Vol.3, No.7, 429-440 (2013) Open Journal of Preventive Medicine
http://dx.doi.org/10.4236/ojpm.2013.37058
Feasibility, effectiveness, and perceptions of an
Internet- and incentive-based behavioral weight loss
intervention for overweight and obese college
freshmen: A mixed methods approach
Brenda M. Davy1*, Kerry L. Potter2, Elizabeth A. Dennis Parker3, Samantha Harden1,
Jennie L. Hill1, Tanya M. Halliday1, Paul A. Estabrooks1,4
1Department of Human Nutrition, Foods and Exercise, Virginia Tech, Blacksburg, USA; *Corresponding Author:
2Bon Secours Health System, Porstmouth, USA
3Office of Minority Health & Health Disparities Research, Georgetown University, Washington DC, USA
4Department of Family and Community Medicine, Carilion Clinic, Roanoke, USA
Received 10 August 2013; revised 15 September 2013; accepted 1 October 2013
Copyright © 2013 Brenda M. Davy et al. This is an open access article distributed under the Creative Commons Attribution License,
which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
ABSTRACT
Challenges inherent with the transition to col-
lege are often accompanied by weight gain
among college freshmen. Weight gain and dura-
tion of obesity increase metabolic syndrome and
cardiovascular disease risk in young adulthood,
which supports the need for weight loss inter-
ventions tailored to college students. The pur-
pose of this investigation was to conduct a
mixed methods pilot trial to determine the effi-
cacy and acceptability of a semester long Inter-
net- and incentive-based weight loss interven-
tion for overweight/obese college freshmen. Par-
ticipants (n = 27, aged >18 yrs, BMI >25) were
randomly assigned to a 12-week social cognitive
theory (SCT)-based intervention (Fit Freshmen
[FF]) or a health information control group. The
FF intervention also included modest financial
incentives for weight loss. Primary outcomes
included body weight/composition, dietary and
physical activity (PA) behaviors, and psychoso-
cial measures (i.e. self-efficacy, self-regulation)
associated with diet, PA, and weight loss. Stu-
dents in the FF intervention participated in focus
groups to provide qualitative feedback on pro-
gram structure and design. FF participants
demonstrated significant reductions (all group
differences p < 0.10) in body weight (−1.2 kg), fat
mass (−0.6 kg), dietary energy (−673 kcal/d), fat
(−37 g/d) and added sugar intake (−41 g/d), and
increases in diet and PA-related self-regulatory
skills at week 12 compared to control partici-
pants (+1.0 kg, +1.1 kg, −334 kcal/d, −15 g/d, −13
g/d, respectively). No changes in PA were noted,
but FF participants demonstrated increases in
self-efficacy to overcome barriers to PA relative
to control participants. Themes for content im-
provement from focus groups included reducing
email contact and increasing in-person interac-
tions. Program characteristics that were posi-
tively evaluated included incentives for weight
loss and access to an onsite weigh station kiosk.
Overall, this efficacious SCT Internet- and incen-
tive-based weight loss intervention was well
received and can be adapted for larger-scale use
in the college population.
Keywords: College Freshmen; Weight Gain; Social
Cognitive Theory; Diet; Physical Activity
1. INTRODUCTION
Weight gain is common in young adulthood (18 to 29
years) [1], with young adults in the United States gaining
an average of 0.8 kilograms per year [2]. The college-
aged population is susceptible to weight gain, experi-
enceing a mean weight gain of 1.8 to 4 kilograms dur-
ing their first year of college [2-5]. In addition, women
living on campus, such as in a dormitory, gain weight 36
times faster compared to women of the same age living
off-campus [6]. More importantly, metabolic syndrome
risk is increased with weight gain in young adults, re-
gardless of initial weight status [7]. Although research

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440
430
has demonstrated that weight loss programs are effective
in middle-aged adults [8], these programs may not trans-
late to younger populations such as college students, who
deal with typical barriers such as demands on time and
financial issues, but also have additional challenges such
as peer and academic pressure [9-11]. Yet, recent data
from the CARDIA study [12] emphasize the need for
interventions promoting the adoption of healthy lifestyle
behaviors, including achievement and maintenance of
healthy weight status through appropriate dietary intake
and physical activity levels.
Students’ positive health behaviors such as healthful
eating and regular exercise often decline upon entering
college [13-15]. Students report less physical activity in
college as compared to high school, and increased con-
sumption of energy-dense foods from fast food restau-
rants and vending machines [13-15]. Further, weight loss
programs targeting college students may not be success-
ful when they target only physical activity or nutrition
knowledge, do not include behavioral strategies, fail to
address population specific barriers and motives and are
not developed using established behavior change theories
or models (e.g., the Social Cognitive Theory, Transtheo-
retical Model) [15-18]. In addition, a qualitative analysis
of college student preferences for different weight man-
agement strategies included the provision of incentives
for program participation [15]. To date, few studies in
college students have included monetary incentives [19-
21] and these trials focus on weight-related health be-
haviors and/or prevention of weight gain, and not on
weight loss. While participant retention was high (likely
because students were enrolled in an official university
course for credit), intervention effectiveness was limited
[19]. Social cognitive factors such as goal setting, plan-
ning, self-monitoring, and self-efficacy also play a sig-
nificant role in preventing weight gain in college stu-
dents and could be incorporated into university-based
health promotion programs [18,19,22,23]. Additionally,
behavioral skills such as planning and tracking are asso-
ciated with lower energy intake as well as increased fruit
and vegetable consumption [15]. Unfortunately, college
students rarely report using dietary strategies to regulate
and track food intake, and only occasionally use them to
incorporate more fruit and vegetables into their diets [15].
