JMIR FORMATIVE RESEARCH

Hendrie et al

Original Paper

The Development of VegEze: Smartphone App to Increase
Vegetable Consumption in Australian Adults
Gilly A Hendrie1, BSc, PhD; Genevieve James-Martin1, BHSc, M Nutr & Diet; Gemma Williams1, BHSci, M Nutri& Diet; Emily Brindal1, BPsych (Hons), PhD; Ben Whyte2, BInternetSci; Anna Crook2
1

Health & Biosecurity, Commonwealth Scientific and Industrial Research Organisation, Adelaide, Australia

2

SP Health Co Pty Ltd, Sydney, Australia

Corresponding Author:
Gilly A Hendrie, BSc, PhD
Health & Biosecurity
Commonwealth Scientific and Industrial Research Organisation
PO Box 10041
Adelaide, 5000
Australia
Phone: 61 88305 ext 0662
Fax: 61 883038899
Email: gilly.hendrie@csiro.au

Abstract
Background: Poor-quality dietary patterns are often characterized by inadequate consumption of fruits and vegetables. Changing
dietary behavior is difficult, and although it is often clear what needs to change, how to enact change is more difficult. Smartphones
have characteristics that may support the complexity of changing dietary behavior.
Objective: This paper describes the iterative process of developing a theory-based smartphone app called VegEze that aimed
to increase vegetable consumption.
Methods: To upscale, reach target users, and create a user-friendly end product, a collaborative research-industry partnership
was formed to build the app over a 20-week period. The Integrate, Design, Assess, and Share framework was used as a scientificbasis to guide the development. The behavior change wheel was also used as a theoretical grounding in combination with othertheory-based strategies, such as self-monitoring, social comparison, and gamification—which have all been shown to be successful
in dietary change or digital health interventions. We conducted 1 consumer survey (N=1068), 1 usability testing session (N=11),
and a pilot effectiveness and usability trial (N=283) to inform the design of the app.
Results: The target behavior for the app was defined as having 3 different types of vegetables at dinner. The perceived achievabilityof this target behavior was high; 93% of respondents (993/1068 users) felt they were likely or very likely to be able to regularly
achieve the behavior. App features that users wanted included the following: recipes and meal ideas (876/1068, 82% of users),
functionality to track their intake (662/1068, 62%), and information on how to prepare vegetables (545/1068, 51%). On the basisof importance of self-monitoring as a behavior change technique (BCT) and its rating by users, the vegetable tracker was a corefeature of the app and was designed to be quick and simple to use. Daily feedback messages for logging intake and communicating
progress were designed to be engaging and fun, using friendly, positive language and emoji icons. Daily and weekly feedback
on vegetable consumption was designed to be simple, informative, and reinforce monitoring. A creative team was engaged toassist in the branding of the app to ensure it had an identity that reflected the fun and simple nature of the underlying behavior.
The app included 16 BCTs, most of which were from the goals and planning subsection of the BCT taxonomy.
Conclusions: Combining a theoretical framework with an industry perspective and input resulted in an app that was developedin a timely manner while retaining its evidence-base. VegEze is an iOS app currently available in the App Store, and the overall
impact of the VegEze app will be evaluated in an uncontrolled, quantitative study.
Trial
Registration:
AustralianNew
Zealand
Clinical
TrialsRegistry
ACTRN12618000481279;
http://www.anzctr.org.au/TrialSearch.aspx?searchTxt=ACTRN12618000481279(Archivedby
WebCite:at
http://www.webcitation.org/769oG9EaA)(JMIR Form Res 2019;3(1):e10731) doi: 10.2196/10731
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KEYWORDS
mHealth; mobile applications; vegetables; adult

Introduction
Background
Poor diet quality is one of the most important modifiable risk
factors for chronic disease [1]. Poor-quality diets are generally
characterized by inadequate consumption of fruits andvegetables, and overconsumption of unhealthy, energy-dense,
discretionary foods [2]. A diet that contains plenty of vegetables,
including a variety of types and colors, can provide a range ofbeneficial nutrients that may help to reduce the risk of obesityand some chronic diseases [3]. Despite the known benefits ofincreasing vegetable consumption, intake remains low [4,5].
For example, in Australia, about 95% of adults do not meet therecommended intake of vegetables [5], which means that they
are missing out on essential vitamins, minerals, and dietary fiberthat vegetables can provide.
Population-level nutrition and obesity prevention interventions
have had small to modest success in improving diet quality[6-8]—most likely because dietary behavior change is difficultand multifaceted. Although, it is often clear what needs tochange, for example eat more vegetables, how to action changes
is more difficult [9]. The interplay between individual-level (eg,willpower and motivation), household-level (eg, availability
and finances), and community-level factors (eg, accessibility
to fresh food and social norms) are all likely to affect dietarychange [10].
Smartphones have characteristics which may support thecomplexity of changing dietary behavior. For example,
smartphones are increasingly ubiquitous, have the ability toreach individuals at nearly any time or place, can be highlyinteractive, can deliver information in a way that is engaging
and rewarding, and provide timely feedback [11]. Tailored
feedback can also grow with user inputs [12], creating apersonalized experience, which may encourage extended
engagement and success with an intervention [13]. Therefore,
smartphone-based behavior change interventions have thepotential to be effective and also accepted by individuals. They
may also serve as a cost-effective and scalable way to deliver
behavioral nutrition interventions to a large audience. However,to have the greatest likelihood of success, these interventions
also need to utilize existing scientific knowledge and theory[12,14].
An explosion of healthy eating smartphone apps has occurredin recent years (eg, MyFitnessPal, Lifesum, Lose It!, and Easy
Diet Diary). However, many commercial apps are notscientifically developed, based on behavioral theory or evidence,and have yet to undergo rigorous evaluation [11,15]. Regardless

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are also being developed and used by the research community,
but unfortunately the pace of development and evaluation in
research means that the temporal lag limits their potential impact[17]. Despite contrasting times from conceptualization to market,
both scientific and commercial entities want to develop engaging
and effective apps and working together could result in betterend products.

