A Study on mHealth Adherence for Bipolar Disorder: A Case Study with

the BraPolar2 Application

Abel Gonz

alez Mond

ejar

1 a

, Luiza Oliveira R

egnier

1 b

, Greis Francy M. Silva-Calpa

1 c

and Daniel C. Mograbi

2,3 d

Department of Informatics, Pontiﬁcal Catholic University of Rio de Janeiro, Rua Marqu

es de S

ao Vicente, 225, G

avea,

Rio de Janeiro, Brazil

Department of Psychology, Pontiﬁcal Catholic University of Rio de Janeiro, Rua Marqu

es de S

ao Vicente, 225, G

avea,

Rio de Janeiro, Brazil

Institute of Psychiatry, Psychology & Neuroscience, King’s College London, 16 De Crespigny Park, Camberwell, SE5 8AF,

London, U.K.

Keywords:

mHealth, Bipolar Disorder, Active Data, Passive Data, Patient Adherence.

Abstract:

Bipolar disorder (BD) is a mental illness that affects 40 million people worldwide. Fluctuations in mood,

activity, and self-awareness mark this condition. Studies using mHealth applications to monitor people with

BD have shown promising results in the early detection of these ﬂuctuations; however, they usually require

participants to complete daily tasks in the app, which causes them to abandon the study and compromises the

quality of the research. This paper explores the adherence to BraPolar2 mHealth through a set of development

strategies. To identify the aspects that lead patients with BD not to complete daily data in an mHealth appli-

cation and the factors that motivate them to use the application as a habit, we conducted qualitative research

with BraPolar2 mHealth. Nine people with BD participated in the study and used BraPolar2 for more than

3 months, answering a semi-structured interview. The results show that users can ﬁll in all the data quickly

and begin to pay more attention to their mental health daily. The paper contributes by demonstrating how a

simpliﬁed interface in mHealths, coupled with qualitative research, can lead to the participation of mHealth

applications for mental health follow-up, allowing an improved follow-up in next studies.

1 INTRODUCTION

Bipolar Disorder (BD) is a mental condition charac-

terized by extreme mood swings between emotional

highs, called manic episodes, and lows, known as de-

pressive episodes (Sajatovic et al., 2010). The term

bipolar reﬂects these two extremes: during a manic

episode, a patient experiences intense feelings of eu-

phoria, sleeplessness, racing thoughts, impulsive ac-

tions, and risky behaviours (Sajatovic et al., 2010). In

contrast, depressive episodes involve loss of interest

and pleasure in activities, feelings of hopelessness,

and low energy, making even the simplest mundane

tasks difﬁcult (de Figueiredo et al., 2022). Without

treatment, these mood swings become more frequent

and intense, complicating the patient’s ability to man-

https://orcid.org/0000-0001-7111-5444

https://orcid.org/009-008-8448-3527

https://orcid.org/0000-0001-8264-3808

https://orcid.org/0000-0002-4271-2984

age their routines. Although there are different types

of BD, all are deﬁned by mood swings; the differ-

ence lies in the frequency and intensity of these mood

changes (Tondo et al., 2022). This condition makes

managing daily social activities and functions such as

work, relationships, and self-care extremely difﬁcult

as patients struggle to maintain emotional balance.

The most common way to monitor and treat pa-

tients with BD is through medication and scheduled

appointments with healthcare providers. However,

the time gap between appointments allows for un-

monitored mood swings that may not be accurately

reported during the next visit (de Figueiredo et al.,

2022). Daily appointments are impractical, so a con-

venient solution is using mHealth applications to keep

track of patients with BD (Chan et al., 2021).

Although these m-health apps ensure consistency

and frequency in collecting data to support tracking

mood swings, these applications would be limited if

the user showed low adherence to the app. Adherence

Mondéjar, A. G., Régnier, L. O., Silva-Calpa, G. F. M. and Mograbi, D. C.

A Study on mHealth Adherence for Bipolar Disorder: A Case Study with the BraPolar2 Application.

DOI: 10.5220/0013308600003911

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 18th International Joint Conference on Biomedical Engineering Systems and Technologies (BIOSTEC 2025) - Volume 2: HEALTHINF, pages 813-820

ISBN: 978-989-758-731-3; ISSN: 2184-4305

813

to mHealth is deﬁned by how well the user follows

the app’s protocols, considering their frequency of use

and duration of time of use. In addition, mHealth apps

also offer beneﬁts such as lower costs due to more

spaced appointments and more reliable daily data col-

lection (Chan et al., 2021).

