On the Involvement of Mental Healthcare Professionals in the Co-design

of Highly-rated Anxiety Apps

Nidal Drissi

and Soﬁa Ouhbi

Dept. Computer Science & Software Engineering, CIT, U.A.E. University, Al Ain, U.A.E.

Keywords:

m-Health, Requirements Engineering, Mental Health, Anxiety, Cognitive Behavioral Therapy.

Abstract:

Mobile applications (apps) have the potential to assist people with their mental health issues. They have

shown promising results in mitigating many mental health disorders and symptoms, including issues related

to anxiety. Mental health apps are based on different approaches, one of which is cognitive behavioral therapy

(CBT). However, these solutions still face many concerns and challenges, such as the lack of involvement

and inputs of mental healthcare professionals (MHP) in their design and evaluation. This paper focuses on

highly-rated CBT-based apps for anxiety and investigates the involvement of MHP in their co-design. Based

on the obvious importance of inclusion of mental health professionals in the creation of mental care apps, the

following hypothesis was formed: MHP are involved in the design and creation of CBT-based apps for anxiety.

To investigate this hypothesis, 23 apps were selected and analysed. Results showed that contrarily to the initial

hypothesis, about half of the selected CBT-based apps for anxiety did not involve MHP in their design. Results

also showed that the number of installs of the selected apps might be impacted by the involvement of MHP.

The average of installs of apps which involved MHP was signiﬁcantly higher than the average of installs of

apps that did not. This might indicate that users tend to trust apps that involve MHP more, which might

have impacted their decision to install them. Findings of this study might be of interest to people suffering

from anxiety, to help them ﬁnd apps for anxiety that are based on MHP input, as well as to developers and

researchers targeting similar apps.

1 INTRODUCTION

Requirements engineering (RE) is critical for the suc-

cess of software projects (Pohl, 2010). There are four

main phases in the requirements development pro-

cess: (1) requirements elicitation, (2) requirements

analysis, (3) requirements speciﬁcation, and (4) re-

quirements validation (Bourque et al., 2014). The

requirements elicitation phase can be viewed as the

most important step in any software project, includ-

ing the development of mobile applications (apps). It

is the base for all the steps that follow in the creation

process (Stephens, 2015). In this phase, the require-

ments engineer or the software engineer works to col-

lect the needs of different stakeholders that have inter-

est in the software product. The stakeholders that can

be involved include, among others, the customer, the

user, and the developers. It should be noted that the

customers are not always the users. The customers are

the ones paying for the creation of the software prod-

https://orcid.org/0000-0001-9667-5931

https://orcid.org/0000-0001-7614-9731

uct, while the users are the ones that will be using

the product. End-users are very important stakehold-

ers that are very often overlooked and not included in

the design process (Costabile et al., 2009). Many de-

sign approaches such as user-centred design stress on

the importance to understand the expectations of end-

users and to capture their needs (Van Leersum et al.,

2020). Several studies have also shown the impor-

tance of including end users in the co-design and co-

creation of the software product, particularly in con-

nected health solutions (Ouhbi et al., 2019; Dey et al.,

2019).

In the case of connected mental health solutions

(Drissi et al., 2020a), RE process is crucial and critical

as it will produce functionalities that are supposed to

help end-users with their mental health issues. Mental

health in general and anxiety in particular should be

approached and treated carefully. Which is why it is

not enough to opt for including only end-users in the

co-design of related apps, as in many cases the end-

users do not know what treatment approaches are suit-

able to assist them with their anxiety. Therefore men-

Drissi, N. and Ouhbi, S.

On the Involvement of Mental Healthcare Professionals in the Co-design of Highly-rated Anxiety Apps.

DOI: 10.5220/0010183102810287

In Proceedings of the 14th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2021) - Volume 5: HEALTHINF, pages 281-287

ISBN: 978-989-758-490-9

281

tal health professionals (MHP) should be involved in

the co-design of these apps, especially that the end-

users with anxiety are vulnerable users. Anxiety is

a “psychological and physiological state (mind and

body) associated with feelings of fear, worry, uneasi-

ness, dread, or nervousness” (Cortman et al., 2015).

