006 for a review), HIV
(e.g., Bowen, Williams, Daniel, & Clayton, 2008;
Roberto et al., 2008), drug abuse (e.g., Schwinn,
Schinke, & di Noia, 2010), and depression (e.g., Van
Voorhees et al., 2009). Conn (2010) recommends
increasing the use of Internet-based health preven-
tion programs due to their lower cost, higher
consistency, greater accessibility (i.e., both tempo-
rally and with physical location), and the ability for
program participants to remain anonymous. Extrap-
olating from the results of previous studies, a video-
based cyberbullying prevention program that con-
tains brief informational segments combined with
short depictions of common cyberbullying incidents
that show victim responses, and peers commenting
on the inappropriateness of these actions, may be
effective in reducing positive cyberbullying attitudes
and behavior. Moreover, the technology currently
exists to widely disseminate this type of program at
low cost.
Aggr. Behav.
138 Doane et al.
Present Study
Based on the TRA and previous research, the purpose
of the present study was to evaluate the success of a
video-based cyberbullying prevention program devel-
oped by the first author presented in an online format
(Doane, 2011). It was predicted that: (1) compared to
baseline, positive attitudes toward cyberbullying, pos-
itive injunctive and descriptive norms concerning
cyberbullying, and intentions to cyberbully would be
significantly lower and cyberbullying knowledge and
empathy toward cyberbullying victims would be
significantly higher in the experimental group immedi-
ately after completing the program. In addition, it was
hypothesized that: (2) at one-month follow-up, positive
attitudes toward cyberbullying, positive injunctive and
descriptive norms concerning cyberbullying, intentions
to cyberbully, and cyberbullying perpetration would be
significantly lower and cyberbullying knowledge and
cyberbullying victim empathy would be significantly
higher in the experimental than in the control group after
controlling for baseline scores, gender, and age.
METHOD
Participants
At a large university in southeastern Virginia, an e-
mail invitation to participate in a study on negative
experiences via electronic devices was distributed to
freshmen (n ¼ 3,187) and sophomores (n ¼ 3,128) who
were 18–23 years old. Students were randomly assigned
to either the video-based cyberbullying prevention
program or no prevention program (assessment-only).
Of the 375 students (190 in the experimental group, 185
in the control group) who participated in the initial part
of the study (baseline), 167 students (73 in the
experimental group, 94 in the control group; 68.7\%
females, 31.3\% males; Mage ¼ 19.02, SD ¼ .91) com-
pleted both study time points (baseline and one-month
follow-up). The majority self-reported their ethnic group
as White (62.9\%) or African American (18.0\%).
Students were entered into a raffle for a $25 Amazon.
com gift certificate for completing the first assessment.
For completing the one-month follow-up assessment,
participants were entered into a total of 31 raffles (one
$50 Amazon.com gift certificate and 30 $15 gift
certificates for Amazon.com, Starbucks, Walmart,
iTunes, or Subway). For each assessment, participants
enrolled in psychology courses were also offered
research credit. This study was approved by the
university’s Institutional Review Board prior to data
collection. Prior to beginning the study, participants read
a study description and provided informed consent.
More information regarding the 375 students who
completed the baseline portion of the present study
has been reported elsewhere (Doane et al., 2014).
Measures
Cyberbullying knowledge. Cyberbullying know-
ledge was assessed by a five-item multiple choice quiz
based on video content. A sample item is, “Which of the
following are individuals who have been cyberbullied at
greater risk for?” with the following choices: A. School
related problems, B. Alcohol and drug use, C. Attempted
suicide, D. All of the above, E. A and C only.
CES. The 20-item perpetrator scale of the CES
(Doane et al., 2013) was used to measure four types of
cyberbullying behavior: malice (six items, as ¼ .89–.90,
e.g., “Have you sent a rude message to someone
electronically?”), deception (three items, as ¼ .85–.89,
e.g., “Have you pretended to be someone else while
talking to someone electronically?”), public humilia-
tion (three items, as ¼ .76–.93, e.g., “Have you posted
an embarrassing picture of someone electronically
where other people could see it?”), and unwanted
contact (eight items, as ¼ .96, e.g., “Have you sent an
unwanted pornographic picture to someone electroni-
cally?”). Cyberbullying behavior items are answered
on a six-point scale ranging from “Never” (0) to
“Everyday/Almost Everyday” (5). For the present
study, behavior was assessed for the past month.
Convergent validity with Ybarra et al.’s (2007) measure
of Internet harassment and the Cyberbullying Assess-
ment Instrument (Hinduja & Patchin, 2009) has been
established.
Empathy toward victims. Based on a study by
Endreson and Olweus (2001), to assess empathy toward
victims (as ¼ .90–.99), participants reported the degree
to which they feel sorry for a person who has
experienced each of the 20 cyberbullying behaviors in
the CES. For example, “I feel very sorry for a person
who has been [teased by others electronically]” was
answered on a six-point scale ranging from “Does not
apply at all” (0) to “Applies exactly” (5). Four composite
scores were formed by averaging across the items in
each CES subscale. We have found support for
convergent validity of these empathy subscales as they
have been shown to be negatively associated with
cyberbullying perpetration (Doane et al., 2014).
Attitudes, injunctive norms, descriptive
norms, and intentions. Based on recommenda-
tions by Ajzen (2006), questions were administered that
assess attitudes toward cyberbullying, perceived norms
concerning cyberbullying, and intentions to engage in
cyberbullying behavior. Each group of items comprised
all 20 items from the four CES perpetration subscales
(Doane et al., 2013). To measure attitudes toward
a behavior, Ajzen suggests using adjective scales
Aggr. Behav.
Cyberbullying Prevention: Theory of Reasoned Action 139
characterizing instrumental (e.g., harmful-beneficial),
experiential (e.g., unenjoyable-enjoyable), and overall
evaluation (e.g., bad-good). Thus, the item “For me, to
[tease someone electronically] in the forthcoming month
is” was given for all 20 CES perpetration items and
answered on the three six-point scales (0–5) with the
anchors listed above. Attitude composite scores
(as ¼ .77–.96) were computed by averaging these sets
of attitudes items separately for each CES subscale.
Higher scores indicated more positive attitudes toward
cyberbullying.
Injunctive norms (as ¼ .88–.96) were measured by
repeating the stem “My peers would ______ of my
[teasing someone electronically] in the forthcoming
month” for each item with a six-point response scale
ranging from “disapprove” (0) to “approve” (5). To
report descriptive norms (as ¼ .88–.97), participants
selected responses on a six-point scale from “completely
false” (0) to “completely true” (5) to the stem “My peers
[tease others electronically]” for each item. For both
injunctive and descriptive norms, four composite scores
were computed by averaging across the 20 CES items.
Higher scores indicated more favorable injunctive and
descriptive norms regarding cyberbullying.
The stem “I intend to [tease someone electronically]
within the next month” was answered on a six-point scale
ranging from “extremely unlikely” (0) to “extremely
likely” (5) for each CES item to measure intentions to
engage in cyberbullying (as ¼ .80–.97). The 20 CES
items from the four subscales were averaged across to
create composite scores. Higher composite scores
indicated higher intentions to engage in cyberbullying
in the next month. Support for convergent validity of
these measures has been established, as attitudes toward
cyberbullying, injunctive norms, descriptive norms, and
intentions were significantly associated with all four CES
perpetration subscales (Doane et al., 2014).
Procedure
Program development and content. A video-
based cyberbullying program (approximately 10 min)
was developed for students in the experimental group to
view during the online prevention program. During the
development phase of the study, a cyberbullying
researcher not associated with the project, faculty
members, and graduate students reviewed the video
content and actor scripts and made suggestions. Once the
scripts were finalized, young actors from the participat-
ing university were recruited and assigned parts. The
first author supervised practices and identified appro-
priate set designs. The video-based program was
directed, filmed, edited, and the final product developed
by the award-winning video production team at the
participating university.
Given previous support for empathy and TRA
constructs as predictors of cyberbullying perpetration
(e.g., Doane et al., 2014), our goal was to improve these
constructs with the video content. Thus, the cyberbully-
ing prevention video alternated between (1) four brief
flashes in which actual news stories were summarized
about teenagers who were cyberbullied and eventually
committed suicide (i.e., to improve victim empathy and
attitudes toward cyberbullying); (2) brief attention-
grabbing informational slides with voiceovers that
presented key information about cyberbullying (e.g.,
definition of cyberbullying, the different types of
cyberbullying, the modes used for cyberbullying,
common outcomes associated with cyberbullying, and
the prevalence of cyberbullying; i.e., to increase
cyberbullying knowledge); and (3) six short, memo-
rable, realistic vignettes that consisted of narration and
depictions of common cyberbullying events (e.g.,
receiving mean text messages; i.e., to improve victim
empathy and cyberbullying attitudes and norms). The six
vignettes are based on actual cyberbullying events and
common cyberbullying events identified in previous
research.
To increase victim empathy and reduce positive
cyberbullying attitudes, four vignettes are from the
victims’ point-of-view and involve common modes of
electronic communication used for cyberbullying (e.g.,
instant messaging). These scripts illustrate how upset-
ting cyberbullying can be. For instance, one video
segment shows a female actor sitting at her laptop in her
dorm room with multiple instant message windows
open with hurtful messages from other people. She then
describes how upset she becomes when she receives
these messages.
To decrease favorable norms, five actors discussed
how cyberbullying is unacceptable and not “cool.” The
rationale for including young actors discussing the
inappropriateness of cyberbullying is that: (1) students
may think that their peers believe cyberbullying is
unacceptable, and (2) they may perceive that their peers’
frequency of cyberbullying behavior is lower. In other
words, the video may decrease injunctive norms and
descriptive norms about cyberbullying behavior. For
example, one scenario shows a group of students sitting
around and talking about their friends’ experiences, and
how cyberbullying is “stupid” and “immature.”
Pilot study. Prior to testing the program, a pilot
study was conducted with 57 college students to
determine if the cyberbullying video appeared effective
in facilitating the study goals. Results of the pilot test
revealed favorable attitudes toward cyberbullying,
favorable injunctive and descriptive norms about
cyberbullying, and intentions to cyberbully were
significantly lower and cyberbullying knowledge and
Aggr. Behav.
140 Doane et al.
empathy toward victims were significantly higher
immediately after viewing the video online than at
baseline.
Evaluation design. After pilot testing, the pre-
vention program was evaluated using two designs.
Specifically, the experimental group viewed the cyber-
bullying prevention video and participated in a pre-,
immediate post-, one-month follow-up design (i.e.,
completed three assessments), whereas the control group
did not view the video (i.e., assessment only) and
participated in a pre-, one-month follow-up design (i.e.,
completed two assessments) at the same time as the pre-
and one-month follow-up assessments for the exper-
imental group.
