=Paper=
{{Paper
|id=Vol-2102/paper_2_Manninen
|storemode=property
|title=Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
|pdfUrl=https://ceur-ws.org/Vol-2102/paper_2_Manninen.pdf
|volume=Vol-2102
|authors=Iikka Manninen,Piiastiina Tikka
|dblpUrl=https://dblp.org/rec/conf/persuasive/ManninenT18
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==Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game==
https://ceur-ws.org/Vol-2102/paper_2_Manninen.pdf
Developing a Gamified Behavior Change Support
System: Case Implicity – The Food Game
Iikka Manninen1 and Piiastiina Tikka,1
1 University of Oulu, Pentti Kaiteran katu 1, Oulu, Finland
piiastiina.tikka@oulu.fi
Abstract. This paper describes the development process of a gamified mobile
Behavior Change Support System for increasing its users’ fruit and vegetable
consumption. The system was based on the principles of implicit association
measures as the behavioral feedback for reflection. The project used the Persua-
sive Systems Design (PSD) together with gamification principles and the Im-
plicit Association Test (IAT). The present paper describes the background and
process of implementing IAT in a gamified form for a mobile device platform.
Key outputs from the process include perceiving such a system to be built of a
basic BCSS core which is then gamified, and identifying a system to have seg-
ments that each have their own relevant persuasive features.
Keywords: Gamification, PSD, BCSS, Implicit association, behavior change,
systems development
1 Introduction
When building behavior change interventions that are based on self-tracking, the ap-
proach is typically to keep track of some specific behavior or activity. Today’s tech-
nology allows behavior and performance tracking directly, using the various sensors
that are now readily available in just about any smartphone. Alternatively, activities
and behavior can be tracked by self-reported means, for example by writing a food
diary. This approach focuses, necessarily, on what a person is already doing or has
completed doing – the person is already engaged with the target behavior. However, it
is perhaps possible to expand tracking-based behavior change to include attitudes and
automatic thinking in an effort to support actual behavior. Awareness of our own
thinking and attitudes, arising from implicit attitude measures, offers a means to en-
gage in reflection on our own behavior even at times when not engaging in that be-
havior. Such awareness can also allow rehearsing target behaviors and responses to
stimuli in a safe and controlled manner so that we can be ready when a real situation
arises.
In the present paper we describe the development steps leading to the creation of a
gamified Behavior Change Support System (BCSS)[1] for promoting fruit and vege-
table consumption. Using Persuasive Systems Design (PSD) [2] model as the design
framework and to guide the development process, we analyzed and evaluated re-
quirements for a system that would offer an engaging rehearsal environment for the
target behavior. The system employed implicit measures of existing attitudes (auto-
26 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
matic responses) in triggering self-reflection, and allowed response rehearsal as re-
gards food item responses through gamified rehearsal.
2 Background
2.1 Implicit Measures of Attitude and Cognitive Dissonance Theory
Implicit association test (IAT) was first presented in a paper by Greenwald, McGhee
and Schwartz [3] as a means for measuring implicit attitudes (attitudes that result
from automatic evaluations not under the control of an individual). In their original
paper, Greenwald et al. [3] posited that IAT would be able to reveal attitudes or auto-
matic associations that would be otherwise unavailable because of variety of reasons.
IAT has been utilized in a wide variety of domains: a meta-analysis on predictive
validity of IAT [4] included nine different domains from intergroup behavior to con-
sumer preferences, and found that there was variance between the domains. in social-
ly sensitive topics, IAT’s validity was significantly higher compared to self-report
measures [4].