It can be manged with several treatment approaches

such as cognitive behavioral therapy (CBT) (Loerinc

et al., 2015). CBT is a common type of psychother-

apy, based on helping patients becoming aware of

inaccurate or negative thinking, in order to be able

to deal with challenging situations in a more effec-

tive way (Mayo Clinic Staff, 2020). CBT has been

proven to be effective for anxiety (Norton and Bar-

rera, 2012; Lyneham and Rapee, 2006), and can help

with other issues like depression and sleep disorders

(Mayo Clinic Staff, 2020).

Mobile mental health is one of the most adopted

forms of use of technology for mental care (Drissi

et al., 2020a). The number of mobile mental health

apps is increasingly growing in app repositories (Hol-

lis et al., 2015; Olff, 2015), especially due to the cur-

rent COVID-19 pandemic, which has increased the

interest in digital mental health (Torous and Kesha-

van, 2020). In fact, COVID-19 has resulted in the

surge of several psychological issues, including anx-

iety, in the general population (Salari et al., 2020).

There is a wide range of apps that offer different func-

tionalities targeting anxiety self-treatment and man-

agement, such as breathing exercises, meditation,

yoga, games, and online therapy (Drissi et al., 2020b;

Drissi et al., 2019). The use of apps for mental health

has been reported to be effective for many psycholog-

ical issues, including stress, anxiety, and depression

(Harrison et al., 2011; Loo Gee et al., 2016). But the

majority of the available apps lack evidence on their

efﬁciency and only few have been thoroughly tested

(Larsen et al., 2019; Anthes, 2016). Involvement of

MHP in the co-design, testing and evaluation of such

apps, might help overcome those problems, as well as

help insuring users’ trust, and improving clinical out-

comes (Hollis et al., 2015).

This paper investigates the involvement of MHP

in the co-design of anxiety apps. To do so, 23 highly-

rated CBT-based apps for anxiety were selected and

analyzed. Highly-rated apps are considered to pro-

vide a certain level of satisfaction to end users. Users’

satisfaction is related to the quality of the app, partic-

ularly to its usability. For this reason, we included

only highly-rated apps. To the best of our knowledge,

there are no similar studies that address the involve-

ment of MHP in the co-design of mental care apps.

Since the involvement of MHP in mobile mental care

apps is important on many levels, our hypothesis is as

follows: CBT-based mental care apps for anxiety do

include MHP in their co-design.

2 METHODOLOGY

This study mainly focuses on answering this research

question (RQ): Do CBT-based apps for anxiety in-

volve MHP in their design?

This section presents the methodology followed to

answer the RQ and select the apps to be analysed in

this paper. The search conducted in this study fol-

lowed the guidelines of the Preferred Reporting Items

for Systematic reviews and Meta-Analysis (PRISMA)

group (Liberati et al., 2009).

2.1 Sources and Eligibility Criteria

A general search string composed with only the term

“Anxiety” was used, and it was automatically applied

to the names and descriptions of the apps. Each app

identiﬁed from the search result was analyzed to de-

termine whether to be included or excluded from the

selection.

The following Inclusion criteria (IC) were used:

• IC1: anxiety-related apps in Google Play Store

• IC2: apps that have a free version

• IC3: apps rated 4+ stars

IC1 focuses on apps available in Google Play

Store as, in contract with Apple App Store, it pro-

vides the number of installs of each app. Google Play

is a very popular app repository, with a wide range

of health apps, it includes over 41,377 app (Statista,

2019).

IC2 focuses the selection on free apps, as many

people can use them without payment. Moreover,

recent statistics in March 2020 showed that 96.3%

of Android apps were freely available worldwide

(Clement, 2020).

IC3 includes only apps that provide high user sat-

isfaction as the app’s user ratings reﬂect a certain level

of the app’s user satisfaction.

The apps identiﬁed from the search results that

met at least one of the following exclusion criteria

(EC) were excluded:

• EC1: apps that do not include the CBT approach

• EC2: apps that could not be installed

EC1 includes only anxiety app based on the CBT

approach, which are the focus of this study. EC2 ex-

cludes apps that could not be installed, therefore could

not be examined.

