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Running Head: USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 1
Using Psychological Theory to Inform the Development of Digital Health Education
Sara Einhorn
University of North Texas
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 2
Abstract
The internet and other digital technologies expanded the delivery of health education across time
zones and geography. However, the practice of digital health education lacks tested theoretical
models for effective ways to leverage technology for learning. Therefore, health educators
should look to psychological theories, including theories of behavior change, as the foundation
for the practice and delivery of digital health education. More specifically, health educators can
look to theories of tailoring, such as Elaboration Likelihood Model (ELM) and Stages of Change
(SOC) as well as theories of motivation, such as Self-Determination Theory (SDT), Social
Cognitive Theory (SCT), and Goal-Setting Theory (GST). Health educators should use these
theories as a basis for the creation and study of methods for designing and delivering effective
digital health education. Future research should aim to understand the mechanisms of how
technology can enhance health education to provide evidence-based digital health education
programs.
Keywords: digital health education, behavior change, stages of change, self-determination
theory, social cognitive theory, goal-setting theory
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 3
Using Psychological Theory to Inform the Development of Digital Health Education
After decades of existence, health education programs persist and grow, with more
created every day. However, health education programs only recently began to leverage
technology. According to Berhardt, Chaney, Chaney and Hall (2013), the development and
advancement of technology empowered internet-enabled media, which can potentially transform
health education “by enhancing our ability to implement evidence-based behavior change
strategies in manners that are often far more effective and efficient than were possible in the
past” (p. 1).
As part of the enhancement of health education, or behavior change strategies,
technology now allows health education to reach a wider audience and over a longer period
(Bernhardt et al., 2013). The Internet revolutionized the delivery of health education, from
implementation to evaluation. Along with this revolution comes the need to determine the most
effective and efficient manners in which to deliver health education using these new
technologies. While many questions arise regarding health education and new technologies, not
all of them have answers. Regardless, some insight exists when exploring theories of behavior
change.
Like the more traditional types of health education, technology-based programs should be
based on behavior change theories to result in positive long-term outcomes (Riley et al., 2011).
While some information exists on theory-based technology interventions, research has not
saturated the topic area. Like traditional educators, to combat the lack of research, Morrison
(2015) and Riley et al. (2011) look to psychological theories, including theories of behavior
change, to inform the implementation of digital health education. This paper will explore the use
of tailoring, motivation, social support, and self-regulation to inform digital health education to
motivate students to learn.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 4
Tailoring Digital Health Education to Motivate Students
Tailoring occurs in the larger continuum of mass communication, group targeting, and
individualized targeting (Hawkins, Kreuter, Resnicow, Fishbein & Djikstra, 2007). According to
Hawkins et al. (2007), these three groupings highlight two distinct factors in tailoring:
segmentation, meaning the defined groupings of people, and customization, meaning the degree
to which people perceive materials as personally relevant (see Figure 1). Ideally, to achieve the
most tailored message, the materials would use high customization and segmentation. While both
of these are not always attainable, the rest of this section will look into the use of individually
targeted tailoring.
Figure 1. Continuum of tailoring (p.455)
Individualized targeting falls under the term ‘tailoring’ which refers to the use of
personalized information including known behaviors and characteristics specific to the student
(Bensley et al., 2004; Rimer & Kreuter, 2006; Morrison, 2015). Many studies suggest that
tailoring information positively affects motivation, behavior change, and engagement (Bensley et
al., 2004; Hawkins et al., 2007; Lustria, Cortese, Noar & Glueckauf, 2009). In fact, tailored
materials result in an increased likelihood students read and recall the information in addition to
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 5
viewing it as personally relevant (Rimer & Kreuter, 2006; Hawkins et al., 2007; Lustira et al.,
2009; Morrison, 2015).
Additionally, tailored material “enables individualized feedback, commands greater
attention, is processed more intensively, contains less redundant information, and is perceived
more positively by health consumers” (Lustria et al., 2009, p.156). Tailoring information in
health education could engage students on a deeper level because students identify the
information as relevant and individualized. While education via the Internet may not allow for as
much personalization as face-to-face interactions, computers and technology have the unique
ability to use complex tailoring algorithms that can be programmed and executed instantly.