A modified version of the IAT called EAST was used to investigate whether dif-
ferences in implicit attitudes toward healthy and unhealthy food existed among obese
children and a control group [5]. The study found that obese children did not have an
implicit preference to unhealthy food; however, their implicit attitude towards both
healthy and unhealthy food was greater than what it was in the control group. A study
into implicit and explicit attitudes towards high-fat foods in obese persons and a con-
trol group indicated that implicit attitude in obese subjects towards high-fat foods was
more negative than in the control group [6]. The IAT score has also been found to
correlate with dieting activity: participants who according to their self-reported be-
havior restricted their intake of high calorie food also had implicit attitudes that fa-
vored low calorie products [7]. Finally, a study investigating whether IAT can be used
as a predictor of food choice found a small but significant effect of IAT being able to
predict behavioral food choice [8]. The above-mentioned studies point to cases where
IAT has been used in the study of implicit attitudes with regards to food. Where pre-
dicting behavior may not always be a straight-forward affair as in [6], the studies
illustrate that food and nutrition can be observed through implicit measures.
In the development of the application described in this paper, we build the behav-
ior change potential on self-reflection. As regards self-reflection’s role in behavior
change, one theory that may help in part explain its effectiveness is the cognitive dis-
sonance theory [9], which posits that when a person encounters information that does
not match his or her present state of cognition, the resulting state of imbalance is so
uncomfortable that the person will try to reduce the dissonance. In the present gami-
fied BCSS the player is given a score based on his or her response times to common
food items (positive or negative categorization). The higher the score, the more in line
the player is with the target attitude of associating healthier food items with positive
words. However, if the scores are consistently poor, the player is presented with in-
formation that his or her food associations do not match the expectation. The player
sees how his or her thinking is skewed to favor the less-than-healthy food items. The
Sixth International Workshop on Behavior Change Support Systems (BCSS’18): 27
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
player must, then, evaluate whether to accept this information and try to change their
behavior or to reject it entirely and carry on as always. The information is, however,
based on an implicit measure that is difficult to explain away – it is not a result of
external factors or influenced by other people – which, we assume, makes the rejec-
tion more difficult.
2.2 Gamification
In their systematic survey of gamification, Seaborn and Fels [10] define gamification
“as the use of game elements and mechanics in non-game contexts” (p. 16). In their
seminal paper on gamification, Deterding, Dixon, Khaled and Nacke [11] define gam-
ification as “the use of game design elements in non-game contexts". Gamification
has also been described as “process of game-thinking and game mechanics to engage
users and solve problems” [12] and as the “use of game elements and game-design
techniques in non-game contexts” [13].
Many alternative, yet distinct, terms related to gamification exist [11]. Some ex-
amples of these are “productivity games, surveillance entertainment, behavioral
games and applied gaming” [10]. One prominent concept is serious games, which
encompasses game software that has been developed with an intention to be more
than entertainment. The purpose of serious game is to provide learning material that is
played through [11]. As Seaborn and Fels [10] advocate that gamified systems use
game elements but are not games, and Detering et al. [11] point out that it is impossi-
ble to know whether a system is a game or a gamified application without knowing
the designer’s intentions or without knowing how the users perceive a system, we
propose in the present paper to define the developed application to be a gamified
BCSS to the design intention.
Deterding et al. [11] describe five levels of game design. The most concrete level
is interface design patterns, followed by game design patterns and game mechanics.
More abstract levels of game design elements are game design principles and heuris-
tics, game models and game design methods. Werbach and Hunter [13] define game
design to be a combination of science, art and experience and compare it to strategic
leadership or team management.
Game elements are normally expected to be used as parts of an entertainment
game. Gamification aims to use these elements to improve user experience in other
contexts, or as used in the definition, non-game contexts. Deterding et al. [11] explic-
itly instruct to not place limitations on what these contexts may be. Werbach and
Hunter [13] define non-game contexts to mean internal, external or behavior-change
situations. In their definition, these situations involve business in the real world or
goals with social impact.
Points, badges and leaderboards are widely a used implementation of gamifica-
tion. They have been criticized as being a stock approach to gamification called
“pointsification” [10]. The main purpose of points is to keep score, determine win
states, create connection between game progression and extrinsic rewards, provide
feedback, show an external display of progress and provide data for the game’s de-
signer. A badge represents an achievement within the game and they are often used as
28 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
a substitute for achievements; Leaderboards provide a way to see progress in ways
that points or badges are not able to [13]. For instance, a leaderboard can show pro-
gress in comparison to other users of the gamified application. Other common ele-
ments include progression, status, levels, rewards and roles.