In the spring of 2011, all freshmen and sophomores
enrolled at the participating university who were
traditional college age (i.e., 18–23-years-old) were
invited to participate via their university e-mail address
which included a link to the study. Both the cyberbully-
ing prevention group and the control group completed
electronic surveys that assessed cyberbullying knowl-
edge, cyberbullying attitudes, injunctive and descriptive
norms concerning cyberbullying, intentions to engage in
cyberbullying, cyberbullying behavior, and empathy
toward cyberbullying victims at baseline and one month
after baseline. To assess immediate effects of the
program, only the experimental group completed the
measures of knowledge, cyberbullying attitudes, in-
junctive norms, descriptive norms, intentions to cyber-
bully, and cyberbullying victim empathy immediately
after completing the video-based prevention program.
RESULTS
Data Analysis Plan
Given that most of the outcome variables in the present
study were not normally distributed, it is important to use
a method that is robust to normality violations (Erceg-
Hurn & Mirosevich, 2008); thus, all analyses were
conducted with bootstrapping (Efron & Tibshirani,
1993). Rather than relying on a theoretical sampling
distribution that is assumed to be normal, bootstrapping
creates an empirical sampling distribution by resampling
from the sample with replacement. Then, statistical tests
are based on these empirically derived sampling
distributions.
Preliminary Analyses
Demographic comparisons were conducted between
the study participants and the university population,
between students who participated only in the baseline
survey and those who completed both time points, and
between the experimental and control group. Further-
more, participants who completed both assessments
were compared to participants who did not complete
both assessments on all study variables (knowledge and
for all four types of cyberbullying: attitudes, injunctive
norms, descriptive norms, intentions, behavior, and
empathy toward victims).
Compared to the larger population of traditional-aged
freshman and sophomore classes at the university,
participants in the present study were more likely to …
46
ABSTRACT
This study assessed the Integrated Behavioral Model’s (IBM)
utility in explaining high-risk drinking among college students.
A total of 356 participants completed a four-page questionnaire
based on the (IBM) theory and their drinking behavior. The
results from a path analysis revealed three significant constructs
(p<0.05) which predicted intentions to engage in high-risk drink-
ing: experiential attitude (0.34), injunctive norms (0.23), and
self-efficacy (-0.28). The IBM explained approximately 45\% and
26\% of variance in intentions and high-risk drinking, respec-
tively. Although limited in its use thus far, the IBM shows promise
in its application regarding high-risk drinking prevention among
college students.
Keywords: High-risk drinking, college students, and behavioral
science theory
Robert E. Braun, Ph.D., MPH, CHES
Otterbein University
Tavis Glassman, Ph.D., MPH, MCHES, Jiunn-Jye Sheu,
Ph.D., MSPH, MCHES, Joseph Dake, Ph.D., MPH,
& Tim Jordan, Ph.D., MEd
The University of Toledo
Faith Yingling, Ph.D., MEd, CHES
Bowling Green State University
Using the Integrated Behavioral Model
to Predict High-Risk Drinking among
College Students
47USING IBM TO PREDICT HIGH-RISK DRINKING
BACKGROUND
The drinking behavior college students’ exhibit remains an ongoing public health concern across the nation. High-
risk drinking, defined by Johnston and colleagues (2001), as con-
suming five or more drinks in one occasion within the previous
two weeks, is quite prevalent. With approximately 43\% of the
student population engaging in this behavior, for the better part
of the last quarter century, the issue appears to be intractable
(American College Health Association, 2010; Core Institute at
Southern Illinois University, 2011; Substance Abuse and Mental
Health Services Administration, 2011; Wechsler, Lee, Kuo,
Seibring, Nelson, & Lee, 2002). College students who drink at
these levels are at an increased risk for experiencing a variety
of negative health outcomes. Results from the National College
Health Assessment II (American College Health Association,
2010) reveal that college students experience the following when
they over indulge: regret something they did (35\% of males; 33\%
of females), forget where they were or what they did (32\% of
males; 28\% of females) and physically injure themselves (18\%
of males; 15\% of females). Other consequences suffered from
consuming too much alcohol include death, injury, assault, sex-
ual abuse, unsafe sex, and family problems (American College
Health Association, 2010).
The National Institute on Alcohol Abuse and Alcoholism
(NIAAA) provides a number of recommendations on how to
remedy this issue including the use of evidence based and theory
driven interventions (Presley, Meilman, & Leichliter, 2002). The
Integrated Behavioral Model (IBM) represents an emerging the-
ory to address health behavior. Much like the Theory of Reasoned
Action (TRA) and the Theory of Planned Behavior (TPB), the
IBM’s predecessors, the IBM posits the intention to perform a
behavior as the strongest predictor of behavior; however, this
model includes new concepts not utilized within the TPB. The
IBM includes three global constructs ― attitude, perceived norm,
& personal agency ― with two specific constructs per category.
For example, the two constructs that compose attitude are experi-
ential and instrumental attitude; within perceived norm includes
injunctive and descriptive norms, and personal agency consists of
perceived control and self-efficacy.
48 USING IBM TO PREDICT HIGH-RISK DRINKING
The first primary construct within the IBM, attitude, mea-
sures the respondent’s feelings toward that behavior. It answers
the question, “Does he or she have an unfavorable or favorable
beliefs towards performing that behavior” (Montano & Kasprzyk,
2008, pg.78). In the IBM, attitudes are based on experiential and
instrumental attitudes. Fishbein (2007) states the emotions asso-
ciated with the behavior help to shape experiential attitude. For
instance, if an individual had a favorable response in the past to
performing a behavior, then he or she is more likely to perform it
in the future. Past behavior is an important component of expe-
riential attitude and influences future behavior. Instrumental atti-
tude, a cognitively based construct, involves the evaluation of
the behavior which subsequently influences intentions and future
behavior.
The second primary construct, perceived norm, is based on
social acceptance. This approval can come from a family mem-
ber, significant other, or friend (referents). Injunctive norms, in
this model, are similar to subjective norms in the TPB. While
injunctive norms measure what the beliefs of your referents are,
descriptive norms take into account the referent’s behavior. This
is important for two reasons. First, it answers the question, “do
your referents participate in a particular behavior you are inter-
ested in,” and second, “how often do they participate in a par-
ticular behavior?” This is critical because the higher the per-
ceived prevalence of peers participating in the behavior, the more
likely the individual will also engage in the behavior of interest
(Montano & Kasprzyk, 2008).
The third primary construct, personal agency, consists of per-
ceived control and self-efficacy. Perceived control is the percep-
tion a respondent has towards the environment around them, and
the effect the environment has on their ability to perform a partic-
ular behavior; in general, their control of both internal as well as
external factors around them. If an individual’s perceived control
is high, then he or she believes they can perform the behavior
regardless of external influences. Self-efficacy, conversely, is an
individual’s belief in their ability or confidence in performing a
particular behavior (Montano & Kasprzyk, 2008).
Although limited in its use thus far, research has been done
with the IBM to assess college students’ use of emergency contra-
ception, with the model predicting 50\% in the variance in inten-
49USING IBM TO PREDICT HIGH-RISK DRINKING
tion (Wohlwend, Glassman, Dake, Jordan, Khuder & Kimmel,
2013). Turchik and Gidycz (2012) conducted a study assessing
the sexual risk behaviors among college students and surmised
that using additional constructs, accounted for more variance
than the TPB alone. Another study was performed comparing the
TPB to the IBM; the results indicated that the IBM elicited more
variance than the TPB. The authors attribute the difference in
the outcomes between the theories to the better fit the IBM con-
structs provided (Elliot & Ainsworth, 2012). Thus, a precedent
has been set using the IBM to explain various health behaviors
with different populations, yet research with this theory is sparse.
The purpose of this research is to determine the IBM’s utility
in explaining high-risk drinking among college students and to
assess which constructs are the most predicative of this behavior.
METHODS
Participants
The sample for this study consisted of college students from
a large Midwestern public university. After approval from the
University’s Institutional Review Board, the university regis-
trar randomly selected 40 classes to administer the survey with.
Researchers also employed a shadow sample for this investiga-
tion in the event the originally selected course instructors were
not able or willing to participate. Out of the 40 randomly selected
classes; two classes had duplicate professors, two classes were
offered online, three classes were cancelled, and one class was
designated for graduate students only. Thus, of the 32 available
classes, 16 professors agreed to allow the research team to admin-
ister the survey in their classroom. No pattern emerged among
respondent versus non-respondent classes in this study. Of the
16 classes included in this study, 356 out of 402 students com-
pleted the survey generating a response rate of 89\%. According
to Hoyle (1995), in order to show statistical significance for path
analyses, a minimal sample size of 250 was required (Hoyle,
1995). A power analysis for this research was conducted using
the G*Power 3 software and resulted with a similar minimum
sample size projection (Faul, Erdfelder, Lang, & Buchner, 2007).
50 USING IBM TO PREDICT HIGH-RISK DRINKING
Procedure
Researchers employed a cross-sectional research design for
this inquiry. After curtailing the list of possible classes to 16,
selected dates and times were agreed upon by the researchers and
professors to administer the survey. Once in the classroom, the
research staff member instructed participants about the informed
consent process. Students were told that their voluntary participa-
tion in this study would not affect their grade or class standing.
After completion of the survey, participants placed the completed
form in a brown envelope, walked it to the front of the room,
and place it in a locked box. The proctor stressed confidentiality
throughout the data collection process.
Instrument
The current study utilized a customized survey instrument to
answer the research questions. Development of this question-
naire included a comprehensive literature review focusing on
alcohol consumption among college students, and the Integrated
Behavioral Model. Additionally, a total of six focus groups (two
for abstainers, two for social drinkers, and two for high-risk
drinkers) were used to elicit information to help design the sur-
vey and related items. The written questionnaire assessed the
alcohol related behaviors among college students, comprised of
69 items on four pages. The questions included in this survey
consisted of items related to the IBM, drinking habits, and demo-
graphics. Questions based on the IBM were developed using
either a 7-point semantic differential or Likert-type scale. All of
these scales were developed using the suggestions by Montano
and Kasprzyk (2008).
Three types of validity were assessed in this study: face, con-
tent, and construct validity. Five experts reviewed the question-
naire for face validity (i.e., formatting, readability and general
organization of the instrument) and content validity of items. The
experts included two Alcohol, Tobacco, and Other Drugs (ATOD)
practitioners, two ATOD researchers, and one psychometric
expert. A Principle Components Analysis (PCA) was conducted
using Varimax Rotation to assess construct validity. Consistent
with the IBM, the results of the PCA yielded eight constructs or
themes.