Prior work in non-overweight college students found that
frequent, required online tracking of diet and physical
activity behaviors was not rated favorably [19]. Although
a social cognitive theory (SCT)-based intervention that
provides training across these areas for college students
may lead to changes in physical activity, healthful eating,
and facilitate weight control, optimal self-monitoring fre-
quency or mode is uncertain.
Given the challenges related to the transition from
high school to college, the channel of delivery of inter-
ventions for college freshmen is an important considera-
tion. The high-level of electronic communication and
media use by the college-aged population [24,25] sug-
gests that Internet-based weight loss programs [26,27],
which may be less resource-intensive to deliver than tra-
ditional in-person interventions, are a promising option.
There is support for the positive effects of Internet-based
programs that can be accessed through a personal com-
puter or smartphone to address a wide range of health
behaviors including weight loss and eating habits [18,21,
28,29]. In a university setting where Internet access via
computers or mobile phones is ubiquitous, this delivery
mechanism could increase the reach of tailored weight-
loss programs [30]. However, the optimal way in which
the Internet can be utilized for delivery of a weight loss
and/or health-related behavior change intervention is yet
to be determined [19,20].
Weight loss programs should include a combination of
diet, physical activity and behavior-change strategies
[31]. An efficient and effective interactive technology-
based intervention could be used to access a large popu-
lation and incorporate important weight loss program
components. Our primary aim was to conduct a mixed
methods pilot trial to determine if an Internet-and incen-
tive-based weight loss program is feasible and effective
for overweight and obese college freshmen, over a 12-
week period.
2. Materials and Methods
This pilot study was designed as a randomized con-
trolled trial including both quantitative and qualitative
data collection. A mixed methods approach was used to
enhance and clarify quantitative findings [32]. Focus
groups were conducted with participants in the interven-
tion group to provide insight on the barriers and facilita-
tors for adherence to the program as well as perceptions
related to intervention features and structure, in order to
inform the development of a future intervention in this
target population. Participants were recruited from the
2009 Virginia Tech Freshmen class. The Institutional
Review Board approved all study procedures and par-
ticipants provided informed consent before enrollment.
2.1. Participants
Eligible participants were first time college freshmen,
at least 18 years of age, with a BMI> 25 kg/m2, who
were not pregnant or pregnant in the last 12 months, and
free from eating disorder symptoms, as assessed by the
Eating Attitudes Test (EAT-26). Students with a score
>20 on the EAT-26 were excluded from the study [33].
Additionally, students with a chronic disease such as
diabetes, lung disease, heart disease or a thyroid disorder
were excluded due to the potential risk in not meeting the

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440 431
needs of a special population through a generalized diet
prescription and exercise regimen.
2.2. Data Collection
An overview of the study design and participant
recruitment/retention is provided in Figure 1. Briefly,
two research assistants posted signs in student areas
across the university and made announcements in 3 large
undergraduate classes with a goal to recruit approxima-
tely 40 participants during the first week of classes. Eli-
gible participants completed a series of questionnaires
and laboratory-based measurements including health
history and health behavior surveys, body weight meas-
urement, waist circumference and dual energy X-ray
absorptiometry (DEXA). Participants were paid $10
upon completion of baseline and 12-week (post interven-
tion) measurements and $5 upon completion of monthly
in-laboratory weigh-ins. Focus groups with randomly
selected participants from the SCT-based intervention
group (Fit Freshmen [FF]) were completed to determine
program feasibility and acceptability following the 1st, 6th,
and 12th week of the intervention. Participants were paid
$20 upon completion of a focus group.
2.3. Quantitative Methodology
At baseline and the conclusion of the study (week 12)
the following laboratory measurements were completed
by a research assistant blinded to participants’ group
assignment. Height was measured in inches without
shoes using a wall-mounted stadiometer. Body weight
was assessed to the nearest 0.1 kg using a digital scale
calibrated for accuracy prior to each assessment period
(Scale-Tronix model 5002, Wheaton, IL). Body mass
index was calculated as weight(kg)/height(m)². Waist
circumference was measured to the nearest 0.5cm using a
Gulick tape measure (Gulick, Country Technology, Gays
Mill, WI) at the level of the umbilicus. Body fat per-
centage, absolute fat mass and fat-free mass were meas-
ured using DEXA (GE Lunar Prodigy; GE Healthcare,
Madison, WI).
