Nutrition education for Pendekatan Perubahan Perilaku

Research Brief
A Supplemental Produce and eLearning Nutrition Education
Program for Georgians Who Use Safety-Net Clinics for Their
Health Care
Sarah A. Stotz, PhD, RD, CDE 1,y ; Jennifer Jo Thompson, PhD 2 ; Vibha Bhargava, PhD 3 ;
Andrea Scarrow, MAL 4 ; Krissy Capitano, RN, BSN 5 ; Jung Sun Lee, PhD, RD 3
ABSTRACT
Objective: To explore the experiences of safety-net clinic patients who engaged in a 12-week supplemental
produce and eLearning nutrition education program.
Methods: This mixed-method study employed a nonrandomized comparison study design. Participants
(intervention [n = 20] and comparison control [n = 6]) had diet-related chronic diseases. Data collection
included pre- and post-intervention, focus group interviews, 24-hour diet recalls, and clinical and anthropometric
outcome assessments. Interviews were recorded, transcribed, and coded using the constant comparison
method. Nonparametric data analyses were conducted for quantitative data.
Results: Three primary themes emerged: (1) program benefits, (2) challenges to achieving health benefits
and optimal engagement of the program, and (3) recommendations for program improvement. Quantitative
data analysis did not show significant differences in pre- and post-clinical and anthropometric measures
between the intervention and comparison groups.
Conclusions and Implications: Findings suggest a unique Supplemental Nutrition Assistance Program
Education dissemination model that may decrease barriers to healthful eating and increase engagement
in eLearning nutrition education.
Key Words: nutrition education, eLearning, SNAP-Ed, food security, medically underserved (J Nutr Educ
Behav. 2019; 51:1099−1106.)
Accepted June 17, 2019. Published online July 23, 2019.
INTRODUCTION
Food insecurity is a household-level
economic and social condition of limited
or uncertain access to adequate
food. Low-income adults who suffer
from food insecurity and limited
access to fresh produce disproportionally
suffer from complications of dietrelated
chronic diseases such as diabetes,
hypertension, and cardiovascular
disease. 1,2 One approach to mitigating
the health impacts of food insecurity
is through nutrition education. Nutrition
education, when appropriately
tailored for low-income audiences,
can help prevent nutrition-related
chronic disease, provide food resource
management guidance, and support
reduction in food insecurity. 3
The University of Georgia Supplemental
Nutrition Assistance Program
1 Colorado School of Public Health, University of Colorado Anschutz Medical Campus,
Aurora, CO
2 Department of Crop and Soil Sciences, University of Georgia, Athens, GA
3 Department of Foods and Nutrition, University of Georgia, Athens, GA
4 Cooperative Extension, University of Georgia, Tifton, GA
5 Clinical and Translational Research Unit, University of Georgia, Athens, GA
yDr Stotz was affiliated with the Department of Foods and Nutrition, University of Georgia
at the time this study was completed.
Conflict of Interest Disclosure: The authors have not stated any conflicts of interest.
Address for correspondence: Sarah A. Stotz, PhD, RD, CDE, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Mail Stop F800, 13055 East
17th Ave, Aurora, CO 80045; E-mail: sastotz@uga.edu
Ó 2019 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights
reserved.
https://doi.org/10.1016/j.jneb.2019.06.018
Education (UGA SNAP-Ed) includes
an innovative nutrition education
eLearning program as a means to
reach a broad statewide SNAP-Ed−eligible
audience in Georgia. The program
is based on a comprehensive
needs assessment and was launched
as a part of UGA SNAP-Ed programming
in 2016. 4−6 This approach is
unique in that it provides comprehensive
eLearning nutrition education
through a series of interactive
lessons, learning games, educational
and cooking videos, and online
assessments to evaluate changes in
participants’ food- and nutritionrelated
behaviors. 5 By working with
statewide UGA Cooperative Extension
and safety-net clinic networks,
UGA SNAP-Ed has offered eLearning
nutrition education as a means
to serve SNAP-Ed−eligible Georgian
adults outside of large metropolitan
areas where direct registered dietitian
−led nutrition education opportunities
are limited. 7
More than 44 million adults use
safety-net clinics for their primary
Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019 1099

1100 Stotz et al Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019
care, and these clinics often lack
access to registered dietitian−facilitated
nutrition education. 8 Safetynet
clinics which exist outside of a
more extensive hospital system could
benefit from UGA SNAP-Ed nutrition
education eLearning resources. 9 In
rural areas, outside of large hospital
networks and urban areas, shortages
of registered dietitians exist, and eLearning
nutrition education programs
have the potential to fill in these
gaps. 6,10 As a new initiative, encouraging
collaboration between UGA
Cooperative Extension and safetynet
clinics may serve as a sustainable
partnership to provide SNAP-Ed
nutrition education for medically
underserved Georgians.