On the other hand, Djikstra (2005) has noted mixed results in past studies of tailoring
educational materials due to the varying types of tailoring. Additionally, certain types of health
education and behavior change may require more effective motivators than tailored material. For
example, Morrison (2015) found that extraneous information (less tailored) may be a positive
factor when offering information that contradicts students’ typical beliefs so that they can
process the contradictions more peripherally. Therefore, health educators must understand the
past experiences and knowledge of the students, which may prove difficult when using only
technology.
The varying information about tailoring health education and the situations to which it
applies generates outstanding questions. How does tailoring truly work? What exactly triggers
these feelings in students? Are these methods of tailoring that are better than others? How can
the ‘digital’ component of digital health education make use of or enhance students’ learning and
motivation?
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 6
A Theoretical Basis for Tailoring
Elaboration Likelihood Model (ELM), psychology theory, explains how personalizing
information can persuade people (Petty, Cacciopo & Goldman, 1981). The theory suggests
“information that is perceived to be personally relevant (as in the case of tailored information)
enhances an individual’s motivation to elaborate on the message, and consequently, his/her
receptivity to persuasion efforts” (Lustria, 2009, p.157). According to Dijkstra (2005), ELM does
not specify how cues can make information more personally relevant; it simply proposes that the
perception of personal relevance allows for easier persuasion. Therefore, Djikstra (2005)
suggests self-referent encoding explains the effectiveness of tailoring materials.
Self-referent encoding occurs when a person makes personal connections between the
material presented and his/her own life (Hawkins et al. 2007; Djikstra, 2005; Morrison, 2015).
For example, a graduate of the University of North Texas will find a study of University of North
Texas students more personally relevant than a study of students from the University of
Washington. The reader in this example will likely make the personal connection to the
University of North Texas and thus begin self-referent encoding. In the study by Djikstra (2005),
tailoring the information only slightly in an online smoking cessation intervention led to more
self-referent encoding and, in turn, more quitting behaviors when compared to standard (non-
tailored) materials. Djikstra (2005) concludes personalization and feedback may relate to higher
effectiveness in online health education programs (in this case for smoking cessation).
Further supporting the mechanisms above, a review of digital health education studies
that used tailoring found that effective tailoring occurred via personalization, feedback, and
content matching (Hawkins, et al., 2007; Lustria et al., 2009). Personalization involves the
inclusion of small but identifiable personal details (age, gender etc.). Feedback consists of
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 7
individualized recommendations based on information provided by each person. Content
matching provides content based on relevant information determined by individual responses.
These three methods of tailoring serve to make the health information more personally relevant
to persuade students to change behavior and so that students will see themselves in the material
(self-referent encoding).
Three main types of feedback exist (Hawkins et al. 2007, Lustria et al., 2009).
Descriptive feedback simply reports known facts based on student responses, such as stating that
the student reported eating three fruits and vegetables each day. Comparative feedback takes
information reported by the student and compares it to information known about others. For
example, comparative feedback may state that because a student eats three fruits and vegetables
each day, s/he eats about as much as the rest of the population. The third type of feedback,
known as evaluative feedback, makes judgments based on student information, such as reporting
that the student’s fruit and vegetable intake is below the recommended value of 5-9 each day.
To elaborate on how tailoring can provide personalized information, feedback, and
matched content, digital health education can further look to the Transtheoretical Model (TTM)
or Stages of Change (SOC). Health education already makes use of SOC when developing
interventions aimed at behavior change but may not register as a distinct method of tailoring.
According to the SOC, change occurs over a long period instead of in one instant action (Bensley
et al., 2004). Therefore, people exist in five different stages of change, shown in Figure 2.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 8
Figure 2. Stages of change
When tailoring digital health education, programs should account for individual stages of
change to pair personally relevant material with each person. For example, providing a student in
the pre-contemplation stage with materials on how to take specific action to lose weight would
not be an effective method of tailoring. Instead, the student in the pre-contemplation stage could
receive information that demonstrates why s/he should consider making a change. Screening
questions can determine each student’s stage of change to ensure the collection of appropriate
information. If the educational program occurs over an extended period, instructors should ask
these questions multiple times as students can move to a different stage.