Objectives
This paper describes the iterative development process to builda mobile app that considers both the scientific and commercial
validity and that targets a complex and critically importantdietary behavior—increasing vegetable consumption. The
Integrate, Design, Assess, and Share (IDEAS) framework wasused as a scientific basis to guide the development of the app[18]. The IDEAS framework is a flexible approach fordeveloping digital interventions and is used here to provide a
detailed description of the journey of building VegEze—an app
to increase vegetable variety and consumption.

Methods
Ethics Approval
The development and evaluation of the app was approved by
the Commonwealth Scientific and Industrial Research
Organisation (CSIRO) Health and Medical Human Research
Ethics Committee Low Risk Review Panel (LR13/2017) andregistered with the Australian New Zealand Clinical Trials
Registry (ACTRN12618000481279).

Overview
The development of the VegEze app was conducted using the
IDEAS framework. The IDEAS framework brings together acombination of approaches necessary for the development ofeffective technologies. The framework draws on behavioral
theory, design thinking, user-centered design, rigorous
evaluation, and dissemination—which have all been shown to
be important for digital health interventions [18]. The frameworkoutlines a step-by-step process for integrating these approaches,
and although depicted as a linear process, it is intended to be
iterative, and stages should be revisited as required during thedevelopment process [18]. The framework also provides
theory-based behavioral science strategies to support theintervention design. Figure 1 is an adaptation of the IDEAS
framework flowchart [18], providing an overview of theprocesses that were used in the development of the VegEze app.

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Figure 1. The application of the IDEAS (Integrate, Design, Assess, and Share) framework to the development of the VegEze smartphone app. Due toproject requirements, the first 3 phases of part 1 of this study took place in a different order to original IDEAS framework. COM-B: capability, opportunity,and motivation to engage in the behavior.

Part 1: Integrating Insights From Users and Theory
Procedure
The first 3 phases of the IDEAS framework were designed togather insights from users and behavioral theory to focus theintervention process around a specific and measurable target
behavior.
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Phase 1: Specify Target Behavior
Specifying the target behavior was, in the first instance, anevidence-based decision drawing on existing data and literature,
which was later tested with potential users before proceedingwith the app development. To determine the degree of the
problem, which is inadequate consumption of vegetables in theAustralian population, we examined data from the Australian
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National Nutrition and Physical Activity survey. This is thelatest nationally representative survey of dietary intake available
in Australia [5]. The complex sampling method and design ofthis survey means we are able to make estimates of intake for
the Australian population based on the data collected from asample of 9341 adults [19]. These data provided estimates ofthe percentage of the population meeting the recommended
vegetable intake targets as prescribed by the Australian Dietary
Guidelines [3].
To more precisely define a specific target behavior within thecontext of increasing vegetable consumption, secondary data
analysis of the CSIRO Healthy Diet Score survey was
performed. The CSIRO Healthy Diet Score is an online shortfood survey that has collected data from over 198,000
Australians [2]. This survey asks about food group intake suchas fruits and vegetables, as well as a range of food habits
including how often does your evening meal contain 3 or moredifferent vegetables? Secondary analysis explored theassociation between this specific behavior and individuals’ total
vegetable consumption and likelihood of meeting the Australian
Dietary Guideline targets.
Phase 2: Ground in Behavioral Theory
The development of the app also drew on the behavior change
wheel (BCW) as a theoretical grounding [20,21] in combination
with other theory-based strategies, such as self-monitoring,social comparison [22-24], and gamification [25-27]—whichhave all shown to be successful in either dietary change or digital
health interventions. The BCW is an integrative guide forunderstanding behavior change and is a synthesis of many
previously published theoretical frameworks from this field.
Central to the BCW is the capability, opportunity, motivation,and behavior (COM-B model) that recognizes that for a behavior
to occur, an individual must have the capability, opportunity,and motivation to engage in the behavior (COM-B). The firststep of the BCW process is to specify the target behavior (similar
to phase 1 described here). Then, subsequent steps identify whatneeds to change to perform this target behavior. To help quantify
this and prioritize features of the app, we administered the
COM-B self-evaluation questionnaire in a sample of potential
users [20].
The app also drew on theory-based behavior change techniques(BCTs). The final version of the app was independently codedby 2 trained research assistants for inclusion of techniques fromthe 93 BCTs taxonomy [23]. This coding was done at the endof the development process to reflect the techniques employedin the final version of the app.
Phase 3: Empathize With Target Users
We conducted an online consumer survey with potential users
to understand how the identified target behavior (eat 3 different
vegetables at dinner) was received by potential users, and toelicit perceptions about performing this behavior.
Participants
Potential users were recruited via email from a database ofindividuals who had previously participated or expressed aninterest in participating in online nutrition and health-related
surveys or programs. An email was sent to 9900 individuals on
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the database and 1068 individuals completed the survey within
24 hours. These participants were majoritively female (84%female) with an average age of 56 years (range 20-90 years).