When purpose of gamification is considered, the concepts of motivation, behavior
change and engagement were a common theme [10]. Additionally, the reviewed liter-
ature [10] agreed in three areas: design theory, theoretical constructs and theoretical
framework. For design theory, user-centered design was consistently applied. The
main theoretical constructs were intrinsic and extrinsic motivation, which are ground-
ed in self-determination theory [10].
According to a literature review conducted by Mora et al. [14], the Six Steps to
Gamification framework by Werbach and Hunter is the best known framework and
that many other frameworks are based on it. Werbach and Hunter [13] point out that
implementing gamification requires constant testing and iteration to see which aspects
of the system and its design work and which do not. Playtesting, analytics and inter-
views are some of the ways that can be used to aid the design process.
3 Case Description
The software artifact we developed is based on the Implicit Association Test (IAT) as
given by Project Implicit [15] and the central idea was to build a gamified version of
the IAT for the purpose of using the IAT format as a means for the user to track his or
her responses to aid in self-reflection and self-monitoring. This chapter describes the
design and development process of the application. A Persuasive Systems Design
(PSD) [2] analysis was performed to identify important issues and to select relevant
software features to be included in the application, followed by iterative rounds of
development from mock-up and prototype development leading into finalizing the
application release.
3.1 Persuasion Context Analysis
The PSD model [2] was used to analyze the persuasion context. It was also used to
select design features that would be implemented in the application.
Intent. The persuader of the application can be viewed from two different angles.
First, as the application’s premise originates from an information processing science
researcher, the researcher can be thought to be the persuader of the application. The
alternative way is to assign the role of persuader to the user of the application, having
chosen to use a system aiming at promoting behavior change. In this approach the
gamification principles are an important element as they should preferably be able to
encourage the user to keep using the application for a longer period of time.
From a research perspective the intent of creating the application is to see whether
a gamified implicit association test can cause user to change his or her attitude and/or
behavior. In other words, it is not sufficient if the user only complies but does not
Sixth International Workshop on Behavior Change Support Systems (BCSS’18): 29
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
ultimately change dietary habits. Since the user background may vary, formation,
reinforcement and change are all relevant when considering change outcomes that are
being targeted.
Event. User Context. The potential users of the application are all individuals who are
interested in adopting healthier eating habits although it is possible that the applica-
tion could be used by individuals purely interested in testing their association
strengths as in the original IAT.
The user interface, textual descriptions and other central characteristics of the ap-
plication can be thought to implicitly exclude certain user groups such as children or
visually impaired. Because the implicit association test is based on response times to
determine the strength of associations, there was a need to consider the issue of reac-
tion times in designing the game logic to accommodate different types of users. How-
ever, to keep the technical implementation of the application more manageable it was
decided that additional features such as a more personalized scoring system or social
comparison features were to be left out from this iteration. For instance, more custom-
ization could have been achieved by providing customized sets of foods, adjustable
difficulty level or offering the chance to provide additional information concerning
long-term or short-term issues that affect dietary habits. In practice this could have
meant that the user would have been able to tell whether s/he was feeling tired, happy
or hungry before a game session, with the view to offering more context for self-
reflection based on performance visualizations in the ‘profile’ part of the system.
Use context. The application provides support for adopting healthier eating habits.
The game logic would be designed in a way that only correct categorizations would
lead to points and being able to advance in the game. Information on healthy foods
would be provided to further support behavior change. Tools that give ability to see
past performances would be included.
Technology context. The base platform used in the development of this application
was Cordova, a hybrid mobile application development framework. Cordova allows
the developer to deploy for multiple different platforms including iOS, Android and
Windows Mobile. Android was chosen as the main platform on which the application
was developed and tested. The database engine used for storing user data was SQLite.
The frontend was built with AngularJS, a JavaScript based single-page application
framework. Other web technologies such as HTML and CSS were used whenever
necessary.