Further exacerbating food security
status, many patients who use safetynet
clinics also lack access to affordable
fresh produce, which creates a
significant limitation for the outcomes
of any nutrition education program
translating to behavior change
for diet-related chronic disease management.
11 This paper reports the
experiences of low-income adult participants
who engaged in a 12-week
supplemental produce and eLearning
nutrition education program. The
unique nature of this project was to
combine nutrition education eLearning
and supplemental produce to
improve the nutritional health of
low-income Georgian adults who use
safety-net clinics for their health care.
METHODS
Study Design and Study Sample
The project employed a nonrandomized
comparison group design. The
sample included SNAP-Ed−eligible
Georgian adults (≥18 years old) who
live in households with income
below 185% of the federal poverty
level as evidenced by their enrollment
in the safety-net clinic. Eligible
participants were either actively
enrolled or previously enrolled in
safety-net clinic diabetes education
and prevention classes; were fluent
in English; and had a diagnosis of
diabetes, hypertension, and hyperlipidemia,
or a combination of these.
Safety-net clinic staff, located in rural
South Georgia, helped to recruit 26
participants (20 for the intervention
group and 6 for the comparison
group) using a convenience sampling
method. The intervention group
(n = 20) received access to a nutrition
education eLearning program and a
bag of locally grown produce for 12
weeks. The comparison group (n = 6)
did not receive produce or eLearning
access. Biochemical indices and
anthropometrics were measured at
the start of the intervention (baseline)
and 3 months after the start
of the program (baseline) for all 26
participants. All participants engaged
in a focus group interview before
the intervention and the intervention
participants also engaged in a
post-intervention focus group. Key
informants from each collaborating
organization (safety-net clinic, local
Cooperative Extension, farmer, and a
clinical research nurse) were interviewed
both before and after the
intervention.
Intervention
The intervention consisted of the 10
eLearning nutrition education lessons
and a weekly bag of locally grown
fresh produce for 3 months. The feasibility
of Georgia SNAP-Ed eLearning
nutrition education programs among
SNAP-Ed−eligible Georgians has been
rigorously examined using a mixedmethod
methodology. 4,6,12 Feasibility
studies suggested that SNAP-Ed−eligible
Georgians have the digital literacy
skills to use a smartphone-based eLearning
program effectively and that
incentives for program engagement
ought to be included to enhance
motivation. Also, these studies suggested
eLearning lessons should be
short (<3 minutes) to accommodate
the busy lives of many SNAP-Ed−eligible
Georgians and include interactive
games, activities, and audio features
to encourage program use. The lessons
are supported by constructs from
Adult Learning Theory (ALT) 13 and
eLearning theory. 14−16 Examples of
these theory-based constructs include
“anytime anyplace” asynchronous
learning opportunities (ALT) and
interactive visual-based learning (ALT
and eLearning theory). The eLearning
lessons are targeted to the cultural
preferences and education needs of
low-income Georgians. The eLearning
lessons feature a southern-accented
voiceover to serve those with low literacy,
images that reflect the population
in Georgia, and foods used in
cooking demonstrations and interactive
activities common in southern
cuisine. The lessons include a focus
on food resource management to
serve those who experience food insecurity
and feature budget-friendly recommendations
for healthful eating.
Each intervention participant was
loaned a smartphone with an unlimited
data plan to access the 10 interactive
eLearning lessons. The purpose
of the loaned smartphone was to
decrease participant burden for
involvement in the study and respect
participants’ limited resources as
many participants have limited data
plans on their own devices. The lessons
are augmented with cooking,
exercise, and just-in-time educational
videos. The nutrition education programs
are titled Food eTalk and Food
eTalk: Better U. These programs are
focused on general healthy eating,
grocery shopping, cooking, and food
safety, and they include principles
from the Dietary Approaches to Stop
Hypertension and Diabetes Prevention
Program specific to low sodium, high
fruits and vegetables, limited added
sugar, and portion control. The latter
of the 2 programs, Food eTalk: Better U,
includes a focus on healthy weight
management principles. The weekly
local fresh produce was delivered to
the safety-net clinic as this is a central
location familiar to all participants.
