Mental Balance: A Goal-oriented Well-being

Mobile Application for Self-monitoring

Mohammed Al-Kandari, Rakan Al-Halak, Rony Hamza, Rawan Mostafa and Iyad Abu Doush

Computing Department, College of Engineering and Applied Sciences, American University of Kuwait, Salmiyah, Kuwait

Keywords: eHealth, Emotions, Mental Health, Mobile Phone, Usability.

Abstract: In today’s digital age a lot of people get caught in an overwhelming data flow being delivered through their

smartphones and one can quickly forget to see the big picture and how each aspect of his life plays a critical

whole in his overall wellbeing. Well-being is the experience of health, happiness, and prosperity. It includes

having good mental health, high life satisfaction, and a sense of meaning or purpose. Smartphones can

improve the well-being of the individual and people already are using many applications to do so. The problem

is that these applications tend to focus on a single aspect of someone’s life or try to do everything at once and

end up being a bloated app with a steep learning curve. In this paper, we propose Mental Balance, a goal-

oriented wellbeing tool for people with mental illness. It takes a holistic approach in improving the wellbeing

of the user by letting him set goals for different aspects of his life and then perform daily self-assessments to

record their level of commitment to the goal, their mental state, and a journal summarizing their day. The

assessment of the user's well-being is based on a recommended measure called MARS. The application will

present personalized recommendations of hand-picked educational materials over time that will target specific

aspects of the user's life based on his progress over time. Giving users the ability to look at their well-being

from multiple perspectives. The application was evaluated on 3 target users. The results show the effectiveness

and efficiency of the developed solution, especially in behavior-changing and information quality.

1 INTRODUCTION

According to World Health Organization (WHO,

2021), mental health is defined as a state of well-

being in which every individual realizes his or her

potential, can cope with the normal stresses of life,

can work productively and fruitfully, and can

contribute to her or his community. Well-being is the

experience of health, happiness, and prosperity. It

includes having good mental health, high life

satisfaction, and a sense of meaning or purpose. More

generally, well-being is just feeling well (Rickard et

al., 2016).

According to the Mental Health First Aid

England, more than 90 % of people who commit

suicide have a diagnosable mental disorder

. The

National Institute of Mental Health statistics shows

that in the United States 26.2 % of the population

suffers from at least one type of mental disorder

Unfortunately, less than 40 % of people with serious

mental illnesses get access to proper stable treatment.

https://mhfaengland.org/mhfa-centre/research-and-

evaluation/mental-health-statistics/

There are several reasons for this number of people

such as financial barriers, many people believe that

they are the best at solving their problems and trust

problems and confidentiality with a psychiatrist.

Monitoring people daily activities can help in

tracking if there is any possibility of developing

depression, anxiety, or reduced physical health.

According to Latham & Locke (2013) goals are

specific aims of the action to achieve a specific

standard or professionalism during a predefined

amount of time. They are the level of competence that

we wish to achieve and create a useful lens through

which we assess our current performance. Goal

setting is the process by which we achieve these

goals. The importance of the goal-setting process

should not go unappreciated as every person's life

relies on selecting an appropriate goal to achieve

(Latham & Locke, 2013; Isakadze et al. 2018).

Clinical and professional health services would

prefer daily monitor of the users' daily progress. Such

a real-time daily process is a challenge. Self-

https://www.hopkinsmedicine.org/health/wellness-and-

prevention/mental-health-disorder-statistics

Al-Kandari, M., Al-Halak, R., Hamza, R., Mostafa, R. and Doush, I.

Mental Balance: A Goal-oriented Well-being Mobile Application for Self-monitor ing.

DOI: 10.5220/0010630500003060

In Proceedings of the 5th International Conference on Computer-Human Interaction Research and Applications (CHIRA 2021), pages 109-114

ISBN: 978-989-758-538-8; ISSN: 2184-3244

109

monitoring can be used as an alternative for mental

health care as many patients do not look for

professional support (Burns and Rapee, 2006).

Mobile phones are considered powerful tools to

track users' behaviour and emotional condition (Abu

Doush and Jarrah, 2019; Al-ghurair et al., 2021). This

paper introduces a tool to help users with mental

illness to be aware of their life to achieve mental

balance and general wellbeing. The tool allows users

to set goals on different aspects of their life and rate

their progress every day and write a short journal

about it. The proposed solution is evaluated in terms

of usability using the Mobile Application Rating

Scale (MARS) (Macias et al., 2015; Kim et al. 2018).

In addition, users are asked if the application helped

them in improving their lives. The proposed solution

automatically collects information related to the

user’s physical activity and sleep pattern to see if

these habits are improving which is demonstrates

users' general wellbeing.

The rest of the paper is structured as follows: The

background is presented in Section 2. The

methodology is described in Section 3. Section 4

provides the results and discussions. Finally, the

conclusion and some future directions are drawn in

Section 5.