51USING IBM TO PREDICT HIGH-RISK DRINKING
The results from the test/retest reliability were all significant
at p<0.01 level with Pearson coefficient values listed as fol-
lows: instrumental attitude (r=0.87), injunctive norms (r=0.79),
self-efficacy (r=0.78), descriptive norms (r=0.76), experiential
attitude (r=0.73), perceived control (r=0.62), and behavioral
intention (r=0.60). The Cronbach’s alpha coefficients for each of
the sub-constructs also demonstrated the instrument’s reliability:
experiential attitude (α=0.96), behavioral intention (α=0.92), per-
ceived control (α=0.91), instrumental attitude (α=0.89), self-effi-
cacy (α=0.86), injunctive norms (α=0.84), and descriptive norms
(α=0.82).
More than two-thirds of the survey was dedicated for the
measurement of the IBM constructs. To assess the theory, the
researchers measured each construct. The measurement of instru-
mental attitudes and experiential attitudes constructs included
five items each. The response style for each item used a semantic
differential style response with 7 potential responses anchored by
two polar opposite anchor descriptors. For instrumental attitudes,
descriptor examples include “bad-good” and “risky-not risky.”
Example anchors for experiential attitudes included “embarrass-
ing-not embarrassing” and “not fun-fun.” The measurement for
injunctive norms, descriptive norms, and behavioral intention
included four items each. The response style for each item used
a Likert-type scale ranging from “strongly disagree” to “strongly
agree.” The perceived control construct included five items, coded
on a scale, yielding potential scores ranging from one through
seven. The response style for each item used a Likert-type scale
ranging from “totally not under my control” to “totally under my
control.” Finally, the measurement of self-efficacy included five
items with a response options scale ranging from “very difficult”
to “very easy” on a seven-point scale.
Data Analysis
Data analysis for this study utilized SPSS (Statistical Package
for the Social Sciences) version 17. Statistical analyses for this
investigation assumed a Type I error of 0.05. Descriptive sta-
tistics, including frequencies, means, proportions, percentages,
and standard deviations, were calculated to describe the sam-
ple. Nonparametric tests such as the Chi-square was used for
this study due to the non-normal distribution of the data obtained.
52 USING IBM TO PREDICT HIGH-RISK DRINKING
The path analysis was conducted using, EQS v6.1, a structural
equation modeling software.
RESULTS
As Table 1 illustrates, participants in this study included 171
males (48.2\%) and 184 females (51.8\%). Approximately 75\%
of the respondents identified themselves as Caucasian (74.7\%;
n=263), followed by African-American (10.5\%; n=37), Asian or
Pacific Islander (6.3\%; n=22), Hispanics (3.7\%, n=13), and oth-
ers (4.8\%; n=17). The mean age of the participants was 23.4 years
(SD=5.9 years), with the minimum and maximum ages ranging
from 19 and 60, respectively. Third-year undergraduate students
made up the largest proportion of respondents (41.5\%; n=146)
followed by 2nd year (21.9\%; n=77), 4th year (20.5\%; n=72),
5th year or greater (11.1\%; n=39), and first year (5.1\%; n=18).
Finally, 37\% of the respondents reported high-risk drinking the
last time they partied/socialized.
TABLE 1
Participant Demographics
Characteristic Frequency Percent SD
Gender
Male 171 48.2
Female 184 51.8
Age 23±6
Year in School
1st Year 18 5.1
2nd Year 77 21.9
3rd Year 146 41.5
4th Year 72 20.5
5th Year or greater 39 11.1
Ethnicity
African American (Black) 37 10.5
Asian or Pacific Islander 22 6.3
Caucasian (White) 263 74.7
Hispanic (Latino) 13 3.7
Others 17 4.8
53USING IBM TO PREDICT HIGH-RISK DRINKING
Means, Standard Deviations, and zero-ordered correlations
were conducted to describe participants’ perceptions and to deter-
mine the association among the IBM constructs (Table 2). The
mean values for experiential attitude and instrumental attitude
indicate that student perceptions were neutral concerning high-
risk drinking affect and outcome beliefs. Conversely, a mean of
2.38 for injunctive norm demonstrated their referent’s disapproval
to perform this behavior while a mean of 4.43 among descriptive
norm indicated uncertainty regarding their referents high-risk
drinking behaviors. Perceived control and self-efficacy elicited
high mean values which signify confidence and strong personal
control concerning their intentions to engage in high-risk drink-
ing. The results from Table 2 showed that with the exception
of descriptive norms and perceived control, all constructs were
correlated with one another. Conducting a correlation matrix is
a prerequisite step (assess the data) to performing a path analy-
sis. Overall, the correlation values indicate statistically signifi-
cant relationships between the variables, but were not highly cor-
Greek Status
No 306 86.7
Yes 47 13.3
Member of an NCAA Team
No 345 98.0
Yes 7 2.0
Participation in Intramural/Club
No 272 77.3
Yes 80 22.7
Hours spent drinking 4±2.4
Those who high-risk drank the last
time they partied or socialized
No 224 63.3
Yes 130 36.7
# of alcoholic beverages consumed 5±5.4
# of drinks consumed to become drunk 5±6
Enrollment Status
Part-time 39 11.1
Full-time 311 88.9
54 USING IBM TO PREDICT HIGH-RISK DRINKING
related. The IBM variables are independent from one another,
thus limiting concerns of multicolinearity.
Figure 1 depicts the results from the path analysis illustrating
the relationships among the IBM constructs. Using the maximum
likelihood estimation, the model accounted for 45\% of the vari-
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55USING IBM TO PREDICT HIGH-RISK DRINKING
ance (R2) in the intention to high risk drinking. Three constructs,
experiential attitude, injunctive norm, and self-efficacy were
statistically significant (p<0.05) with path coefficients of 0.34,
0.23, and -0.28 respectively. Results also indicated the model
predicted 26\% of the variance in high-risk drinking. Overall,
the model yielded acceptable model fit indices, as demonstrated
by the Joreskog-Sorbom’s Goodness of Fit (GFI) Index (.97),
Comparative Fit (CFI) Index (.90), and Root Mean-Square Error
of Approximation (RMSEA) of 0.15 and its 90\% confidence interval of 0.11-
0.19. Although model fit indices are descriptive in nature with-
out a clear cut point for significance level, a CFI value greater
than or equal to 0.95 and a RMSEA value less than or equal to
0.05 are suggested as adequate fit (Browne & Cudeck, 1992; Hu
& Bentler, 1999). The model fit indices suggest the data fit at
acceptable ranges.
Another path model was generated to assess the three primary
constructs associated with the IBM, i.e. attitude (ATT), perceived
norm (PN), and personal agency (PA), in predicting behavioral
Figure 1: Path Analysis of High-Risk Drinking using the IBM
ATTITUDE
Experiential
Attitude
PERSONAL
AGENCY
Instrumental
Attitude
PERCEIVED
NORM
Injunctive
Norms
Perceived
Control
Descriptive
Norms
Behavioral
Intentions
High-Risk
Drinking
R2=.45 R2=.26
Self-Efficacy
0.34*
0.17
0.23*
-0.04
-0.06
-0.28*
0.03*
Note: *equals statistically significant at p<0.05
56 USING IBM TO PREDICT HIGH-RISK DRINKING
intentions to engage in high-risk drinking. Each of the primary
constructs was created by combining the respective sub-con-
structs. All three constructs, ATT, PN, and PA, exhibited statisti-
cal significance (p<0.05) with path coefficients of 0.27, 0.10, and
-0.17, and accounted for 44\% of the variance in behavioral inten-
tion. Overall, the model showed an acceptable model fit indices,
as exhibited by the Joreskog-Sorbom’s GFI Index (.95), Joreskog-
Sorbom’s AGFI Comparative Fit Index (.9175), and RMSEA of
0.19 with a 90\% C.I. of 0.14-0.25 (see Table 3). Although the
goodness of fit estimates were within acceptable range, the Chi-
square values (statistically significant) associated with each path
analysis did not fall within acceptable limits which is not uncom-
mon with large sample sizes (Kline, 1998).
DISCUSSION
Alcohol abuse continues to compromise academic perfor-
mance and student health at colleges and universities across the
country (Hingson, Zha, & Weitzman, 2009). Utilizing theory to
design interventions to help address this issue represents a funda-
mental approach in attempting to change this entrenched behavior
(NIAAA, 2010). This study used the IBM, the latest iteration of
the Theory of Reasoned Action/Theory of Planned Behavior in
an attempt to better understand the high-risk drinking patterns of
college students. Each of the three primary constructs, i.e. atti-
tude (ATT), perceived norm (PN), and personal agency (PA), and
their sub-constructs were assessed to predict behavioral intention
and high-risk drinking.
A path analysis was conducted to determine the direction and
significance of the IBM constructs to predict behavioral intentions
and high risk drinking. The results revealed the IBM explained
approximately 44\% and 26\% of variance in intentions and high-
risk drinking, respectively. These findings are consistent with the
meta-analytic review published by Armitage and Conner (2001),
which reported on average, for any behavior, the TPB explained
39\% of the variance in behavioral intention and 27\% in behavior.
Results from the path analysis also revealed that experiential
attitude was the strongest positive predictor of intention to engage
in high-risk drinking, which reflects trends in this area of research
(Elliot & Ainsworth, 2012). Favorable attitudes towards alcohol
consumption were indicative of high-risk drinking. Attitudes are
57USING IBM TO PREDICT HIGH-RISK DRINKING
based in part, by the previous experiences people have. The more
positive the experience, the more likely they are to perform the
behavior again. Challenging alcohol expectancies and lessening
student’s beliefs about benefits of high-risk drinking remains an
intervention focal point based on this and other studies (Ham,
2009).
Consistent with the literature, injunctive norms yielded a sta-
tistically significant, albeit, moderate path coefficient value of
0.23 (Ham, 2009; McMillan & Conner, 2003). Injunctive norms
depict the referent’s approval or disapproval in performing a
particular behavior. Perhaps, the relatively low value was due
to the fact that some respondents are more motivated by certain
referents than others. For example, college students may seek
approval from their peers but not their parents, thus diminishing
the predictive value of this construct. These results corroborate
similar outcomes in which the subjective norms construct is the
weakest predictor within the TPB (Armitage & Conner, 2001).
Nevertheless, in this study and others, injunctive norms, to some
degree, influence the drinking patterns among college students
(Park, Klein, Smith, & Martell, 2009).
In this study, self-efficacy yielded a statistically significant,
moderate path coefficient of -0.28. Self-efficacy is an internal
belief a person has to perform a particular behavior within a spe-
cific context. In this study, results yielded a negative path coeffi-
cient, which indicate an inverse relationship between self-efficacy
and behavioral intention. Thus, as self-efficacy became stronger,
intention to high-risk drink lessened, and vice versa. For exam-
ple, if participants believed they had the confidence to refuse
alcohol consumption then they tended not to engage in high-risk
drinking. Collins and Carey (2007) also found a negative link
between self-efficacy and intention. This finding indicates that
prevention efforts should target college student’s self-efficacy,
perhaps focusing on peer refusal skills.