Fresh produce was coordinated by a
local farmer who agreed to collaborate
in this project. Produce bags contained
locally grown fruit and vegetables
including strawberries, collard
greens, peppers, onions, squash, and
sweet potatoes. The safety-net clinic
staff stored, dispersed, and tracked
pick-up of produce bags every Tuesday
morning between March and
May, 2018.
Data Collection
This project employed a mixed-methods
evaluation. Quantitative measures
used for evaluation included selfreported
24-hour dietary recall, food
insecurity assessed by the validated
modified 6-item USDA Household
Food Security Survey Module, 17
demographic information, general

Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019 Stotz et al 1101
nutrition practices, and selected clinical
outcomes as collected and analyzed
by the safety-net clinic standard
of care. The 24-hour dietary recalls
were entered by research staff and
analyzed to determine Healthy Eating
Index (HEI) using Automated Self-
Administered 24-Hour Dietary Recall
(ASA24). 18 The clinic staff conducted
anthropometric measures per their
standard of care protocols. Participants
visited the local hospital,
which offers blood draw services to
the safety-net clinic patients at no
charge, for their standard venipuncture.
Blood draws were processed in
this hospital laboratory per standard
hospital and safety-net clinic collaborative
agreement. Clinical measures
included lipid panel (total cholesterol,
low-density lipoprotein cholesterol,
high-density lipoprotein cholesterol,
and triglycerides), fasting blood glucose,
glycated hemoglobin (HbA 1C ),
weight (HD-BK digital weight scale,
Tanita, Arlington Heights, IL), height
(Seca 213 stadiometer, Hanover, MD),
and blood pressure for each of the participants,
collected at the baseline and
3-month time points. A collaborating
UGA Clinical and Translational
Research Unit (UGA CTRU) research
nurse traveled to the safety-net clinic to
train clinic staff on weight, height, and
blood pressure measurement protocols
for outcome assessment standardization.
Clinically relevant categorical
measures were also derived and analyzed
for hypertension (normal, elevated),
blood glucose (normal,
prediabetes, diabetes), total cholesterol
(normal, borderline high, high), and
body mass index (BMI) (normal weight,
overweight, obese).
The qualitative evaluation included
focus group interviews using a semistructured
moderator guide. All participants
engaged in baseline focus
groups and only the intervention participants
engaged in post-intervention
focus groups. Moderator guide questions
before the intervention included
the following: (1) Tell me about where
you could learn about nutrition in your
community, and (2) Tell me what it’s
like to get healthy food in your community.
Post-intervention moderator
guide questions included the following:
(1) Tell me about your experience
with the nutrition education program on
the phone, and (2) Tell me about the
produce you received as a part of this
project. The UGA Institutional Review
Board approval was established before
research was conducted on any
human participants.
Analysis
All participants’ qualitative interview
data were analyzed. Quantitative
data analysis included only
participants with complete data on
key pre- and post-outcome measures.
The comparison group had
more missing data in post-intervention
data compared with the intervention
group (eg, 67% vs 15% for
HbA 1c , respectively).
Focus group interviews were
recorded and transcribed verbatim.
Data were analyzed using a notebased
constant comparison method, 19
including field notes, memos, debriefing
notes, and verbatim transcriptions.
20 The constant comparison
coding approach included coding
data, categorizing the codes, and reorganizing
the categories into thematic
representation through a series of
assertions and interpretations. 19 By
using this method, the data could be
compared across transcriptions to
find similarities and differences; the
researcher’s observations, ideas, and
intuitions influenced this process. 19
The first level coding involved inductive
free coding, which was narrowed
by collapsing and integrating codes
for redundancy during the second
pass. These categories were then used
to construct overarching themes
across the interviews. Two co-authors
discussed coding and qualitative analysis
progress throughout the process.
21 Qualitative data analysis and
data organization were digitalized
using Atlas.ti (Mac version 8.0, Scientific
Software Development GmbH,
Berlin, Germany; 2018).
Quantitative data were analyzed
for descriptive and inferential statistics.