Strategy. Outside game instructions, text content was used scarcely in the initial ver-
sion of the application. For each healthy food, a short text containing information
about health benefits was collected from various online sources. The longer refer-
ences were included in the background section. A large part of the content that a play-
er sees is based on his/her performance; the system itself does not make judgments on
how the player is performing as it is only displaying data.
30 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
3.2 Persuasive Software Features
The PSD model includes four categories of persuasive system principles. From these
categories, principles from primary task support, dialogue support and system credi-
bility were included in the application. Social support features were left out of the
present release of the application owing to time and resource limitations. Selection of
features was based on the context analysis, guiding the selection for example by rul-
ing out features that did not support the design goals of creating a quick and light
game that will expose the players to their own automatic responses, offers repetition
of task to allow users to try and improve, and offers all content in a fluent and simple
manner.
The overall structure of the application can be divided into three main parts: game,
profile and background information. The game section contains the gamified implicit
association test. In the profile section the user can track his or her progress by looking
at statistics, charts and achievements. The background section contains information
on healthy eating and the application itself. For each section, a walkthrough of each
category of persuasive system features was conducted to determine what features
could be implemented in the application. Tables 1, 2 and 3 list the design principles
included in each section.
Table 1. Design principles used in the Game section.
Persuasive feature Persuasive
Description
category feature
Primary task support Adopting healthier eating habits means choosing
Rehearsal healthy food over unhealthy. This is the central idea
of the gamified test.
Health information displayed after the game is in
Reduction
easily digestible form (e.g. language use and style).
Dialogue support After the game praise is given if enough points are
Praise
scored or achievements have been reached.
Virtual rewards in the form of additional content are
Rewards
given.
Table 2. Design principles used in the Profile section.
Persuasive feature Persuasive
Description
category feature
Primary task support Self- User can track progress via statistics, charts and
monitoring achievements.
Dialogue support Rewards Achievements are shown in the profile page.
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Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
Table 3. Design principles used in the Background section
Persuasive feature Persuasive
Description
category feature
Primary task support Advice on healthy eating is presented in a brief man-
Reduction
ner.
System credibility Trustwor-
Health information is from reliable sources.
support thiness
Authority Quote authorities.
Include links to literature and official sources when
Verifiability
relevant.
Expertise Provide health information sources.
4 Development Process
Being based on the IAT, an existing construct, many technological requirements and
design elements could be determined by studying the implementation available in
Project Implicit’s [15] website. The development process began by gathering the
high-level requirements of the application from the existing implementation of IAT.
These requirements were then used in selecting the appropriate technologies and
frameworks used for development.
4.1 Selecting the Platform and Programming Framework
As the IAT heavily relies on measuring the user’s reaction time in determining the
strength of association between concepts and attributes, the technological requirement
of being able to accurately measure time was a factor in framework selection. The
framework’s performance was also considered from the angle of persuasiveness in
terms of general responsiveness, mainly start-up time, and how straightforward it was
for the developer to build a user-friendly interface (Surface credibility principle [2]).
Three different platforms were compared (Table 4). The process included setting
up the development environment for each framework and then building a single ap-
plication that measured time between two clicks. Minor details that were included in
the comparison were the application’s size, application start-up time, supported oper-
ating systems, the programming languages used and the expected development time.
The data on application’s size was gathered with the framework’s default settings
and thus does not include any optimizations that are available for applications ready
for release. The start-up time was measured by touching the application icon on the
phone screen and waiting until the application was loaded. In this case, it meant the
appearance of a single test button and the ability for the user to interact with it. The
accuracy was tested by enabling USB debugging from the phone, turning on the re-
mote debugging features of the framework, which allowed the application to be con-
trolled with Google Chrome browser’s remote debugging tools. This was done be-
cause no straightforward way to automatically click or touch the screen within the
32 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
phone was found. An auto-clicking software was then used from the desktop to de-
termine the framework’s accuracy. Based on the results, Ionic framework was
dropped from the list of possible frameworks as at the time of testing the slow start-up
was a known feature of the framework. A long start-up time would have negatively
affected the user experience, as it would have discouraged the user from playing the
game in short sessions.
