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GAMIFICATION IN E-MENTAL HEALTH: DEVELOPMENT OF A DIGITAL INTERVENTION ADDRESSING SEVERE MENTAL ILLNESS AND METABOLIC SYNDROME

Conference Paper

GAMIFICATION IN E-MENTAL HEALTH: DEVELOPMENT OF A DIGITAL INTERVENTION ADDRESSING SEVERE MENTAL ILLNESS AND METABOLIC SYNDROME

Abstract

MetaMood is a gamified Android application, developed from an existing paper-based health intervention program, designed to increase the motivation and engagement of participants. The development process followed a clinician-based design which was necessary to avoid exposing participants to an untested and unverified clinical tool. This paper describes design considerations and outcomes which could be useful for similar gamification attempts. It also presents the implementation and evaluation of a clinician review process, a vital step required before a full clinical trial. The success of MetaMood, evaluated through the results of the clinician review, suggests that a similar design, development, and evaluation process should be followed by future mobile e-health interventions before they are released through a public App Store.
GAMIFICATION IN E-MENTAL HEALTH:
DEVELOPMENT OF A DIGITAL INTERVENTION
ADDRESSING SEVERE MENTAL ILLNESS AND
METABOLIC SYNDROME
Alec Shaw1, David Paul1, William Billingsley1, Paul Kwan1, Rhonda Wilson2,3
1School of Science and Technology, University of New England, Armidale, NSW, Australia
2Telepsychiatric Research Unit, Faculty of Health, University of Southern Denmark, Odense, Denmark and
Mental Health Region of Southern Denmark, Odense, Denmark
3 School of Health, University of New England, Armidale, NSW, Australia
ABSTRACT
MetaMood is a gamified Android application, developed from an existing paper-based health intervention program,
designed to increase the motivation and engagement of participants. The development process followed a clinician-based
design which was necessary to avoid exposing participants to an untested and unverified clinical tool. This paper
describes design considerations and outcomes which could be useful for similar gamification attempts. It also presents the
implementation and evaluation of a clinician review process, a vital step required before a full clinical trial. The success
of MetaMood, evaluated through the results of the clinician review, suggests that a similar design, development, and
evaluation process should be followed by future mobile e-health interventions before they are released through a public
App Store.
KEYWORDS
Gamification, e-mental health, digital intervention, mental illness, metabolic syndrome.
1. INTRODUCTION
People who experience severe mental illness, for example chronic schizophrenia, or bipolar disorder, are
frequently treated with atypical antipsychotic medications (Usher, Foster, & Bullock, 2008). One of the side
effects of this type of medication is excessive weight gain, which can lead to obesity (Hoffmann, Case,
Stauffer, Jacobson, & Conley, 2010; Malhi et al., 2015; Wu et al., 2008). Other co-morbid conditions develop
in part related to obesity, including hypertension (high blood pressure) and diabetes (Usher et al., 2008). The
combination of these three health problems (obesity, hypertension and diabetes) are collectively known as
Metabolic Syndrome (Mental Health and Drug and Alcohol Office, 2009). Finding innovative and cost
effective ways to motivate and engage people with severe mental illness to develop healthy lifestyle
behaviors as a means to mitigating their physical and mental health problems is particularly challenging for
consumers and health care professionals (Kwasniewska, Kaleta, Dziankowska-Zaborszczyk, & Drygas,
2009). Some success with interventions using digital technologies has been noted (Christensen & Petrie,
2013; Jorm, Morgan, & Malhi, 2013; Titov, Dear, & Rapee, 2013). Depression is a neurological feature of
severe mental illness, and with it, amotivation is a frequent occurrence. This, combined with an alteration in
metabolic needs and hormone changes triggering appetite deregulation, often underpins a lifestyle where
physical activity levels are low, and weight gain accumulates, which in turn perpetuates symptoms of
depression (Blows, 2011).
Meanwhile, it is well known that the uptake of digital technologies has been increasing for some time
with most people now owning an active internet account and smart device such as a smart phone, tablet or
personal computer, with many users seeking health information in this environment (Australia Bureau of
Statistics, 2013; Fox & Duggan, 2012). E-health, using a range of digital technologies, is increasingly seen as
an efficacious mechanism for the delivery of meaningful health interventions, with funding bodies keen to
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support development of e-health strategies to meet the expanding needs for health service delivery to
populations (Department of Health and Aging, 2012).