Baseline characteristics of
the intervention and comparison
groups were compared by using the
Wilcoxon-Mann-Whitney test for
continuous variables and the Fisher
exact test for categorical variables.
Difference in difference model was
used to assess the intervention effect
on HEI, BMI, fasting blood glucose,
and total cholesterol using the
Wilcoxon-Mann-Whitney test. Because
of a high level of missing data in the
comparison group’s post-intervention
data, not all outcome measures were
included in this analysis (eg, HbA 1c ).
Statistical analyses were conducted by
SAS (version 9.4; Cary, NC), and the significance
level was set at .05.
RESULTS
Characteristics of Participants
The demographic and baseline health
characteristics of the participants are
presented in the Table. The mean age
of the sample was 47.7 § 11.5 years,
and demographic surveys indicated
the sample included female (69%)
and white (60%) participants. There
were no significant differences in
demographic and health characteristics
between the intervention and
comparison group. As required for
inclusion criteria in this project, both
groups had a high prevalence of diabetes
(46.2%), hypertension (81.0%),
and obesity (88.5%). Nearly half of
the participants reported food insecurity
during the previous 30 days.
Overall, there were no significant differences
between pre- and post-intervention
assessments or between the
intervention and comparison groups
on key quantitative outcome measures,
including biochemical indicators,
anthropometric measures, and
HEI scores.
Qualitative Findings
The post-intervention focus groups
included only participants from
the intervention group. Three key
themes were constructed primarily
from these interviews and field notes:
(1) program benefits, (2) challenges
to achieving health benefits and optimal
engagement of the program, and
(3) recommendations for program
improvement.
Program benefits. A major strength
and benefit of the program was a sense
of community and togetherness. This
included community among themselves
as recipients of the produce bag
each week, shared group texts using
the loaned smartphones, and community
between participants, the clinic,
the farmer, and the local Extension

1102 Stotz et al Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019
Table. Baseline Demographic and Health Characteristics of SNAP-Ed−Eligible Participants From One Rural
Georgian Safety-Net Clinic (n = 26)
Variables
Intervention Group
(n = 20)
Control Group
(n = 6)
Age, y, mean (SD) 47.7 (12.1) 48.7 (10.4)
Female, n (%) 15 (75%) 3 (50%)
White, n (%) 11 (55%) 4 (66.7%)
Black, n (%) 6 (30%) 2 (33.3%)
Non-Hispanic, n (%) 18 (90%) 6 (100%)
Food insecure, n (%) 11 (55%) 3 (50%)
Total cholesterol, mg/dL, median (q1, q3) 158.0 (141.5, 171.0) 171.0 (144.0, 205.0)
Fasting blood glucose, mg/dL, median (q1, q3) 118.5 (103.5, 176.5) 119.0 (95.0, 179.0)
Prediabetes 7 (35%) 1 (16.7%)
Diabetes 9 (45%) 3 (50%)
BMI, kg/m 2 , median (q1, q3) 39.88 (34.18, 49.20) 45.13 (35.7, 59.8)
Overweight 3 (15%) 0 (0%)
Obese 17 (85%) 6 (100%)
Systolic BP, mm Hg, median (q1, q3) 128.0 (121.0, 141.0) 128.0 (124.8, 135.5)
Diastolic BP, mm Hg, median (q1, q3) 81.0 (73.0, 86.0) 79.8 (76.5, 84.0)
Elevated, n (%) 17 (85%) 4 (66.7%)
HEI, median (q1, q3) 54.03 (46.2, 62.8) a 52.74 (39.9, 77.6) a
BMI indicates body mass index; BP, blood pressure; HEI, Healthy Eating Index; (q1, q3), (first quartile, third quartile); SNAP-Ed,
Supplemental Nutrition Assistance Program Education.
a Individual-level HEI-2010 scores for each intake day were calculated using the SAS macros provided by the National Cancer
Institute. 22
Note: Differences in the median were tested using the Wilcoxon-Mann-Whitney test, and differences in frequency were tested
using the Fisher exact test. There were no statistically significant differences at .05 level of significance.
Office. Participants shared that they
even enjoyed talking to one another
in the focus group interviews:
It was an unexpected bond. Like
even right here, I’m sure none of
us knew each other before this,
but we’re talking as if we’ve
known each other for years.
Several participants shared they
had begun spending time together
outside of the program because of
the bond they formed during their
weekly bag pick-ups, and some indicated
they were learning from one
another and felt a sense of camaraderie.