Table 4. Framework Comparison
Platform Android React Native Ionic Cordova
Application
1,5 MB 7 MB 3,5 MB 2 MB
size
Start-up ~1 s ~1 s ~5 s ~2 s
Accuracy ~2 ms ~2 ms ~50-75 ms ~2ms
Operating Android, iOS, Android, iOS, Android, iOS,
Android
systems Windows Windows Windows
JavaScript, JavaScript,
Language Java Java, JavaScript
HTML5 HTML5
The main decision was made between React Native and Cordova. While React
Native’s performance is supposedly much closer to native platform than with Cordo-
va, which operates in a native WebView, there was the trade-off of React Native hav-
ing its own syntax and idiosyncrasies that would have taken time to learn. However,
on a simple application the performance difference was negligible and the develop-
ment time with Cordova was expected to be much shorter. As a result, Cordova was
chosen as the underlying framework.
Although there have been concerns of the accuracy of web-based reaction times
and how they may be influenced by several factors such as variation of operating
systems, CPU speed, and browsers and so on, it should be noted that Project Implicit
itself is built with JavaScript. Numerous studies concerning reaction time accuracy in
web-based experiments have been done. For example, JavaScript can be used to accu-
rately detect reaction time differences with some caveats [16]. Variability of hardware
and software can have a detrimental effect on accuracy but it can be partly compen-
sated with a larger sample size, and web-based experiments can be an acceptable
source of data that is comparable to a laboratory setting [17]. Hilbig [18] explains
how numerous web-based studies have been able to replicate laboratory-based find-
ings, but that skepticism still remains widespread. Hilbig’s own experiment indicated
that web-based findings were not in any way inferior to other methods.
4.2 Steps in Systems Development
After the framework selection, the next steps involved mock-ups and prototype de-
velopment in order to produce a user interface that was both functional and had the
right style for the purpose of the application. The style (look and feel) were guided by
experiences with mobile games overall, as well as the objective of keeping the system
Sixth International Workshop on Behavior Change Support Systems (BCSS’18): 33
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
light and simple. In addition the developer team drew on 10+ years of experience on
mobile application design and UX assessment experience – making the process a
combination of science, art and experience [13]. Layouts, color schemes and applica-
tion views were designed by using mock-ups, evaluating the look and feel within the
development team, and finally a prototype to iterate the designs. For example, where
the original IAT test [15] is fairly serious and succinct as regards the test results, and
in a gamified approach it was necessary to display a score and offer all content in a
light and casual style. Developing the application itself involved two main segments:
the IAT based core, and then gamifying the core. Where the original IAT test online
[15] provided guidance for functional requirements for gathering the implicit
measures needed in the system, the PSD analysis and the design principles filtered
from that analysis provided further design requirements so that specific persuasive
features could be implemented. For the backend SQLite was used as a database en-
gine. The database was accessed with Cordova-sqlite-storage plugin. To provide more
compatibility with AngularJS, database queries were run through a wrapper provided
by ngCordova library. During a game session, data is stored in an AngularJS service.
After each game session data is saved into an offline SQLite database.
Based on the requirements based both on the model from the IAT and PSD model,
two game modes were implemented. In the first mode, the user would associate foods
with two different words (a negative word and a positive word) displayed on left and
right side of the screen. In the second mode, the same categorization would be per-
formed the other way: instead of words, food icons would be placed on left and right
side of the screen while the user would be shown different words, both positive and
negative, on center of the screen.
User interface was constantly revised during the creation of both game modes. Af-
ter it was tested that the game data was correctly being recorded, functions for saving
the data into database were created.
4.3 Programming a Gamified System
When both required game mods were completed, the next step was to design a gami-
fication system for them. The framework provided by Werbach and Hunter [13] was
used as a basis for design. The relatively simple structure of the IAT framed and lim-
ited the analysis and selection of gaming elements. On the other hand, IAT also pro-
vided a foundation from which gamification could be implemented.