The behavioral intention construct predicted 26\% of the vari-
ance in high-risk drinking, which is similar to the results by other
researchers (Armitage & Conner, 2001). However, the complex-
ities surrounding intentions and actual behavior merit further
examination, as intentions are not always predictive of behav-
ior. For example, unique circumstances may result in different
intentions or the need for individuals to change their original
58 USING IBM TO PREDICT HIGH-RISK DRINKING
intention, some of which may not be captured with traditional
survey data. How do intentions change when alcohol is free or
when somebody is pursuing a “significant other” are just a cou-
ple of examples, which could influence the findings. In general,
the more complicated the behavior or social dynamics the more
challenging it is to assess intentions. The time between intentions
and behavior is yet another variable to consider with this type
of research. Nevertheless, behavioral intention within the TRA/
TPB/IBM consistently predicts drinking behavior within the col-
lege population (Collins & Carey, 2007; O’Callaghan, Chant,
Callan, & Baglioni, 1997).
Somewhat unexpectedly, neither instrumental attitude,
descriptive norms nor perceived control predicted intentions to
engage in high-risk drinking with statistical significance. Thus, to
examine the efficacy of the IBM further a path analysis was per-
formed using exclusively the three primary constructs within the
IBM. The results showed that each of the primary constructs were
statistically significant, with the model explaining approximately
44\% of the intention to engage in high-risk drinking. Similar, to
the first path analysis attitude was the strongest predictor followed
by personal agency and then perceived norms.
The findings from this study indicate that the IBM provides
utility in explaining high-risk drinking among college students.
More specifically, researchers and practitioners should focus on
experiential attitude, injunctive norms, and self-efficacy in design-
ing interventions with this population and behavior. The preci-
sion the IBM provides in identifying which specific constructs to
address when combating high-risk drinking demonstrates its use-
fulness beyond the theory’s predecessors, the Theory of Reasoned
Action and Theory of Planned Behavior.
Limitations
Several limitations exist within the current study. As with most
surveys, the use of self-reported data merit concern, particularly
recall bias (Portney & Watkins, 2000). Indeed, respondents may
not remember the number of alcoholic beverages they consumed
the last time they partied and/or socialized, or may not remember
suffering a consequence due to their drinking behavior. The sam-
ple was obtained from 16 of the 32 randomly selected classes —
represents another concern — response bias. However, the focus
59USING IBM TO PREDICT HIGH-RISK DRINKING
of this study was on the student response rate, not the instructor.
The participants in the sample closely matched the overall student
population, with the exception of the small number of first year
students. This may have been due to the time of the year when the
study was conducted, students matriculating through their respec-
tive programs, and students entering the university with college
credits obtained from high school. Regardless, the purpose of this
study was not to generalize data, per se, but to assess a theory,
which the sample provided an adequate means to accomplish
this objective. In addition, a cross-sectional research design was
employed for this study, thus causal inferences cannot be made.
For example, attitudes, intentions, and behaviors do not always
change concurrently, because these variables are constantly fluc-
tuating, this may have possibly affected the results. Also, the
items used to assess instrumental attitude, descriptive norm, and
perceived control might not have accurately assessed these con-
structs, which may explain the insignificant values yielded from
this study. Finally, a theory cannot be proven or disproven with
one study, thus additional studies need to be conducted to further
assess the efficacy of the IBM.
Indeed, a number of recommendations for future research
using the IBM emerged from this investigation. First, to more
accurately assess the utility of the IBM a time-series research
design is suggested. The IBM posits that the intention to perform
a behavior is the strongest predictor of behavioral performance.
Assessing a respondent’s intention to perform a behavior at time
one and measuring how much they performed the behavior at time
two warrants additional inquiry. Further, in order to assess con-
struct validity more effectively, prospective research needs to be
conducted with the IBM. Additional assessments should include
other high-risk behaviors, such as marijuana use, cigarette smok-
ing, or prescription drug abuse. There are many applications for
this model; expanding it to other populations such as minorities,
athletes, or Greek social fraternities or sororities represents addi-
tional possibilities.
Correspondence concerning this article should be addressed
to: Robert E. Braun PhD, MPH, CHES, Assistant Professor,
Otterbein University, Department of Health and Sport Sciences,
160 Center Street, Rike 226, Westerville, OH 43081; Phone:
(614) 823-3535; Fax: (614) 823-1965; Email: [email protected]
edu.
60 USING IBM TO PREDICT HIGH-RISK DRINKING
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Journal of Social Service Research
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Health Education Intervention on HIV/AIDS
Prevention Behaviors among Health Volunteers
in Healthcare Centers: An Applying the Theory of
Planned Behavior
Hadi Alizadeh Siuki, Nooshin Peyman, Mohammad Vahedian-Shahroodi,
Mahdi Gholian-Aval & Hadi Tehrani
To cite this article: Hadi Alizadeh Siuki, Nooshin Peyman, Mohammad Vahedian-Shahroodi,
Mahdi Gholian-Aval & Hadi Tehrani (2019) Health Education Intervention on HIV/AIDS
Prevention Behaviors among Health Volunteers in Healthcare Centers: An Applying the
Theory of Planned Behavior, Journal of Social Service Research, 45:4, 582-588, DOI:
10.1080/01488376.2018.1481177
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Health Education Intervention on HIV/AIDS Prevention Behaviors among
Health Volunteers in Healthcare Centers: An Applying the Theory of
Planned Behavior
Hadi Alizadeh Siukia , Nooshin Peymanb , Mohammad Vahedian-Shahroodib ,
Mahdi Gholian-Avalb, and Hadi Tehranib
aDepartment of Health Education and Health Promotion, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran;
bDepartment of Health Education and Health Promotion, Social Determinants of Health Research Center, Mashhad University of
Medical Sciences, Mashhad, Iran
ABSTRACT
Present study aims to investigate the impact of health education intervention on improving
HIV/AIDS preventive behaviors among Health volunteers in Torbat-e Heydarieh Iran. 120
Health volunteers were involved in this quasi-experimental study (60 participants in inter-
vention group and 60 participants in control group). Data collection tool was a question-
naire based on theory of planned behavior along with demographic questions which was
applied before and 2 month after intervention. Data analysis was conducted using SPSS16
with descriptive analysis, and analytical tests (independent t-test, correlation coefficient)
were conducted at 5\% significance level. The findings of the study showed no significant
difference between two groups in terms of mean scores of knowledge, attitude, perform-
ance, behavioral intention, and behavioral control before intervention (p > 0.05). But a sig-
nificant difference was observed between two groups after the health education
intervention (p < 0.05). Health education intervention based on theory of planned behavior,
regarding AIDS disease preventive behavior, significantly affects Health volunteers.
Therefore, according to behavior theory, such educations lead to positive changes in AIDS
preventive behaviors.
KEYWORDS
Health behavior; education;
health volunteers; AIDS
Introduction
The main cause of AIDS (acquired immune defi-
ciency syndrome) is a retrovirus that when enters
into body attacks to the T Helper cells which
play a key role in defense system of the body,
disables immune system cells, and increasingly
disrupts body defense against diseases. Incubation
period of the disease is long and may take
5–10 years or more, or HIV infection may remain
a lifelong (Morlat et al., 2014). AIDS is a health,
social, and psychological crisis that not only
affects adults but also children and adolescents
(Kelly & Lawrence, 2013), so that it can be said
that currently AIDS is the problem of young peo-
ple that 85 percent of them live in developing
countries (Atwine, Cantor-Graae, & Bajunirwe,
2005). On the other hand, 50 percent of new
cases infected with the virus happen in people
aged 10–24 years old (Joint United Nations
Programme on HIV/AIDS, & World Health
Organization, 2007). According to WHO 7.000
individuals per day, i.e., 5 young people per
minute get infected with this virus (UNICEF,
Joint United Nations Programme on HIV/AIDS,
& World Health Organization, 2002).
Different statistics show that approximately 39.5
million people are infected with this disease around
the world and every year 2 million people die due
to this disease (Heald, 2006). From 1999 to 2009, a
growth of 27\% has happened in the number of peo-
ple with HIV infection (Mee et al., 2014).
According to the latest statistics on HIV/ADIS in
the Islamic Republic of Iran, published by the
Ministry of Health, Treatment and Medical
Education, from the beginning of the epidemic
until April 2011, 22,727 individuals infected with
CONTACT Hadi Tehrani [email protected] Department of Health Education and Health Promotion, Social Determinants of Health Research
Center, Mashhad University of Medical Sciences, 91778-99191 Mashhad, Iran.
� 2018 Taylor & Francis Group, LLC
JOURNAL OF SOCIAL SERVICE RESEARCH
2019, VOL. 45, NO. 4, 582–588
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https://ORCID.org/0000-0003-2053-3229
http://orcid.org/0000-0002-6218-4787
http://orcid.org/0000-0002-5402-1646
http://orcid.org/0000-0001-8747-8717
https://doi.org/10.1080/01488376.2018.1481177
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HIV are identified in the country, where 91.7 per-
cent of them are men and 8.3 percent are women
(Fallahzadeh, Morowatisharifabad, & Ehrampoosh,
2009). In Torbat-e Heydarieh, 4 cases are
reported that 1 of them is male and three others
are female. The first case was reported in 2010
and one of the cases has led to death
(Fallahzadeh et al., 2009). Currently, a large num-
ber of health volunteers around the Iran’s country
cooperate with healthcare centers and after pass-
ing training courses, convey the acquired infor-
mation to the covered household and attempt to
realize healthcare objectives as well as providing
other services such as case-finding, health educa-
tion, patient care, raising awareness, and provid-
ing public health services (Eslami, Marzban, &
Mazloomy, 2016).
Theory of planned behavior is one of the
healthcare theories which is considered the best
and most perfect theory to study behavior
(Vafaeenajar et al., 2015). This theory was
presented in 1988 by Ajzen and through develop-
ment of reasoned action theory (Ajzen &
Madden, 1986). The structures of the model
include: behavior_intention of behavior_attitude
toward behavior_control of perceived behavior_
subjective norm (Gebreeyesus Hadera, Boer, &
Kuiper, 2007). In present study, using theory of
planned behavior as theoretical framework of
the study, a training program will be developed
and implemented to improve the awareness and
attitude of health contact persons toward AIDS
and its preventive methods. According to some
studies, training based on theory of planned
behavior helps to the creation of the required
skills to postpone the suggestions of high risk
behaviors regarding AIDS and leads to training
and attitude improvement through peers and
consequently leads to attitudes and awareness
reinforcement (Armitage & Conner, 2001; Eggers,
Taylor, Sathiparsad, Bos, & de Vries, 2015;
Tyson, Covey, & Rosenthal, 2014). Today, AIDS
is an obstacle to economic, social, and cultural
development, so that it has turned to a compli-
cated social and economic emergency. Given eco-
nomic and social loses resulted from expansion
of this disease, it is considered the most import-
ant challenge against development (Duflo, Dupas,
& Kremer, 2015). Informing the community to a
large extent can decrease the number of people
affected with AIDS (Shojaeizadeh, Taheri, &
Tehrani, 2012). To that end, using theory of planned
behavior, the present study aims to improve
HIV/AIDS preventing behaviors among Health
volunteers of Torbat-e Heydarieh in Iran.