At the clinic, participants felt a
sense of connection and importance
during their produce pick-up:
Everyone was so nice, like they
would carry the box for me to the
car because I can’t carry heavy
things. They were the nicest and
they remembered my name every
time, so I was like, “I feel
famous.”
Participants also described how
the benefits of this program reached
beyond themselves and their
households, into their networks of
family and friends. One participant
had a weekly family meal and featured
the produce she had received
that week:
So what I did was each week I
invited over some family members...
I would cook something
with the veggies in the box, there
was really always plenty to go
around. It felt good to be that way
− you know, generous with my
blessings.
Participants also shared they
benefited from the program by noticing
a reduction in their grocery bill
and some improvements in their
blood glucose, contrary to the insignificantchangesinkeyquantitativeoutcome
measures. These benefits were
the inspiration for most recommendations
regarding program improvement
and expansion. Here participants
shared their noticed benefits:
It certainly reduced the grocery
bill, I didn’t think that would happen
or be noticed, but it really
helped.
Challenges to achieving health benefits
and optimal engagement of the
program. Before the program, participants
were optimistic about the
health benefits they would see after
12 weeks of fresh produce and eLearning
nutrition education. They
shared goals such as decreasing
HbA 1c and body weight and increasing
their whole family’s intake of
fresh produce and meals eaten
together at home. One participant
explained:
Because of my diabetes situation. I
think more or less ...I wanted me
[to be] in this program just to see
if it would help me to lose weight
and just see how I did on it, as far
as I have high cholesterol, I have
high blood pressure, I have diabetes,
I’m insulin dependent. I just
pretty much wanted me in it to
just see how I do with it.
After the program, participants
were vocal about the myriad of reasons
the program did not work for
them as well as they had hoped. Central
to these critiques was lack of variety
of the produce, the time it took

Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019 Stotz et al 1103
to prepare the produce, lack of
knowledge and skills of how to prepare
certain produce items, challenges
with transportation to pick up
the weekly produce, technical issues
with the loaned smartphone, preferences
to unhealthy Southern food, and
life that got in the way. Participants,
generally unfamiliar with seasonal
eating, suggested that because the
produce bag often contained the
same late winter vegetables (ie, collard
greens, onions, bell peppers, and
sweet potatoes) that they grew tired
of making the same meals each week
and wished for more variety in the
produce.
Overall you know, collards are a
“Thanksgiving” or a “Christmas”
thing at my place, so to get them
every week was a lot. More diversity,
or variety in the box would
have helped − I didn’t have time
to make collards every week and
everything in the box basically
had to be prepared, I don’t have
time for that much cooking each
week.
Participants reported that gas prices,
vehicle access, and the time it
took to drive to the clinic each week
to pick up produce sometimes made it
hard to retrieve the produce bag each
Tuesday. Participants also blamed
Southern way of cooking and the way we
cook as reasons the produce bags did
not result in more desired health benefits
(such as weight loss and improvement
in blood glucose).
The one thing about us Southerners
though, and greens, is some
people season them with smoked
turkey, but most of us either use
fat back or ... some salty pork.
They’re just not good otherwise, in
my mind. I mean I’m a Southerner.
I’ve seen them cooked other
ways, but I don’t enjoy them any
other way.
Participants said their motivation
decreased throughout the 12-week
program, often because of the challenges
of the monotony of the produce
and preparation, but also
related to life getting in the way of
healthful behavior.
For me, if I had better time management
with what was going on,
I coulda ate it more frequently is
what I’m saying. I started off
good, but then life starts happening.
You’re not home, or you’re
coming home late, so then it
starts... But if I had better time
management and was eating
them on a regular basis like I
could have done, then it wouldn’t
have been wasted.
Several conversations during focus
group interviews suggested that
patients had misinformation and
misconceptions about nutrition. The
most common misinformation
reported was that participants were
instructed never to eat particular
foods, such as sweet potatoes, to
manage their blood glucose.
Finally, most of the participants’
feedback concerning the eLearning
lessons centered on challenges
using the loaned smartphone. As
many participants were familiar
with an Android smartphone, they
shared that navigating an iPhone
was frustrating and that it was hard to
learn a whole new phone. Participants
said they most enjoyed the video
and diabetic education parts of the
eLearning lessons and would have
liked more nutrition education that
was specific to the produce bag.