The Bottom Line in Tailoring Digital Health Education
Regardless of the exact mechanism of tailoring, Kreuter, Oswalkd, Bull & Clark (2000)
found that matching information relevant to the individual or customizing the material presented
results in increased motivation to change health behavior, even if intentional tailoring using the
mechanisms previously described doesn’t occur. When considering the theories and mechanisms
of tailoring, this result demonstrates that, at the very least, matching personally relevant
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 9
information engages the student and invites contemplation of behavior change. However, it
becomes somewhat clear that tailoring information at any level can positively affect health
education.
Transferring health education to the digital realm allows for increased tailoring, despite
decreased personal interaction, which can further motivate students to absorb, contemplate, and
act on the information provided. ELM, self-referent encoding, and SOC provide a theoretical
groundwork on which to tailor materials as they all guide educators on the personalization,
feedback, and content matching necessary to address students in their current situation with their
current views. However, tailoring material in this fashion does not consider other factors such as
preference in media used for delivery, cultural norms, and motivation levels (Kreuter et al.,
2000). While a psychological framework for including all of these factors does not necessarily
exist, health educators should still be careful to consider them. Instead, health educators can look
to psychology to explain theories of motivation to drive sustained behavior change.
Using Theories of Motivation in Digital Health Education
Using technology may also pose a challenge when employing theories about the
motivation for health education. Instructors frequently neglect persistence, retention,
achievement, and satisfaction in motivation in digital learning (Chen & Jang, 2010). Clearly,
behavior change interventions in digital health education need to consider theories of motivation.
As an example, many people experience the difficulty of trying to change behaviors to lose
weight or be more active, especially external instead of internal pressure exists to do so. As
described below, external versus internal factors differ in their ability to motivate students to
learn and change health behaviors.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 10
According to Self-Determination Theory (SDT), the following can enhance student’s
motivation to engage in the health education program and make a change: supporting the
student’s basic human needs to feel as though s/he has chosen to make the change (autonomy),
that s/he is capable of making the change (competence), and that s/he finds connection and
support in making the change (relatedness) (Chen & Jang, 2010; Morrison, 2015). Technology
can enhance the delivery of each of these factors by programming classes appropriately.
Conversely, a person no longer feels motivated and may feel alienated or disjointed if the
program excludes any one of the three elements (Chen & Jang, 2010).
Within SDT, three constructs deal specifically with motivation, as shown in Figure 3
below (Ryan & Deci, 2000; Chen & Jang, 2010). First, intrinsic motivation occurs when a person
completes an activity for enjoyment or a challenge. For example, when someone chooses to run a
race to challenge herself to continue to be healthy after casually running for a few months.
Second, extrinsic motivation occurs when a person completes an activity for a reward or external
pressure. For example, when a man chooses to quit smoking because his wife wants him to quit.
Extrinsic motivation consists of four constructs: external regulation – motivation from an
external reward; introjected regulation – motivation to demonstrate self-worth; identified
regulation – motivation through valuing of the end goal; integrated regulation – motivation
integrated into personal beliefs. Amotivation, the third construct, consists of the lack of
motivation. According to SDT, the types of internal motivation possess the most positive affect
while lacking motivation or obtaining motivation from external factors can lead to negative
consequences.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 11
Figure 3. The self-determination continuum.
The constructs that form SDT relate closely to several theories of online learning, thus
supporting the choice to use SDT as a theoretical starting point for online health education.
According to Chen & Jang (2010), “flexible learning, computer-mediated communication and
social interaction, and challenges for learning technical skills” (p.742) connect to autonomy,
competence, and relatedness. Previous research shows that SDT can predict many learning
outcomes such as performance, diligence, and course approval (Deci & Ryan, 1985). Therefore,
online learning can apply SDT to address and evaluate the rampant attrition in online courses
while serving as the foundation upon which to create effective digital health education.
Additionally, many studies have already established effective ways to motivate students in health
education using SDT.
