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: rswinett@vt.edu (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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