Many of these program strengths
lead participants to share how they
would recommend expanding and
improving the program.
Recommendations for program improvement.
Participants were generous and
enthusiastic with their recommendations
for continuing and growing
this program. Because participants
enjoyed the sense of community fostered
through this program, they
strongly recommended that future
programs should include more
opportunities for cohort interaction
including potlucks, cooking classes,
social gatherings, recipe sharing, and
opportunities to meet the farmer and
visit the farm. Participants suggested
additional opportunities to meet in
person as a group:
I would just stress, like we talked
about, let’s have meet-ups every
now and then because I want to
keep seeing this group. We can
exchange recipes and keep this
educational process going. I can’t
stress enough, teamwork makes
the dream work.
Many participants lamented they
never got to meet the farmer and
wished they could have thanked him
in person for providing the produce.
They indicated meeting the farmer
and seeing where their produce came
from would have been beneficial for
their whole family, and that the
farmer may have liked to meet the
recipients as well.
Likeifwehadtogotothefarm,
that would make us feel more
connected to the food and the
farmer might like that too, so he
can see who is benefiting from
this program.
Participants were also eager to
transform critiques of this program
into practical recommendations for
future program implementation; as
they understood the pilot nature of
this project and their critical role in
providing feedback for the researchers.
They offered alternative produce
bag distribution ideas to accommodate
those with transportation limitations,
food preferences or allergies,
and to increase variety. Some of these
included the following: farm-based
pick-up, farmer’s market−style pickup
where participants choose the
items they want each week and
home-based delivery options for
those with mobility and transportation
concerns. Participants recommended
that future programs allow
participants to use their smartphones
to access the eLearning lessons,
as most of us have a phone
anyway. This change would alleviatesomeofthestressfromhaving
to learn how to use the loaned
iPhone or carry 2 phones. Finally,
participants strongly suggested the
eLearning lessons more closely correspond
to each week’s produce
and include videos, recipes, and a
social media platform for participants
to communicate among one
another. One participant said:
I liked those texts, to see what
everyone was making. There could
have been more of that. Plus, I
used my phone to find recipes −
like new ways to make collards
(laughter), maybe that could have
been part of the [eLearning]

1104 Stotz et al Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019
program on the phone, to help
with produce cooking ideas.
Participants were generous and verbose
in their focus group participation.
Their experiences and recommendations
are crucial to enhance community
engagement and strengthen the
program’s acceptance and use.
DISCUSSION
The goal of this project was to test a
new SNAP-Ed implementation model,
including both innovative programming
and collaboration among key
community stakeholders. The latter is
important when considering community
capacity-building and sustainability
of the program, and findings
from those key community stakeholders
interviews are reported elsewhere.
12 Previous work exploring
eLearning nutrition education and
limited-income Georgians suggested
the cost of fresh produce and motivation
to engage in an education program
as barriers to the program’s
success 4 ; therefore, the purpose of the
supplemental produce was to mitigate
these barriers, as well as support local
farmers through collaboration with
Cooperative Extension.
The most prominent finding
included the many eLearning nutrition
education opportunities and
how to marry the 2 components of
this program in a way which synergistically
supports the nutrition
behavior change of the participants.
Qualitatively, participants shared
that both themselves and their families
ate more fresh vegetables primarily
because of increased access.
Participants recommended tying
the eLearning nutrition education
topics more closely to the contents
of the produce bag, and nutrition
misinformation shared during focus
groups indicated the lack of access
to reliable, reputable nutrition education.
Participants’ recommendations
to tie more closely the
eLearning nutrition education
topics to the produce bag contents
could be facilitated by partnerships
between County Extension offices
and SNAP-Ed by combining knowledge
of the foods in season in any
givenweekand,thus,whichrecipes
or cooking demonstration videos
to feature. Participants’ complaints
about lack of variety in the produce
bags certainly indicate the need for
education on seasonal produce,
benefits of locally grown produce,
and cooking local, seasonal foods
in a variety of dishes to mitigate
monotony, as supported by the
literature. 23 Nutrition education
programs within Extension have
provided similar resources with
food banks 24 and farmers markets. 25
It would be beneficial to garner support
from County Extension offices
to support their staff in facilitating
the SNAP-Ed nutrition education
resource and safety-net clinic
connection. 7
The most prominent inductive
finding included the participants’
strong sense of community and togetherness,
as well as their desire for more
opportunities to gather in person.