2 BACKGROUND

According to World Health Organization mental

health is defined as a state of well-being in which

every individual realizes his or her potential, can cope

with the normal stresses of life, can work

productively and fruitfully, and can contribute to the

community (WHO, 2021).

According to Latham & Locke (2013) Goals are

“the object or aim of an action, for example, to attain

a specific standard of proficiency, usually within a

specified time limit.” They are the level of

competence that we wish to achieve and create a

useful lens through which we assess our current

performance. Goal setting is the process by which

we achieve these goals. The importance of the goal-

setting process should not go unappreciated as it can

provide meaning for someone’s life and improve

mental health.

According to Gravenhorst et al. (2015) there are

six main uses for mobile phone applications as

medical devices for mental disorder treatment. The

first type is self-reporting in which the patient is

self-reporting. It allows users to input their daily

progress independently. Users can answer questions

that can help in collecting data on behavioural and

cognitive factors like stress, mood, sleep, and daily

activities. The second type is automatic data

sampling as user’s behaviour is a core factor in

mental disorders to track users' progress. This

technique utilizes sensors that calculate the users

surrounding environment. Activity and mobility

data can be tested through the accelerometer and the

location sensors such as GPS. It has been proven that

there is a solid correlation between a mentally ill

patient’s state of her or his illness and social activity.

Being able to connect the daily activities with the

state or illness is a core factor for the treatment. The

third type is behavioural patterns recognition

which combines self-reporting and activity analysis.

It is useful for the psychiatrist to find the correlation

in the data given. Activity recognition is crucial for

the psychiatrist to track users' progress. Behaviour

recognition could identify walking, running,

sleeping, shopping, and attending work. This level

of recognition would be more useful and important

to the psychiatrist to track rather than the low level-

accumulator. The fourth type is data visualization

to track users' progress by using charts. The patient

or psychiatrist would investigate the visualization of

the tracked activity such as sleep, mood, stress, or

physical activity. The fifth type of application is

therapeutic feedback in which psychiatrists can

adjust prescriptions and advise through the designed

platform by the ability to track the user’s daily

progress. The platform allows daily real-time

analysis of the patient, and the psychiatrist would be

able to modify the prescriptions accordingly. For

example, in a case of observing the patient going

from a high-level of depression to a low-level of

depression, modifying the dosage of medicine is

vital. Lastly, the sixth type is communication which

allows direct communication between patient and

psychiatrist. A mobile phone can be used for

supporting remote, real-time communication using

text, video, and images. Several studies have shown

that a simple message from the psychiatrist to a

schizophrenic patient can benefit him/her through

the treatment.

The well-being we all strive to achieve comes

through considering the many aspects of one's life and

how they are connected and how one can improve

each one of these aspects. Goal setting and habit

formation are one of the most important skills one can

learn to achieve their goals in reaching wellbeing and

mental stability. Lent (2019) experiment to see how

does goal setting help in the performance of students.

Students were asked to set goals for their study but

also can include goals for other aspects of life. The

results show that goal setting allowed students to

avoid working too hard and in return lowering their

stress levels and focus on goals that are not related to

their studies. Goal setting can be used to increase life

satisfaction and improve overall well-being.

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Goal setting can be better if it is paired with

helpful habits that can help the person in achieving

goals. Habit formation can be improved using

smartphone applications (Stawarz et al., 2015).

According to Stawarz et al. (2015) applications that

contain elements of encouragement through

reminders and game elements through points and

rewards are the best as they made users use them

regularly.

Macias et al. (2015) investigate the engagement

rate of adults using a mobile application to promote

physical and psychiatric wellbeing. A solution is

developed for adults with schizophrenia, major

depression, or bipolar disorder. The results show that

the application encouraged users to engage in healthy

behaviours such as taking a walk for example.

3 PROPOSED SYSTEM

In this paper, a system to help people with mental

illness called Mental Balance is developed. It was

developed and designed after several visits to a

professional mental health clinic in Kuwait. The

recommendation was to add a general well-being

scale (GGWBS) (Gravenhorst et al., 2015). During

the system design, we utilize the recommendations

from the literature (Stawarz et al., 2015; Macias et al.,

2015) to design an efficient solution.

3.1 System Outline

The proposed solution is developed for iOS. The

solution utilizes HealthKit in the iOS SDK

to grab

information related to the user’s physical activity and

sleep pattern. It records user data by acquiring user

reviews (self-reporting) about different aspects of

life which are sleep, work, family, health, food, and

money (see Figure 1).

In addition, users would rate their mental state by

answering a questionnaire with a scale from 1 to 10

and by writing a small journal about their feelings.

Users can set goals and set reminders to achieve these

goals. They can also record assessments using journal

writing. The obtained information is then retrieved

and presented as charts (data visualization) to show

users their performance in different aspects and

display educational contents based on users' needs

(e.g., the aspect in life that has low performance). The

solution uses the phone sensor to track users' sleep

patterns and physical activity (automatic data

sampling and behavioral patterns recognition).

https://developer.apple.com/documentation/healthkit

This can help us track if the application is improving

these habits and the user's general wellbeing.