Part 2: Design Iteratively and Rapidly With User
Feedback
Procedure
Phase 4: Ideate Creative Implementation Strategies
To upscale, reach target users, and create a user-friendly end
product, a collaborative research-industry partnership wasformed which brought a multidisciplinary team together to build
the app over a 20-week build phase. The team was led by a
product development manager (from industry) and nutrition
scientist (researcher), and included research dietitians,behavioral scientists, product developers, and software
engineers. The multidisciplinary project team met regularly
throughout the development process to ensure a rapid build
phase. The ideation phase also focused on translating insightsfrom users and theory into features of the app. The process ofbrainstorming ideas for the app was highly iterative andincremental.
The app was built using the principles of agile softwaredevelopment which supports a minimum viable productapproach. The development team had 7 2-week sprints (14weeks total development) and aimed to release usable featuresat the end of each sprint for the broader project team to review
and then test with users.
Phase 5: Prototype a Potential Product
The build started by prototyping different ways to trackvegetable intake. On the basis of the importance ofself-monitoring as a BCT and its rating by potential users in the
consumer survey (a tracker for vegetable intake was the second
highest rated feature that users expected and highest in termsof a functionality feature), this feature was going to be a corecomponent of the app. In addition to communicating progress,a tracker can be used to communicate and reinforce the specifictarget behavior.
Phase 6: Gather User Feedback on the Prototype
Initial user testing was conducted in a small sample of people,
who were not known to the project team. Members of thedevelopment team approached individuals and asked them tocomplete 4 tasks on the prototype provided. The individuals
were observed using the prototype app as they were asked to:
add cauliflower, sweet potato, and corn to dinner; add capsicum
to breakfast; add salad for lunch; and add carrots for a snack.
Participants
A total of 11 people were approached within a local cafe andasked to participate in the initial user testing session. They wereasked to use to the app to do the 4 tasks and provide feedbackon their experience. The perceived age of the participants was
25 to 45 years (demographic information was not asked tomaintain anonymity).

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Phase 7: Build Minimum Viable Product
The beta version of the app was developed with fully functionalversions released and tested iteratively by the project team, withfeedback provided to the project lead of the development teamat regular intervals. To ensure the effectiveness and usabilityof the app could be assessed, evaluation surveys were designed
and embedded into the app using Apple ResearchKit software.
The length and usability of these surveys were tested as part ofthis phase as well. The beta version of the app focused on the
onboarding process, refining the vegetable tracker and user
experience, developing a framework for providing feedback,and the visual branding. In addition, a creative team wasengaged to assist in the branding of the app to ensure it had an
identity that reflected the fun and simple nature of the underlying
behavior.

Part 3: Assess Effectiveness and Usability
Procedure
Phase 8: Pilot Potential Effectiveness and Usability
The aim of this phase was to conduct a small-scale evaluation
to test the potential effectiveness of the app and to inform final
refinements as required. In this phase, it was also important tounderstand potential of usage of the app in terms of frequency
and duration of use, as well as user satisfaction with the app.
Potential users were invited to use the app for 3 days, providing
feedback through 3 evaluation surveys that included 1
immediately post download, 1 after 24 hours of use, and 1 after
3 days of use. On the basis of the feedback and experience ofthe participants, a list of suggestions for improvements wascompiled. The list of suggestions was discussed among the
project team and prioritized before it was implemented into thefinal version of the app.
Participants
A new sample of potential target users, recruited through thesame database described above, was invited to download thebeta version of the app. A total of 553 participants registered
their interest in the pilot study. Of these, 311 downloaded theapp (311/553, 56% of those interested) and 283 completed thebaseline survey (283/311, 91% of those who downloaded theapp). Participants used the app for about 24 hours and wereasked to complete a second survey (post download survey,
n=146), followed by a final survey about 3 days after download(post pilot survey, n=103). The sample that completed thebaseline survey was largely female (84%), with mean age 48
years, and 46% were overweight or obese.

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Results
Part 1: Integrating Insights From Users and Theory
Phase 1: Specify Target Behavior
Data from the latest Australian National Nutrition survey suggestthat less than 4% of adults consume enough vegetables to meet
the Australian Dietary Guidelines [5]. The Australian Dietary
Guidelines and Go for 2 & 5 campaigns encouraged the
population to “enjoy plenty of vegetables”, “increase
consumption”, and include “different types and colours” witha prescription for total daily recommended servings [7].
However, in the context of behavior change, the advice within
this literature broadly addresses the problem of inadequate
vegetable consumption, without identifying a highly specifictarget behavior.
Data from the CSIRO Healthy Diet Score survey showed that
respondents reporting “always” having 3 different types ofvegetables at their evening meal had higher overall vegetableconsumption relative to other frequencies. These people werealso more likely to meet the recommended daily intakes [28].
Review of other literature also suggests that serving a varietyof vegetables can help in selecting a healthier meal [29] and isan effective strategy to increase vegetable consumption in asingle meal [30]. On the basis of the CSIRO Healthy Diet Score
data and other acute studies, the target behavior for the app was
defined as having 3 different types of vegetables at dinner. Thisis a novel, specific, and an actionable behavior that is associatedwith an increased likelihood of the desired outcome—that isincreased vegetable consumption. In addition, it is measurable,
easy to self-monitor, and has the potential to produce a cascade
benefit, that is improving vegetable consumption at other meal
times. Therefore, the initial target behavior was to eat 3 different
vegetables at dinner.