This article presents the BraPolar2 development

process (Mond

ejar et al., 2024), an application to

monitor people with BD. We discuss and evaluate

BraPolar2 adherence in nine people with bipolar dis-

order as the reasons why these BD patients show

higher or lower levels of adherence to the app, aban-

doning or discontinuing the use of the app in some

cases, despite knowing that it helps them collect

daily data about their mental state. This study an-

alyzes patient interaction with BraPolar2 and semi-

structured interviews with patients who used the ap-

plication for at least 3 months. Using the adapta-

tion of the mHealth Usability Questionnaire (MAUQ)

(Muro-Culebras et al., 2021), we focused on the pa-

tient’s motivations, reasons for daily use and factors

contributing to inconsistent use of the app.

This article is structured as follows. Section 2

presents related works, and Section 3 details the ad-

herence strategies, development and MAUQ presenta-

tion. Later, in Section 4, we present the methodology

and evaluation procedure with bipolar patients in an

ambulatory clinic. Finally, Section 5 describes the re-

sults and presents the discussion, limitations, future

work and conclusions in Section 6.

2 RELATED WORK

Developing mHealth apps for patients with mental

illness can be challenging depending on the type of

illness being treated and the illness-related factors

ohringer et al., 2013) and therefore requires spe-

ciﬁc design choices. mHealth applications are in-

tended to provide support for the outcome of men-

tal ill patients in many different ways, such as symp-

tom monitoring apps where the patient can report

their symptoms during the day, remote consultations,

medication management reminding the patient to take

their medication, and cognitive behavioral therapy

(CBT) tools that allow the patient to use some alter-

natives to help manage conditions such as anxiety and

depression (Batra et al., 2017). Recent research shows

that the main factors that inﬂuence users to ﬁrst adopt

mHealth apps are social inﬂuences, such as internet

ﬁndings, comments, and reviews on apps (Woldey-

ohannes and Ngwenyama, 2017). However, adher-

ence level would depend on the type of mHealth app

being used, the friendly interface, and the develop-

ment of a habit during the time period of use (Wold-

eyohannes and Ngwenyama, 2017).

Knowing that BD is characterized by unstable

moods that vary from depressive states to euphoric

states, it is interesting both for the patient and their

doctor that these mood swings remain trackable and

under constant observation (de Figueiredo et al.,

2022), mHealth applications (Mond

ejar et al., 2019)

(Mond

ejar et al., 2020) turn daily mood reports into

reality, requiring the patient to ﬁll in only a simple

questionnaire on his phone.

Furthermore, despite the heterogeneous mHealth

apps available for download nowadays (Batra et al.,

2017), these applications remain rarely implemented

in treatments (Patoz et al., 2021). After download-

ing, the user quickly abandons them (Baumel et al.,

2019), further strengthening the need for more studies

on lack of adherence when it comes to adherence of

patients with bipolar disorder to mHealth apps. These

studies are relevant because the mood swings make

BD a unique case among mental illnesses, as these

swings can speciﬁcally affect adherence levels when

it comes to treatment (Sajatovic et al., 2010) and will

be dicussed in the next section our proposal.

3 BraPolar2 AND ADHERENCE

STRATEGIES

Despite the ﬁndings in current literature regarding ad-

herence to mHealth, in this section we present four

adherence strategies developed to reduce the lack of

adherence to mHealth. Later, we develop a new ver-

sion of BraPolar2 and present the evaluation test to be

applied.

3.1 Adherence Strategies

Non-adherence to mHealth applications to monitor

people with bipolar disorder can lead to incorrect di-

agnoses by specialists (Jakob et al., 2022) (Siegel-

Ramsay et al., 2023). With this new version, we

aim that BraPolar2 (Mond

ejar et al., 2024) were to

be less intrusive in the day-to-day collection of ac-

tive user data, following this background approach of

collecting subjective information, we could get valu-

able information that users could forget about on a

speciﬁc day when asked in consults or feel uncom-

fortable (Siegel-Ramsay et al., 2023). In this line, as

adherence to mHealth is a challenge mentioned in the

literature (Patoz et al., 2021) (Averous et al., 2018),

we propose that the new version of BraPolar (BraPo-

lar2) should address the following points:

HEALTHINF 2025 - 18th International Conference on Health Informatics

814

1. Simpliﬁed user interface (UI).

2. Regular feedback loops and progress tracking.

3. Lower power consumption for extended battery.

4. Ofﬂine functionality for no-internet areas.

With those four considerations, we developed a

new version of mHealth supported by psychiatrists

and psychologists from the Institute of Psychiatry

of the Federal University of Rio de Janeiro (IPUB).