This paper introduces a project that seeks to match the clinical profile of a disorder experienced by a
vulnerable population, and apply a gamification approach to an Android-app-based intervention designed to
motivate supportive healthy behaviors as an adjunct to usual therapeutic approaches to address metabolic
syndrome among people with severe mental illness. The project is based on an eight-week program aimed
specifically at rural patients who may have difficulty accessing clinicians. The program attempts to educate
participants about their illness and promote and encourage a healthier lifestyle, whilst combatting the onset of
associated illnesses such as depression (Wilson & Warren, 2011).
Gamification is an area receiving interest from several different fields (Chen, 2014; Comstock, 2012;
Loria, 2014). The premise of gamification is to utilise game elements in non-game environments. While the
word ‘game’ can refer to traditional games such as sports or card, dice and word games, in this context it is
more typically related to video games. The elements and mechanics utilised include, but are not limited to,
quests, achievements, tutorials and social aspects. In many cases this has led to increased levels of
engagement, motivation and success rates (Luminea, 2013).
This paper describes issues related to the gamification of an intervention program to assist people with
severe chronic mental illness in combination with metabolic syndrome. The result is a mobile app named
MetaMood. MetaMood has been developed by applying gamification techniques and processes to the
existing paper-based program, with an aim of increasing engagement and intake of the relevant information
by participants.
Unlike some other health-related apps, which have been released through relevant App Stores before any
clinical evaluation, MetaMood has undergone a clinical review. Increasingly, within the medical
technological sector it is important to demonstrate quality and safety of an evidenced-based intervention prior
to the administration of the intervention through access points such as app stores. Implementation of Internet
based medical intervention requires that a rigorous ethical process has been demonstrated to show that the
product has undergone sufficient review, such that health care professionals, intervention users, and the
general public can trust that all reasonable steps have been taken to promote human benefit and conversely to
limit or mitigate any potential harms or risks associated with usage. In this we decided to share the app with
field professionals using the Google Play beta process, ensuring the public cannot access a completely
untested clinical tool, ensuring that public safety was not risked. Data was collected from the professionals by
means of a survey to enable the analysis of the gamification attempt to determine how successful it has been,
and to understand if the product was acceptable, feasible and adhered to the concepts of recovery for the
clinical problem it was designed to treat. This was seen as a vital first step before the app can undergo
clinical trials to determine its effectiveness and suitability to be released to the general public through the
Google Play Store.
2. RELATED WORK
A game is an activity that one engages in for amusement, played according to rules. Gamification is the use
of game elements and mechanics in non-game contexts, with specific goals of increasing user engagement
and amusement to achieve a particular aim. It has been used in numerous contexts, such as education (e.g.
(Iosup & Epema, 2014; Kingsley & GrabnerHagen, 2015)), commerce (e.g. (Hamari, 2013)), and work (e.g.
(Anderson, Huttenlocher, Kleinberg, & Leskovec, 2013)), however we will concentrate on applications
related to healthcare, where there have been numerous projects with varying levels of success.
One example is a study in a hospital in the United Kingdom, where an electronic leader-board was
attached to a cardiopulmonary resuscitation (CPR) training and feedback device. The device was made
available 24 hours a day and calculated scores based on factors such as: rate, depth and hand position. At the
end of the trial, the control group did not show any increase in score while the test group had a significant
median score increase. It was concluded that the self-motivated gamification led to a statistically significant
change in scores and infant CPR ability (MacKinnon et al., 2015).
Gamified online and mobile apps have also been developed to help improve mental health. SuperBetter is
an application that was initially developed with the goal of helping people afflicted with depression, anxiety
and post-traumatic stress disorder (Chen, 2014). It utilises quests and makes small suggestions to the player.
ISBN: 978-989-8533-72-2 © 2017
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After completion, the player receives points and access to the next quest. A study around SuperBetter
involved participants signing up and being randomly assigned to either a control group or an intervention
group who played the game for a month. The 0-60 depression scale from the Center for Epidemiologic
Studies was used, where a score above 16 suggests a case of depression (Montgomery & Asberg, 1979), and
while the control group had a decrease in score of 4.3 points, the test group had a decrease of 11.3 points
(Chen, 2014).
Social engagement has also been shown to be effective in gamification for health purposes. Type 2
diabetes accounts for almost 95 percent of all diagnosed cases of diabetes in adults and has prompted a health
gaming company, Ayogo, to turn to gamification techniques to create a game to assist these people. The core
aspect of their game is socialising with other players through an online community. The game allows the
creation of an avatar and the player completes mini-games such as “choose your own adventure” story lines,
where they can gain gold coins. The game attempts to help players help themselves (Comstock, 2012).