Phase 2: Ground in Behavioral Theory
The app draws on the BCW framework, and the COM-B
self-evaluation questionnaire was administered as part of theonline consumer survey to elicit reasons associated withindividuals’ COM-B. When asked what they thought it would
take to increase vegetable intake, 37% of responses from survey
participants were reasons associated with their capability (eg,have better planning skills, cooking skills, and knowing how
to eat more vegetables), 33% were for reasons associated withmotivation (eg, developing better plans and a habit of eating
more vegetables, feeling like I want to eat more vegetables),and 30% were reasons associated with opportunity (eg, having
more time and triggers to prompt me to eat more vegetables).
Therefore, respondents reported needing help in all areas ofbehavior change according to the COM-B theory (Table 1).

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Table 1. Most common reasons reported for wanting to eat more vegetables from the consumer survey (N=1068). Survey question: “Why might you
want to eat more vegetables?”Response to survey question

Users, n (%)

To be healthier822 (77)

Increase nutrient intake

726 (68)

Increase fiber intake

662 (62)

Want to lose weight555 (52)

Feel better

491 (46)

Meet recommendations

267 (25)

Feel like I should

160 (15)

Doctor or health professional told me to32 (3)

Friends/family eat more than I do

11 (1)

Phase 3: Empathize With Target Users
The online consumer survey aimed to understand how the target
behavior (eat 3 different vegetables at dinner) was received bypotential users, and to elicit perceptions about performing thisbehavior. Respondents were generally health conscious andhealth literate, with 94%-99% reporting that they felt it was“important” or “very important” to eat enough and a wide
variety of vegetables each day, and 71% correctly identifying
the daily recommended number of serves of vegetables.
However, 66% of this sample still believed they would like to
eat more vegetables, and this was largely for health-related
reasons (Table 2).
In addition, 56% of respondents were “interested” or “veryinterested” in an app to specifically help with achieving thetarget behavior of eating 3 types of vegetables at dinner (Table3). Interestingly, this was similar to those interested in the more
traditional intervention target of “increasing vegetable intake”(55%). In the context of the app and perceived achievability ofthis target behavior, 93% of respondents felt they were “likely”
or “very likely” to be able to regularly achieve the behavior,and most (68%) thought they would be able to do it for 30 daysor more (Table 3).
In addition to administering the COM-B self-evaluationquestionnaire, the survey respondents indicated their preferences
for features in an app and their current vegetable eating
behaviors. App features that users reported to want included
recipes and meal ideas (82% of users), functionality to track
their intake (62%), and information on how to prepare
vegetables (51%, Table 3).
Most people reported to consume vegetables at their dinnermeal (98% of respondents), but many also included vegetables
with lunch (85%). Consuming vegetables at breakfast (11%) or
as a snack (19%) was less common. The most common ways
participants indicated eating vegetables in their meals were byincluding vegetables in dishes such as stir fries (48%), salads(39% as a side salad and 38% as a main), and 32% reported
hidden within a dish such as spaghetti bolognaise. In addition,
66% of respondents reported that they mix it up and consume
vegetables in a variety of ways. This information was used to
guide the development of recipes and meal ideas.

Table 2. Most common reasons from the Capability, Opportunity, and Motivation to Engage in the Behavior Self-Evaluation Questionnaire about what
it would take to increase vegetable intake from the consumer survey (N=1068). Survey question: “What do you think it would take to increase yourvegetable intake?”
Response to survey question

Users, n (%)

Having better planning skills

150 (14)Developing better plans for eating more vegetables

128 (12)Developing a habit for eating more vegetables

107 (10)

Having more time

96 (9)

Having better cooking skills

85 (8)

Knowing how to eat more vegetables

75 (7)

Having more triggers to prompt me to eat vegetables

64 (6)Developing greater will power

53 (5)

Feeling that I want to eat more vegetables

53 (5)

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Table 3. Evaluation questions about the proposed app from the consumer survey (N=1068).
Survey question

Users, n (%)

How interested are you in an app to help you to eat 3 types of vegetables at dinner?
Very interested

299 (28)

Interested

299 (28)

Neutral224 (21)

Not interested

96 (9)

Not at all interested

117 (11)How long do you think you could do this for?
Less than 7 days

53 (5)

7 days96 (9)

14 days107 (10)21 days

85 (8)

30 days or more

726 (68)

What features would you like to see in an app to increase vegetable intake?
Recipes

726 (82)

Tracker

662 (62)

How to info

545 (51)

Weekly reports

459 (43)

Info on guidelines

417 (39)

Health info

342 (32)

Challenges

310 (29)

Rewards

235 (22)

Engage family

150 (14)

Photo gallery

96 (9)

Social sharing

64 (6)

Leaderboard

43 (4)Part 2: Design Iteratively and Rapidly With User
Feedback
Phase 4: Ideate Creative Implementation Strategies
The multidisciplinary project team met twice per weekthroughout the 20-week development process that allowed us
to generate and refine ideas and implement behavior change
strategies within features that target users had reported to expectfrom the app. This was done collaboratively to retain thescientific evidence base while also maximizing the user
experience.
At the end of each of the 7 development sprints, usable features
were released, reviewed, and tested by the project team. From
the fourth sprint, we started to release features to test with users.
By using this approach, we were continually able to provide
feedback to the development team and facilitate a rapid assemblyof the app.