This psychiatric institution maintains clinical research

in psychoanalysis. The next subsection details the

BraPolar2 development process and how we adapt

the four-adherence proposal to this new version of

mHealth.

3.2 BraPolar2 mHealth Development

BraPolar2 is a mHealth that captures active and

passive data from bipolar patients. Although ac-

tive data requires conscientious data into patients’

mHealth, passive data is collected using smartphone

sensors. The detailed development process of this

mHealth was described by Mond

ejar et al. (Mond

ejar

et al., 2024), considering previous work experience

(Mond

ejar et al., 2019) (Mond

ejar et al., 2020) and

adherence strategies described above.

Summarizing the BraPolar2 development process,

we could highlight that psychiatrists and psycholo-

gists participated in all stages of the Software De-

velopment Life Cycle (SDLC) (Agarwal et al., 2023)

deﬁning the main features or requirements to be col-

lected with BraPolar2 such as mood, mood intensity,

energy level, sleep and sleep quality, medication and

menstrual cycle and the sequence of interfaces with

which patients interacted during the investigation re-

garding the request of medical personnel.

Once the application was developed, we collected

the digital phenotype in BD patients. Meanwhile, as

adherence in mHealth is of considerable relevance for

collecting digital phenotype, we investigated how to

evaluate the adhesion and acceptance to the applica-

tion. In this way, we proceed with an mHealth app us-

ability questionnaire (MAUQ) adaptation into a semi-

structured interview, as detailed above.

3.3 MAUQ

When exploring adherence to apps, one way to gather

material for evaluating the factors that inﬂuence the

degree of adherence is by applying a usability ques-

tionnaire. This tool is used to evaluate the user experi-

ence when using an application. These questionnaires

measure aspects of the application’s usability, such as

ease of use, utility, and user satisfaction, so that the re-

sponses obtained help developers identify the applica-

tion’s strengths and weaknesses that can be improved

(Zhou et al., 2019).

To identify the aspects that cause patients with

bipolar disorder not to ﬁll in the data in a mHealth

application and the factors that motivate them to use

the application as a habit, we conducted qualitative re-

search on the use of mHealth BraPolar2 supported by

an adaptation of the mHealth Usability Questionnaire

(MAUQ) (Muro-Culebras et al., 2021). These ques-

tionnaires aim to measure different aspects of the us-

ability, satisfaction, and acceptance of mHealth apps

among users and healthcare professionals. In addi-

tion, it is widely used in the ﬁeld of study by other au-

thors (Manzano-Monfort et al., 2023) (Mustafa et al.,

2021) (Hajesmaeel-Gohari et al., 2022) who adapt to

their native language, then we proceed to adapt it to

our context, described below.

In the next section, we present the methodology,

highlighting the steps taken to evaluate adherence in

this study.

4 EVALUATION

In this section, we present and adapt the MAUQ ques-

tionnaire into a semi-structured interview and ethical

considerations. Finally, we comment on the data col-

lection procedure when the interview was conducted

with nine bipolar patients.

4.1 MAUQ Adaptation Interview

Although MAUQ is designed primarily as a self-

administered questionnaire, it can also be adapted for

interviews to gather more in-depth qualitative insights

into user interactions with mHealth applications, con-

sidering that long questionnaires can potentially lead

to respondent fatigue, impacting the quality of the col-

lected data (Glise et al., 2020). Consequently, we

adapt MAUQ for BraPolar2 to determine whether pa-

tients adhere to the app through an interview script.

