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Transcript of Long-term weight gain prevention: A theoretically based Internet approach
www.elsevier.com/locate/ypmed
Preventive Medicine 4
Long-term weight gain prevention: A theoretically based Internet approach
Richard A. Winett, Ph.D.a,T, Deborah F. Tate, Ph.D.b, Eileen S. Anderson, Ed.D.a,
Janet R. Wojcik, Ph.D.a, Sheila G. Winett, M.S.c
aDepartment of Psychology, Virginia Polytechnic Institute and State University, Virginia Tech, Blacksburg, VA 24061-0436, USAbUniversity of North Carolina, Chapel Hill, NC 27514, USA
cPC Resources, Blacksburg, VA 24061-0436, USA
Available online 1 April 2005
Abstract
Background. A major focus of Healthy People 2010 is promoting weight management and physical activity because overweight, obesity,
and a sedentary lifestyle are strongly associated with risk for heart disease and stroke, diabetes, cancers, and premature death.
Methods. Prevalence data and a focused review of weight management and physical activity studies point to the long-term weight gain
prevention in normal weight (21–25 BMI), overweight (25–29 BMI), and even moderate obese (30–34 BMI) people as one alternative to
prioritizing weight loss in health behavior interventions. This is because on a population basis annual weight gain is small (~0.8 kg/year) and
preventing weight gain appears to require only an energy shift of about 100 cal/day either through a modest increase in physical activity and/
or consuming slightly less calories to maintain an energy balance. A more dynamic use of social cognitive theory (SCT) for developing
programs to maintain health behavior changes is emerging with some evidence of long-term maintenance. The high use of the Internet
provides a vehicle to reach different population segments with readily accessible, SCT-tailored long-term programs. Research studies using
the Internet with tailored SCT interventions have shown changes in nutrition practices, physical activity, and weight loss for up to a year.
Conclusions. One promising approach to weight gain prevention in population segments is the development and wide spread use of
longer-term Internet programs using specific principles and procedures from SCT.
D 2005 Elsevier Inc. All rights reserved.
Keywords: Weight gain prevention; Weight management; Physical activity; Internet; Health behavior; Social cognitive theory
Introduction
Two of the ten leading health indicators of Healthy
People 2010, a comprehensive plan and roadmap for
improving the health of all Americans [1], focus on
bodyweight and physical activity. Decades of research show
the central role of these health behaviors for disease
prevention [2]. Overweight, obesity, and a sedentary life-
style are associated with type 2 diabetes and the metabolic
syndrome [3–6], heart disease (particularly, the association
with central obesity [7–9]), stroke [10], colon, breast,
endometrial, esophagial, and renal cancers [11–17], and
the loss of quality and years of life and premature death [18–
21]. It has been postulated that a sedentary lifestyle is the
0091-7435/$ - see front matter D 2005 Elsevier Inc. All rights reserved.
doi:10.1016/j.ypmed.2004.12.005
T Corresponding author.
E-mail address: [email protected] (R.A. Winett).
common factor underlying chronic diseases in developed
countries [22]. An enormous burden is placed on the health
care system by the diseases associated with overweight and
obesity [23,24]. Despite increased attention to this problem,
more Americans and people in other developed countries
are becoming overweight (body mass index; BMI 25–29)
and moderately obese (BMI 30–34) [25–27] and remain
largely sedentary [28–31]. Hill and colleagues [32] predict
that if current rates of increases in prevalence continue, by
2008 about 75% of the U.S. population will be overweight
and close to 40% of those will be obese.
Weight management most often has been approached
from a clinical perspective with extended, higher dose
interventions [33]. However, the prevalence rates of over-
weight, obesity, and a sedentary lifestyle suggest that lower-
cost approaches need to be developed that can be adapted to
many population segments. One such approach is weight
1 (2005) 629–641
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641630
gain prevention [32], a dharm reductionT strategy. Instead of
attempting weight-loss interventions with millions of
people, the goal of weight gain prevention is to stabilize
weight across population segments. If weight gain preven-
tion is a viable concept then methods are needed to
effectively promote the dietary and physical activity
practices central to weight gain prevention. Internet weight
gain prevention programs can reach different population
segments, and if based on health behavior theory, could be
effective and not expensive per user.
The purposes of this paper are to develop the rationale
for weight gain prevention as a major public health policy
and to show based on recent research how an Internet
delivery system can be effective for weight gain prevention
interventions. The first sections of the paper briefly review
weight-loss and physical activity interventions and describe
effective procedures that can be used in weight gain
prevention. The next section describes the bases for weight
gain prevention and necessary program components. Later
sections develop the theoretical rationale for weight gain
prevention, provide examples of computer and Internet
programs that show evidence for changing dietary and
physical activity behaviors, and suggest research and steps
that need to be taken to make weight gain prevention a
centerpiece of effective public health policy. The assump-
tions are that there are multiple causes for the increased
prevalence of overweight and obesity [34,35] and that
programmatic efforts aimed at behavioral changes across
population segments require supportive policy, regulatory,
and environmental changes [32,35–37]. The focus, how-
ever, of this paper is the theory, programming, and
exemplars of the health behavior components of these
larger and multifaceted issues and efforts required for
weight gain prevention.
Behavioral approaches for overweight and obesity
The problem of overweight and obesity has been
addressed by both behavioral treatments and more tradi-
tional public-health approaches emphasizing policy and
environmental changes. We focus on behavioral approaches
that typically have been used with small groups of people in
order to glean effective program components that can be
adapted to weight gain prevention programs and eventually
delivered to population segments using the Internet.