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Phase 5: Prototype a Potential ProductConsumer feedback indicated that a large proportion of users
consumed vegetables at lunch as well as dinner, so the project
team decided that the tracker would allow vegetables to be
tracked at all meals across the day.
To empathize with users, the vegetable tracker feature needed
to be quick and simple to use, highly applicable to a range ofusers by including a large variety of different vegetables andaccommodating of users from across the health and motivation
spectrums. Unlike traditional scientific methods, emphasis wastherefore placed on simplicity and intuitiveness of this dietaryintake recording tool. Its core functionality was to record varietyof vegetables consumed (ie, the types) as well as servings (ie,the amount). A vegetable list of 125 vegetables was created,
and a prototype vegetable tracker allowed users to scroll thevegetable list and click through to record the type and amountof vegetables consumed at each meal of the day. The prototype
featured only the core component to ensure the app reached thetarget behavior as effectively as possible (Figure 2).

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Figure 2. Early low resolution wireframes used in iterating the prototype for the vegetable tracker functionality of the app.

Phase 6: Gather User Feedback on the Prototype
The initial user testing provided feedback on the prototype andassessment of the functionality of navigating the vegetable list
and logging vegetables consumed in meals. The key
observations were that all participants were able to complete
all tasks in minimal time and the flow of entering items was
reasonably easily learnt. The meal icons for breakfast, lunch,dinner, and snacks appeared to be confusing, as users were notable to easily differentiate meals. Using circles for the meal
icons also appeared to be confusing as users seemed to require
more context in terms of what they were aiming for and how
to fill them in. The recommendations for refinement from thedevelopment team included (1) further iteration on the designof meal icons, (2) creation of onboarding screens to help theuser navigate, (3) more focus on the development of progress
indication, and (4) to continue testing and iterating thedashboard design for further testing in the pilot trial. This
feedback was included into the next iterations of the app.
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Phase 7: Build Minimum Viable Product
The beta version of the app was developed with fully functionalversions released and tested iteratively by the project team, withfeedback provided to the project lead of the development teamat regular intervals. The beta version of the app focused on the
onboarding process, refining the vegetable tracker and user
experience, developing a framework for providing feedback,and the visual branding.
The onboarding process included ethics documentation andconsent as well as the baseline evaluation survey. The consent
process and evaluation surveys were embedded into the app
using Apple ResearchKit software (Figure 3). The survey
questions drew on previously validated questionnaires to assessamount and variety of vegetables (as the primary outcomes)[31] and psychological predictors of intake (as possible
covariates of behavior change) such as attitudes, intentions, andnutrition-related self-efficacy [32-34]. The baseline evaluation
survey was initially designed by researchers, and then refined
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for length and readability based on feedback from developers
and the broader project team. Although it extends the registration
process, inclusion of the survey is considered essential to allow
for detailed evaluation of the app. Google Analytics was used
to collect app usage data to allow us to understand theinteractions between patterns of use and successful behavior
change.
The user experience for the early versions of the app wascentered on perceived ease of logging intake and usability ofthe vegetable list. In the prototype, the vegetable list was orderedby frequency of consumption per meal based on population
intake data from the Australian National Nutrition Survey [35],and then over time ordered with user’s inputted data. Eachvegetable item in the list had a name, image, and an information
button (which allowed users to click through to details on
standard serve size information). Serves could be added with atap of the “ + ” and “ − ” icons for each vegetable in the list.

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The framework for the frequency and content of feedback
messages sent via push notifications was developed by the
project team. A total of 3 types of notification messages would
be sent including daily feedback for logging as well as content
and recipe notifications which were sent on a random schedule
3 to 4 times per week. Daily feedback messages for logging
intake and communicating progress were designed to beengaging and fun using friendly and positive language and emoji
icons. Daily and weekly feedback and graphs on the variety andserves of vegetables logged were designed to be simple andinformative and reinforce monitoring.
Finally, the creative team proposed various names and logos
that were tested as part of the pilot study (phase 8). The name
VegEze with the byline Do 3 at dinner received the most positive
response from potential users and the project team agreed touse this branding for the app.

Figure 3. A sample of screenshots of the consent process which was embedded in the app using Apple ResearchKit software.

Part 3: Assess Effectiveness and Usability
Phase 8: Pilot Potential Effectiveness and Usability
The majority of the participants who registered (492/553, 89%)
reported they thought they would like to use the app at least
once a day, and 87% felt they would use the app for 2 to 3 min
per day or more. When asked how long they thought they could
maintain the challenge of eating 3 different types of vegetables
at dinner, 67% of users at baseline felt they could maintain it
for 21 days or more.

App Usage
During the testing period (7 days), 265 (265/283, 94%) users
who completed the baseline survey logged their vegetable intake
at least once. Users averaged 5 sessions in the app during thisperiod, with an average daily engagement time of 3 min 54
seconds. There were 1419 vegetable logs recorded, an averageof 5.4 logs per user. The majority of these logs were for theevening meal (1042/1419, 73%).
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Feedback Questionnaire
After downloading the app, at least 80% of users agreed orstrongly agreed that the setup process of the app, including
completing the baseline evaluation survey, was clear andrelatively easy to complete. After using the app for a few days,
85% of users reported to like the tracking feature to record typeof vegetables, and 79% liked the tracking feature to record
serves consumed. Importantly, 75% of users felt the vegetable
logging feature was easy to use, and 69% found it was useful:
A powerful motivator - more than I expected. I liked
the quality of the images of vegetables and the searchfunction.
I find the information about how much a serving size
is for each vegetable is really useful. I would probably
just assume I’m eating enough by having a few beans,pieces of carrot and broccoli florets for dinner - butknow I know exactly how much I need to eat.