MetaMood combines both mental and physical health and, as such, results from the Blue Marble Game
Co are of interest. The company focuses on therapeutic games where data can be generated after every
movement, providing immediate quantitative feedback to the physical therapist. While the games have
extremely positive feedback (Loria, 2014), it is important to note that the success varied with the nature of
the patient. Some participants were extremely reluctant to participate while older participants were dubious
that the game was “real therapy”. This study also revealed that the graphics were an integral part of the
gamification process though, while they can help motivate and engage players, care must be taken not to
overdo the graphics as they have the potential to distract the player and reduce the positive aspects (Loria,
2014).
The program that MetaMood is based upon was developed for people in rural environments, who may
feel isolated, so a social feature like in the apps from Ayogo is important. By allowing users to interact with
others in similar circumstances, it is hoped they will feel less alone and more likely to complete the program.
Results from Blue Marble Game Co show that it is also important that the app is easy to use and not
overdone, while obviously being related to the treatment program being undertaken, so not to distract the
player or make them feel the app is not beneficial.
3. DESIGN AND GAMIFICATION
The design and development of this gamification attempt was iterative and clinician-based, with a field
professional involved at every step of the process. After analysing the anticipated future users’ needs and
considering the nature of the gamification attempt, which included making decisions regarding the art style
and gamification techniques (Iosup & Epema, 2014; Loria, 2014), it was necessary to analyse and gamify the
original model. The paper-based program that MetaMood is based on was split over eight weeks, with each
week focusing on a different aspect of a healthy lifestyle and/or medical education. The analysis of the
existing paper-based program resulted in each aspect or element of the original program having to be
separated and categorised as either a lesson (something to be taught to the player), task (something the player
must do) or question (something the player must answer), which was then converted to tutorials, quests or
actions, respectively, as described in Table 1.
Other gamification techniques used in the process include:
Incorporating a storyline: A storyline serves the purpose of giving the player some perspective of
how far along they are in the game and hopefully also encourages them to continue to play so
they can complete the story line. The story line chosen for this application was to make the
player travel through eight villages, one for each week in the paper-based program.
Including a “helpful character”: An owl character was implemented to greet new players and
guide them on their journey through the story and the villages. This character offers hints, tips
and tricks throughout the game while also being available at any time for the player to “talk” to
and gain knowledge about various items of interest.
Achievements and coins: After completing a quest, the user is rewarded with an achievement
and a set amount of coins. This in-game reward is a core component of many previously
successful gamification attempts (Chen, 2014; Comstock, 2012; Loria, 2014; MacKinnon et al.,
2015) and the coins can be spent at the in-game “Arcade Corner” which acts as another reward
mechanism, promoting engagement and motivation.
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Social Feature: Incorporating a social feature, implemented as a pseudonymous chat room where
the player can specify their own screen name, assures the player that they are not alone and in
turn they are further encouraged to continue in their “journey” while engaging with other
players. A profanity filter was implemented over the chat room to help prevent players from
feeling threatened, and use of particular keywords (such as “suicide”) result in an automatic
intervention informing the player of various resources available to help in these cases.
Table 1. Traditional to game element conversion
Traditional Techniques
Lesson
Question
Gamified
Technique
Tutorial
Consider using a
relatable character to
deliver the lesson in
appropriate language.
“Try to”: This category
is asking the player to
learn something new,
that isn’t necessarily
vital to the progression
of the game.
Quest
An example would be
“Learn how to”. This
can link to a question
category as an
examination of the
skills learnt.
“You must answer
something to progress”:
This category can easily
be linked to tasks or
lessons.
Action
The most prominent of
these would be guided
gameplay of a particular
level or section of a
level.
“Can you complete?”:
This category can
sometimes come across
as something like a
dare, and must be used
with caution.
Figure 1. Screenshots of the final interface
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Figure 1 shows some screenshots of the final interface. Players begin only able to access one village, but
can further their progression by visiting characters in the buildings of the village. These characters prompt
the user to complete the required tutorials, quests, and actions, gaining the player achievements and coins
when they are successful. Coins can be spent in the “Arcade Corner” to play side-games not directly related
to the program. The owl character is always available to offer helpful suggestions or encouragement to the
player, and the player can access the chat room to interact with other players. After successfully navigating
the villages and learning the tools and skills necessary, the player confronts a boss character, who is the
personification of all the negative habits and lifestyle choices associated with metabolic syndrome. Use of the
app is anonymous, however collected data is securely uploaded to a server when the player is connected to
WiFi to allow the effectiveness of the app to be analysed.