This adaptation study matches the MAUQ model,

as it is split into four subscales focused on ease of

use, interface satisfaction and utility, resulting in more

reliable responses from the interviewed users (Zhou

et al., 2019). To adapt the script to make it fully under-

standable for the participants (Brazilian patients with

BD), we follow the following steps:

1. Translation to Portuguese MAUQ questionnaire.

2. Adapt him to conduct a semi-structured interview.

3. Validate it with psychiatrists and psychologists.

A Study on mHealth Adherence for Bipolar Disorder: A Case Study with the BraPolar2 Application

815

As conducting an interview can be challenging,

we obtain a questionnaire to assess adherence in a

semi-structured interview, avoiding closed questions

and intending to be an open-ended question that pro-

motes discussion and leads to a conversational part-

nership (Lazar et al., 2017) (Grande et al., 2019)

(Grau-Corral et al., 2020). As part of the preparation,

we applied a pilot interview test with six specialists

(two psychologists and four psychiatrists) to reﬁne the

questions for the patients.

Once we have concluded that this phase is over,

we intend to know the easy and frequency of use, mo-

tivation, satisfaction with interface, utility, feelings

towards collected passive data and general opinion.

Then, with the translated MAUQ model, an adapta-

tion was made so that the questionnaire could be ap-

plied to assess the usability of the BraPolar2 app.

4.2 Ethical Considerations

Ethical considerations are highly relevant in mHealth

when collecting people’s information. As mHealth

technologies raise unique risks to user privacy and

conﬁdentiality, often embedded in lengthy and com-

plex user agreements (Gelinas et al., 2023). In this

line, we care about the Brazilian legal base, data pro-

tection laws, rights over users’ data, anonymity, and

the security process of collected information. For

all interviews conducted, patients signed an informed

consent form (ICF) stating that they agreed to record

their voices and would be analyzed to publish scien-

tiﬁc research.

4.3 Participants

We met with psychologists and psychiatrists to de-

ﬁne inclusion and exclusion criteria to recruit patients

with BD. As a result, we included people diagnosed

with BD between 18 and 60 years old. We excluded

patients who were pregnant, had a lack of knowl-

edge of the Portuguese language, who could not learn

the technical details of using a smartphone, and who

were seriously ill or also diagnosed with schizophre-

nia, schizoaffective disorder or delusional. Regarding

the quantity and demographic characteristics of the

participants, nine (seven women and two men) aged

21 to 48 years were enrolled. They used BraPolar2 for

at least 3 months from the beginning of the research.

The participants were labeled from P1 to P22.

We intend to reach those participants who decided to

abandon the research (P1, P6, P7, P9, P10, P14, P17,

P19, P20, P22) too; however, it was not possible due

to their free decision to stop the research. Further-

more, we focus on nine people with bipolar disorder

who participated in the study and used BraPolar2 for

at least three months from the beginning of our re-

search. To be as less intrusive as possible, the inter-

view occurred during one of their regular consulta-

tions while waiting for their medical appointment in

IPUB Institute. First, we invited patients to partici-

pate in the research and proceeded to sign the ICF;

neither one refused to participate or record their voice

and was invited to a consultation room where the

questionnaires were applied, recorded and analyzed

by the researchers later.

The following section presents the main user ad-

herence results using the MAUQ interview collection

method.

4.4 Data Collection Procedure

The interviews were conducted at IPUB, where the

participants were already waiting to be seen by their

psychiatrists. The interviewers sat beside the partici-

pants, reading out loud the MAUQ adapted script and

listened to the participants’ answers. Due to the place

being usually crowded and limited in space, the inter-

view had to be interrupted because the patients were

called during it, resulting in the data being split into

two different audio ﬁles. The interviews lasted an av-

erage of 15 minutes in total, with the longest lasting

21 minutes; a total of 9 interviews were conducted, all

of which were ﬁrst recorded using the interviewer’s

phone voice recorder app and later transcribed, facili-

tating the analysis of the collected data.

Once the interviews were complete and properly

transcribed, many sentences were disregarded for the

ﬁnal analysis as they were irrelevant to the study.

Such parts included sentences spoken by third parties

not participating in the interview or segments where

the participant or interviewer strayed from the inter-

view topic. Once this ﬁltering was performed, the

transcription was organized by the topics of each set

of questions asked.

In the next section, we present the results with

BraPolar2 on active data and qualitative research from

MAUQ.

5 RESULTS

In this section, we describe the main results of the

research on the adherence of the user to BraPolar2 and

the main ﬁndings. First, we describe the main results

of the investigation regarding the user’s adhesion to

the proposed solution and the main ﬁndings.