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I like the scroll and search option to find veges andthe incremental steps to measure vege intake. REALLY
liked the option to click on the vege to show what aserving actually is AND the photo of the vege - great;ease of use, thumbs up.
Immediately following download, 75% of users (104/146) felt
their overall experience of using the app was positive, and aftera few days of using the app, 81% of users felt their experience
was positive. Immediately following download, 86% of users
reported they would use the app at least once a day, and thisremained high at the end of the pilot trial (78% of users). Post
download and post pilot, 80% and 87% of users, respectively
felt they would use the app for 2 to 3 min. About one-third ofusers felt they would use the app for 1 to 3 months, and anotherthird for more than 3 months. Finally, 63% of users whocompleted the post pilot survey (n=103) felt the app was easieror much easier than other health apps, and 69% indicated theywould give the app 4 out of 5 stars
Enjoying using the app so far and it’s definitely
challenged me to increase my veg intake at dinner.
Yes, I’m very impressed with how many veggies there
are to choose from. Being a creature of habit itcertainly opens your eyes to what you can eat.

Refinement Before Final Release
On the basis of the pilot evaluation, a few issues were identified
by users in regard to the vegetable list and logging of vegetables
that were addressed in the final sprint of the app. For example,
the development team further refined the process for adding
and deleting vegetables at different meal times to make it easierfor users, the order of the vegetable list was revisited, andfinally, users wanted more visual feedback of their total
vegetable servings in addition to total types.
The final sprint focused on the gamification elements of the app
and the content, which was not part of the beta version. The
consumer survey in phase 3 suggested that gamification features
such as challenges and rewards were expected by 29% and 22%of respondents, respectively. Although these were not the mosthighly ranked features, gamification is increasingly popularwithin apps [26]. Gamification has the potential to facilitate
behavior change by increasing motivation and making an
everyday task more fun to achieve [25]. The release version of
the app invites users to participate in a 21-day challenge to have

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3 different types of vegetables at dinner (Figure 4). To encourage
autonomy, challenges can be reset and restarted at any time by
the user. In addition to the challenge, other gamification features
include rewards and a form of leaderboard (Figure 4). A
rewards-based scheme was built into the challenge whereby
individuals achieved different levels depending on their intake.
A leaderboard displays the different awards and the percentage
of individuals using the app who are striving for each award—adeidentified form of social comparison. These gamification
elements in the app were developed by the behavioral scientists
and then further fleshed out by the project leaders to achieve
features that were fun and motivating but also realistic within
the project constraints.
The consumer survey described in phase 3 suggested that 82%
of respondents expected recipe and meal ideas in the app aswell as information on how to prepare vegetables (51% of
respondents). The content framework divided articles into 3
categories: (1) evidence-based fun facts on vegetables, (2) recipe
and meal ideas all containing 3 different vegetables, and (3) tips
and tricks on how to prepare and include vegetables in meals(Figure 4). The recipe and meal ideas covered stir fries, mixed
dishes, and main and side salads as well as meals with hidden
vegetables given that the consumer survey suggested
respondents were eating vegetables in a variety of ways.
Moreover, 2 research dietitians worked together to develop 74
short articles and 57 recipes and meal ideas for inclusion in theapp.
Two-way user feedback was central to the app (Figure 4). The
home screen became the place where users can review theirprogress of the day with carrot icons representing the numberof types consumed in each meal for the current day. With a bar
slider at the top of the screen, users can review previous days
at a glance with a tick indicating that the goal was met (Figure4) or across the challenge period in a calendar format (Figure4). With a swipe from the home screen, users can also review
their progress toward reaching the recommended number ofserves per day as well as review the past progress on reaching
this target with a simple visual bar chart (Figure 4).
As described in phase 2, the app drew on theory-based BCTs.
The final release version of the app was independently codedby 2 trained research assistants, who identified 16 BCTs usedwithin the app, most of which were from the goals and planning
subsections of the BCT taxonomy (Table 4).

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Figure 4. A sample of screenshots from the VegEze app as published in the App Store. (a) Log in and welcome screen; (b) Home screen displaying
motivational feedback message, progress for current day for types of vegetables consumed, and vegetable log; (c) Vegetable list and logging functionality;(d) Example of a standard serve of vegetables; (e) Summary challenge screen and level achieved; (f) Feedback screen of serves of vegetables consumed
for the day and across the challenge; (g) Leader board of achievements; (h) Example of “How to” content from the Learn section; (i) Learn screen; (j)Example of a recipe from the Meal ideas section.

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Table 4. The VegEze app was coded for the inclusion of 16 behavior change techniques (BCTs) from the BCT taxonomy.
BCT category

BCT description

Example of intervention component in the app

Goals and planning
1.1 Goal setting (behavior)

Set or agree a goal defined in terms of the behavior Sets a goal to eat 3 types of vegetables at dinner
to be achieved
each day for 21 days

1.4 Action planning

Prompt detailed planning of performance of the
behavior

Encourages planning and preparation to eat a variety of vegetables at dinner

1.5 Review behavior goals

Review behavior goals in light of achievement

Daily feedback messages and visual displays provided on types of vegetables consumed

1.6 Discrepancy between current behav- Draw attention to discrepancies between current
ior and goal
behavior and the goal

Home screen and daily feedback messages pointout differences between the number of types ofvegetables consumed and target; and feedback
screen provides feedback about consumption ofserves of vegetables relative to Dietary Guidelines

1.7 Review outcome goals

Review the outcome goal in light of achievement

At the end of the challenge, feedback on achievement is provided and a new goal can be set

2.2 Feedback on behavior

Monitor and provide informative or evaluative
feedback on behavior

Daily feedback messages and visual displays provided on types of vegetables consumed