Typically, the IAT includes at least the following elements: two target concepts,
an attribute, scoring and feedback. The general structure of the test is as follows: in-
structions, test, where images or word are shown and feedback (score is calculated in
the background based on the responses). On its own, IAT does not contain a particu-
larly large amount of content. For instance, in the test that measures racial bias, a total
of 12 faces and 16 words are included. The test results are given in verbal form as
follows: strong (implicit preference), moderate, slight and little to no difference. As
such, in its design IAT does not necessarily encourage the user to retake the test mul-
tiple times since the content stays the same and the feedback is given in a relatively
vague and non-transparent manner.
34 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
The first two steps in the gamification implementation process [13] concern busi-
ness objectives and target behaviors. The underlying goal in the present system is to
see whether a gamified test could be used to help people adopt healthier eating habits.
In practical terms, in the context of this application the ideal scenario would be that
the user would correctly categorize the given images and words as fast as possible and
without any errors. With this and the self-reflection functionalities contained in the
application, the implicit decision-making is expected to translate into corresponding
behavior in the real world.
The third step in the process [13] is to describe the users, which is accomplished
as part of the PSD analysis. The most relevant issue concerning gamification and
different user groups was reaction time as it is a central feature in IAT. To make im-
plementation more straightforward, it was decided that timing thresholds for what
would constitute too fast, fast, normal and slow reactions would be gathered from
existing research [3,19,20] rather than trying to implement a complex system where
user’s own performance would change timing thresholds between different game
sessions.
In the fourth step [13], activity loops in the form of engagement loops and pro-
gression stairs are described. The IAT provides the central part of the loop where the
user categorizes foods or words correctly. Feedback is provided by allowing the play-
er to continue to the next image or word, or by presenting an error indicator. After the
player has finished the session, results are presented. This loop was refined further by
introducing the concept of unlockable content. The player starts with 10 available
foods, five healthy and five unhealthy. Overall, the game contains 72 different foods.
34 healthy foods were selected as items that could be unlocked by playing the game.
For each food, a short informative text describing health benefits was created. Un-
healthy foods would also be unlocked in the background but no information on them
would be provided to the user. The food selection (healthy vs. less healthy) was based
on the principles presented in current governmental dietary recommendations 1, on the
principle that lower fat and sugar content is to be favored over high fat or sugar con-
tent, among other things.
To provide a more concrete way to see progress, the concept of levels was intro-
duced. By tying one unlockable food to each level, the game contains an elementary
type of progression stairs. In earlier research, points had been identified as a key ele-
ment in a gamified system. Points were also a suitable construct for this game to al-
low the tracking of user progress and to be able to differentiate between different
levels. When the user’s point total would exceed the required points to reach a new
level, the informational text of the unlocked food would be displayed to the user.
In the end, the engagement loop would ideally work so that the player’s initial
motivation would be further encouraged by providing the player information about
different foods. Additionally, the self-monitoring functionalities that would be im-
plemented would also function as a form of feedback that would sustain or increase
1 Finnish Food Safety Authority (EVIRA): Nutrition recommendations for all.
https://www.evira.fi/en/foodstuff/healthy-diet/nutrition-recommendations-for-all/ (date of
reference 15 March, 2018.
Sixth International Workshop on Behavior Change Support Systems (BCSS’18): 35
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
motivation. Almost all game components, including points and levels implemented in
this game can be considered a form of feedback that affects motivation, which in turn
causes actions, which provide feedback and so on [13].
The fifth step [13] deals with fun and making the system engaging. The structure
of IAT by itself does not necessarily contain aspects that could make it fun. Due to
this, whenever possible the text content of the application was written in a more casu-
al and informal manner compared to the content found in the original IAT. Random
appearances of different foods that granted bonus points were also added to provide a
little bit of gameful atmosphere. Additionally, instead of using real food images,
game-like icons were selected to portray the foods displayed to the user. Finally, as
detailed in the previous paragraph, implementing progression stairs with its related
points, levels and unlockable content should make the game more engaging compared
to a normal implicit association test. Finally, in the sixth step [13] the actual elements
and structures are deployed. Points, levels and content unlocking were selected as
central gamification elements for this application.