Method
Study Design and Study Target
Present study is a quasi-experimental study (60
participants in intervention group and 60 partici-
pants in control group) which was conducted in
2016 in healthcare centers. The study population
included health volunteers. Consideration a loss
rate of 10\%, the total sample size was calculated
120 participants. The participants were in the age
range of 18–50 years. The inclusion criteria were
to have at least middle school education and
not moving resident place since the beginning
of the study. The participants were entered
into study through cluster sampling method. The
participants were permitted to leave the study
at any stage; if they were not interested to con-
tinue and they were excluded if didn’t take part
in two or more training sessions. To that end,
after coordination with University authorities the
author referred to health deputy of the Torbat-e
Heydarieh City and obtained the list of healthcare
centers. Then two centers were selected randomly
as intervention centers and two other centers as
control centers. It should be noted that interven-
tion centers had similar conditions in terms of
cultural and geographical characteristics.
Before filling the questionnaires regarding
research objectives, the manner of filling the
questionnaire and other required explanations
were presented and the questionnaires were
completed at the presence of the author. After
conducting the initial test, the data were extracted
and analyzed. Then, emphasizing theoretical
structures of planned behavior (attitude toward
behavior, behavior or performance, behavior
intention, subjective norms, perceived behavior
control) and awareness and performance regarding
AIDS preventive behaviors, the author embarked
for developing training materials and implement-
ing intervention. Training materials regarding
JOURNAL OF SOCIAL SERVICE RESEARCH 583
HIV/AIDS were formulated according to the
latest epidemiological information of Iran and
other countries of the world, in accordance
with social and cultural conditions, and were
presented by author to 30 people groups through
two workshops using PowerPoint slides, pam-
phlets, and leaflets.
One week after first workshop, the second
workshop was held and besides reviewing the
headlines of educational materials, the ground
was prepared for group discussion and answering
the questions. Two month after completion of
educational interventions, using a written ques-
tionnaire similar to the initial test, the second
test was conducted simultaneously for interven-
tion and control groups.
Measures
Data collection tool was a two-part questionnaire.
The first part included demographic questions
and second part included awareness questions
(9 items), attitude toward behavior (10 items),
behavior or performance (6 items), behavior
intention (4 items), subjective norms (4 items),
and Perceived behavioral control (6 items). The
content validity was obtained by 7 professors and
reliability was calculated 82.0 through Cronbach’s
alpha. Scoring the questionnaire was in this way
that regarding awareness questions yes answers
received two points and I don’t know answers
received one point. Scoring attitude, subjective
norms, and Perceived behavioral control was in
this way that yes answers received two points, no
answers received zero points, I have no idea
answers received 2 negative points and I disagree
answers received one point. Regarding reverse
questions in the part of attitude, subjective
norms, and Perceived behavioral control, scoring
was in this way that I agree answers received one
point, I have no idea answers received two nega-
tive points, and I’m disagree answers received 3
points. In the part of behavioral questions, yes
answers received 1 point, and no answers received
any points and scoring was reverse regarding the
question with negative load. Regarding behavioral
intention, the questions always take 3 or 2 points
and never take one point.
Statistical Analyses
After collecting the questionnaires, data analysis
was conducted using SPSS version 16 and
descriptive analysis (frequency, percentage, mean,
and standard deviation), and analytical tests
(independent t-test, paired t-test, correlation coef-
ficient) were conducted in a significance level
of 0.05.
Ethics Approvals
Ethical approval was gained from the Torbat-e
Heydarieh University of Medical Sciences Ethics
Committee. The health volunteers were explained
the purpose of the study and consent letter was
taken. Written informed consents were obtained
from all the study participation. Moreover,
they were assured that all the information would
be kept confidential and would not be revealed
unless for research purposes and in an anonym-
ous form. Participants were allowed to decline
participation at any stage of research. As part of
the consenting process, participants were reminded
that their participation in this research was
confidential and that no personal identifiable
information will be stored with the data.
Results
In the study, the mean age and standard deviation
of the intervention and control groups were
33.13 ±7.10 and 32.68 ±6.62years, respectively.
According to the results, two groups are homoge-
neous in terms of demographic variables (age, edu-
cation, marital status, and occupation) (Table 1).
According to independent t-test, no significant
difference was observed between two groups
before intervention in terms of all structures of
theory of planned behavior, but after intervention
the scores increased and the differences were stat-
istically significant (Table 2). Paired t statistical
test shows that the mean of awareness, perform-
ance, behavioral intention, subjective norms, and
the control of intervention and control groups
behaviors before training had no significant dif-
ference (p > 0.05) but after training and holding
education course, the mean score of above men-
tioned variables showed a significant difference in
intervention and control groups (p < 0.05). It can
584 H. A. SIUKI ET AL.
be said that training intervention significantly
affected all structures of planned behaviors in
health contact persons (Table 2).
Also, a significant correlation was observed
regarding the components of theory of planned
behavior between health contact persons in inter-
vention and control groups after training inter-
vention (awareness and behavioral intention
(p ¼ 0.01), attitude and performance (p ¼ 0.08)
and subjective norms (p ¼ 0.003), performance
and subjective norms (p ¼ 0.003), behavioral
intention and subjective norms (p ¼ 0.002), sub-
jective norms and behavioral control (p ¼ 0.01))
(Table 3).
Discussion
The significant changes in awareness scores in
intervention group, compared to control group,
have been due to direct impact of training inter-
vention on health contact persons and this
training has increased awareness. This increase is
in line with many other related studies. A study
by Alizadeh Siuki et al. (2013) and Pakpour
Hajiagha, Mohammadi Zeidi, and Mohammadi
Zeidi (2012) showed an increase in awareness
score which is in line with the findings of present
study. Since the first step to change behavior is
increasing awareness, different ways exist to that
end, such as training through self-learning voice
messages, face to face training, group discussion,
and movies (Reeves, Perrier, Goldman, Freeth, &
Zwarenstein, 2013). In present study, PowerPoint
slides, pamphlets, and leaflets were used to
increase awareness in health contact persons and
were identified as useful tools.
In present study, a significant difference was
observed between attitude scores before and after
intervention which indicates substantial changes
in the attitudes of health contact persons. It
seems that the increase of attitude score among
health surveyed health contact persons is due to
their awareness increase and positive impact of
training interventions. A study by Mohammadi
Zeidi, Pakpour Hajiagha, and Mohammadi Zeidi,
(2013) shows also an increase in attitude com-
pared to behavior after intervention which is con-
sistent with the findings of present study.
The mean score of behavior performance
before and after training showed a significant dif-
ference in intervention group. This significant
increase in intervention group was an expected
finding and shows positive impact of presented
training course regarding AIDS preventive
Table 2. Comparison between changes in the behavior and constructs of TPB before and after the intervention.
Post-intervention Pre-intervention
p Value�Mean ± SD Mean ± SD
Knowledge Control group 12/11 ± 2/40 12/15 ± 2/42 0/673
Experimental group 11/03 ± 2/82 12/48 ± 1/85 0/0001
p value�� 0/34 0/001
Attitude toward behavior Control group 24/68 ± 2/24 2/26 ± 7340 0/49
Experimental group 22/26 ± 2/19 25/36 ± 3/13 0/0001
p value 0/24 0/002
Behavior Control group 1/10 ± 2/58 1/11 ± 2/61 0/159
Experimental group 0/98 ± 2/98 1/49 ± 3/83 0/001
p value 0/15 0/0001
Subjective norm Control group 1/31 ± 11 1/49 ± 11/15 0/172
Experimental group 1/09 ± 11/46 1/82 ± 12/20 0/003
p value 0/922 0/002
Perceived behavioral control Control group 1/07 ± 14/21 1/09 ± 14/30 0/199
Experimental group 0/46 ± 14/13 0/68 ± 14/33 0/013
p value 0/170 0/003
Behavioral Intention Control group 0/68 ± 9/55 0/71 ± 9/70 0/162
Experimental group 2/09 ± 9/30 1/30 ± 11/13 0/001
p value 0/001 0/392
��Independent t-test; �Paired t-test.
Table 1. Mean and standard deviations of demographic varia-
bles in the intervention and control groups.
Control group Intervention group
Number (\%) Number (\%)
Level of
education
Diploma 48 (80) 49 (81/7)
Associate Degree 9 (15) 7 (11/6)
Bachelor Degree 3 (5) 4 (6/6)
Total 60 (100) 60 (100)
Job Housewife 41 (68/3) 42 (70)
Employee 9 (15) 8 (13/3)
Student 2 (3/4) 3 (5)
Others 8 (13/3) 7 (11/7)
Total 60 (100) 60 (100)
Marital status Single 10 (16/7) 9 (15)
Married 50 (83/3) 51 (85)
Total 60 (100) 60 (100)
JOURNAL OF SOCIAL SERVICE RESEARCH 585
behaviors on improvement of the above men-
tioned concept. Also, as the results show, the
intervention has been successful in present study.
This finding is consistent with the findings of
a related study by Medley, Kennedy, O’Reilly,
and Sweat (2009). Behavior usually happens
following intention and without intention no
behavior happens. In present study, the mean
score of behavioral intention was good in both
groups and a significant increase was observed
in behavioral intention of the intervention
group after intervention. Highness of behavioral
intention in both groups before intervention has
positive impact on increase in AIDS protective
behaviors among participants. In a related study
by Pakpour Hajiagha et al. (2012) Training inter-
vention led to improving the skills of rejecting
and postponing high-risk behaviors. The increase
in behavioral intention mean score probably
has been because of appropriate training of
health contact persons through lectures and
group discussions.
The mean score of subjective norms in inter-
vention group had a significant increase, while
this difference wasn’t significant in control group.
Subjective norms occur due to the performance
of some believes that particular people may con-
firm or not confirm conducting them. Present
study shows that community members and the
households of health contact persons have high
expectations of health contact persons in terms of
adopting AIDS protective behaviors. The findings
are consistent with a related study by Meister,
Grugel, & Meis (2014), where using theory of
planned behavior they showed the significant
impact of training on attitude change in interven-
tion group. But as it was mentioned before, no
significant increase was observed regarding the
behavior performance of health contact persons
in control group. The results of control group
suggest that so long as there is no motivational
initial condition and training plans are not devel-
oped regarding AIDS protective behaviors, no
significant change happens in behaviors.