2.3 Self-monitoring of behavior

Establish a method for the person to monitor andrecord their behavior

Vegetable log asks participants to record consumption daily

Feedback and monitoring

Natural consequences
5.1 Information about health consequences

Provide information about health consequences of Learn section provides information on the healthbehavior
benefits of consuming vegetables

5.3 Information about social and envi- Provide information about social and environmental Learn section provides information about the beneronmental consequences
consequences of behavior
fits to their family and environmental benefits to
consume and not waste vegetables
5.6 Information about emotional conse- Provide information about emotional consequences Learn section provides information that eating
quencesof behavior
vegetables increases energy and sense of well-being
Comparison of behavior
6.2 Social comparison

Draw attention to other people’s performance toallow comparison with own performance

A leaderboard displays the different awards and thepercentage of individuals using the app who are
striving for each award

8.1 Behavioral practice or rehearsal

Prompt practice of the behavior to increase habit

Daily push notifications to prompt behavior

8.3 Habit formation

Prompt rehearsal and repetition of the behavior in
the same context repeatedly

Push notification to prompt consumption of 3 types
at dinner each day

Repetition and substitution

Reward and threat
10.3 Nonspecified reward

Arrange delivery of a reward if there have been ef- Virtual rewards received for logging and achieving
fort and progress in behavior
progress toward 3 vegetables at dinner

10.6 Nonspecific incentive

Inform that a reward will be delivered if effort and Information section informs of virtual rewards for
progress in behavior are madelogging and achieving progress toward 3 vegetables
at dinner

Scheduled consequences
14.5 Rewarding completion

Build up behavior by arranging reward following
final component of the behavior

Phase 9: Evaluate With a Trial of the Product
It is planned that the overall impact of the VegEze app will be
evaluated using the Reach, Effectiveness, Adoption,
Implementation, and Maintenance (RE-AIM) framework [36,37]
in an uncontrolled, quantitative study designed to measure its
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Participants receive virtual rewards for eating 3
vegetables, which is contingent on them buying,cooking, and eating vegetables

effectiveness in increasing daily vegetable consumption after
21 and 90 days as well as to determine the associations between
user characteristics and outcome measures. The RE-AIM
framework focuses the evaluation on 5 program componentsthat are considered together to determine the public healthimpact of the initiative. These components include reach,
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effectiveness, adoption, implementation, and maintenance. The
RE-AIM evaluation framework is commonly used to translate
research and understand impact within real-world settings[36,37]. Changes in vegetable intake will be measured via
self-report in the surveys embedded in the app and will beadministered at baseline, day 21, and day 90. User
characteristics, which will be explored in the evaluation trial
for their association with app usage patterns or dietary intake,include, for example, demographic characteristics such as age
and gender, health indicators such as weight status, and baseline
vegetable intake.
VegEze is currently available in the App store as a standalone
research app, and participants have been recruited to take partin the evaluation study through television, radio, and social
media. The results of this evaluation will be published and theexecution of a communication plan will ensure the results areshared widely at the completion of the trial (phase 10 of the
IDEAS framework but not discussed here).

Discussion
Overview
This paper has described the theoretically and commerciallyderived development of the VegEze app and its features andfunctionality. Combining a theoretical framework with anindustry perspective and input has resulted in an app that wasdeveloped in a timely manner while retaining its evidence-base.
It has been suggested that the pace of the development,
evaluation, and dissemination cycle is too structured and slow
in academia, inhibiting the progress in meaningful and engaging
smartphone interventions [12,17]. However, few have worked
closely with industry partners to remedy this. The quick build
phase of VegEze is evidence that academic-industry partnerships
can work efficiently and effectively to develop products thattarget important population health issues.
There are advantages and disadvantages of a rapid build phasethat should be acknowledged. The sequential sprints and thestaged release of new app features at the completion of eachsprint allowed the project team to provide timely feedback to
the development team in a highly iterative and continuousrefinement process. The rapid development phase also ensured
the project team focused on the essential functionality and corefeatures expected by the target users and spent relatively lesstime on the nice to have features that were of limited appeal
and utility to our audience. However, with more time we may
have been able to benchmark normal usage and develop
strategies to maximize user engagement for all features of theapp. Regardless, this project demonstrates that a high-quality
app that meets users’ expectations can be built in a short timeframe, with industry support, a commercial development partner,
and a motivated multidisciplinary project team.
Internet and mobile phone technology are commonly used as adelivery medium to promote health behavior, both in research
and within the health and wellness industry. It has been
estimated that half of all mobile phone users have downloaded
a health-related app, with fitness and nutrition apps being mostcommonly downloaded and used at least once daily [38].
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Hendrie et al
However, the effectiveness of these products is not always
evaluated, and more specifically, the features of digital productsthat are associated with effective behavior change is not wellunderstood [14,15]. Only a small proportion of commerciallyavailable apps have a theoretical grounding [15], yet reviewsof digital interventions published in the scientific literature
support the use of theoretical frameworks and theoretically
based BCTs [14,15]. A recent review suggested interventions
that used theory more extensively and included a greater numberof BCTs were more effective than those without a strong
theoretical foundation or which used fewer techniques [14].
VegEze is available in the App store; however, it differs fromother commercially available apps—its development wasstrongly guided by an evidence-based framework, behavioral
theory, and drew on 16 BCTs. The planned trial will evaluate
the impact of VegEze and explore the use of app features andtheir association with increased vegetable intake.
Review of literature suggest interventions in the general adult
population can increase consumption of fruits and vegetables
by 0.2 to 0.6 serves per day or up to 1.4 in more controlledenvironments [39], but this increase is likely because of changes
in fruit intake and to a lesser extent, vegetable intake [40]. A
more recent review of electronic and mobile health interventions
for young adults found from the studies that reported vegetableintake independent of fruit, 4 out of 5 studies increased intake,with reported increases between 0.1 and 0.4 serves per day [41].
Through media coverage and the use of social media, we are
expecting that the VegEze app will reach over 5000 people andachieve an average increase of between a quarter to half a serve,
and possibly higher in those who have low vegetable intakes.