The two chosen tasks, associating foods with words and words with foods, were
not the same type of tasks that IAT uses to calculate the IAT effect, so an elementary
scoring system had to be developed for the game. The reaction time, defined as the
time between displaying an item and the user responding to it for the first time, was a
straightforward choice on which the scoring would be based, and only correct re-
sponses would award points to discourage extremely quick responses.
For tasks similar to this game, the reaction time had varied from 500 milliseconds
to 700 milliseconds [3]. In another implicit attitude measurement instrument, the
Go/No-go Association task, 500 to 850 milliseconds is explained to be an appropriate
range for measuring automatic attitudes [19]. In A 200 millisecond response time has
been considered to be too fast to process and respond [20]. In [3] all responses below
300 milliseconds were recoded to 300 milliseconds before conducting any analyses.
On the other end, all responses above 3 seconds were recoded to 3 seconds. Based on
these values the lower limit for the scoring algorithm was set to 300 milliseconds and
the upper limit to 2000 milliseconds to still award a small amount of points so as not
to discourage players needlessly. However, the reaction times that were recorded still
contained the original reaction times as only the point scoring part was done with
recoded values.
With the goal of faster responses awarding more points, a simple formula of
(1/(reaction time/100))^1.5*10 was created (where reaction time is in milliseconds,
for example 552). At the same time when the scoring formula was developed, the
different levels and their required points were also created. By testing the application
prototype, a rough estimation of the length of one game session could be obtained.
This allowed the testing of different types of reaction times to determine how long it
would take for a user to reach a new level. In an exhaustive gamification project this
step would have involved a larger scale testing with different users to find a perfect
balance between different reaction times and the time needed to reach a new level. In
the present project, the final values were mostly based on developer testing. To pro-
vide slight variability in progression, required points for each level were varied (see
Table 5).
36 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
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Table 5. An extract from the level structure
Level Total score needed Unlocked food Level name
1 750 Chili Chilin’ along
2 1500 Fig Figuring it out
3 2500 Banana Going bananas
4 3500 Avocado Playing devil’s avocado
5 5000 Coconut Go nuts
Database structure was revised further to add a new level table to contain level in-
formation. Other gamification related fields, such as a field for unlock texts, were also
added to other tables when necessary. For scoring purposes, a scoring service was
created. After this, the functions that handled storing the player and round information
into the database were modified to include the handling of points. The logic for ad-
vancing from one level to another was also implemented.
4.4 Feedback and Background Content
To support self-reflection, the need for a feedback channel was identified in the PSD
analysis. ‘My profile’ in the system consists of three views. The main view contains
the overall status of the player, including current point total, high score and level. It
also includes three different charts containing a line chart for points and reaction data
and a bar chart for the amount of correct responses. In the main view, the user is also
able to reset his/her gameplay data. As the application was planned to be used for
research purposes [21], an option for sending data was built. It fetches all the availa-
ble gameplay from the database and sends it to a server in a JSON format, where it is
saved into a database and if needed, sent in a CSV format to a researcher.
Within the main view, links for additional statistics and a list of unlocked foods
are provided. Statistics displays information about the Food Association gameplay
mode and lists the percentage of correct responses and average points and reaction for
each food. Finally, a longer version of game instructions was written for the About
section and pages for other miscellaneous information, including icon and open
source software licenses were created.
4.5 Application Structure in the Initial Release
Table 6 gives an overview of all the views and their related controllers in this applica-
tion. Fig. 1 illustrates the basic UI hierarchy, and Table 7 lists the application’s ser-
vices and modules.
The basic structure of the application (Fig. 1) aims at quick access to gameplay
without compromising the visibility of the remaining persuasive elements offering
feedback on performance and providing credibility support. The start screen offers the
same three basic options as the navigation bar at the bottom of the screen (always
available to the user as shortcuts): play, look at profile page, and ‘About’ section. The
primary task for the user is to play the game, and the path is to simply select Play,
Sixth International Workshop on Behavior Change Support Systems (BCSS’18): 37
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
then pick of two modes (food association or word association), and play. To make
repeated play easier, at the end of each game a ‘quick play’ option simply starts a new
game in the same mode as selected before. This way player does not have to go to
mode selection again until he or she wishes to change the mode.