Contemporary, higher dose, longer-term behavioral inter-
ventions that focus on self-regulation strategies (i.e., mon-
itoring food consumption, planning and scheduling meals,
goal setting, self-incentives), dietary changes including a
lower-fat and calorie restricted diet, and physical activity via
lifestyle changes have shown modest, but enduring and
meaningful weight loss [33,38–54]. Most striking is that a
weight loss of 5% to 10% if maintained favorably impacts
risk factors for heart disease (e.g., blood pressure and lipids),
cancers (e.g., body fat), and diabetes (e.g., insulin resistance)
[33]. In addition, some people are successful in long-term
weight loss on their own [48,49], while there are many people
attempting to manage their weight who are not very
consistent or persistent in using existing strategies [50].
Much has been learned from people who are successful
at maintaining meaningful levels of weight loss (5–10% of
bodyweight) for at least a year including the importance of
self-regulation strategies such as careful monitoring of food
consumption and physical activity, frequent weighing,
adherence to lower fat diets, and increasing the variety of
lower-fat foods and fruits and vegetables and decreasing the
variety of higher fat foods, fats and oils, and sweets
consumed [48,51–53]. Key studies [38,54–57] have placed
an emphasis on physical activity and exercise for weight
loss and preventing weight regain. These studies show
that convenient, moderate intensity exercise or physical
activity – primarily walking – can be maintained by
overweight people, and such physical activity has been
linked to better long-term weight management [45,57,58]. A
caveat is that it appears that considerably more physical
activity (60–90 min/day) than the current recommendation of
30 min/day may be required to help maintain weight loss
among people with a history of overweight and obesity [57–
61]. More recent research, however, indicates that the caloric
expenditure equivalent of 6–7 miles/week of walking (i.e.,
~30 min/day of walking) appears to be a threshold level to
prevent weight gain [62], although other research suggests
somewhat more physical activity may be needed [63,64].
The major dilemma for weight loss and for physical
activity and exercise programs has been the difficulty of
maintaining health behavior changes once a program ends
[33]. Relapse has been the rule rather than the exception.
Longer duration programs have shown more success and
have suggested a conceptual shift for programming for long-
term maintenance. Recent trials in physical activity, for
example, have shown that when interventions continue in
some reasonable dose, then long-term health-behavior
change and health benefits are apparent [65–68]. Similarly,
longer-term, sustained interventions are becoming more
prominent in weight management with some evidence of
efficacy at 18–24 months after post-test [33].
These longer-term interventions treat sedentary behavior
and over-consumption of food as chronic problems needing
some form of continuous intervention just as chronic
diseases are treated [69]. Such interventions need to be
theoretically based, dynamic to deal with changing life
circumstances, and engaging enough to keep people focused
on physical activity and nutrition for years. Adoption of new
physical activity patterns and nutrition behaviors are fragile
changes for many people, suggesting the need for contin-
uous intervention [70].
The projects reported by Perri and Corsica in their
extensive review of weight management studies [33] show
positive long-term results with programs lasting a year or
more. Their review also highlights three important, con-
tinuing problems: (a) the difficulty of obtaining long-term
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641 631
program adherence, (b) the relatively high cost of providing
such longer-term interventions, and (c) the need to better
specify and articulate theoretically based strategies appro-
priate for different phases of change. For example, analyses
of long-term intervention studies indicate that specific self-
regulatory strategies programmed in timely and appropriate
ways to deal with predictable obstacles and not simply
didactically delivered content and extended contact are
critical [33].
Data from physical activity trials also indicate that long-
term interventions need to be dynamic to meet changing
circumstances and of sufficient dosage to maintain changes
[65,68]. Such long-term programs present cost and feasibility
problems. Later sections of this paper show that part of this
dilemma may be solved by the use of advanced technology
and the Internet where the primary costs of interventions are
in the initial development and less in their continuance. The
use of advanced technology also allows for fine-grain and
ongoing tailoring and strategy delivery. Recent research
shows how mediated interventions, including print and
Internet-based interventions, are more effective when there
is sufficient tailoring to important variables associated with
health-behavior change [43,71–74,106–110]. These are
points consistent with the theoretical base we describe for
such interventions.
While much is gained by considering the effective aspects
of traditional weight-loss programs, there are a number of
key limitations in addition to dose and program duration that
do not make weight-loss programs the singular public health
policy. Traditional weight-loss programs tend to attract self-
selected and more motivated participants [33]. Weight gain
prevention programs need to attract and continually engage a
broad array of people if such programs are to have public
health impacts. In traditional weight-loss programs, weight
loss may be realized and maintained with important health
benefits particularly if people remain physically active.
However, most participants are still overweight or obese at
the end of treatment, despite considerable effort, and remain
at risk [38]. For example, a 7% weight loss that is
successfully maintained does result in favorable changes in
risk factors as noted, but a person who was 91.0 kg at the
start of the program will now weigh 84.5 kg and will still be
at appreciable risk. Achieving and maintaining substantial
weight loss while perhaps getting easier over time for those
with some degree of success [76] is very difficult for most
people. Thus, while traditional weight-loss programs have
become more effective and provide direction for weight gain
prevention programs, they cannot be viewed as the only
strategy for slowing the trend of increased prevalence of
overweight and obesity across the population.
Weight gain prevention
While dramatic presentations of the problem of over-
weight and obesity are needed to galvanize concerted effort,
in actuality as Hill and colleagues [32] and Jeffrey and
French [77] have pointed out, the annual mean weight gain
across the population is small. Hill et al. [32] estimated that
among people 20–40 years old, the annual weight gain is
slightly less than 1.0 kg/year. Data from the CARDIA study
[78], which investigated weight changes in African Amer-
ican and Caucasian males and females over 15 years,
indicate that overall weight gain during young to middle
adulthood averages ~0.70 kg/year. It appears that the largest
weight gain occurs in the 20s and then levels off. Thus, for
the most part, the problem may be a relatively small energy
imbalance (denergy gapT) played out over many years.