The results of the study regarding the impact of
training intervention show an increase in perceived
behavior control variable in intervention group
after training, while the mean score of behavioral
control in control group shows no significant
difference. This finding is consistent with findings
of a related study by Sadeghi & Khanjani (2015).
In present study, the author faced some limita-
tions, such as: difficulties in developing training
materials due to age difference in target groups,
coordination with Department of Health to
implement training interventions in health cen-
ters, participants’ attrition in different steps of
the program. Given the findings of the study it is
suggested that some more studies should be con-
ducted regarding effectiveness of other healthcare
models and theories in adopting AIDS protective
behaviors. Also theory of planned behavior
and other models in adopting AIDS protective
behaviors should be compared. Finally, present
study is conducted regarding adopting AIDS
protective behaviors among health contact persons
Table 3. Correlation between constructs of the TPB.
Perceived
behavioral control
Subjective
norm
Behavioral
intention Behavior
Attitude
toward behavior Knowledge
Knowledge Correlation
coefficient
1 0/16 0/01 0/30 0/17 0/21
p value 0/20 0/88 0/01 0/18 0/10
Attitude
toward behavior
Correlation
coefficient
0/16 1 0/22 0/11 0/25 0/10
p value 0/20 0/08 0/37 0/04 0/44
Behavior Correlation
coefficient
0/01 0/22 1 0/04 0/37 0/07
p value 0/88 0/08 0/71 0/003 0/55
Behavioral
intention
Correlation
coefficient
0/30 0/11 0/04 1 0/38 0/12
p value 0/01 0/37 0/71 0/002 0/33
Subjective norm Correlation
coefficient
0/17 0/25 0/37 0/38 1 0/12
p value 0/18 0/04 0/003 0/002 0/33
Perceived behav-
ioral control
Correlation
coefficient
0/21 0/10 0/07 0/12 0/30 1
p value 0/10 0/44 0/55 0/33 0/019
586 H. A. SIUKI ET AL.
in Torbat-e Heydarieh city. It is suggested that
the same study should be conducted among
health contact persons in other cities.
The results of the study indicate the impact
of training intervention on AIDS protective
behaviors based on theoretical structures of
theory of planned behavior. Theory of planned
behavior is one of the best theories to predict
behaviors which were used as main framework
in present study. The findings of the study reaf-
firmed effectiveness of this health training theory
in changing behaviors.
Acknowledgements
The authors of the study express their sincere gratitude of
all authorities of Torbat-e Heydarieh University of Medical
Sciences, Deputy of Health and health contact persons who
helped us in conducting this research.
Disclosure Statement
No potential conflict of interest was reported by the authors.
ORCID
Hadi Alizadeh Siuki https://ORCID.org/0000-0003-
2053-3229
Nooshin Peyman http://orcid.org/0000-0002-6218-4787
Mohammad Vahedian-Shahroodi http://orcid.org/0000-
0002-5402-1646
Hadi Tehrani http://orcid.org/0000-0001-8747-8717
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https://www.unicef.org/publications/index_4447.html
Abstract
Introduction
Method
Study Design and Study Target
…
NIH Publication No. 05-3896
Printed September 2005
2931-NCI Theory cvr.f 11/17/05 3:18 PM Page 1
Theor y
at a Gl ance
U.S. DEPARTMENT
OF HEALTH AND
HUMAN SERVICES
National Institutes
of Health
A G u i d e F o r H e a l t h P ro m o t i o n P ra c t i ce
Theory
at a
Glance
A Guide For Health Promotion Practice
(Second Edition)
U.S. DEPARTMENT OF HEALTH AND HUMAN SERVICES
National Institutes of Health
Foreword
A
decade ago, the first edition of Theory at a Glance was published. The guide was
a welcome resource for public health practitioners seeking a single, concise
summary of health behavior theories that was neither overwhelming nor superficial.
As a government publication in the public domain, it also provided cash-strapped
health departments with access to a seminal integration of scholarly work that was useful to
program staff, interns, and directors alike. Although they were not the primary target audience,
members of the public health research community also utilized Theory at a Glance, both as
a quick desk reference and as a primer for their students.
The National Cancer Institute is pleased to sponsor the publication of this guide, but its
relevance is by no means limited to cancer prevention and control. The principles described
herein can serve as frameworks for many domains of public health intervention,
complementing focused evidence reviews such as Centers for Disease Control and
Prevention’s Guide to Community Preventive Services. This report also complements a
number of other efforts by NCI and our federal partners to facilitate more rigorous testing
and application of health behavior theories through training workshops and the development
of new Web-based resources.
One reason theory is so useful is that it helps us articulate assumptions and hypotheses
concerning our strategies and targets of intervention. Debates among policymakers
concerning public health programs are often complicated by unspoken assumptions or
confusion about which data are relevant. Theory can inform these debates by clarifying key
constructs and their presumed relationships. Especially when the evidence base is small,
advocates of one approach or another can be challenged to address the mechanisms by
which a program is expected to have an impact. By specifying these alternative pathways to
change, program evaluations can be designed to ensure that regardless of the outcome,
improvements in knowledge, program design, and implementation will occur.
I am pleased to introduce this second edition of Theory at a Glance. I am especially
impressed that the lead authors, Dr. Barbara K. Rimer and Dr. Karen Glanz, have enhanced
and updated it throughout without diminishing the clarity and efficiency of the original. We
hope that this new edition will empower another generation of public health practitioners to
apply the same conceptual rigor to program planning and design that these authors exemplify
in their own research and practice.
Robert T. Croyle, Ph.D.
Director
Division of Cancer Control and Population Sciences
National Cancer Institute
Spring 2005
Acknowledgements
The National Cancer Institute would like to thank Barbara Rimer Dr.P.H. and
Karen Glanz Ph.D., M.P.H., authors of the original monograph, whose knowledge of
healthcommunications theory and practice have molded a generation of health promotion
practitioners. Both have provided hours of review and consultation, and we are grateful to
them for their contributions.
Thanks to the staffs of the Office of Communications, particularly Margaret Farrell,
and the Division of Cancer Control and Population Sciences and Kelly Blake, who guided
this monograph to completion. We appreciate in particular the work of Karen Harris,
whose attention to detail and commitment to excellence enhanced the monograph’s
content and quality.
Table of Contents
Introduction viii
Audience and Purpose 1
Contents 1
Part 1: Foundations of Theory in Health Promotion and Health Behavior 3
Why Is Theory Important to Health Promotion and Health Behavior Practice? 4
What Is Theory? 4
How Can Theory Help Plan Effective Programs? 4
Explanatory Theory and Change Theory 5
Fitting Theory to the Field of Practice 5
Using Theory to Address Health Issues in Diverse Populations 7
Part 2: Theories and Applications 9
The Ecological Perspective: A Multilevel, Interactive Approach 10
Theoretical Explanations of Three Levels of Influence 12
Individual or Intrapersonal Level 12
Health Belief Model 13
Stages of Change Model 15
Theory of Planned Behavior 16
Precaution Adoption Process Model 18
Interpersonal Level 19
Social Cognitive Theory 19
Community Level 22
Community Organization and Other Participatory Models 23
Diffusion of Innovations 27
Communication Theory 29
Media Effects 30
Agenda Setting 30
New Communication Technologies 31
Part 3: Putting Theory and Practice Together 35
Planning Models 36
Social Marketing 36
PRECEDE-PROCEED 39
Where to Begin: Choosing the Right Theories 43
A Few Final Words 44
Sources 48
References 49
Tables and Figures
Tables
Table 1 An Ecological Perspective: Levels of Influence 11
Table 2 Health Belief Model 14
Table 3 Stages of Change Model 15
Table 4 Theory of Planned Behavior 17
Table 5 Social Cognitive Theory 20
Table 6 Community Organization 24
Table 7 Concepts in Diffusion of Innovations 27
Table 8 Key Attributes Affecting the Speed and Extent of an Innovation’s Diffusion 28
Table 9 Agenda Setting, Concepts, Definitions, and Applications 31
Table 10 Diagnostic Elements of PRECEDE-PROCEED 42
Table 11 Summary of Theories: Focus and Key Concepts 45
Figures
Figure 1 Using Explanatory Theory and Change Theory to Plan and Evaluate Programs 6
Figure 2 A Multilevel Approach to Epidemiology 10
Figure 3 Theory of Reasoned Action and Theory of Planned Behavior 18
Figure 4 Stages of the Precaution Adoption Process Model 19
Figure 5 An Integrative Model 21
Figure 6 Sociocultural Environment Logic Framework 26
Figure 7 An Asthma Self-Management Video Game for Children 33
Figure 8 Social Marketing Wheel 38
Figure 9 The PRECEDE-PROCEED Model 40
Figure 10 Using Theory to Plan Multilevel Interventions 46
Introduction
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his monograph, Theory at a Glance: Application to Health Promotion and Health
Behavior (Second Edition), describes influential theories of health-related behaviors,
processes of shaping behavior, and the effects of community and environmental
factors on behavior. It complements existing resources that offer tools, techniques,
and model programs for practice, such as Making Health Communication Programs Work:
A Planner’s Guide,i and the Web portal, Cancer Control PLANET (Plan, Link, Act, Network
with Evidence-based Tools).ii Theory at a Glance makes health behavior theory accessible
and provides tools to solve problems and assess the effectiveness of health promotion
programs. (For the purposes of this monograph, health promotion is broadly defined as the
process of enabling people to increase control over, and to improve, their health. Thus, the
focus goes beyond traditional primary and secondary prevention programs.)
For nearly a decade, public health and health care practitioners have consulted the original
version of Theory at a Glance for guidance on using theories about human behavior to inform
program planning, implementation, and evaluation. We have received many testimonials
about the First Edition’s usefulness, and requests for additional copies. This updated edition
includes information from recent health behavior research and suggests theoretical
approaches to developing programs for diverse populations. Theory at a Glance can be
used as a stand-alone handbook, as part of in-house staff development programs, or in
conjunction with theory texts and continuing education workshops.
For easy reference, the monograph includes only a small number of current and applicable
health behavior theories. The theories reviewed here are widely used for the purposes of
cancer control, defining risk, and segmenting populations. Much of the content for this
publication has been adapted from the third edition of Glanz, Rimer, and Lewis’ Health
Behavior and Health Education: Theory, Research, and Practice,1 published by Jossey-Bass
in San Francisco. Readers who want to learn more about useful theories for health behavior
change and health education practice can consult this and other sources that are
recommended in the References section at the end of the monograph.
i Making Health Communication Programs Work (http://www.nci.nih.gov/pinkbook/) describes a practical
approach for planning and implementing health communication efforts.
ii Cancer Control PLANET (http://cancercontrolplanet.cancer.gov) provides access to data and resources
that can help planners, program staff, and researchers to design, implement, and evaluate evidence-based
cancer control programs.