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282

2.2 Apps Analysis

The description of each app selected available in the

Google Play was examined. Each selected app was

installed in OPPO A9 (Android 9) and analyzed. Ex-

tracted data included:

• Name of the app

• Rating

• Number of raters

• MHP involved (e.g. therapists, counselors, re-

searchers, advisors, and others with a mental

health background), this information was re-

trieved from the app’s description

• Number of downloads

• Release date, which was retrieved from the App

Annie platform (https://www.appannie.com/en/)

3 RESULTS AND DISCUSSION

A total of 23 apps were included in the ﬁnal selec-

tion as shown in Fig. 1. Table 1 presents information

on the included apps, and Table 2 presents apps that

involve MHP and information on the latest. It must

be noted that for some apps, the stated involvement

of MHP in the app was general, and did not provide

speciﬁc names. Twelve selected apps included MHP

in their design, while the rest did not.

Figure 1: Selection process.

One way to conduct requirements gathering is by

looking for answers to these questions: Who, What,

When, Where, Why and How (Stephens, 2015). In

the case of CBT-based apps for anxiety, the answer

to the “who” question is users suffering from anxiety;

the answer to the “what” is functionalities that will

help with anxiety; the answer to the “why” is to help

people suffering from anxiety to deal with it; and the

answer to the “how” can be any method able to de-

liver the functionalities identiﬁed in the “what” ques-

tion. Looking for answers of these questions from

end-users is not enough to create an app able to help

users deal with anxiety, even if they suffer from it.

They should not be considered as experienced in the

ﬁeld of anxiety as they cannot provide a clear insight

on how to deal with it. Therefore, incorporating MHP

in mental health apps is necessary as they can provide

science- and evidence-based answers to the aforemen-

tioned questions. However, only half of the selected

apps involved MHP in their design. Inclusion of MHP

in the creation and design of apps for mental health,

is crucial to insure the safety of the end-user.

Many mental treatment approaches can be used

in a wrong way if not under supervision of a pro-

fessional. This is also the case of CBT, as it has

many disadvantages that should be acknowledged

(The Healthy CBT-Clinic, 2020), and in many cases

it works only under certain circumstances (Institute,

2020). MHP are knowledgeable of approaches used

for anxiety, like the CBT approach, and can present

methods to manage and treat anxiety, that can be

transformed to app functionalities, and can also pro-

vide directions on how to best implement those func-

tionalities in apps.

According to the U.S. Food and Drug Adminis-

tration (FDA), an app is considered of a “minimal

risk” to the user, if it helps users self-manage their

condition, provides tools to help users organize or

track their health information, or provide easy ac-

cess to information about a health condition or a

treatments, among others (FTC, 2016). Apps se-

lected in this study provide functionalities that fall un-

der the aforementioned characteristics, such as self-

assessment tests, guided relaxation audios, breathing

exercises, providing educational content, journaling

and mood tracking. This “minimal risk” can be miti-

gated by the involvement of MHP.

For an app to keep its health claims healthy

according to the Federal Trade Commission (FTC)

(Lesley Fair, 2015), it should ﬁrst respect this prin-

ciple: “Claims about serious medical conditions call

for serious science”. The perfect way to ensure that a

mental care app respects this principle is by involving

MHP in the co-design of m-health apps in general and

mental health apps in particular. This would insure

that all implemented treatment-related functionalities

are based on well comprehended and previously prac-

ticed science, that have proof of being effective on

previous patients.

There is also a lack of research evidence on the

efﬁcacy and effectiveness of health apps (Giota and

Kleftaras, 2014), including mental health apps, which

despite their potential effectiveness and ability to im-

prove treatment access, and improve the monitoring

and management of many mental health symptoms

and disorders, the majority of available ones still lack

On the Involvement of Mental Healthcare Professionals in the Co-design of Highly-rated Anxiety Apps

283

Table 1: Results.