Indeed, Hill et al. [32] estimated mean energy accumulation
accounting for both the metabolic costs of storing energy
and considering their estimates for the 90th percentile for
excess energy storage was only about 50 kcal/day. This
means that many people may be consuming on average as
little as 100 kcal more than expended each day to account
for storage of 50 extra kcal/day needed to gain ~0.70 kg/
year [32]. This is not to suggest that most people eat in a
consistent way each day; that what people are eating is
optimal; that some people do not consistently gain and lose
weight in a year; or that the average weight fluctuation for
the population best reflects the wide range of annual weight
gain and weight loss for some population segments [32].
Rather, this does suggest that across a year and for many
people, the imbalance appears to be small and correctable.
The relatively small annual weight gain across the popu-
lation also suggests that even in the face of a dtoxicenvironmentT [79] many people do some self-regulation of
food consumption. For example, if the mean caloric excess
was 350 cal/day, certainly within a range suggested by
portrayals of the dtoxic environmentT [79], then the mean
weight gain would be 16.6 kg/year. Weight gain prevention
also seems viable given that Block [80] has found that about
30% of calories consumed in the United States are derived
from soft drinks, candy, and snacks, seemingly ddisposablecaloriesT that can be curtailed. These data and attendant
interpretative points suggest conceptual and public policy
shifts entailing more focus on achieving the goal of the
weight gain prevention for people of dnormal weightT (BMI
21–24) and the seemingly viable goal of harm reduction, if
not weight loss, for people who are doverweightT (BMI 25–
29) or even dmoderately obeseT (BMI 30–34).
The most basic notion of weight gain prevention is
straightforward and involves the denergy equationT. If thereis a balance between energy expenditure and energy
consumption, weight remains the same. Balance may be
achieved through combinations of modest changes in
physical activity and diet that can contribute to an increase
in energy expenditure and/or decrease in energy consump-
tion to eliminate the energy excess of 100 kcal/day. These
figures provide a quantifiable public health goal that can be
achieved, for example, by consistently walking 1 mile/day
(~2,000 pedometer steps, or walking 15–20 min all at one
time or throughout the day), or by eating slightly less at each
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641632
meal, or eating one less cookie per day or two fewer soft
drink servings over a period of 3 days. There is little
evidence to suggest that small increases in physical activity
will be compensated for by an increase in consumption [81],
and there is emerging evidence discussed later that such
smaller though targeted changes in physical activity and
food consumption are acceptable and quite achievable by
many people.
Weight gain prevention in theory seems easy to achieve.
However, because most people neither monitor food
consumption nor physical activity in any systematic way
[82], seemingly a requirement for weight gain prevention
and a major self-regulatory strategy used in weight-loss
programs, weight gain prevention will not be that easy to
achieve in practice. Consider, for example, one potential
recommended strategy for weight gain prevention; ddrinkone less soft drink (~150 cal) per dayT. The calories saved
from eliminating one soft drink, however, can easily be
compensated for by eating a small quantity of food or
reducing physical activity. Self-regulation strategies must be
enacted over time and need to be added to the other key
components for weight gain prevention [77]. It also is not
clear what are minimum amounts of physical activity that
are required to prevent weight gain although that amount
likely depends upon the ability to self-regulate food
consumption. Assuming we can develop effective programs
based on research addressing these issues, a viable delivery
system is then needed to reach population segments.
Weight gain prevention with large groups of people has
been examined. The best known of these programs is the
randomized control study, Pound of Prevention [77]. At the
end of the 3-year Pound of Prevention trial, however, there
were no differences between the intervention groups and the
non-treated control group with all groups gaining a small
amount of weight over time. As with a number of other
interventions conducted during that era, the Pound of
Prevention trial attempted to demonstrate the efficacy of a
lower-cost, lower dose (e.g., 2–4 page monthly newsletters),
relatively standardized intervention applied to many people.
This approach has obvious appeal for reaching public health
goals, but when objective outcome measures are used, few
studies have shown its efficacy [83].
Jeffery and French [77] made specific recommendations
to improve weight gain prevention programs by (a)
increasing the frequency of contact; (b) making programs
more tailored and interactive; (c) focusing more on physical
activity and changes in eating patterns; (d) having provi-
sions to respond to observed weight gain; and (e) maintain-
ing motivation over the long-term. In addition, there are
studies that have demonstrated weight gain prevention in
smaller, targeted groups, although these interventions have
used much higher doses (e.g., more and extended personal
contact) than used in the Pound of Prevention trial [84–89],
and pilot data from the America on the Move campaign [90].
These studies and the conclusions reached by Jeffery and
French [77] suggest that weight gain prevention may be
achievable in larger population segments. However, to
achieve these goals, research needs to be directed to
strategies and delivery systems to reach large groups of
people at low cost while still allowing interventions that
have frequent, tailored, and interactive content, focus on key
health behaviors plus respond quickly to weight gain, and
remain engaging over long periods.
Internet-based interventions
One vehicle that can be used to deliver tailored, relatively
high dose interventions over an extended time and at modest
cost once an effective program is developed is the Internet.
Access to the Internet is moving towards universal coverage
though with evidence of some continued ddigital divideTparticularly for broadband, high-speed access [91,92]. The
data suggest groups prone to overweight or obesity (e.g.,
African Americans [26]) may have somewhat lower rates of
Internet use and broadband access is considerably less in
rural compared to urban areas. One limitation of Internet-
based interventions is that some non-users correspond to
people at greater health risk.