The interviews with the modiﬁed version of

MAUQ were conducted at different times for each

HEALTHINF 2025 - 18th International Conference on Health Informatics

816

participant. In addition, we include their current state

on the day of the interview (manic, hypomanic, eu-

thymic, or depressed) deﬁned by their therapists, con-

sidering that patients with bipolar disorder can ex-

hibit varying levels of understanding and insight into

research participation based on their current mental

state (Misra et al., 2008) and the total interview time

in mm:ss (TT), summarized in Table 1 and is com-

mented on in detail in the discussion subsection (5.1).

Table 1: Patient state in interview day.

ID Date Mental

State

P2 04/06 Manic 10:38

P3 04/06 Hypomania 16:36

P5 21/05 Depressed 14:15

P8 21/05 Euthimia 21:49

P11 07/05 Depression 18:24

P15 28/05 Depression 14:53

P16 14/05 Euthimia 11:58

P18 04/06 Euthimia 08:58

P21 21/05 Euthimia 21:44

Avg

time

- - 15:28

Although we have continuous follow-up and pa-

tient recruitment, some participants decided not to

continue (P1, P6, P7, P9, P10, P13, P14, P17, P19,

P20 and P22); we observed that they were not in-

terested and left to complete the daily questionnaire

or did not return to IPUB on the scheduled date and

summarized the reason for the abandonment of the

study. P1, P6, P17 and P22 withdrew immediately af-

ter their ﬁrst consultation. P7 and P10 faced technical

or compatibility issues with the app, and P9-10 cited

personal or workload constraints to continue, and P13

P14 presented more complex mental health. Finally,

P19 and P20 transitioned to private consultation.

In the next section, we discuss the feedback from

those participants who completed the minimal assess-

ment time of three months.

5.1 Discussion

Interview analysis may be challenging (Lazar et al.,

2017) (Barbosa et al., 2021). Taking into account

the notes and prescription of the audios mentioned in

the interview, we analyze each prescription, split into

categories (Lazar et al., 2017): ease and frequency

of use, motivation, satisfaction, utility, and an open

question called general user opinion.

Ease of Use. The participants considered the ap-

plication practical and easy to use, with some ini-

tial challenges overcome with practice. First, P2 de-

scribed the application as practical and easy to use,

quickly overcoming the initial difﬁculties. P5 found

the application very easy to use, highlighting the

smooth navigation between screens and the ability to

enter the necessary information without problems. P8

found it difﬁcult to view the history of his entries,

which negatively impacted his motivation for contin-

ued use and the lack of reminders. P11 mentioned

that the restricted time to enter the data was a signif-

icant problem, resulting in the loss of records. Fur-

thermore, navigation, although generally consistent,

presented some glitches. P15 found using the ap-

plication intuitive, with clear questions and objective

markings and did not face signiﬁcant difﬁculties in

navigation. P16 considered the application easy to

use, mentioning that alarms and reminders were not

uncomfortable, although he occasionally forgot to re-

spond due to routine. P18 also found the application

easy and intuitive but noticed that the answers were

reset when returning to a previous page, which was

an issue solved later.

Frequency of Use. Regarding the frequency of use,

participants showed variations in the frequency of us-

ing the application, inﬂuenced by different factors. P2

used the application daily, feeling satisﬁed and with

a sense of mission accomplished after ﬁlling in the

daily data. P5 highlighted that the lack of availabil-

ity at certain times affected their frequency of use,

emphasizing the importance of having more ﬂexible

schedules to facilitate continuous use. P8 mentioned

that the absence of reminders negatively affected her

frequency of use, indicating that she would have used

the application more regularly if she had been notiﬁed

at speciﬁc times. P11 used the application daily, ex-

cept when he forgot or missed the time allowed for

data entry, considering this restriction a signiﬁcant

impediment to continued use. P15 used the app al-

most daily but occasionally forgot, especially when

he was away from home or feeling ill. He felt frus-

trated when he could not ﬁll in the data after midnight

due to the impossibility of retroactive entry. P16 used

the application daily but sometimes forgot to ﬁll in the

data, especially at night, feeling bad when he could

not complete the entries for several days. P18 used

the application daily, except on some days when she

forgot, usually due to her menstrual routine, feeling

frustrated when she failed to ﬁll in the data.