ID App name Link Rating #Raters Latest

Update

Initial

release date

#Installs

A1 Youper - Emotional Health https://bit.ly/32AAnKq 4.7 46,031 22-May-20 27-Aug-15 1,000,000

A2 Wysa: stress, depression & anxiety ther-

apy chatbot

https://bit.ly/2Q3NAss 4.7 36,225 21-May-20 6-Oct-16 1,000,000

A3 Moodpath - Depression & Anxiety Test https://bit.ly/2X6FelC 4.6 23,980 15-Apr-20 1-Jun-17 1,000,000

A4 Sanvello (ex Paciﬁca) https://bit.ly/2rmJGAG 4.6 14,106 5-May-20 25-Jan-15 1,000,000

A5 InnerHour: Calm,Sleep,Depression &

Anxiety Therapy

https://bit.ly/2pNLOBn 4.5 4,109 9-May-20 22-Aug-17 500,000

A6 What’s Up? - A Mental Health App https://bit.ly/2Q2Hzwj 4.4 3,126 20-Apr-20 10-Mar-15 500,000

A7 BetterHelp: Online Counseling & Ther-

apy

https://bit.ly/32svl2A 4.3 7,392 15-Apr-20 17-Nov-14 500,000

A8 Stop Panic & Anxiety Self-Help https://bit.ly/2K5YaeS 4.7 2,353 15-Apr-20 21-Jan-12 100,000

A9 CBT Thought Record Diary https://bit.ly/2NyGHxH 4.7 671 22-May-20 28-Jun-14 100,000

A10 Woebot: Your Self-Care Expert https://bit.ly/33ySl1g 4.5 6,223 15-Apr-20 6-Mar-18 100,000

A11 Clear Fear shorturl.at/lsOUX 4.4 173 15-Apr-20 3-Dec-18 100,000

A12 Depression CBT Self-Help Guide https://bit.ly/36OIfvh 4.2 1,446 15-Apr-20 26-Feb-12 100,000

A13 feel better - Mood & CBT therapy to

manifest goals

shorturl.at/eowKP 4.6 539 15-Apr-20 24-Jul-17 50,000

A14 FearTools - Anxiety Aid shorturl.at/mnwY9 4.4 96 20-Apr-20 6-Dec-16 50,000

A15 UP! - Mood Tracker for Burnout and

Bipolar

shorturl.at/lFOQ6 4.3 1,859 30-Jul-19 50,000

A16 Moodﬁt - Tools & Insight to Shape Up

Your Mood

shorturl.at/rvHQR 4.6 280 2-May-20 19-Jan-17 10,000

A17 GG Relationship Doubt & Obsessions

(ROCD)

shorturl.at/cyF16 4.5 163 15-Apr-20 4-Jun-16 10,000

A18 OCD Daily Exercise by GG (GGOC) shorturl.at/joFIV 4.5 153 15-Apr-20 7-Sep-16 10,000

A19 Psychiatry Pro-Diagnosis, Info, Treat-

ment, CBT & DBT

shorturl.at/vwIV2 4.4 185 10-May-20 19-Mar-19 10,000

A20 Stress & Anxiety Companion https://bit.ly/2Vs9OXp 4.1 14 2-May-20 15-Oct-18 10,000

A21 Pocketcoach - Anxiety Helper https://bit.ly/2XmrLql 4.6 63 20-May-20 8-Aug-19 5,000

A22 De-StressMe: CBT Tools to Manage

Stress

shorturl.at/lsuPY 4.3 42 15-Apr-20 21-Jun-18 5,000

A23 Self-manage Depression: Daily exercise

(GGDE)

shorturl.at/czWZ2 4.3 33 11-May-20 24-Jul-18 1,000

Table 2: Mental health professionals involved.

ID Mental health professional involved

A1 Team of doctors and scientists led by Dr. Jose Hamilton (a psychiatrist)

A2 Advisors with a mental health background

A3 Experienced therapists and doctors.

A4 Psychologists

A5 Psychiatrists and therapists

A7 Counselors and therapists

A9 Licensed mental health professionals at Duke university

A10 Dr. Alison Darcy (a clinical research psychologist) and Dr. Athena Robinson (a psychologist and expert clinician).