To assess habitual energy intake, participants were in-
structed in proper methods to record their food intake
and provided with two-dimensional food models to assist
in accurate portion size determination. The food record
covered four consecutive days, including three weekdays
and one weekend day. Records were reviewed for accu-
racy and completeness upon their return and analyzed
using diet analysis software (NDS-R 4.05, University of
Minnesota, Minneapolis, MN).
Habitual physical activity was measured using Godin’s
Leisure Time Exercise Questionnaire [34,35]. The ques-
tionnaire assesses time and intensity of physical activity
by evaluating weekly minutes and days spent doing mild,
moderate and vigorous exercise as well as strength train-
ing. The scales were scored based upon published proto-
cols [35-37].
Psychosocial measures associated with physical ac-
tivity, dietary intake and weight loss in a college-aged
population were assessed using with a validated health
beliefs survey [38]. This 102-item SCT survey consists
of measures of self-efficacy, outcome expectations, and
self-regulation for both physical activity and nutrition
[39]. The survey assesses SCT determinants of eating
behaviors and for physical activity behaviors using a 5
point Likert scale (1 = never to 5 = always) for self-
regulatory skills and outcome expectations [38] and a
scale from 0 to 100 (0 = Certain I cannot to 100 = Cer-
tain I can) for self-efficacy regarding dietary and PA
behaviors. The scales have adequate internal consistency
(Cronbach’s α = 0.68 − 0.90 in this study) and are predict-
tive of physical activity [3] and dietary intake [15,40].
2.4. Qualitative Methodology
The three focus groups were conducted using ran-
domly selected participants (n = 4 − 5 per focus group;
Figure 1, [41]) from the experimental condition to col-
lect specific feedback on the structure and design of the
intervention and to provide directions for future refine-
ments. Students were ineligible to participate in future
focus groups after participating in one in order to give
each participant in the experimental condition an equal
opportunity to share their perceptions on the content and
structure of the program [42]. Each semi-structured focus
group lasted one hour. We used a standard protocol of
developing focus group questions [41]. We derived the
questions to align with the study purpose (to create an
effective weight loss program for overweight college
freshmen) and allow for members of the target audience
to provide iterative feedback on program content and
structure to enhance the likelihood of having a gener-
alizable effect and reaching a large proportion of the in-
tended audience. One of the graduate research assistants
(K.P.) led each focus group through a series of standard-
ized semi-structured, open-ended questions. The ques-
tions focused on the following areas: feasibility and ac-
ceptability of the FF eating and exercise plan; percep-
tions of overall intervention including barriers to and
facilitators of program adherence; perceptions of daily
e-mails and attitudes towards e-mail content.
Two trained research assistance facilitated the focus
groups. Qualitative data were verified by summarizing
key points with the participants and asking if the sum-
mary was accurate and inclusive of the discussion. Upon
participant authorization, the sessions were recorded us-
ing a digital voice recorder and written transcripts were
generated using Transana 2.30 (Madison, Wisconsin).

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440
432
Data were transcribed, coded and interpreted using both
inductive and deductive methods to allow for exploration
and discovery of new themes and strategies for inter-
venetions [43].
2.5. Intervention Development and Delivery
Both the intervention and control weight loss pro-
grams were developed to help overweight college fresh-
men lose weight. Both groups received identical health-
related information (i.e., educational content) that in-
cluded exercise and eating plans, strategies to maintain
the plans, and expert advice on weight loss. In both pro-
grams, nutrition information incorporated nutritional
guidelines set by the United States Department of Agri-
culture (USDA) 2005 Guidelines [44] as a foundation of
the program and also included suggestions provided by
the National Weight Control Registry such as eating
smaller more frequent meals across the day (i.e., 5 to 6
rather than 3 meals a day) [45]. Participants were pro-
vided with the tools to create a 12-week exercise pro-
gram that could be executed in their dormitories or in the
university fitness facility. To aid in retention efforts par-
ticipants received $5 for completing a monthly weigh-in.
Each program also encouraged participants to select a
workout option that was reflective of their current health
and fitness status.
2.6. Fit Freshmen Intervention Group
Fit Freshmen (FF) participants received daily e-mail
support, access to a comprehensive website with educa-
tional and skill related information, and monthly mone-
tary incentives for both weight loss from baseline and
self-monitoring of nutrition, physical activity, and body
weight. Body weight could be tracked weekly via weigh-
ins on a weigh station located in an academic building on
campus. The weigh-station was originally created to
promote healthy lifestyles for employees in corporate
companies (incentaHealth, LLC, Denver, CO). Weigh
station data, which included body weight and a photo-
graph of the participant, was uploaded to the intervention
website so students could track their progress over the
course of the program. The images were used to provide
motivation for the participant over the course of the in-
tervention. Additionally, the camera and weigh station
were linked via a computer that provided a connection to
the Internet for the two-way transmission of data to in-
tervention staff (all data encrypted).