Educators may start exploring theory as a basis for digital health education, but they also
need to test this theory. As Chen & Jang (2010) note from various studies, motivation differs
depending on the setting in which the learner participates. In other words, students learning in a
traditional environment will be motivated by different factors than those learning in an online
environment. Therefore, researchers need to study and validate the use of SDT in online settings
to glean the most appropriate use for digital health education.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 12
To assess SDT in an online learning environment, Chen & Jang (2010) created a
theoretical model for online learner motivation, shown in Figure 4, which they tested among
students in an online certificate program. Results showed supporting autonomy and competence
positively affected perceived satisfaction of the three basic needs identified by SDT. Positive
needs satisfaction, in turn, positively affected self-determination. Additionally, and contrary to
many studies of SDT, self-determination did not affect learning outcomes but positive support of
autonomy and competency coupled with perceived satisfaction of needs positively affected
learning outcomes.
Figure 4. Chen & Jang (2010) proposed theoretical model for SDT in online learning.
Several implications exist for teachers and instructional designers using SDT for online
education according to Chen & Jang (2010). To support students’ self-determination, teachers
need to provide a meaningful reason to complete each lesson, a relationship that supports choice
and flexibility instead of pressure, and acknowledgment of any negative feelings that arise. This
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 13
study also found that not supporting students’ needs had negative effects and that perception of
social support impacted students more than actual support given, further supporting the idea that
student needs’ must be understood to provide successful online education. Furthermore, student
motivation should be understood in the context of SDT instead of on a dichotomous level
because, as described above, different reasons for course enrollment can lead to varying levels of
course completion.
Social Support and Connection
Providing the student with connection and social support may provide the biggest
challenge of the three factors of SDT (Morrison, 2015). According to White and Dorman (2001),
research studied traditional social support groups for several diseases and health education topics
and results showed enhanced quality of life, improved decision making, and empowered
participants. Shifting focus to online support groups, benefits include 24/7 access from anywhere
in the world and anonymity which can reduce biases and increase openness (White & Dorman,
2001). Online support can also reach those who are potentially difficult to reach including those
who may not normally obtain social support in-person despite a desire to do so. Online support is
also much more cost-effect compared to in-person support.
Health educators should consider certain situations when designing technology-based
health education with social support built in. Some health topics, such as those that are more
stigmatized, benefit more from support of weak ties, like strangers on the internet (White &
Dorman, 2001; Morrison, 2015). On the other hand, support from close ties, like family and
friends, benefit stigmatized topics (Morrison, 2015).
Health educators also need to consider the best ways to create behavior change using
social support. One study by Centola (2011) suggests that the more alike a group of people
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 14
within a social support network, the more likely health behavior change will occur. Centola
(2011) notes that “although these correlations do not imply causal effects of specific traits, they
do suggest that a minimal level of overlapping characteristics between social contacts may
improve the spread of [health] behaviors through social networks” (p.1271). This minimal
overlapping of characteristics may mimic some of the constructs in tailoring, such as self-
referent encoding, which then pushes students to absorb the material and make a behavior
change.
In their study of patients seeking information about pain management, Kostova, Caiata-
Zufferey, and Schulz (2015) noted that users’ behavior in an online support forum differed based
on experience/skill with pain management, with more practiced users looking for tailored
information instead of information about experiences. The behavior described by Kostova et al.
(2015) further supports the idea tailored information may drive behavior change in online social
support for health education. Furthermore, users accessed information that was relevant to their
specific disease stage and experience, supporting tenets in SOC and tailoring discussed
previously (Kostova et al.,2015).
On the other side, some possible disadvantages exist, such as negative feedback and
proliferation of negative behaviors to explore. Online support groups can leave out those cannot
access the internet which often includes disadvantaged or older students (White & Dorman,
2001). It can also increase inflammatory language and interactions as well as misinformation due
to the anonymous nature of the internet. Many studies do not report any negative effects but,
instead, note that a potential for negative effects. These mixed results point to the need for more
research on the adverse effects and designs to avoid when creating online social support in health
education.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 15
When comparing face-to-face interaction with online social interaction, disadvantages
exist. Many mixed results occur in this arena, namely because comparisons are not the same
across studies and many studies do not utilize a theoretical base. However, face-to-face
interaction is expensive and cannot reach as many people as a widespread social network on the
internet. Therefore, research should explore the particular mechanism for online support. For
example, online social support did not have any effect on smoking cessation in one study
(Newman, Szkodny, Llera, & Przeworski, 2011). Furthermore, according to a study by Newman
et al. (2011), more sustained behavior change (in this case abstinence from smoking, drugs,
alcohol, or gambling) occurred with contact from a therapist. The results described in the two
examples above highlight the potential need for human contact, but again possibly only in certain
situations such as that of addiction.