Recent data based on 3,553 telephone interviews indicate
a more dynamic picture. Internet users still tend to be
younger, Caucasian, better educated, with higher incomes,
and from suburban or urban areas [93]. Internet users’ levels
and styles of Internet use, however, change frequently; some
people use the Internet regularly on a daily or weekly basis,
others use it more intermittently, and still others use it for a
time and stop. Of those who do not currently use the Internet,
younger African Americans and younger Hispanic Ameri-
cans are more likely to intend to do so in the near future [93].
There no longer appears to be a dgender gapT for Internetaccess and use. In addition, among users reporting annual
incomes of more than US$30,000, the proportion of Internet
users who are Caucasian, African American, or Hispanic is
similar to the general population, although African Ameri-
cans and people with disabilities still use the Internet at
somewhat lower rates than other groups. It appears the
overall percent of the population that uses the Internet has
leveled off at about 60%, since the number of new users
seems offset by the number of people discontinuing use [93].
The spread of Internet use parallels the spread of similar
technological innovations, but, perhaps, Internet use will
increase again as other communication modalities (i.e., cell
phones and television) integrate with Internet access. These
data suggest that at this point an Internet intervention is not
a good match for engaging people with limited income and
education as both access and literacy skills are likely to be
barriers. On the other hand, these data suggest that Internet
use in lower-middle income groups and minorities has
increased in the last 2 years and that the likelihood of
attracting relatively diverse groups of people for an Internet-
based intervention has improved and should continue to
improve in the future [93].
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641 633
Any Internet-based approach to the prevention of weight
gain needs to use strategies to increase the representation of
people less likely to be attracted to an Internet health
behavior program, but who do have the access and skills to
use the Internet. We do not offer Internet-based programs as
a dpanaceaT for reaching all people, much less for sharply
curtailing the epidemic of overweight and obesity. It is
simply one approach that can be used in conjunction with
other public health and clinical efforts. Indeed, our
collective experience suggests, not surprisingly, that Inter-
net-based programs work well with people who have
incorporated Internet use into their daily lives. Further,
while it is estimated that close to half of Internet users report
seeking health information through the Internet [94], this is
not the same as prolonged, programmatic use envisioned for
sustained weight gain prevention. Such programming needs
methods to continually engage people plus use strategies
based on health behavior theory.
Theoretical base
One theoretical base for weight gain prevention builds on
and integrates recent work in behavioral maintenance and
long-term change [43,95–100] with social cognitive theory
(SCT). Triadic SCT emphasizes the dynamic interplay of the
self-system with behavioral competencies and the environ-
ment-key dimensions in long-term behavior change. In the
face of predictable lapses and relapses, SCT suggests what is
needed to recover and return to adherence is a dresilient senseof self-efficacyT. That resilient sense of self-efficacy must be
developed specifically for a given set of health behaviors
(e.g., being physically active and eating nutritiously) and
needs to be developed over time through a series of mastery
experiences. Those mastery experiences must promote some
modification or differential use of self-regulation skills (i.e.,
planning, self-monitoring, problem solving, self-standards,
goals, self-incentives) and some altered behavioral compe-
tencies. SCT further suggests the process of behavior change
and maintenance is enhanced through social support and a
cognizance of the individual’s ecology. That is, as described
by Bandura [95,96], the dfourth generationT of health
behavior interventions does not just rely on information
(first generation), external reinforcement (second), or
entirely on self-regulation (third). Rather it attempts to
embed a more dynamic approach to self-regulation (i.e.,
adaptive self-regulation skills) within a network of social
influences germane to the individual’s ecology and/or
provide continued support [95] so that the individual can
overcome particular barriers to change (i.e., limited time for
physical activity or meal preparation, unsafe neighborhoods)
and prescribe changes within specific contexts.
In addition, the new behaviors need to be functionally
valuable, particularly if they are to be maintained. That
value is likely enhanced if the initial expectations provided
to people about outcomes are realistic [99]. The focus on
outcome expectancies is important for the promotion and
then efficacy of programs for weight gain prevention. This
is because expectations about weight loss are usually
unrealistically positive [99]. On the other hand, the idea of
weight gain prevention is new and its value is likely to be
unknown if not downplayed by diverse segments of people
enamored with weight loss. There may be less question
about the ability to sustain some simple behavior changes
over time for weight gain prevention, but there may be little
motivation to do so if outcome expectancies are neutral or
negative or there is dissatisfaction compared to initial
unrealistically positive expectancies [101].
Rothman and Rothman et al. [98,99] noted that be-
havioral health interventions reliably report lapses and
relapses, yet little attention has been focused on the
processes involved in long-term change. They propose
interventions with successive phases specifically to address
problems in long-term maintenance. Rothman et al. [99]
postulated that positive outcome expectancies are associated
with beginning a behavior change effort and self-efficacy
and self-regulation strategies are predictive of initiation and
the early establishment of behavior change. However,
dsatisfactionT with the actual experience of behavior change
after several months may be more important and predictive
of maintenance. Thus, beginning with realistic expectations
while perhaps quelling some initial enthusiasm, or even
dissuading some people from joining a program, may,
however, facilitate long-term maintenance for those people
enlisted into a program. This is because unrealistically
positive outcome expectancies can predictably result in
dissatisfaction when actual outcomes are then compared to
initial expectations. Rothman et al.’s [99] perspective also
points to the dynamic nature of behavior change with recent
research supporting the postulated relationships between
self-efficacy and initiation of behavior change and satisfac-
tion with maintenance [99]. A more fine-grain theoretical,
albeit speculative rendition of these findings is that there is a
dynamic interplay between self-efficacy, self-regulation, and
outcome expectancies so that over time (and programmati-
cally) self-efficacy and self-regulatory practices need to be
maintained in the face of altered and perhaps less positive
outcome expectancies. Thus, while SCT has been the
theoretical base for numerous health behavior interventions,
the very dynamic, transactional nature of SCT has not
always been appreciated [96]. As a result, dynamic and
longer-term interventions that properly represent SCT
theory have only rarely been implemented.