Daily e-mails. Participants received daily e-mails to
support increased physical activity and healthful eating.
The content of the daily e-mails was targeted to a col-
lege-aged population and explicitly included strategies to
improve self-efficacy and self-regulation [15,16,46].
Each day of the week had a specific focus on issues that
would be relevant to college students in order to sustain
healthful weight habits and aligned with SCT constructs
[47]. Additionally, there was a consistent SCT theme for
each of the 12 weeks of the program, which included
focusing on outcome expectations, developing self-effi-
cacy through small successes, strategies to track physical
activity and eating, ongoing goal setting, and relapse
prevention strategies.
Daily topics began with a success story (Sunday), ex-
ercise opportunities (Monday), nutrition information
(Tuesdays), barriers and strategies to overcome them
(Wednesdays), ask the expert (Thursdays), portion size
strategies (Fridays), and goals (Saturdays). Participants
were also taught self-regulatory behaviors relevant to
weight management through e-mails such as “Ask the
Expert” focusing on knowledge of benefits and risks of
different health behaviors. The weekly “Success Stories”
of other college freshmen who had succeeded in losing
weight emphasized observational learning and vicarious
experiences modeled by relevant peers [46]. Barriers to
adopting healthier lifestyle behaviors faced by young
adults in an academic setting were targeted once a week
in order to address reciprocal determinism between an
individual, his/her behavior, and the environment.
On days focusing on goals, short- and long-term goal
setting were emphasized and aligned with outcome ex-
pectations relevant to each participant [15]. Additionally,
participants could access an online health coach with
specific questions or issues. E-mails included sample
menus stressing the importance of fruit and vegetable
consumption and low-fat food options. The menus also
included specific information from on campus dining
halls to ensure it was relevant to the sample. While this
intervention was completed before My Plate recommen-
dations (www.choosemyplate.gov), a plate method was
used to help students consider appropriate portion sizes.
It was recommended that at each main meal, students
should cover one quarter of their plate with a complex
carbohydrate, one quarter with a serving of protein and
the remainder with non-starchy vegetables. In addition,
every Wednesday, nutrition e-mails addressed certain
SCT variables addressing different dietary issues such as
frequent self-monitoring of intake, methods to avoid
overeating in buffet style student dining centers and
emotional coping strategies other than eating when
stressed. There were also links included throughout the
weekly e-mails to Dining Services online nutrient infor-
mation.
Monetary Incentives. At the end of each month during
the intervention period, participants who lost 1% - 5% of
their initial body weight received $5, those that lost 5.1%
- 10% received $10 and those that lost 10.1% and higher
received $20. To enhance self-regulation, modest incen-
tives were also provided for weekly completion of

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440 433
weigh-ins and self-monitoring of physical activity and
eating. Participants who lost weight each month and
weighed in at least once a week for a month received an
additional $5. Participants that completed weekly online
self-monitoring for a month also received an additional
$5.
2.7. Control Group
The control group received two electronic newsletters,
one at the start of the study and one six weeks after base-
line. The newsletters highlighted messages about a
healthy lifestyle similar to those messages highlighted in
the intervention group. The key difference between the
newsletters delivered to the control group and the daily
e-mails delivered to the intervention group was the
newsletters focused on general educational information
that could be found from any reputable Internet health
site, whereas the daily FF e-mails addressed SCT vari-
ables and self-regulation related to eating and physical
activity. The control group participants did not have ac-
cess to the health coach or the modest monetary incen-
tives for weight loss or tracking.
2.8. Data Analysis
Quantitative statistical analysis was conducted using
statistical analysis software (SPSS v.12.0 for Windows,
SPSS Inc., Chicago, Illinois). Analyses included descrip-
tive statistics (means, standard error, and frequencies)
and repeated measures analysis of variance (ANOVA).
Multivariate, repeated measure analysis of covariance
(ANCOVA) using a two-group design assessed treatment
effect (i.e. weight loss, percent body fat lost). Bivariate
correlations were used to determine the relationships
between changes in SCT variables, physical activity,
dietary intake, and weight loss. Due to the sample size
and pilot nature of this trial, we set an a priori level of
significance at p < 0.10.
Focus group transcripts were reduced to meaning units
using both an inductive and deductive approach. We
used a framework approach [43] using prior qualitative
literature on this population to code deductively and then
took an inductive approach solely from this qualitative
data [43]. After the focus groups were transcribed, each
investigator became familiar with the data by reading
through the transcripts several times. Meaning units were
organized into the themes associated with different
components of the FF content and structure. Additionally,
prior knowledge from qualitative data about barriers and
motivators college students face when leading a healthy
lifestyle was used [10,15,16]. To identify themes and
patterns from focus group data, investigators developed
classification codes during the analysis of data. These
codes were obtained from the research questions used
during the focus groups as well as keywords that con-
stantly appeared in the text from conversations between
participants during the focus groups. For example, the FF
intervention revolved around a meal plan, exercise plan,
self-monitoring and self-regulation skills through the use
of a weigh-in station and regular journaling, as well as
daily e-mails and modest incentives. Thus, codes were
developed around these components of the intervention
when analyzing the data from the focus groups. Every
time words or phrases related to these concepts appeared
in the text, sentences or paragraphs containing them were
bracketed and the code written next to the bracket ac-
cording to standard procedures [48]. In this way, during
the first phase of qualitative analysis, text was organized
based on the codes. In addition, codes were derived using
the constant comparison method [43] where newly gath-
ered data from the second and third focus group was
compared with data from the first focus group and its
coding in order to refine the development of new theo-
retical categories.