Figure 1: Personal goals list.

When we design the solution, we consider the

following choices: first, personalization by collecting

information to profile user's data to tailor the output

on users' needs. Second, a holistic approach by

covering a wide spectrum of health and well-being in

the areas of users' physical, mental, and social well-

being.

As shown in Figure 2, the proposed solution

allows users to record the goal on each life aspect and

then record the commitment level on a scale from 1

to 10 (e.g., record 4 on how the use is committed to

the sleeping goal).

The proposed solution shows the user trends on

his goal progress. Also, it analyses users' data and if

the user had a low level at a certain goal criterion

within a specific timeframe, then it suggests an

educational material with a topic specific to that goal

and an app suggestion that might help the user

improve their progress on that goal as shown in

Figure 4. A demo video of the proposed solution is

presented here

https://www.youtube.com/watch?v=pn1mC47zllU

Mental Balance: A Goal-oriented Well-being Mobile Application for Self-monitoring

111

Figure 2: Daily goals rating.

4 SYSTEM EVALUATION

4.1 Participants and Settings

We asked 3 mental health patients to use the app and

we discussed on the phone which included doing the

Mobile Assessment Rating System and then listening

to their suggestions on how we can improve the

usability of the app and what changes should we add.

The participant's information is presented in Table1.

Table 1: Participant's information.

ID Gender Age Type of mental illness

user-1 M 26 Depression

user-2 M 31

Obsessive-compulsive

disorder (OCD) and

attention deficit

hyperactivity disorder

(ADHD)

user-3 F 25

Generalized anxiety

disorder (GAD)

Figure 3: Resources suggestions based on the user

performance.

4.2 Procedure

The method in which the users are being instructed to

test the app is as follows:

1. The user will install the app manually by

plugging their devices in our development

computer.

2. Users are asked to set goals through a goal-

setting view. Evaluate your progress

through the day in the daily assessment

input view. View the details of the day and

the progress statistics from the stat view.

3. Use the assessment view to evaluate the

depression and anxiety levels.

4. Read the educational content in the

educational content and download

recommended apps from the list.

Due to the unfortunate events of COVID-19, the

rest of the evaluation was done through phone calls.

After the users used the application for 4 weeks, we

called each one of them and sent them a copy of the

MARS questionnaire to evaluate the application

usability. We went through every question and

explained it to the user and recorded the user’s results.

After that, we asked each user if they have any

specific points regarding specific areas in the app

where they would like to be changed and improved.

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4.3 Results and Discussion

The application is tested by the researchers and app

developers to fix any bugs or issues. The users used

the app for 4 weeks and write feedback about their

experience. The information about the study and

electronic consent is required before they use the app.

The evaluation results for the 3 users using

MARS are presented in Figure 4. Note that section A

measures the app engagement, section B measures

functionality, section C measures aesthetics, section

D measures information quality, section E measures

app subjective quality, and section G measures

behavioral changes.

It is worth mentioning that the highest users'

satisfaction was in the part of behavior changing and

information quality which is expected as the app is

meant to improve the lifestyle of the users to enhance

their mental health.

The users presented recommendations to enhance

the app. User-1 recommended adding visual feedback

for actions if possible (e.g., when deleting an item

display an alert, when adding an item display added

successfully). Also, he suggested allowing viewing

more time frames in the charts instead of just the

previous 7 days. Also, user-2 suggested adding a

tutorial on how to use the app when first launching

the app and recommended allowing that the

educational section is to be shared with others. In

addition, he suggested adding a color code for the

score for easier identification of that life aspect state.

Finally, user-3 suggested adding the option to display

the chart on the home screen so progress can be

viewed easily.

These issues mentioned by users have been

addressed in the next version of the app. For instance,

we added colors to determine how good or bad the

user is doing in progress on a certain goal. We used

three color codes green (good), blue (average), and

red (bad) as shown in Figure 5.

Figure 4: MARS score results for the 3 users.

Figure 5: Color indicator.

5 CONCLUSIONS AND FUTURE

WORK

The mobile apps can help in monitoring users and

help to improve their mental health. People check

their mobile phones regularly and this can help them

to get regular feedback which can improve their

mental state.

The developed mobile solution utilizes self-

reporting, data visualization, and behavioral patterns

recognition to provide a holistic approach for tracking

mental health users' progress and to provide

educational recommendations to improve their

mental health. The evaluation results using MARS

show the effectiveness and efficiency of the proposed

solution. Such a solution can help users to overcome

daily challenges and promote their emotional well-

being.

As a future direction, we can automate the

recognition of users' self-reported journals by using a

machine learning method (e.g., IBM API Tone

Mental Balance: A Goal-oriented Well-being Mobile Application for Self-monitoring

113

Analyzer

) to detect the tone of the used language

such as joy, fear, sadness, and anger. In addition, we

plan to evaluate the proposed solution on the users

after having the updated version of the solution.

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