The natural, extended, and dynamic course of health-
behavior change involves a series of episodes of adher-
ence, lapses, relapses, and recovery as the individual faces
new behavioral challenges and contexts. Interventions
need to plan for these predictable episodes and be long
enough to provide individuals with the self-regulatory
tools and supports to effectively problem solve and then
deal with minor and major setbacks and learn from those
experiences.
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641634
Different, though complementary, theories point toward
the central role of actual training in a set of relevant contexts
to equip people to deal with new situations and potential
impediments to behavior change. Bandura [95] describes
such behavioral training as providing bmastery experiences
best accomplished through instruction, modeling, and
planned actions with goals, corrective feedback and problem
solvingQ. Kazdin [102], from an operant perspective,
describes it as dtraining for the general caseT for both
response maintenance and transfer of training. Bouton [70],
from a more general learning perspective, describes this as
learning in different stimulus contexts. It appears partic-
ularly critical that such training be integrated into the entire
intervention and not merely dtacked onT at the end of the
intervention.
We also suggest that weight gain prevention programs
need to be presented and promoted differently than weight-
loss programs. A later section presents preliminary evidence
that weight gain prevention can be either part of a healthy
lifestyle program or, perhaps, simply an outcome of such
programs without much emphasis on weight per se. The
point is that unrealistic outcome expectations would be less
likely to accompany program enrollment and certainly not
encouraged by program content.
Personalization and tailoring of interventions also may be
additive to SCT-based interventions and more powerful if
they (a) reflect the major social cognitive determinants of
health behavior (self-efficacy, outcome expectations, and
self-regulation skills [95,96]) and (b) are ongoing and
responsive as people change over the course of the
intervention.
Interventions that provide a basis for personal re-
identification also may have value. Through re-identifica-
tion, people may begin to perceive themselves as dregularlyactive people who pay attention to nutritionT rather than as
people, who are sedentary, are dnow and thenT physically
active, and who eat whatever is available [103]. Such
dtransformationsT are part of the self-system and self-
standards [96]. They represent personal commitments that
can be reinforced through behavioral enactment and positive
feedback.
SCT represents a theoretical base for developing inter-
ventions, in this case, advanced technology Internet
interventions, capitalizing on the cost efficiencies, tailoring
ability, ready and long-term access, and the potential reach
of the Internet. These interventions could be used by
significant segments of the population to meet the public
health goal of weight gain prevention.
What evidence is there that computer-based and Internet-
delivered interventions can result in meaningful health
behavior changes, and what is their potential for long-term
change? As demonstrations of the feasibility of taking the
next steps to make more population-wide weight gain
prevention a reality, we briefly describe our recent studies in
nutrition, physical activity, and weight loss computer-based
and Internet interventions and the SCT underpinnings of this
work. There are at least two caveats for these exemplars.
They are rudimentary examples and not the more complex,
much longer-term, multiphase SCT-based interventions that
are likely needed. Other researchers also have demonstrated
the efficacy of Internet-based interventions though few have
used objective measures of outcome [75]. Computer- and
Internet-based interventions described in the next section
have used self-report measures and food shopping receipts,
1-mile walk time, and direct assessment of bodyweight to
assess outcomes.
Studies
Computer- and Internet-based nutrition and exercise
interventions
The Nutrition For A Lifetime System (NLS) is a
computer-based multimedia intervention originally housed
in a kiosk in the supermarket. The NLS helped shoppers
alter their family food purchases to meet NCI’s nutrition
guidelines. The NLS is a user-activated program that
tracked participant-use through a PIN number. The NLS
used pictures, graphics, narration, and interactions, and
principally SCT-based planning, goal setting, and feedback
and operated through a touch-screen monitor. The final NLS
presented a series of 10 main programs (a new program was
available each week) and a set of individualized main-
tenance programs available for an additional 4 weeks. The
NLS programs focused on small, targeted changes within a
food group to meet nutritional guidelines. A series of
randomized control field studies with NLS demonstrated
that NLS users decreased fat and increased fiber, fruits, and
vegetables in their supermarket food purchases [104–107]
and could maintain some of these changes after contact with
the program ended as assessed by a system using
participants’ food shopping receipts [108]. Program accept-
ability and nutrition effects held across study participants
from a range of socioeconomic groups [105–107].
The NLS followed SCT and its programs contained
tailored information based on assessments and progress in
meeting goals, personal feedback, goal setting, planning,
and incentive components. Winett and colleagues developed
and tested measures of specific SCT variables operating in
the NLS [104]. In a unique empirical test of the SCT model,
Anderson, Winett, and colleagues demonstrated that the
NLS was effective in changing users’ nutrition-related self-
efficacy and outcome expectancies, which resulted in
dietary changes [105].
Work with the NLS was expanded through a project with
rural high school students [109,110]. In Eat4Life, we first
modified the NLS template through formative work result-
ing in an Internet-based series of modules for ninth and
tenth grade girls and boys. These modules focused on
modifying targeted nutrition practices within and outside
school and activity and exercise and were used as part of the
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641 635
school’s health curriculum. The modules provided each
student with individualized content, planning mechanisms,
and immediate feedback on progress in reaching a series of
user-selected weekly and overall program goals [110].
Eat4Life used ethnically diverse on-screen models of both
genders (a precursor to the on-screen guide later developed
in our Guide to Health [GTH] project) to relay information
and provide feedback. Formative research was used to
develop acceptable alternatives and strategies for changing
target foods and reaching nutrition goals similar to the ones
used in NLS. Formative work tailored the NLS target food
alternatives and strategies, identified acceptable alternatives
to teens’ fast-food fare, developed acceptable physical
activities that provided health benefits, and found an
appealing presentation format. The templates used for the
fast food and physical activity planners were adapted and
greatly expanded for the church-based Guide To Health
intervention described below.