3. RESULTS
The sample population was ~18 years of age (age 18.5
± 0.6 yrs) and predominantly white (83%) and female
(76%). At baseline, the mean weight status of the sample
classified as obese (BMI~31 kg/m2). No baseline group
differences were detected.
3.1. Quantitative Findings
Participants in the FF group demonstrated significant
decreases in body weight, fat mass and BMI at 12 weeks
when compared with the control group, whose weight
had increased over the 3-month period (Table 1). How-
ever, there were no group differences over time in body
fat %, total lean body mass or waist circumference.
Diet, physical activity, and SCT outcomes at baseline
and at week 12 are presented in Table 1. At 12 weeks,
FF participants reported consuming significantly less
energy and fat (g and % of total energy) and more pro-
tein (% of total energy) compared to control participants.
The % of total energy from carbohydrates did not differ
between groups at baseline or 12 weeks, but there was a
significant group difference in reduction in added sugar
(AS) intake in the FF group compared to control partici-
pants. Importantly, this reduced level of AS consumption
in FF participants is similar to that recommended by the
American Heart Association (AHA; 25 to 37.5 grams/d
or 100 - 150 kcals/d) [49]. Changes in physical activity
were not significant by time or condition (Table 1). FF
participants demonstrated increases in self-regulatory
skills related to portion sizes, planning and tracking,
fruits and vegetables and physical activity as compared
to control participants. Self-efficacy to overcome barriers

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440
434
Table 1. Body weight and composition, social cognitive theory (SCT) factors and self-reported dietary intake and physical activity in
Fit Freshmen and Control group participants before and after a 12-week weight loss intervention.
Control Group Fit Freshmen Group Between Group
Comparisons
Baseline
(SD)
Week 12
(SD)
∆ Wk 12 -
Baseline
Baseline
(SD)
Week 12
(SD)
∆ Wk 12 -
Baseline p
Body weight and composition
Weight (kg) 87.5(4.9)88.5(5.0)1.0 93.1(5.1)91.9(5.1) −1.2 0.06**
Fat Mass (kg) 38.0(4.6)39.1(4.8)1.1 42.9(4.8)42.3(5.0) −0.6 0.09**
Lean Mass (kg) 50.5(3.5)50.4(3.4)−0.1 48.4(3.6)47.7(3.5) −0.7 0.51
Body Mass Index (kg/m2) 29.5(1.4)29.9(1.4)0.4 32.3(1.4)31.9(1.5) −0.4 0.06**
Body Fat (%) 38.4(2.2)39.4(2.4)1.0 42.5(2.3)42.2(2.5) −0.3 0.15
Waist Circumference (cm) 95.6(3.8)96.8(3.8)1.2 105.2(3.9)104.4(4.0) −0.8 0.14
Dietary Intake
Energy (kcal/d) 2170(154)1836(149)−334 2224(148)1551(143) −673 0.07**
Fat (g/d) 88(8) 73(7) −15 90(7) 53(7) −37 0.02**
Protein (g/d) 83(6) 70(7) −13* 84(6) 72(7) −12* 0.89
Carbohydrate (g/d) 265(20) 232(19)−33* 276(19)203(18) −73* 0.12
Alcohol (g/d) 0.08 (0.03)0.03(0.7)−0.05 0.08(0.03)0.98(0.69) 0.9 0.35
% Fat (% energy) 36(1) 36(2) 0 36(1) 30(2) −6 0.02**
% Protein (% energy) 16(0.7) 15(0.7) −1 15(0.7) 18(0.7) 3 0.03**
% Carbohydrate (% energy) 49(2) 50(2) 1 50(2) 53(2) 3 0.47
% Alcohol (% energy) 0.03(0.01)0.0(0.2)−0.03 0.02(0.01)0.26(0.19) 0.24 0.33
Added sugars (g/d) 76(10) 63(6) −13 80(9) 39(6) −41 0.04**
Fiber intake (g/d) 16(1) 15(1) −1 15(1) 12(1) −3 0.26
Fiber intake per 1000 kcal (g/d) 7(0.7) 8(0.6) 1 7(0.6) 8(0.6) 1 0.99
Physic al Activit y (P A)
Moderate PA (min/wk) 246(138)115(26)−131 71(144)111(27) 40 0.42
Vigorous PA (min/wk) 121(36) 163(48)42 88(38) 123(50) 35 0.89
Strength Training (min/wk) 68(32) 90(33) 22 35(33) 56(34) 21 0.98
SCT constructs: PA and Dietary Behavior scores
Regulating Calories and Fat Self-Efficacy# 2.9(0.2) 3.5(0.2)0.6 2.7(0.2)4.0(0.2) 1.3 0.02**
Planning and Tracking Self-Regulation# 2.2(0.1) 2.9(0.1)0.7 2.4(0.1)3.7(0.1) 1.3 <0.01**
Regulating Fruits and Vegetables# 3.8(0.3) 3.6(0.2)−0.2 3.1(0.3)4.2(0.2) 1.1 <0.01**