Motivation. The participants presented different

motivations for using the application, often related

A Study on mHealth Adherence for Bipolar Disorder: A Case Study with the BraPolar2 Application

817

to their daily routines and personal needs. P2 pre-

ferred to ﬁll out the information at night, as this co-

incided with when she took her medication, helping

her to remember this important task. P5 felt that the

app helped record her mental state, providing self-

awareness of her mood and sleep. The absence of a

visual history impacted P8’s motivation as she would

like to see her progress over time, especially concern-

ing personal aspects such as menstruation. P11 did

not directly discuss her motivation, but her regular

use suggests that she was committed to the process

despite the app’s limitations. P15 preferred to use the

application at night, after completing his daily activ-

ities and taking medication, considering ﬁlling in the

data as a diary that provided a positive feeling of con-

trol over his data. P16 also preferred to ﬁll in the data

at night, but suggested that answering in the morning

could be more accurate, especially for questions about

sleep and medication. P18 preferred to complete the

data in the evening, to ensure that all changes in mood

throughout the day were captured.

Satisfaction of Use. The participants presented dif-

ferent opinions on the application interface, highlight-

ing positive aspects and suggesting improvements. P2

liked the interface of the application, thought the in-

formation was well organized, and felt comfortable

using it in social environments, considering the time

spent using it as appropriate and expressing general

satisfaction with the application, stating that he would

use it again. P5 described the interface as organized

and easy to use, as well as comfortable in social set-

tings. Considering that the usage time is adequate, it

generally takes around ﬁve minutes to complete the

entries. P8 found the interface neutral and mentioned

that the information was well organized, but felt a lack

of adequate notiﬁcations and feedback on information

entered, feeling comfortable using the application in

social environments, but not satisﬁed with the current

version, highlighting the need for improvements to in-

crease usefulness. P11 described the interface as ba-

sic and normal, with well-organized and intuitive in-

formation, feeling comfortable using the application

in social environments, but preferring to use it before

bed. P15 considered the application interface simple

but suggested improvements to align with more mod-

ern designs, including accessible graphics and results

for users. P16 considered the application interface

simple and well organized, comfortable using the ap-

plication in social settings, and found the time spent

adequate. P18 liked the app’s interface, found the in-

formation well organized, felt comfortable using the

app in social settings, and found the time spent appro-

priate.

Utility. Participants expressed different perceptions

about the app’s usefulness for their health and well-

being. P2 found the app useful for remembering to

take her medication and managing her bipolar disor-

der, believing that the app had all the necessary fea-

tures. P5 considered the application useful for under-

standing and managing his mental state, but suggested

improvements such as greater schedule ﬂexibility (in-

sert the information at any moment of day). How-

ever, P8, did not ﬁnd the application useful due to the

lack of access to recorded information and the lack of

feedback on his daily entries, which diminished his

perception of usefulness. P11 also did not ﬁnd the app

particularly useful for monitoring her mood, citing the

lack of transparency about where her data go and the

lack of practical use in everyday life, highlighting the

need for more transparency and features in future ver-

sions. P15 believed in the app’s usefulness for mental

health, especially if used in conjunction with a psychi-

atrist or psychologist, suggesting the presentation of

graphical results to help users better understand their

mood ﬂuctuations. P16 found the application use-

ful, especially for remembering medications, suggest-

ing the inclusion of a ﬁeld for personal observations

to better contextualize the data collected. P18 also

found the app useful for keeping track of her mental

state, but would like access to visual feedback, such

as graphs, to better understand her mood trends.

General User Opinion. The participants presented

valuable suggestions to improve the usability and

effectiveness of the application, with an emphasis on

ﬂexibility and data presentation. P2 highlighted the

importance of the application in improving your day

and positively incorporating it into your daily life.

P5 suggested greater ﬂexibility in the times to ﬁll in

the information to facilitate the continuous use of

the application. P8 recommended leaving the ﬁeld

of emotions open without limiting it to predeﬁned

options and eliminating the time limit to ﬁll out the

information, which would increase the ﬂexibility and

usefulness of the application. P11 did not directly

mention feelings about passive data collection. Still,

it highlighted the need for greater transparency,

suggesting clearer communication about collecting

and using these data could improve their satisfaction.