As a result of the formative work, the Internet program
was effective in helping girls reach nutritional goals
compared to girls only involved in the standard health
curriculum [109]. A subsequent study with four cohorts of
ninth and tenth grade girls (n = 250) demonstrated that their
weekly use (20 min) of the modules resulted in consistent
reported changes in target foods, reduction in calories and
fat from fast-food, and increases in frequency of activity and
exercise compared to girls taking the regular health
curriculum [110]. The Eat4Life Internet-based program
was subsequently used in a number of middle and high
schools across the Commonwealth of Virginia.
We have also examined mediated approaches to promot-
ing exercise. The initial study by Lombard, Winett, and
colleagues demonstrated that weekly, very brief, phone
contact can be far more effective in promoting walking than
the same but less frequent contact (once every 2 or 3 weeks
[111]). Later work refined this approach by providing a
progressive paced walking program with more tailored
instruction and feedback through an on-line dpersonalcoachT and comparing the tailored SCT approach to an
online didactic intervention. Results indicated high adher-
ence to the programs and increases in aerobic capacity of
10% to 15% as assessed with a standard 1-mile walk test
and estimated VO2max [112]. Time, distance reported
walking, and increases in fitness in this study were similar
to outcomes of projects using extensive face-to-face contact
[113] while effect size differences between conditions were
~0.75–1.0.
An additional study contrasted two paced walking
interventions delivered by e-mail. One was a standard
SCT intervention with feedback and goal setting and
limited, more standard use of personal coaching by e-mail
while the other enhanced SCT intervention featured more
tailored feedback, goal setting, and mastery experiences,
and electronically delivered dpersonal coachingT. While the
standard SCT group decreased their 1-mile walk test time by
35 s, the enhanced SCT group reduced time by 86 s. The
effect size difference between these two viable conditions
was ~0.50. This overall set of studies helped inform the
physical activity components of GTH.
Building on this work described earlier with the SCT-
based computer-assisted NLS intervention and the subse-
quent Internet-based interventions, we are completing a 4-
year project assessing the short and longer-term (1 year after
pre-test) efficacy of an Internet-based Guide to Health
(GTH) delivered within churches with and without church-
based supports. The GTH program focuses on nutrition
targets similar to NLS but has more emphasis on soft drinks,
sweets, portion sizes, fast-food, and the importance of
energy balance to weight management than was present in
the NLS program. Content for each individual is tailored
based on initial assessments, personal goals for the overall
program, and progress in the program. In addition, GTH
features self-regulation components through planning tem-
plates for physical activity and fast food consumption.
The GTH program also encourages physical activity. The
GTH promotes physical activity through a step-count
program using a pedometer provided to every participant.
After a baseline period where mean steps per day are
calculated, GTH users are provided with weekly goals that
generally allow individual users to increase their baseline
step counts by 3000 steps/day for 5 days/week in increments
of 500 steps/week. The 3000 steps/day equates to about 1.5
miles or 30 min of walking or related physical activity
meeting the Surgeon General’s guidelines. We selected 5
days/week instead of 7 days/week to correspond to dmost
days of the weekT plus to provide some leeway to people.
Thus, with 5 days/week prescribed, the largest expectation
is that participants could increase step counts by 15,000
steps/week. As noted, GTH has other planning components
including a physical activity planner to assist in increasing
step-counts and a fast-food meal planner that allows for
planning lower calorie and lower-fat meals in a wide range
of fast-food restaurants.
GTH was entirely delivered through the Internet and its
content was tailored to participants based on assessments of
nutrition and physical activity practices. GTH included eight
content or program modules and four maintenance modules.
Maintenance modules primarily involved continued report-
ing with feedback on meeting nutrition and physical activity
goals. Participants using GTH had access to a new module
on a weekly basis.
The GTH randomized trial involved 14 Baptist and
United Methodist churches with the goals of increasing
physical activity, making small changes in food choices, and
improving energy balance using an SCT Internet-based
intervention alone or enhanced by the social support and
context provided by the church. Participants from five
churches in the GTH-only condition accessed the 12-
module tailored, interactive GTH Web site from home,
work, or church. Participants in five churches received the
GTH plus additional coordinated church-based supports
(GTH-plus), while participants from four churches served as
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641636
the waitlist control. Trained assessors, blind to condition,
measured participants’ height, weight, and waist and hip
girths. At post-test (7–9 months after baseline) the resulting
sample (N = 849) was 65% female; 19.3% African
American; mean age = 52.2 years; mean BMI = 29.0. At
post-test, participants in the control condition gained weight
(N = 264;M = 0.57 kg, SD = 0.51), while participants in the
GTH treatment conditions lost weight (GTH only: N = 276,
M = �0.10 kg, SD = 0.54; GTH plus: N = 309, M = �0.27,
SD = 0.52). A mixed model ANOVAwith church as the unit
of analysis indicated that differences in weight gain
observed between the control group and GTH only were
marginally significant (P b 0.10, ES = 1.17) while the
difference between the control group and GTH plus was
significant (P b 0.05, ES = 1.61). Weight gain for the
control condition closely followed secular trends reported
by Lewis et al. in the CARDIA study [78]. Similar though
not exact patterns were found by age, gender, and BMI
subgroups.
Although these results are preliminary, they represent one
of the few community-based trials that have demonstrated
the feasibility of weight gain prevention with larger samples
and show that GTH with church supports forms one basis
for future longer-term, weigh gain prevention programs. The
supports used in the GTH-plus treatment were theoretically
based and followed from the SCT [95,96,100] notion of
embedding interventions in social networks and included
planned prompts (in church newsletters, as part of sermons)
and feedback, goal setting, and accountability for an entire
church revolving around targeted foods and physical
activity. However, the preliminary data suggest that GTH
only can be more efficacious. Churches and other organ-
izations can provide a venue for accessing many people.