Strengths
Self-monitoring is one of the most commonly used BCT withinsmartphone interventions [15]. The VegEze app has at its core
the fundamental behavioral techniques of self-monitoring andgoal setting. These techniques have been applied in interventions
targeting a multitude of behaviors and are consistently identified
in various theories as fundamental for the process of behavior
change [42]. However, how these are operationalized is criticalto the target behavior. We have been careful in how thesetechniques have been applied in a way tailored specifically tothe behavior of interest. We have also been careful in balancing
the scientific evidence-base, with the fun, engaging, andusability elements expected from commercial gradeapps—largely the result of an ongoing exchange of ideas
between the members of the multidisciplinary project team.
Finally, the IDEAS framework helped to focus the priorities of
the app development and retain scientific method. The use ofApple ResearchKit software means that evaluation surveys areembedded into the app and will allow for a robust evaluation
phase. Using the ResearchKit software also saved on
development time; however, restricting the initial build to Apple
products could also be seen as a limitation. The results andfeedback from the planned evaluation study will inform further
development of the iOS app as well as expansion to Android
products.

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Limitations
Although the development of the app was informed by large
groups of potential users, they were individuals who had
previously registered or participated in health-related initiatives
and are likely to have a higher vegetable intake overall than thegeneral population. The barriers to consumption and strategies
to increase intake may differ in those who are already consuming
vegetables compared with those with low consumption orcompared with those who intend to increase consumption. The
appeal and impact of the app to a broader range of users will
be part of the evaluation. In addition, the majority of theconsumer sample were women, aged in their late 40s or early
50s, health motivated, and all volunteered to help in thedevelopment of an app targeting vegetable consumption. It is
possible that the particular nature of this sample may haveinformed the development of app features that do not appeal as
much to other groups of the population. We expect using massand social media to recruit for the evaluation trial will result ina more diverse group of users so that as part of the evaluation
we can better understand the variation in uptake and usage ofthe app by different user characteristics. Participants of the pilot

Hendrie et al
trial used the app for 5 out of a possible 7 days, with an average
daily engagement time of almost 4 min. Another literaturesuggests that, among mobile phone users in the United States,
65% opened their health apps once per day, and 44% used theirapp for between 1 and 10 min [38]. Achieving sufficientengagement and maintaining user retention rates is difficult,and although the usage of participants in the pilot trial was
similar to other research, we will explore usage patterns ingreater detail as part of the planned evaluation trial.

Conclusions
The development of VegEze was the result of a
research-industry partnership that brought together scientificevidence and commercial know how to develop an app targeting
inadequate vegetable consumption among Australian adults.
The IDEAS framework involved a number of iterative steps
and helped to retain a theoretical foundation withoutcompromising the pace of the pathway to market. The
effectiveness of the app is currently being evaluated in alarge-scale, real-world trial, and the results will be reported
using the RE-AIM framework.

Acknowledgments
The project team would like to thank the SP Health Co Pty Ltd Technical team for their role in supporting the App development
company in building the VegEze app. The project team would also like to acknowledge Pennie McCoy from SP Health Co Pty
Ltd for her assistance in coordinating the email recruitment and survey administration for the consumer surveys; and Dr Sinead
Golley from the Commonwealth Scientific and Industrial Research Organisation Health & Biosecurity for her behavioral science
expertise and feedback on elements of the gamification design features. Finally, the authors would also like to acknowledge
Brittany Johnson and Chelsea Mauch from the Flinders University who took time to code the BCTs of the app.
This project was funded by Horticulture Innovation Australia Ltd through the Research and Development levy.

Conflicts of Interest
None declared.

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Abbreviations
BCT: behavior change techniques
BCW: behavior change wheel
COM-B: capability, opportunity, and motivation to engage in the behavior
CSIRO: Commonwealth Scientific and Industrial Research Organisation
IDEAS: integrate, design, assess, and share
RE-AIM: reach, effectiveness, adoption, implementation, and maintenance

Edited by G Eysenbach; submitted 09.04.18; peer-reviewed by L Poppe, E Edwards, M Bardus; comments to author 07.08.18; revised
version received 25.10.18; accepted 30.12.18; published 27.03.19
Please cite as:
Hendrie GA, James-Martin G, Williams G, Brindal E, Whyte B, Crook A
The Development of VegEze: Smartphone App to Increase Vegetable Consumption in Australian Adults
JMIR Form Res 2019;3(1):e10731
URL: http://formative.jmir.org/2019/1/e10731/
doi: 10.2196/10731
PMID: 30916653©Gilly A Hendrie, Genevieve James-Martin, Gemma Williams, Emily Brindal, Ben Whyte, Anna Crook. Originally publishedin JMIR Formative Research (http://formative.jmir.org), 27.03.2019. This is an open-access article distributed under the termsof the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use,
distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly
cited. The complete bibliographic information, a link to the original publication on http://formative.jmir.org, as well as thiscopyright and license information must be included.

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