Self Regulation Keeping Track ## 83.1(4.6)80.3(4.1)−2.8 72.6(4.8)75.8(4.3) 3.2 0.38
Physical Activity Self Regulation# 3.0(0.2) 3.4(0.2)0.4 2.7(0.3)4.0(0.2) 1.3 <0.01**
Self Regulatory Self-Efficacy for Fruits and
Vegetables## 74.0(4.2) 76.3(4.1) 2.3 71.2(4.4)72.6(4.3) 1.4 0.87
Positive Outcome Expectancies for Fruits and
Vegetables# 4.4(0.1) 4.5(0.1)0.1 4.5(0.2)4.6(0.1) 0.1 0.81
Negative Outcome Expectancies for Fruits and
Vegetables# 2.5(0.2) 2.5(0.2)0.0 3.0(0.2)3.1(0.3) 0.1 0.42
Self-Efficacy to Integrate Physical Activity into
Daily Life## 77.3(3.2)78.4(3.4) 1.1 71.2(3.5)81.5(3.7) 10.3 0.02**
Self-Efficacy to Overcome Barriers to Physical
Activity## 73.2(4.3) 70.2(4.1)−3.0 61.1(4.6)74.2(4.4) 13.1 0.01**
Physical Activity Positive Outcome Expectancies# 4.1(0.1) 4.4(0.1)0.3 4.2(0.1)4.3(0.1) 0.1 0.83
Physical Activity Negative Outcome Expectancies# 2.4(0.2) 2.5(0.2)0.1 2.3(0.2)2.4(0.2) 0.1 0.92
*Significant time effect, p < 0.10. **Significant group x time effect, p < 0.10. #Scored on a scale of 1 to 5. ##Scored on a scale of 0 to 100.

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440 435
to physical activity significantly increased after the
12-wks in FF participants, relative to control group par-
ticipants.
3.2. Qualitative Findings
All 13 FF participants attended one of the three
semi-structured focus groups (Figure 1). Themes that
emerged were similar across all three focus groups sug-
gesting that saturation was reached. Findings are pre-
sented in detail with selected illustrative quotes in Table 2.
In general, participants felt that spreading their meals
into smaller, more frequent meals across the day was not
Individuals screened
for eligibility (n = 77)Excluded (n = 42):
BMI < 25 kg/m
4
(n = 33)
EAT-26 score >20 (n = 6)
Not current freshmen (n = 3)
Eligible, but declined (n = 6)
Initial Laboratory Tests
Height, Weight, Waist
Circumference, Body
Compiosition, Food Records,
Questuinnaires
$10 Compensation
*
Randomized
(
n = 29
)
Withdrew after randomization, but
prior to intervention implementation
(n = 2)
FF Group (n = 1)
Control Grou
p
(
n = 1
)
Control
(n = 14)
Fit Freshmen (Intervention)
(
n = 13
)
Weeks 1-4
Daily e-mail support and health-related
information, access to study website for
self-monitoring, access to weight-station
for weekly weigh-ins.
Weeks 1-4
healthy Lifestyle information
Newsletter #1
Month 1 Weigh-In
$5 Compensation
*
Month 2 Weigh-In
$5 Compensation
Weeks 6
healthy Lifestyle information
Newsletter #2
Month 2 Weigh-In
Monetary incentives provided for
weight loss goals and self-monitoring
$5 Compensation
Month 1 Weigh-In
Monetary incentives provided for
weight loss goals and self-monitoring
$
5 Com
p
ensation
*
Weeks 5 - 8
Daily e-mail support and health-related
information, access to study website for
self-monitoring, access to weigh-station
for weekly weigh-ins
Weeks 9 - 12
Daily e-mail support and health-related
information, access to study website for
self-monitoring, access to weigh-station
for weekly weigh-ins
FF Focus Group
Following Week 1,
n = 4
FF Focus Group
Following Week 6,
n = 4
FF Focus Group
Following Week 12,
n = 5 Post-Intervention Laboratory Tests
Height, Weight, Waist Circumference,
Body Composition, Food Records,
Questionnaires
$10 Compensation
Included in analysis (n = 14)
Post-Intervention Laboratory Tests
Height, Weight, Waist Circumference,
Body Composition, Food Records,
Questionnaires
Monetary incentives provided for
Month 3 weight goals and
self-monitoring
$10 Compensation
Included in anal
y
sis
(
n = 13
)
Figure 1. Overview of the Internet- and incentive-based weight loss intervention. *Compensation paid for completion of
measurements and was not dependent upon meeting weight-loss goals.