The virtual guide or counselor that is part of GTH and other
similar programs can be further developed and may provide,
perhaps, more salient, tailored ongoing supports than those
developed in this project through churches.
We also note an important set of findings, albeit
qualitative, from focus groups we conducted with parti-
cipants that lend some credence to the importance of the
virtual guide or counselor. As predicted by Reeves and Nass
[114], participants reported finding the narrator’s (guide’s)
report on the audio track of the program of their individual
feedback and the narrator’s perceived tone and use of words
as very powerful. For example, participants reported that the
very positive or less than positive feedback (we did not use
negative feedback) had emotional meaning to them and
motivated them. These findings suggest that formative and
pilot research needs to use the same modality as the
intervention. For example, it is likely that if the narrator’s
content was simply read by formative research participants,
the emotional and motivational impact would not have been
apparent. Participants also liked and endorsed the use of
weekly e-mail prompts for GTH use. Rather than finding
these annoying, participants noted that prompts kept them
on track. Building on these findings and those from Internet-
based weight-loss programs (below), future programs can
feature a virtual dmastery-counselorT who has an on-screen
and audio presence and guides program users through
tailored content and mastery experiences.
Internet weight-loss programs
Randomized control trials have been conducted by Tate
and colleagues assessing the efficacy of delivering weight-
loss programs via the Internet [115,116]. The first study
[115] hypothesized that using the Internet to deliver an SCT-
based, structured behavioral weight-loss program would
produce better weight loss than providing access to readily
available educational weight-loss Web sites. The behavioral
Internet program produced better weight loss (~4 kg) than
the education-only Web sites (~1.6 kg) at 6 months.
However, the study design did not allow the determination
of the significance of the live counselor contact via e-mail in
relation to the overall program. Such information is critical
to directing Internet-based treatments and for the public
health application of the Internet to the treatment of obesity
since human counselors are relatively more expensive than
other aspects of the program.
A second, longer-term study [116] compared the efficacy
of an SCT-based, Internet weight-loss program alone or with
the addition of e-mail counseling from a human therapist
over 1 year. This study confirmed that Internet approaches
could be used for longer periods and that counselor feedback
increases program efficacy. At 1 year, the Internet plus e-mail
counselor program group lost more weight (~4.3 kg) than the
basic Internet program group (~2 kg). Counselors act to
develop and guide mastery experiences, assist participants
with setting and realizing important goals and milestones,
and providing ongoing supports to encourage persistence in
the face of outcomes that might be less than expected.
Although Internet programs with counseling from a human
therapist may make treatment more effective for consumers,
developing technologies make virtual counselors possible.
Other models may combine virtual counselors or tailored
messages with intermittent use of human counselors to make
more disseminable lower cost treatments.
The next step in creating a more public health treatment
has been to develop an online weight-loss program that uses
tailored virtual-counseling rather than a human therapist.
Preliminary findings from a study by Tate and colleagues
[117] testing the feasibility and efficacy of the (virtual)
computer-assisted, e-counseling approach found the com-
puter-assisted program produced weight loss equivalent to
the (real) counselor-assisted program at 3 months and both
were better than the control. By 6 months, the real
counselor-assisted program produced better weight losses
than the virtual counselor group suggesting that program-
ming may need to make the virtual counselor as dynamic
and interesting as the real counselor and focus on such
strategies as problem solving in order to show effectiveness
over extended time periods [33].
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641 637
The studies using the Internet as a vehicle for weight-loss
programs together with the computer and Internet-based
studies on nutrition and physical activity show that
theoretically driven Internet programs can be one means
for helping many people prevent weight gain. Indeed, we
envision long-term programs where there is a tailored and
seamless approach to both maintaining weight and dealing
with smaller weight gains in a very proactive way. The GTH
study and its data suggest that weight gain prevention may
be marketed within the context of an overall nutrition,
physical activity, and health program and not as dweightmanagementT or dweight gain preventionT per se. The
studies described above also suggest that at the heart of
such effective programs are key SCT-based procedures that
we have called following Bandura [95,96] the Guided-
Mastery Process.
Guided mastery process
The interventions we have described revolve around the
virtual dmastery-counselorT and a specific set of SCT-based
processes that we call the Guided-Mastery Process. A
mastery-counselor is a competent and successful model who
provides guidance in goal setting, planning, and self-
monitoring at each phase of behavior change (e.g., initiating
behavior change, establishing new behaviors in one’s
repertoire, and behavioral maintenance) as well as serving
as an exemplar of those behaviors [95,96,118,119]. The
mastery-counselor specifically addresses the self-doubt and
setbacks inherent in behavior change. Indeed, a model’s
overall competence appears to be far more influential than
other model characteristics (i.e., age, gender, and ethnic
background). dModel competence is an especially influential
factor when observers have a lot to learn and models have
much they can teach them by instructive demonstration of
skills and strategiesT ([95] pp. 101–102). The mastery-
counselor can, for example, recount difficulties people have
had and show how resilient self-efficacy, persistence, and
specific strategies helped to overcome these difficulties. The
mastery-counselor also can model problem solving skills
(e.g., delineating alternatives and reaching decisions) and
self-regulatory skills (e.g., planning, problem solving, self-
monitoring, and goal setting)—skills particularly effective
in behavioral change [95]. The tailoring and personalization
within such a guidance schema need not be so specific that a
person’s burden is excessive (i.e., extensive assessments
prior to and within the intervention) or that production and
delivery costs are so high as to render the enterprise
infeasible.