It is necessary to make a distinction between MetaMood and other mobile applications with a similar
focus in the medical intervention field. MetaMood is a digital intervention that uses a blended care approach
in conjunction with clinical face-to-face consultations. It particularly targets people with severe chronic
mental illness in combination with metabolic syndrome. If use of MetaMood was not anonymous then, due to
the nature of the mental illnesses associated with metabolic syndrome, target users might not trust the app
and use it improperly. Thus, the sign-up process used by SuperBetter, which required an email address,
cannot be used for MetaMood, where the ideal distribution vector would be through native app stores with no
need to sign in. However, this is problematic, since the app has not yet been subject to a clinical trial, so
should not be made publicly available. Because of this, a clinician review stage has been completed for
MetaMood first.
Clinicians were asked to provide feedback about the acceptability of the app as part of a clinical
intervention for treating metabolic syndrome in a blended care format were the patient is supported to use the
app during and outside of regular clinic sessions. A validated app assessment tool was used to collect data
provided by the expert review of clinician informants in a modified online survey (Stoyanov et al., 2015).
Clinicians were asked to first download the app and then become familiar with the components and features
of the app, and then to complete an online survey to provide their feedback about the feasibility and
acceptability of the app. This clinician review was considered an important step because it minimises the
likelihood of the app causing any issues when a clinical trial is performed, and will strengthen reliability
during the future patient test phase in the trial period.
4. CLINICIAN REVIEW
While user-centered design dictates an iterative process of prototypes and mockups being presented to
stakeholders and users, the development of MetaMood, as a clinician-based design process, was quite
different. The development and prototypes were kept within the project team until such a time that the team
felt that it was ready to be tested and reviewed by other field professionals and clinicians. This is a necessary
first step in the rigorous process of designing a clinical digital intervention. The application must undergo
testing and trials prior to administering to people with specific conditions to ensure that the intervention is
safe and efficacious. For this reason, it was important to ensure that an ethical process was used in the
prototype development phase so that a treatment was not prematurely available to people in an untested and
unvalidated form. This clinician review, approved by our human research ethics committee, consisted of
clinicians being invited to download and install a beta version of the application on their Android smart
phone device. The beta process was handled by the functions available through the Google Play Developer
Console and the Google Play Store, ensuring that the app was not available to the general public. After using
the application for a period of time, the clinicians were asked to complete a short survey based on the
standard Mobile App Rating Scale (MARS) tool (Stoyanov et al., 2015) for mobile application reviews and
ratings. The surveys were administered through the online service Survey Monkey.
Twelve clinical professionals were contacted for the clinician review, though only five downloaded the
application, and only four submitted the survey. While this is a small number, the reviewers are all experts in
their field, so this is an adequate number to obtain an overall impression of these professionals, and to ensure
that no obvious problems were overlooked in the development of the app. One of the main issues that caused
this low participation rate was that many of the health professionals contacted had iPhones, and thus could
not test an Android application. MetaMood was specifically developed for Android phones because it was
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suggested by the team’s clinician that people with metabolic syndrome and associated mental illnesses were
more likely to be using this platform. The low completion rate was exacerbated by the fact that clinicians
needed to express interest in evaluating the app before they could be added to the beta process (which
required manually adding their email address) to be allowed access to the app, meaning they had to actively
seek to evaluate the app twice.
The most important result is that all respondents answered “yes” to the question asking whether the app
should proceed to clinical trial, with no requirement for further revision. Further, when asked whether they
would recommend the app to people who might benefit from it, 50% responded “Definitely. I would
recommend this app to everyone relevant”, 25% responded “There are many people I would recommend this
app to”, and 25% responded “Maybe. There are several people I would recommend this app to”, with all
respondents indicating they could see themselves recommending the app to 10-50 clients in the next 12
months.
Respondents were also asked more specifically about the content and presentation in the app. When asked
“Is the app content (visual information, language, design) appropriate for your target audience?”, 75% of
respondents said the app was well targeted, with either negligible or no issues, with the remaining 25%
labelling the content as “acceptable, but not targeted”. Respondents also believed the app was
fun/entertaining to use, both by using strategies to increase engagement (50% “moderately fun and
entertaining”, 50% “Highly entertaining and fun”) and by presenting content in an interesting way (50%
“moderately interesting”, 50% “very interesting”). All participants also indicated that it was “easy to learn
how to use the app or has clear instructions”, with one respondent indicating that they were “able to use the
app immediately; intuitive; simple”.