(http://www.nci.nih.gov/pinkbook/)
(http://cancercontrolplanet.cancer.gov)
Audience and Purpose
This monograph is written primarily for public health workers in state and local health
agencies; it is also valuable for health promotion practitioners and volunteers who work in
voluntary health agencies, community organizations, health care settings, schools, and the
private sector.
Interventions based on health behavior theory are not guaranteed to succeed, but they are
much more likely to produce desired outcomes. Theory at a Glance is designed to help users
understand how individuals, groups, and organizations behave and change—knowledge they
can use to design effective programs. For information about specific, evidence-based
interventions to promote health and prevent disease, readers may also wish to consult the
Guide to Community Preventive Services, published by the Centers for Disease Control and
Prevention (CDC) at www.thecommunityguide.org.
Contents
This monograph consists of three parts. For each theory, the text highlights key concepts
and their applications. These summaries may be used as “checklists” of important issues to
consider when planning or evaluating programs or to prompt project teams to think about the
range of factors that influence health behavior.
Part 1. Foundations of Theory in Health Promotion and Health Behavior describes ways that
theories and models can be useful in health behavior/health promotion practice and
provides basic definitions.
Part 2. Theories and Applications presents an ecological perspective on health
behavior/health promotion programs. It describes eight theories and models that
explain individual, interpersonal, and community behavior and offers approaches to
solving problems. A brief description of each theory is followed by definitions of key
concepts and examples or case studies. The section also explores the use of new
communication technologies.
Part 3. Putting Theory and Practice Together explains how theory can be used in health
behavior/health promotion program planning, implementation, and evaluation.
Two comprehensive planning models, PRECEDE-PROCEED and social marketing,
are reviewed.
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Part 1
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Why Is Theory Important to
Health Promotion and Health
Behavior Practice?
Effective public health, health promotion,
and chronic disease management programs
help people maintain and improve health,
reduce disease risks, and manage chronic
illness. They can improve the well-being
and self-sufficiency of individuals, families,
organizations, and communities. Usually,
such successes require behavior change at
many levels, (e.g., individual, organizational,
and community).
Not all health programs and initiatives are
equally successful, however. Those most
likely to achieve desired outcomes are
based on a clear understanding of targeted
health behaviors, and the environmental
context in which they occur. Practitioners
use strategic planning models to develop
and manage these programs, and
continually improve them through
meaningful evaluation. Health behavior
theory can play a critical role throughout
the program planning process.
What Is Theory?
A theory presents a systematic way of
understanding events or situations. It is a
set of concepts, definitions, and propositions
that explain or predict these events or
situations by illustrating the relationships
between variables. Theories must be
applicable to a broad variety of situations.
They are, by nature, abstract, and don’t
have a specified content or topic area.
Like empty coffee cups, theories have
shapes and boundaries, but nothing inside.
They become useful when filled with
practical topics, goals, and problems.
• Concepts are the building blocks—the
primary elements—of a theory.
• Constructs are concepts developed or
adopted for use in a particular theory.
The key concepts of a given theory are
its constructs.
• Variables are the operational forms of
constructs. They define the way a
construct is to be measured in a specific
situation. Match variables to constructs
when identifying what needs to be
assessed during evaluation of a theory-
driven program.
• Models may draw on a number of theories
to help understand a particular problem in
a certain setting or context. They are not
always as specified as theory.
Most health behavior and health promotion
theories were adapted from the social and
behavioral sciences, but applying them to
health issues often requires that one be
familiar with epidemiology and the biological
sciences. Health behavior and health
promotion theories draw upon various
disciplines, such as psychology, sociology,
anthropology, consumer behavior, and
marketing. Many are not highly developed
or have not been rigorously tested. Because
of this, they often are called conceptual
frameworks or theoretical frameworks; here
the terms are used interchangeably.
How Can Theory Help Plan
Effective Programs?
Theory gives planners tools for moving
beyond intuition to design and evaluate
health behavior and health promotion
interventions based on understanding of
behavior. It helps them to step back and
consider the larger picture. Like an artist,
a program planner who grounds health
interventions in theory creates innovative
ways to address specific circumstances.
He or she does not depend on a “paint-by
numbers” approach, re-hashing stale ideas,
but uses a palette of behavior theories,
skillfully applying them to develop unique,
tailored solutions to problems.
Using theory as a foundation for program
planning and development is consistent with
the current emphasis on using evidence-
based interventions in public health,
behavioral medicine, and medicine. Theory
provides a road map for studying problems,
developing appropriate interventions, and
evaluating their successes. It can inform the
planner’s thinking during all of these stages,
offering insights that translate into stronger
programs. Theory can also help to explain
the dynamics of health behaviors, including
processes for changing them, and the
influences of the many forces that affect
health behaviors, including social and
physical environments. Theory can also help
planners identify the most suitable target
audiences, methods for fostering change,
and outcomes for evaluation.
Researchers and practitioners use theory
to investigate answers to the questions of
“why,” “what,” and “how” health problems
should be addressed. By seeking answers
to these questions, they clarify the nature
of targeted health behaviors. That is, theory
guides the search for reasons why people
do or do not engage in certain health
behaviors; it helps pinpoint what planners
need to know before they develop public
health programs; and it suggests how to
devise program strategies that reach target
audiences and have an impact. Theory also
helps to identify which indicators should be
monitored and measured during program
evaluation. For these reasons, program
planning, implementation, and monitoring
processes based in theory are more likely
to succeed than those developed without
the benefit of a theoretical perspective.
Explanatory Theory and
Change Theory
Explanatory theory describes the reasons
why a problem exists. It guides the search
for factors that contribute to a problem (e.g.,
a lack of knowledge, self-efficacy, social
support, or resources), and can be changed.
Examples of explanatory theories include
the Health Belief Model, the Theory of
Planned Behavior, and the Precaution
Adoption Process Model.
Change theory guides the development of
health interventions. It spells out concepts
that can be translated into program
messages and strategies, and offers a basis
for program evaluation. Change theory
helps program planners to be explicit about
their assumptions for why a program will
work. Examples of change theories include
Community Organization and Diffusion of
Innovations. Figure 1. illustrates how
explanatory theory and change theory can
be used to plan and evaluate programs.
Fitting Theory to the Field of Practice
This monograph includes descriptions and
applications of some theories that are
central to health behavior and health
promotion practice today. No single theory
dominates health education and promotion,
nor should it; the problems, behaviors,
populations, cultures, and contexts of public
health practice are broad and varied. Some
theories focus on individuals as the unit of
change. Others examine change within
families, institutions, communities, or
cultures. Adequately addressing an issue
may require more than one theory, and no
one theory is suitable for all cases.
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Figure 1. Using Explanatory Theory and Change Theory to Plan and Evaluate Programs
Problem
Behavior
or
Situation
ChangeTheory
Which strategies?
Which messages?
Assumptions about
how a program
should work
Evaluation
Planning
Explanatory
Theory
Why?
What can
be changed?
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Because the social context in which
behavior occurs is always evolving, theories
that were important in public health
education a generation ago may be of
limited use today. At the same time, new
social science research allows theorists to
refine and adapt existing theories. A recent
Institute of Medicine report2 observed that
several theorists have converged in their
views, identifying several variables as
central to behavior change. As a result,
some constructs, such as self-efficacy, are
central to multiple theories.
Effective practice depends on using
theories and strategies that are appropriate
to a situation.
One of the greatest challenges for those
concerned with behavior change is learning
to analyze how well a theory or model “fits”
a particular issue. A working knowledge of
specific theories, and familiarity with how
they have been applied in the past,
improves skills in this area. Selecting an
appropriate theory or combination of
theories helps take into account the multiple
factors that influence health behaviors.
The practitioner who uses theory develops a
nuanced understanding of realistic program
outcomes that drives the planning process.
Choosing a theory that will bring a useful
perspective to the problem at hand does not
begin with a theory (e.g., the most familiar
theory, the theory mentioned in a recent
journal article, etc.). Instead, this process
starts with a thorough assessment of the
situation: the units of analysis or change,
the topic, and the type of behavior to be
addressed. Because different theoretical
frameworks are appropriate and practical for
different situations, selecting a theory that
“fits” should be a careful, deliberate process.
Start with the steps in the box at the top of
the next page.
A Good Fit:
Characteristics of a Useful Theory
A useful theory makes assumptions about
a behavior, health problem, target
population, or environment that are:
• Logical;
• Consistent with everyday observations;
• Similar to those used in previous
successful programs; and
• Supported by past research in the same
area or related ideas.
Using Theory to Address Health
Issues in Diverse Populations
The U.S. population is growing more
culturally and ethnically diverse. An
increasing body of research shows health
disparities exist among various ethnic and
socio-economic groups. These findings
highlight the importance of understanding
the cultural backgrounds and life
experiences of community members, though
research has not yet established when and
under what circumstances targeted or
tailored health communications are more
effective than generic ones. (Targeting
involves using information about shared
characteristics of a population subgroup to
create a single intervention approach for
that group. In contrast, tailoring is a process
that uses an assessment to derive
information about one specific person, and
then offers change or information strategies
for an outcome of interest based on that
person’s unique characteristics.)3
Most health behavior theories can be
applied to diverse cultural and ethnic
groups, but health practitioners must
understand the characteristics of target
populations (e.g., ethnicity, socioeconomic
status, gender, age, and geographical
location) to use these theories correctly.
There are several reasons why culture and
ethnicity are critical to consider when
applying theory to a health problem. First,
morbidity and mortality rates for different
diseases vary by race and ethnicity; second,
there are differences in the prevalence of
risk behaviors among these groups; and
third, the determinants of health behaviors
vary across racial and ethnic groups.
What People in the Field Say About Theory
“Theory is different from most of the tools
I use in my work. It’s more abstract, but
that can be a plus too. A solid grounding
in a handful of theories goes a long way
toward helping me think through why I
approach a health problem the way I do.”
— County Health Educator
“I used to think theory was just for
students and researchers. But now I have
a better grasp of it; I appreciate how
practical it can be.”
— State Chronic Disease Administrator
“By translating concepts from theory
into real-world terms, I can get my staff
and community volunteers to take a closer
look at why we’re conducting programs
the way we do, and how they can succeed
or fail.”
— City Tobacco Control Coordinator
“A good grasp of theory is essential for
leadership. It gives you a broader way
of viewing your work. And it helps create
a vision for the future. But, of course, it’s
only worthwhile if I can translate it clearly
and simply to my co-workers.”