When it comes to social support in digital health education, only one thing is clear:
researchers need more studies of how theory can inform practice. As an example of this need,
among a review of twelve studies by Laranjo et al. (2015), only five made any mention of a
theoretical basis for including social support. Some studies may include social support just to see
if it helps without giving any thought to the mechanism behind the success or lack thereof. Based
on the studies mentioned, some theories pulled for tailoring as well as SDT apply reasonably in
the realm of social support. Health educators need to reach into this rich psychological research
and determine the best way to apply it to online social support. To further inform online social
support and focusing more on the students’ need for autonomy and competence, health educators
can turn to Social Cognitive Theory and Goal-Setting Theory.
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 16
Using Social Cognitive Theory and Goal-Setting Theory in Digital Health Education
Basic Tenets of Social Cognitive Theory
Building upon SDT, Social Cognitive Theory (SCT) can further help motivate students to
learn digital health education. According to Bandura (1998), SCT combines cognitive factors,
environmental factors, and behavioral factors. Environmental factors include social norms and
one’s ability to change his/her environment. Cognitive factors include knowledge, expectations,
and attitudes. Behavioral factors include skills, practice, and self-efficacy, described below.
These factors interact to determine human behavior and behavior change.
Self-efficacy consists of the sentiment that one’s actions will produce the desired result.
Without this sentiment, many people do not feel motivated to act, for example, someone who
feels s/he will never be able to lose weight has no desire to take action to do so. Therefore, health
education needs to empower people to feel as though their actions will result in the desired
outcome by helping students to set appropriate and attainable goals as well as providing them
with what Bandura (1998) calls mastery experiences to help firmly establish self-efficacy.
Feelings of self-efficacy can affect everything from deciding to make a change to gathering the
motivation to do so (Bandura, 1998). Normative influences frame this view of the self in the
context of society.
Normative influences include the social norms that dictate how people should act and
interact (Bandura, 1998). Norms influence behavior by applying social pressures to behavior that
result in a ‘desired’ outcome and socially expected behaviors gain positive reactions. Due to the
negative reactions that non-socially acceptable behaviors gain, students then self-regulate based
on social norms to avoid negative reactions. Students create goals and compare them to societal
norms, judging themselves against this background. Social norms serve as a significant tenet in
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 17
SCT because Bandura (19998) argues that these norms help form human behavior through
expectation and attitudes pervaded by social norms.
SCT overlaps with many of the health education theories mentioned above, further
supporting the use of theory to inform digital health education practice. Both self-efficacy and
the ideas of competence and autonomy in SDT propose that students need to feel as though they
have chosen to make a change and maintain the capability to manifest the desired outcome.
However, SCT looks more at how expectation influences behavior change. Additionally, both
theories look toward a social component and feedback in this context. SDT cites relatedness
whereas SCT looks at normative influences. Both constructs assert that interactions with others
influence behavior change.
Goal-Setting Theory and its overlap with SCT
Goal-Setting Theory (GST) can help students develop appropriate goals in health
education. Initial findings on goal setting demonstrated that choosing goals that are difficult yet
reasonable to attain lead to better performance than easy or vague goals (Locke & Latham,
2006). Four constructs lead to successful performance of goals including persistence, directing
attention, motivation, and knowledge. Locke & Latham (2006) also include the construct of self-
efficacy from SCT as well as moderating factors of goal setting which include feedback,
commitment to the goal, complexity of the task, and situational constraints.