Table 6. List of application’s views and controllers
View (and controller in
Description
dynamic pages)
Main menu Screen displayed to the user when the application is launched.
Game mode selection Allows the player to select from two game modes.
Start screen for the selected game mode. Shows instructions and
Game start
items that are used in the game session.
Gamified version of IAT where the user categorizes foods or
Game screen
words.
Displays game session results. Also shows progress towards next
Game results locked food. If needed, displays information on unlocked food if
the user has reached a new level.
Displays overall information about the user performance, includ-
ing current level, high score, total points and charts for points,
My Profile
reaction times and correct responses. Provides functionalities for
resetting the user profile and for sending research data.
My Profile - unlocked Displays unlocked foods and allows the user to re-read food
foods information.
My Profile - statistics Provides statistics about the Food Association mode.
Provides general instructions on the game and lists resources
About (how to play,
related to healthy eating. Additionally, shows information about
healthy eating, about this
the app such as the author and links for learning more about IAT.
app)
Open source licenses are also included.
Fig 1. User interface hierarchy basic structure, showing core options a player has on any given
path, starting from the Start screen at the top. The figure does not show every screen, such as
instruction screens.
38 Sixth International Workshop on Behavior Change Support Systems (BCSS’18):
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
Table 7. List of application’s services and modules
Name Description
Functions as a main module on which other modules are
ImplicitFood module
attached. Also contains definition for application’s routing.
A container to which all profile related controllers are
My Profile module
attached.
A container to which all gameplay related controllers and
Play module
services are attached.
Database service Provides functions for running database queries.
Manages user information. Responsible for updating scores
Player service and levels and for getting data from played sessions from
the database.
Responsible for setting up the game session by getting data
Game services
from the database and ensuring it is in needed form.
Scorer service Calculates scores for single rounds and whole session.
Stores round data during game session and handles the
Round service
saving of round data to database.
5 Discussion and Conclusion
The present paper discusses the development steps of a highly gamified BCSS, aim-
ing at increasing its users’ fruit and vegetable consumption. Some behavioral out-
comes form gameplay are described in [21], where game data was combined with
self-reported measures in order to evaluate the effectiveness of system features on the
target behavior. The system was developed to use the IAT as a basis of implicit atti-
tude feedback for reflection, using the PSD model to guide and determine the persua-
sive elements of the system.
From the process itself and the system developed it was possible to see that a two-
tier approach, where the base system (IAT as a BCSS) was put together first and the
gamification part was applied second, was a feasible way of ensuring that both the
requirements of building a BCSS and gamifying in a structured manner, was possible.
In addition, an important outcome in our view was that by treating the BCSS and the
gamification as two entities, the basic structure of the application itself was possible
to see in clear segments (background, profile, game) that all employed their own rele-
vant persuasive system features.
The present iteration of the application did not include social support, which un-
doubtedly would open further avenues for features that would increase both the per-
suasiveness of as well as engagement in the system. Social support is, therefore, iden-
tified as a major further development and research path for the presented system.
The design of the game and its backend allows observing not only players’ reac-
tion times to all items (‘healthy’ and ‘unhealthy’ items) and scores, but also cor-
rect/incorrect responses. Such data will be at the center of analysis when planning the
Sixth International Workshop on Behavior Change Support Systems (BCSS’18): 39
Developing a Gamified Behavior Change Support System: Case Implicity – The Food Game
next iterations for the system. For example, preliminary observations show that play-
ers tend to favor correct responses over faster reactions. In such a situation player data
will directly inform the developers about an important development need: to make the
system more sensitive in measuring automatic reactions, it would be beneficial to
encourage the players to really try to be as fast as possible and not to prioritize correct
answers over speed. With a functional first release of the game available, and the
game data that can be collected with it, it will be possible to execute design iterations
that prioritize the most problematic issues first.
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