This inductive finding was surprising
as the intent of the eLearning design
was to serve an audience where inperson
gatherings were challenging
because of distance, time constraints,
and childcare. These participants’
enthusiastic discussions about the
relationships they made through participation
in this program are unique
and contribute to the current body of
literature. The Social Ecological Theory,
26 which highlights multiple levels
of influence between people’s
physical and sociocultural environment
and the reciprocal relationship
between social environment and
individual behavior, suggests interpersonal
and community relationships
and norms are crucial to
catalyzing and sustaining healthy
behaviors such as healthful nutrition
habits.
The positive experiences these
participants shared regarding their
sense of belonging and community
among themselves, their safety-net
clinic, and the farmer are central
to recommendations for program
improvement. Before engagement in
this study, none of the participants
knew about Extension in their community
in regard to nutrition education
resources. Several cited working
with Extension for support regarding
agriculture, but this was the extent
of their baseline awareness about
Extension resources. Because of this
familiarity with Extension and agricultural
resources, especially in rural
South Georgia, there is potential for
both Family and Consumer Science
and Agriculture Natural Resources
Extension agents to play a role in
supporting SNAP-Ed eLearning nutrition
education. Using (and perhaps
expanding) resources within the
County Extension Office may be a
way to build community capacity
and further activate the community
level factor of influence, as suggested
by the Social Ecological Theory. 27
Many of the participant requests
to increase interaction could be facilitated
by the local Extension staff
including: cooking classes, food demonstration
opportunities, recipe tasting
and sharing events, local produce
and agriculture education, and further
networking with other community
resources. Furthermore, many of
the challenges faced by participants
could be assuaged by Extension support
such as on-the-ground technical
support with smartphones, ideas for
adding variety to the preparation of
local produce, healthful ways to prepare
traditional southern foods, and
alternative means for produce bag
distribution. These solutions could
notably support motivation and
engagement toward the end of the
12-week project, through additional
educational and social opportunities.
Strengths of this program include
its innovative nature, unique community-based
collaboration, and
efforts at using clinical outcomes to
evaluate a SNAP-Ed nutrition education
program. There are also several
limitations to this study. First, the
funding cycle timeframe fell during
the least bountiful growing season
in South Georgia, therefore impacting
the variety of local produce
available during the 3-month intervention.
Second, the eLearning
nutrition education lesson content
was not directly matched with the
specific produce in the weekly bags,
andthiscouldbeamissedopportunity
for scaffolding nutrition education
to behavior change. Third, as
suggested in the literature, technical

Journal of Nutrition Education and Behavior Volume 51, Number 9, 2019 Stotz et al 1105
challenges with a loaned smartphone
may add an unnecessary barrier to
robust engagement in eLearning, 4
and allowing participants to access
the program from their own phone
may involve less of a learning curve to
navigating the eLearning program.
Finally, given there were no significant
differences in identified outcomes
between the intervention and
comparison groups, it is unclear
whether engagement in this program
would precipitate favorable changes
in clinical markers.
IMPLICATIONS FOR
RESEARCH AND PRACTICE
The intent of this pilot project was to
explore innovative ways improve
the health of low-income Georgians
who suffer from food insecurity and
nutrition-related chronic diseases
and who lack regular access to
registered dietitians and nutrition
education resources. Understanding
participants’ experiences of this program
are essential for guiding program
improvement and expansion.
The prominent emergent theme of
building community capacity needs
further exploration as a way to
engage participants and contribute
to the sustainability of this program
dissemination model. Quantitative
findings did not show significant differences
between the baseline and
follow-up clinical and dietary outcome
measures. This lack of significance
may be due to the small
sample size and short follow-up
period. Conducting more rigorous
evaluation is critical to developing
and implementing innovative evidence-based
SNAP-Ed implementation
models based on community
and clinic partnerships to serve medically
underserved individuals.
ACKNOWLEDGMENTS
This project was supported by USDA
SNAP-Ed, Georgia Clinical and Translational
Science Alliance Seed Grant
(UL1TR002378), and UGA College of
Agriculture and Education Sciences
Seed Grant. The authors would like
to thank our participants for their
generous time and insight, the collaborating
clinic staff, the farmer, the
UGA CTRU staff, and the UGA SNAP-
Ed team.
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