5. DISCUSSION
While there is a large amount of literature regarding the use of gamification aimed at addressing a wide range
of health conditions such as diabetes, depression, and physical rehabilitation, there remains a significant lack
of research specifically about the use of gamification strategies to reduce the impacts of metabolic syndrome,
including how it can be applied and how effective it would be. The exploration of this niche area is
significant because it combines the self-care health education about the management of a specific health
condition with a traditional real-world clinic, typically referred to as blended care (Wilson, 2017). The
combination of virtual- and real-world care utilising a blended care format makes this app a unique digital
intervention.
A clinician-based design means that the project team is an interdisciplinary collaboration of professionals
and academics with a single focused goal, and is particularly noteworthy because it has allowed new
perspectives and possibilities for the development process. It has also allowed for the inclusion of previously
unconsidered aspects into the MetaMood application. For example, the “Arcade Corner” would not have
been integrated without the input of the clinician, who pointed out the potential clinical benefits of this
addition, especially with games that had previously been successful in this area (Tong & Chignell, 2013).
The external perspective allowed for a new question, not only about technical viability but also whether the
“Arcade Corner” would fit with the already chosen gamification techniques. Perhaps the most important
aspect of the interdisciplinary team is that it has prompted the examination of unusual design considerations,
such as scenarios, situations or names that can potentially trigger adverse consequences for the players. For
example, a village in the game was originally named “Broadchurch”, but it was recommended that religious
overtones be avoided because they could possibly trigger delusions in participants. These issues obviously
must be considered in the development phase, with measures put in place to avoid any of the adverse
consequences, which can only occur if all relevant parties are involved.
The results of the clinician review show that the app is entertaining and interesting, and well-targeted for
the intended audience. This is a direct result of the iterative cross-disciplinary development process that took
place. These results, alongside the responses indicating that the app was easy to learn and use, imply that
MetaMood is engaging and motivating. When combined with the clinical professionals’ opinion that the app
should move to a clinical trial, and that they would recommend the app to several their clients, the design and
development processes used to create MetaMood can be considered a success. Thus, this process could be
useful for other similar online interventions. In particular, the use of a clinician review before making an
untested clinical tool available through a publicly-accessible App Store is highly recommended.
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6. CONCLUSION
This paper has described the design and development of MetaMood, a gamified Android application
designed to increase motivation and participation for participants in a mental health program that traditionally
requires weekly visits to a health professional. The considerations and lessons learned through the
development of this application could prove useful for similar development attempts in the future. Further,
the use of a clinician review, which allows health professionals beta access and the ability to provide
feedback to ensure the safety and efficacy of the app, is highly recommended for any future mobile e-health
interventions.
From this research, future work can be conducted to explore the value that is added by gamification and
whether gamification improves effectiveness in scenarios similar to this one. The results of the clinician
review indicate that the MetaMood application can now be finalised and taken to a full clinical trial, which
will help determine whether programs designed to be face-to-face are still effective when presented via an
alternative interface and whether anytime social interaction through an always-connected app is beneficial in
this process. It will also give insight into how people who live with a syndrome affecting so many different
aspects of their lives interact with games and game-like interfaces.
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... There are several definitions of gameful designs, and in this project, we define it similar to the one presented by Huotari and Hamari [40]: using design approaches and implementations from the world of games (in our otherwise nongame tools) to add a sense of playfulness and increase users' enjoyment and engagement. To date, gameful eHealth and mHealth tools have been designed for a variety of purposes, such as mental health [41], smoking cessation [42], and promoting physical activity among patients with rheumatoid arthritis [43]. ...
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... There are several definitions of gameful designs, and in this project, we define it similar to the one presented by Huotari and Hamari [40]: using design approaches and implementations from the world of games (in our otherwise nongame tools) to add a sense of playfulness and increase users' enjoyment and engagement. To date, gameful eHealth and mHealth tools have been designed for a variety of purposes, such as mental health [41], smoking cessation [42], and promoting physical activity among patients with rheumatoid arthritis [43]. ...
... A growing need is to attend to Human Computer Interaction (HCI) design elements of digital therapeutics, and to understand these better to enhance the safe administration and navigation of digital health interventions (Søgaard Nielsen & Wilson, in press;Morrison, Yardley, Powell, & Michie, 2012). It is insufficient to create, prescribe and administer an app, digital platform, or wearable technologies without also, scientifically understanding which platform and devices are best suited to particular health conditions, ages groups, developmental stages, digital literacy abilities and preferences (Shaw, Paul, Billingsley, Kwan, & Wilson, 2017). For example, font size, colors, text, image, animation, voice, accent, tone, and volume are some of the aspects that play a role in the accurate administration of the dose of the therapeutic intervention (Bol et al., 2016). ...
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