The guided-mastery process can be woven throughout the
content modules in our future interventions via the mastery-
counselor and provides a specific and individualized process
for gathering information, setting goals, planning, evaluat-
ing, and providing feedback related to behavior-change goals
within the participant’s social and environmental context.
This process represents a theory-based approach to
providing the tailoring, interactions, and frequent contact
suggested as important for successful weight gain
prevention efforts [77]. This 10-step guide-mastery proc-
ess has been developed during almost 20 years of health
promotion research focusing on the use of guided-mastery
in many settings in a wide range of media [104–107,109–
111,115–117,119,120]. The steps are as follows:
(a) Evaluate outcome expectations for behavior change.
(b) Gather information on progress toward goals in
physical activity, fitness, and nutrition.
(c) Evaluate progress toward goals (met or not met)
frequently (weekly, daily, etc).
(d) Provide feedback tailored as to the participant’s
preferred referent (self or others) and format (text,
visual representations, charts, or tables).
(e) Model effective evaluation of current goals (realistic,
too much challenge, not enough challenge).
(f ) Set new goals (keep, reduce, or increase current
goals).
(g) Model effective evaluation of current plan and self-
regulation strategies (feasible, impractical, suggest
alternatives).
(h) Plan for achieving new goals (keep or modify current
plan with prompts from guides).
(i) Obtain commitment to achieve new goal.
(j) Plan for evaluation of goal achievement.
Within this guided-mastery process, we refine the
specific guide-mastery strategies within each step. Such
strategies follow directly from SCT and focus on increasing
self-efficacy, positive and realistic outcome expectations,
and use of self-regulatory strategies. Generally, a parti-
cipant’s continued use of the program allows the mastery-
counselor (real or virtual) to anticipate a participant’s
problems and successes and highlight these areas with
tailored guided-mastery content. Note also that as an
ongoing and dynamic process, the steps allow for assessing
changes in outcome expectancies and dsatisfactionT and
providing new content and goals to match such changes as a
person moves into an extended maintenance and habit phase
[98,99]. An important caveat is that most of our work and
that of other groups has focused on the earlier phases of
health behavior change. Considerable more research needs
to be directed to the processes involved in long-term
maintenance [98,99].
Summary
High prevalence rates of overweight, obesity, and
inactivity have been the impetus for a number of new
initiatives such as dSteps to a Healthier UST [121] and the
potentially large investment by the National Cancer Institute
[122] and other National Institutes of Health divisions on
R.A. Winett et al. / Preventive Medicine 41 (2005) 629–641638
the different dimensions of the denergy balanceT. Trans-
disciplinary efforts also are likely to more precisely unravel
the complexities of genetic and environmental factors, their
interactions, and contributions to overweight and obesity
[122]. Most parsimoniously, however, the increased preva-
lence of overweight and obesity is explainable by a small
energy imbalance between consumption and expenditure
that then becomes cumulative and magnified in the form of
added body weight and body fat year after year. If the
energy imbalance and annual weight gain are small, then the
situation appears correctable if the goal for many population
segments is weight gain prevention.
Interventions are needed to bridge the gap between
intensive individual weight-loss programs that are more
appropriate for people at high risk (e.g., obese) and public
health efforts that can set the supportive context for
individual efforts in order to help diverse groups of people
reach the major health goal of weight gain prevention. This
seemingly simple goal, however, requires sustained changes
in food consumption and physical activity and interventions
need to be designed to reach and be effective with diverse
population segments. Theoretically based tailored programs
delivered via the Internet may provide one vehicle for
engaging large groups of people in ways that meet the
guidelines of Jeffery and French [77] for effective weight
gain prevention programs by: (a) increasing the frequency of
contact; (b) making programs more tailored and interactive;
(c) focusing more on physical activity and changes in eating
patterns, (d) having provisions to respond to observed weight
gain, and (e) maintaining motivation over the long-term.
There also are specific challenges for initiatives and
interventions in weight gain prevention. Those interventions
that focus on changing health behaviors, preferably random-
ized controlled trials either embedded within public health
campaigns or implemented and tested alone, need to address
these challenging efficacy, effectiveness, and dissemination
questions:
(a) How can weight gain prevention be effectively
marketed so that it becomes an appealing and valued,
understandable, concrete, and achievable goal to
different population segments?
(b) What are the specific theoretically based psychological
and physiological (e.g., how much physical activity)
strategies that result in weight gain prevention for at
least 3 years and how do the dynamics of program
delivery, interactions, and dose conform to theory?
(c) For what population segments is weight gain pre-
vention more effective, and are there more optimal
population segments and lifespan points for these
interventions?
(d) How can the use of weight gain prevention programs
be more closely tied to every day practices such as the
use of the Internet?
(e) How well do these programs work in this dembeddedTmode with large groups of people?
(f ) What are the most theoretically based effective
strategies for disseminating weight gain prevention
programs?
(g) What criteria should be used to measure weight gain
prevention or weight maintenance? Given daily
normal fluctuations in weight what percent increase
is weight over what period is considered true weight
gain? How many years of consecutive stable weight
are required to demonstrate weight gain prevention?
Can years of minor weight loss or weight gain be
considered weight gain prevention as long as mean
weight is the same, e.g., 5 years after baseline?
(h) What is the criterion for dprogram adherenceT? A
person might be in a weight gain prevention program
for years. Is success at stabilizing weight evidence of
adherence or must a person frequently log-on to the
program and receive a large ddoseT to qualify as
adhering?
Acknowledgments
Support for writing this paper is from grant RC01-
CA79469 from the NCI to Richard A. Winett and grants 1
RO1 DK 60058-01 from NIDDK and a Clinical Research
Award ADA grant to Deborah F. Tate.
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