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440
436
Table 2. Qualitative findings: Perceptions from Fit Freshmen participants of weight loss program components.
Intervention Component Common Themes Illustrative Quote(s)
Availability of healthy foods
“During the snack times of the day I’m over on the academic side of campus
and not close to anywhere where I can just grab a snack.”
“I did not like it (recommended meal plan) because it would recommend
things such as lightly grilled salmon and I have a campus meal plan!”
Time Management and
Frequency of Meals “You are so busy as a college kid, I think 6 small meals is a lot to ask.”
Self-regulation
“Just having to write it down all the time and knowing someone is going to
look at it helps.”
“It made me more aware of what to eat and what not to eat and how much.
It really helped me focus on my portion (size) more than anything.”
Detail of meal plan “I think it would be neat if meal plan could be taken to the next step to
where the program had full meal suggestions like at D2 (dining hall).”
Meal Plan
Socializing around meals “I always eat with friends, so it makes it a little harder if you do have a
little time [to go to the dining center] if you have no one to go with.”
Time “If I have a test tomorrow, I try to make time for the gym, but I mean
sometimes, it doesn’t happen.”
Structure
“I’ve actually been following the exercise program because I used to only
do cardio. I always thought I had to do cardio every single day and so I
actually try to stay on track when it says to run and when it says to lift weights.”
Variety and Flexibility
“Now I am on the home plan because, gyms and I don’t get along and I can
do it by myself and I like it because it motivates me just to go do it because
once I get this done, I’m done.”
“The thing about the program is it gives us directions and you can do it at
your own pace and in your own time.”
Exercise Plan
Social Support
“I think it would be cool if on a weekly basis you could meet with a group
and see how everyone is progressing. It’s kind of a support group.”
“If it (group interaction) were to be consistent throughout the program,
it could only help. It would only motivate you more because you would
be like ‘Oh I have to go meet up and go workout’”
Frequency of E-mails “I think the e-mails are too frequent. I think if it was just once per week,
I think it would be more effective.”
Daily E-mails E-mail Topics on Success,
Specific Foods,
and Portions
“The success stories are motivating because you see somebody else that
looks like you is doing the same thing you are and they are succeeding at it.”
“I know the one e-mail that had the food suggestions was really good about
actual places on campus to eat.”
“There was one (e-mail) about looking at your plate in four sections… two
vegetables and a protein and a starch or carb. That one really set a visual in
my mind and when I eat now I always picture dividing my plate into four sections.”
Monetary Incentives Format
“The fact that I can get paid just to lose weight is priceless and I love that
system” “I think it (money) helps a little bit. If you don’t feel like going across
campus to weigh in on a Friday afternoon, I remind myself, ‘If I do this, I will
get 5 dollars at the end.’”
“If there was some type of competition between a group of 50 or smaller
(participants), people would be more inclined to lose weight. Like the top
weight loss for the week gets a gift card to Blockbuster or something or the top
weight loss over the whole program gets a $25 gift certificate to some place.
It’s just that people by nature are competitive and they want to do better than
anyone else.”
Weigh Station (Kiosk) Self-regulation and
Tracking Progress
“It [the kiosk] helps me keep track of what’s going on. So that’s a good thing
to do.”
“I like the pictures. I mean I hate looking at myself, but I know eventually that
I will like them.”
Online Journaling Self-regulation “I like to have the same questions to where one week I can look and be like “WOW” I really didn’t do well this week on this particular thing and then
I can work to do better next week on that thing.”
Format of Journals “I just feel like I go over it way too fast because it’s multiple choice.”
feasible due to lack of time, money to buy healthy foods
and accessibility of certain foods offered at campus din-
ing halls. In addition, a barrier to adhering to 5 - 6 small
meals a day was a lack of social support from friends and
the difficulty of following the plan when friends were
eating what they wanted during meal times. However,
participants reported that tracking their daily energy in-
take helped them to follow the recommended meal plan-
and portion sizes accordingly and that the specificity of
the meal plan helped to emphasize portion control skills.
While significant changes in physical activity were not
detected, participants expressed approval and likability

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440 437
for the exercise component of the program. Most par-
ticipants agreed that the exercise program offered a wide
variety of options including gym and dorm options, and
different types of activities/intensities, making it possible
for many types of college students to enjoy. Participants
only felt that lack of time when studying for tests was a
barrier, and expressed a desire for a face-to-face social
support system to encourage physical activity.
Participants felt that the success stories were the most
relevant e-mails to help college students develop behave-
ioral strategies for maintaining a healthful weight.
Viewing successful peers lose weight helped build con-
fidence in the participants. Specific e-mails that focused
on portion control and self-regulatory skills were also
seen as a positive program component. Still, the majority
of participants felt that daily e-mails, as college freshmen
already on multiple e-mail listserves for other academic
organizations, were overwhelming.