— Regional Health Promotion Chief
“It’s not as hard as I thought it would be
to keep up with current theories. More
than ever these days, there are tools and
workshops to update us often.”
— Patient Education Coordinator
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Part 2
Theories and Applications
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The Ecological Perspective: A
Multilevel, Interactive Approach
Contemporary health promotion involves
more than simply educating individuals
about healthy practices. It includes efforts
to change organizational behavior, as well
as the physical and social environment of
communities. It is also about developing and
advocating for policies that support health,
such as economic incentives. Health
promotion programs that seek to address
health problems across this spectrum
employ a range of strategies, and operate
on multiple levels.
The ecological perspective emphasizes the
interaction between, and interdependence
of, factors within and across all levels of a
health problem. It highlights people’s
interactions with their physical and socio
cultural environments. Two key concepts
of the ecological perspective help to identify
intervention points for promoting health:
first, behavior both affects, and is affected
by, multiple levels of influence; second,
individual behavior both shapes, and is
shaped by, the social environment
(reciprocal causation).
To explain the first key concept of the
ecological perspective, multiple levels of
influence, McLeroy and colleagues (1988)4
identified five levels of influence for health-
related behaviors and conditions. Defined
in Table 1., these levels include: (1)
intrapersonal or individual factors; (2)
interpersonal factors; (3) institutional or
organizational factors; (4) community
factors; and (5) public policy factors.
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Figure 2. A Multilevel Approach to Epidemiology
Social and Economic Policies
Institutions
Neighborhoods and Communities
Living Conditions
Social Relationships
Individual Risk Factors
Pathophysiological
Pathways
Individual/Population
Health
Genetic/Constitutional
Factors
Envir
onm
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Li
fe
co
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Source: Smedley BD, Syme SL (eds.), Institute of Medicine. Promoting Health: Strategies from Social and Behavioral
Research. Washington, D.C.:, National Academies Press, 2000.
Table 1. An Ecological Perspective: Levels of Influence
Concept
Intrapersonal Level
Interpersonal Level
Community Level
Institutional Factors
Community Factors
Public Policy
Definition
Individual characteristics that influence behavior, such as
knowledge, attitudes, beliefs, and personality traits
Interpersonal processes and primary groups, including
family, friends, and peers that provide social identity,
support, and role definition
Rules, regulations, policies, and informal structures, which
may constrain or promote recommended behaviors
Social networks and norms, or standards, which exist as
formal or informal among individuals, groups, and
organizations
Local, state, and federal policies and laws that regulate
or support healthy actions and practices for disease
prevention, early detection, control, and management
In practice, addressing the community level
requires taking into consideration
institutional and public policy factors, as well
as social networks and norms. Figure 2.
illustrates how different levels of influence
combine to affect population health.
Each level of influence can affect health
behavior. For example, suppose a woman
delays getting a recommended
mammogram (screening for breast cancer).
At the individual level, her inaction may be
due to fears of finding out she has cancer.
At the interpersonal level, her doctor may
neglect to tell her that she should get the
test, or she may have friends who say they
do not believe it is important to get a
mammogram. At the organizational level,
it may be hard to schedule an appointment,
because there is only a part-time radiologist
at the clinic. At the policy level, she may
lack insurance coverage, and thus be
unable to afford the fee. Thus, the outcome,
the woman’s failure to get a mammogram,
may result from multiple factors.
The second key concept of an ecological
perspective, reciprocal causation, suggests
that people both influence, and are
influenced by, those around them. For
example, a man with high cholesterol may
find it hard to follow the diet his doctor has
prescribed because his company cafeteria
doesn’t offer healthy food choices. To
comply with his doctor’s instructions, he can
try to change the environment by asking the
cafeteria manager to add healthy items to
the menu, or he can dine elsewhere. If he
and enough of his fellow employees decide
to find someplace else to eat, the cafeteria
may change its menu to maintain lunch
business. Thus, the cafeteria environment
may compel this man to change his dining
habits, but his new habits may ultimately
bring about change in the cafeteria as well.
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An ecological perspective shows the
advantages of multilevel interventions that
combine behavioral and environmental
components. For instance, effective
tobacco control programs often use
multiple strategies to discourage smoking.5
Employee smoking cessation clinics have
a stronger impact if the workplace has a
no-smoking policy and the city has a clean
indoor air ordinance. Adolescents are
less likely to begin smoking if their
peers disapprove of the habit and laws
prohibiting tobacco sales to minors
are strictly enforced. Health promotion
programs are more effective when
planners consider multiple levels of
influence on health problems.
Theoretical Explanations of Three
Levels of …
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e. Embedded Entrepreneurship
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Subset 2. Indigenous Entrepreneurship Approaches (Outside of Canada)
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When considering both O
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Identify a specific consumer product that you or your family have used for quite some time. This might be a branded smartphone (if you have used several versions over the years)
or the court to consider in its deliberations. Locard’s exchange principle argues that during the commission of a crime
Chemical Engineering
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aragraphs (meaning 25 sentences or more). Your assignment may be more than 5 paragraphs but not less.
INSTRUCTIONS:
To access the FNU Online Library for journals and articles you can go the FNU library link here:
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In order to
n that draws upon the theoretical reading to explain and contextualize the design choices. Be sure to directly quote or paraphrase the reading
ce to the vaccine. Your campaign must educate and inform the audience on the benefits but also create for safe and open dialogue. A key metric of your campaign will be the direct increase in numbers.
Key outcomes: The approach that you take must be clear
Mechanical Engineering
Organic chemistry
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Topic
You will need to pick one topic for your project (5 pts)
Literature search
You will need to perform a literature search for your topic
Geophysics
you been involved with a company doing a redesign of business processes
Communication on Customer Relations. Discuss how two-way communication on social media channels impacts businesses both positively and negatively. Provide any personal examples from your experience
od pressure and hypertension via a community-wide intervention that targets the problem across the lifespan (i.e. includes all ages).
Develop a community-wide intervention to reduce elevated blood pressure and hypertension in the State of Alabama that in
in body of the report
Conclusions
References (8 References Minimum)
*** Words count = 2000 words.
*** In-Text Citations and References using Harvard style.
*** In Task section I’ve chose (Economic issues in overseas contracting)"
Electromagnetism
w or quality improvement; it was just all part of good nursing care. The goal for quality improvement is to monitor patient outcomes using statistics for comparison to standards of care for different diseases
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Provide a description of an existing intervention in Canada
making the appropriate buying decisions in an ethical and professional manner.
Topic: Purchasing and Technology
You read about blockchain ledger technology. Now do some additional research out on the Internet and share your URL with the rest of the class
be aware of which features their competitors are opting to include so the product development teams can design similar or enhanced features to attract more of the market. The more unique
low (The Top Health Industry Trends to Watch in 2015) to assist you with this discussion.
https://youtu.be/fRym_jyuBc0
Next year the $2.8 trillion U.S. healthcare industry will finally begin to look and feel more like the rest of the business wo
evidence-based primary care curriculum. Throughout your nurse practitioner program
Vignette
Understanding Gender Fluidity
Providing Inclusive Quality Care
Affirming Clinical Encounters
Conclusion
References
Nurse Practitioner Knowledge
Mechanics
and word limit is unit as a guide only.
The assessment may be re-attempted on two further occasions (maximum three attempts in total). All assessments must be resubmitted 3 days within receiving your unsatisfactory grade. You must clearly indicate “Re-su
Trigonometry
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1. In 1972 the Furman v. Georgia case resulted in a decision that would put action into motion. Furman was originally sentenced to death because of a murder he committed in Georgia but the court debated whether or not this was a violation of his 8th amend
One of the first conflicts that would need to be investigated would be whether the human service professional followed the responsibility to client ethical standard. While developing a relationship with client it is important to clarify that if danger or
Ethical behavior is a critical topic in the workplace because the impact of it can make or break a business
No matter which type of health care organization
With a direct sale
During the pandemic
Computers are being used to monitor the spread of outbreaks in different areas of the world and with this record
3. Furman v. Georgia is a U.S Supreme Court case that resolves around the Eighth Amendments ban on cruel and unsual punishment in death penalty cases. The Furman v. Georgia case was based on Furman being convicted of murder in Georgia. Furman was caught i
One major ethical conflict that may arise in my investigation is the Responsibility to Client in both Standard 3 and Standard 4 of the Ethical Standards for Human Service Professionals (2015). Making sure we do not disclose information without consent ev
4. Identify two examples of real world problems that you have observed in your personal
Summary & Evaluation: Reference & 188. Academic Search Ultimate
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We can mention at least one example of how the violation of ethical standards can be prevented. Many organizations promote ethical self-regulation by creating moral codes to help direct their business activities
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The inbound logistics for William Instrument refer to purchase components from various electronic firms. During the purchase process William need to consider the quality and price of the components. In this case
4. A U.S. Supreme Court case known as Furman v. Georgia (1972) is a landmark case that involved Eighth Amendment’s ban of unusual and cruel punishment in death penalty cases (Furman v. Georgia (1972)
With covid coming into place
In my opinion
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The ability to view ourselves from an unbiased perspective allows us to critically assess our personal strengths and weaknesses. This is an important step in the process of finding the right resources for our personal learning style. Ego and pride can be
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While you must form your answers to the questions below from our assigned reading material
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5 The family dynamic is awkward at first since the most outgoing and straight forward person in the family in Linda
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The most important benefit of my statistical analysis would be the accuracy with which I interpret the data. The greatest obstacle
From a similar but larger point of view
4 In order to get the entire family to come back for another session I would suggest coming in on a day the restaurant is not open
When seeking to identify a patient’s health condition
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Your paper must be at least two pages in length (not counting the title and reference pages)
The word assimilate is negative to me. I believe everyone should learn about a country that they are going to live in. It doesnt mean that they have to believe that everything in America is better than where they came from. It means that they care enough
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Single Subject Chris is a social worker in a geriatric case management program located in a midsize Northeastern town. She has an MSW and is part of a team of case managers that likes to continuously improve on its practice. The team is currently using an
I would start off with Linda on repeating her options for the child and going over what she is feeling with each option. I would want to find out what she is afraid of. I would avoid asking her any “why” questions because I want her to be in the here an
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A Health in All Policies approach
Note: The requirements outlined below correspond to the grading criteria in the scoring guide. At a minimum
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Read Connecting Communities and Complexity: A Case Study in Creating the Conditions for Transformational Change
Read Reflections on Cultural Humility
Read A Basic Guide to ABCD Community Organizing
Use the bolded black section and sub-section titles below to organize your paper. For each section
Losinski forwarded the article on a priority basis to Mary Scott
Losinksi wanted details on use of the ED at CGH. He asked the administrative resident