Clearly, constructs from GST overlap with SCT. First, self-efficacy holds a central role in
both theories which makes sense because students need to feel as though they can complete the
chosen goal otherwise they will not work toward it. This ties in with moderating factor of
commitment to the goal; if students set attainable goals, they will become more likely to act and
thus increase their commitment. Appropriate goals should be stated clearly and specifically so
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 18
students will feel committed to them and as though they can reach them. Much like the theories
explained in tailoring, students like to receive feedback on their journey toward achieving a goal
so they can continually develop and support their self-efficacy throughout the process.
Applying SCT and GST to Digital Health Education
According to Morrison (2015), these theories suggest that “goals will be more effective at
motivating behaviour when they are specific, learning orientated, achievable in the short-term
but sufficiently challenging, and linked to a longer-term, distal goals” (p. 4). Therefore,
technology-based health education should help users choose and set appropriate goals (Morrison,
2015), again building on the idea of autonomy from SDT. Technology can enable the constant
feedback addressing student progress that, according to tailoring theories, allows students to feel
positive about their achievements and ability to continue learning and changing behavior.
According to Anderson-Bill, Winnett, & Wojcik (2011), digital health education
programs must help students develop their self-efficacy by using physically and socially
supportive settings while stimulating positive expectations for change. Consequently, students
can then gain self-regulating skills such as planning, problem-solving, and goal-setting.
While less information exists on the use of SCT and GST in online health education,
some preliminary information exists. In one study by Tortelero et al. (2010), an online sex
education intervention based on SCT and self-regulation was shown to reduce risky sexual
behaviors in adolescents. However, this study does not explore the mechanism by which students
changed, or at least delayed, risky behavior. Another study by Turner-McGrievy et al. (2009)
found that a weight loss intervention delivered via podcast was more effective when based on
SCT as compared to a non-theory-based podcast. These podcasts focused on expectations and
reasons to achieve a healthy weight, modeled how to keep a food diary, increased self-efficacy
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 19
behaviors, and increased knowledge about making behavior changes. Due to the limited
intervention, the authors tested an intervention based on SCT that added the ability to self-
monitor and self-regulate and found that participants discover ways to self-regulate outside of the
tools provided, still supporting the use of SCT (Turner-McGrievy & Tate, 2011).
It appears only anecdotal evidence exists for digital health education programs using SCT
and GST. Although health education traditionally uses of both theories, they do not seem to
translate to study in the digital arena. That being said, due to the overlap of constructs and ideas
between SCT, GST and the theories mentioned in previous parts of this paper, SCT and GST
should be studied to determine the most effective way to use them to develop digital health
education. Many questions remain in this arena, highlighting the absence of a formal and
systematic methodology to use theory in digital health education.
Conclusion
The field of health education has been quick to adopt the use of technology, with mixed
results. Health education holds importance for behavior change and disease prevention and
management, supporting a need to discern the effectiveness of digital health education. While
some research exists about digital health education, there is no central methodology for
developing and implementing effective digital health education programs. This lack of central
methodology should drive future health educators to use theory to influence practice and to study
the effectiveness of future interventions to develop a concrete approach.
Many of the psychological theories of behavior change share similar characteristics such
as the need to feel in control and able to make changes that will result in observable outcomes.
Arguably, competence feels much like self-efficacy because both focus on believing one has the
knowledge and experience to attain a goal. The relatedness aspects of SDT closely connect to the
ideas of tailoring including feedback, addressing materials based on where people are in the
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 20
SOC, and making the information personally relevant. The fact that all of these theories overlap
with similar constructs further supports their legitimacy as well as the proposition for further
study of their applications in digital health education.
The sections above clearly show psychological theories and theories of behavior change
should inform design and delivery of digital health education. Future research will need to
combine the underlying theories that support tailoring, motivation, social interaction, and goal
setting to build a framework for developing and implementing digital health education. A great
need for research exists since this field is in its early years. This research should aim to answer
questions such as: What are the most effective ways to motivate students to change health
behavior using technology? How can theory inform digital health education in real world
contexts? How do the practical effects of theory change when taken from in-person to digital
contexts?
USING PYCHOLOGICAL THEORY IN DIGITAL HEALTH EDUCATION 21
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