Overall, participants found the small monetary incen-
tives related to weight loss to be an attractive program
component. Focus group members suggested that small
financial incentives can be used as an external motivator
when trying to lose weight and they did not feel that the
incentives affected their internal motivation to participate
in the program. Participants also indicated that tying the
incentive to weighing in each week motivated them to
complete that task.
Participants reported that the weigh station (kiosk)
scale was a helpful program feature, though one theme
that was derived from the data included having the kiosk
or kiosks more widely accessible across campus to en-
hance access. Findings related to the weekly self-moni-
toring journal were equivocal. Some participants felt that
they were not reflective on their weight management
habits due to the repetitiveness of the weekly questions.
However, others saw the repetition in questions as a tool
to track their weekly and monthly progress and to under-
stand their barriers to maintaining a healthy weight.
4. DISCUSSION
These findings indicate that the 12-week Internet- and
incentive-based weight loss program was effective at
promoting weight loss among overweight and obese col-
lege freshmen. Significant reductions were also noted in
total energy, fat and AS intake, as well as improvements
in planning and tracking self-regulatory skills and
self-efficacy to incorporate physical activity. The need
for behavior-based interventions designed to lower die-
tary intake of solid fats and AS, and improve energy
balance, has been recently highlighted [50]. This issue
may be particularly pressing in the college population as
high sugar-sweetened beverage intake (the primary
source of dietary AS) is associated with increased car-
diometabolic risk in adolescents and young adults [51].
Therefore, the reduction of AS intake to AHA-recom-
mended levels is an important outcome, and suggests
components of the FF intervention approach should be
evaluated among young adults, who tend to be high AS
consumers.
Using the mixed methods approach, improvements in
the intervention content and structure were also identi-
fied which may improve the feasibility and acceptability
of an Internet and incentives-based program targeting
college freshmen. Major themes included reducing the
recommended number of meals associated with the pro-
vided meal plan due to time constraints and difficulty
adhering to the plan while in a buffet-style, social dining
environment typical of college dining facilities, which is
consistent with recent research on meal frequency and
weight loss [52]. Major themes also included the need to
reduce e-mail frequency to one time per week, with a
focus on self-regulation strategies and success stories
from similar peers, and the need for in-person interaction
such as weekly group activities or incentive-based com-
petitions between peers. These themes are consistent
with prior research in this area. For example, college
students have reported that environmental barriers to
eating healthy include the time constraints associated
with being a student, thus making it difficult to fit in
healthy snacks or obtain healthful meals; unhealthful
food served at university dining halls, encouraging over-
eating; a lack of access to healthful food and the inability
to travel to a grocery store; and the high costs of healthy
foods [16]. These barriers align with feedback from stu-
dents in the present investigation. Future interventions in
this population segment could include healthful meal
suggestions that align with foods accessible in campus
dining halls, meals plans with less frequent eating occa-
sions (i.e., three meals/day), and intervention approaches
which are sensitive to the time constraints faced by col-
lege students (i. e., weekly vs. daily e-mails).
Previous work in this area [15,16] has indicated that
social support from peers motivates students to be more
physically active. Despite time constraints, college stu-
dents have expressed a desire for more frequent in-per-
son interactions as part of a weight management inter-
vention program [19]. Our findings are consistent with
this, as students were interested in regular small group
interaction as a social support network. The weigh sta-
tion kiosk was also viewed favorably, as a novel method
to promote weekly self-weighing, which appears to be
important for long-term successful weight management
[53].
This preliminary investigation has several strengths,
including the mixed-methods approach to develop and
evaluate an intervention addressing multiple health be-
haviors which resulted in weight loss, improvements in

B. M. Davy et al. / Open Journal of Preventive Medicine 3 (2013) 429-440
438
dietary habits and in self-efficacy for physical activity.
The attrition rate was very low (only two participants
withdrew), which has also been noted in previous incen-
tive-based weight management interventions in college
students [19-21]. The small sample size, 12-week inter-
vention duration and lack of a long-term follow-up are
limitations of this preliminary investigation. Neverthe-
less, these findings could be used to develop a lar-
ger-scale Internet-and incentive-based weight loss pro-
gram targeting overweight and obese college students.
5. CONCLUSION
SCT-based interventions with modest incentives de-
livered via Internet can significantly decrease weight and
improve eating behaviors (decreased energy, fat and AS
intake), psychosocial mediators of physical activity and
dietary intake in overweight and obese college students.
Future Internet-based interventions should include more
frequent in-person interaction, such as group meetings
for social support and possibly friendly competition. Fu-
ture research should also include a more diverse popula-
tion and include environmental components using multi-
level approaches to promote weight loss efforts. Qualita-
tive feedback from this study suggests opportunities to
further adapt this weight loss intervention to weight gain
prevention programs for a broader weight range of stu-
dents and not just overweight/obese students.
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