A11 Developed by a clinician

A17, A18, A23 Dr. Guy Doron (IDC) (a clinical psychologist and researcher)

scientiﬁc evidence about their efﬁcacy (Donker et al.,

2013; Wang et al., 2018). The majority of studies in-

vestigating health apps were found to test basic mo-

bile features like text messaging, and only few as-

sessed the impact of the apps based on their outcome

(Fiordelli et al., 2013).

CBT-based mental care apps are an example of

that, as even though CBT is an effective approach

when used face to face (Hofmann et al., 2012), the

evidence on its impact when implemented in an app

environment is limited (Giota and Kleftaras, 2014),

especially over a long time periods of use (Rathbone

et al., 2017). Inclusion of MHP in the design as

well as in the evaluation can help solve this issue.

When this is the case, apps will be based on scientiﬁc,

proven mental care approaches since the ﬁrst stages of

their design, and their outcome regarding treatment

results can be properly investigated and tested based

on scientiﬁc evidence. An example of that, is the

selected app A3, which in its description, the devel-

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284

Figure 2: Number of installs and ratings of the selected apps.

Figure 3: Initial release years of selected apps. Acronym: Mental Healthcare Professionals (MHP).

opers speciﬁed the inclusion of researchers from the

ﬁelds of psychology and psychotherapy to conduct

clinical studies on the app. A recent study (Burchert

et al., 2019), compared the results of A3’s assess-

ment of mood dynamics with results from the Patient

Health Questionnaire (PHQ-9) depression screening,

Another recent study (Mulansky, 2020) analysed the

geodata of the A3’s users to determine its connection

to their state of mind.

After a careful analysis of the selected apps, we

found that 48% did not include MHP in their creation

process. If we project the aforementioned insights, we

can assume that many existing mental care apps were

not co-created with MHP. Such apps might jeopardize

the safety of end-users, and provide misguided infor-

mation or harmful practices. Results presented in Fig

2 also show that the involvement of MHP might in-

ﬂuence the number of installs of a CBT-based anxiety

app. The average of installs of apps that mention in

their description the involvement of MHP is 443,417

installs, while the average of installs of the apps that

do not is 80,909 installs. Having MHP involved in the

design of an app might increase its chance of instal-

lation by ﬁve times. This big difference shows that

involvement of MHP might increase the trust of the

users in the app, and encourages them to install the

app and use it. It should be noted that on average both

categories of apps were released 4 years ago as shown

in Fig. 3. Note that the A15’ initial release date was

not available.

This study might have some limitations such as:

(i) including paid apps in the selection might have al-

lowed us to identify additional ﬁndings. However, the

majority of Android apps (96.3% of Android apps),

according to recent statistics, are available freely in

app repositories (Clement, 2020); and (ii) analyzing

low-rated apps might have allowed us to identify ad-

ditional ﬁndings as well. However, we investigated

highly-rated apps to remove concerns about the us-

ability of the studied apps.

4 CONCLUSIONS

This study investigated the involvement of MHP in

the co-design of CBT-based apps for anxiety. A to-

tal of 23 Android highly-rated apps were selected and

analyzed. Contrarily to our hypothesis, not all in-

vestigated apps included input from MHP, as nearly

half of the selected apps did not report any involve-

On the Involvement of Mental Healthcare Professionals in the Co-design of Highly-rated Anxiety Apps

285

ment of MHP in their design or evaluation. A sig-

niﬁcant difference in numbers of installs in the se-

lected apps was identiﬁed. Results suggested that the

fact of mentioning the involvement of MPH in the

description of a CBT-based anxiety app, might im-

pact potential users trust, and increase its installation

chances by ﬁve times. This study further conﬁrms the

existing concerns of existence of non-evidence-based

apps, that are neither co-designed, nor evaluated in

collaboration with MHP, which might inﬂuence the

apps’ safety and effectiveness.

For future work, we intend to work with psychia-

trists and other MHP to co-create a connected health

application for anxiety treatment in UAE.

ACKNOWLEDGMENTS

This work is part of the Abu Dhabi Young Investiga-

tor Award (AYIA) 2019 (#AYIA19-001) awarded by

the Abu Dhabi Research and Development Authority

(ADRDA).

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