P15 emphasized the need for improvements to the

interface and presentation of the results, suggesting

that these changes would increase the satisfaction and

effectiveness of the application. Both P16 and P18

suggested the inclusion of graphs and analyses of the

collected data, which would help better understand

trends and variations in mood over time. P18 also

mentioned that allowing the correction of the answers

HEALTHINF 2025 - 18th International Conference on Health Informatics

818

without losing previous data would improve usability

and overall satisfaction with the application.

In summary, we point out two main reasons peo-

ple abandon ongoing research: personal (un)interest

and lack of commitment. As research participation

is voluntary and personal interest can vary, we were

interested in gaining information about those partic-

ipants who decided to continue with research and

their experience with the BraPolar2 application. Con-

sequently, we apply a qualitative evaluation through

an adaptation interview of MAUQ. At this point, we

could consider the diverse circumstances of a lack of

acceptance of the research described next.

5.2 Limitations of the Study and Areas

for Future Research

The ﬁrst methodology option considered for collect-

ing data for this study was a Google Forms ques-

tionnaire style. However, the number of participants

turned out to be too low for such a form to guarantee

both comprehensive and accurate results. The solu-

tion was to conduct oral interviews, allowing partic-

ipants to elaborate further while answering interview

questions.

Several challenges found during the interviews

were related to the patient’s state during the inter-

views, which was the ability of each patient to re-

spond to the questionnaire in a coherent way. When it

comes to BD, some patients could be found either on a

extreme manic state or depressive state, affecting their

capacity to maintain focus or interest on some of the

questions asked. One interesting case to report was

P3, who had returned after months without coming to

the IPUB institute and talked a lot about personal mat-

ters and less about the questions made during the in-

terview itself. She got dispersed a lot of times and we,

as the interviewers, struggled to keep the interview on

track. Although there were some other patients like

P3, there were also some who were less communica-

tive, giving short kinds of answers and not elaborating

much during the conversation, In contrast to P8 who

talked for 21 minutes while the average interview time

was around 15 minutes.

6 CONCLUSION

This study presents the relevance of BraPolar2

mHealth for an enhanced management of bipolar dis-

order, applying a set of strategies to improve the ad-

herence and tested with nine bipolar disorder patients.

As a result, the app was well-received for its rela-

tive ease of use and utility. However, improvements

in user feedback to enable more ﬂexible data en-

try functionality, visual progress tracking, and inter-

face design can help increase satisfaction and engage-

ment with the app. One signiﬁcant advantage also is

awareness of emotions and help in the management

of bipolar disorder, which makes this application use-

ful. As mHealth continues to evolve, more studies

with a longer collection time and gamiﬁcation tech-

niques can be developed to improve adherence in pa-

tients with bipolar disorder and mHealth, improving

patient outcomes and quality of life.

ACKNOWLEDGEMENTS

This study was ﬁnanced in part by the Coordenac¸

de Aperfeic¸oamento de Pessoal de N

ıvel Superior -

Brasil (CAPES) - Finance Code 001.

REFERENCES

Agarwal, A., Agarwal, A., Verma, D. K., Tiwari, D., and

Pandey, R. (2023). A review on software develop-

ment life cycle. International Journal of Scientiﬁc Re-

search in Computer Science, Engineering and Infor-

mation Technology, pages 384–388.

Averous, P., Charbonnier, E., Lagouanelle-Simeoni, M. C.,

Prosperi, A., and Dany, L. (2018). Illness perceptions

and adherence in bipolar disorder: An exploratory

study. Comprehensive Psychiatry, 80:109–115.

Barbosa, S. D. J., Silva, B. d., Silveira, M. S., Gasparini,

I., Darin, T., and Barbosa, G. D. J. (2021). Interac¸

humano-computador e experi

encia do usuario. Auto

publicac¸

ao.

Batra, S., Baker, R., Wang, T., Forma, F., DiBiasi, F., and

Peters-Strickland, T. (2017). Digital health technol-

ogy for use in patients with serious mental illness: a

systematic review of the literature. Medical Devices:

Evidence and Research, Volume 10:237–251.

Baumel, A., Muench, F., Edan, S., and Kane, J. M. (2019).

Objective user engagement with mental health apps:

Systematic search and panel-based usage analysis.

Journal of Medical Internet Research, 21:e14567.

Chan, E. C., Sun, Y., Aitchison, K. J., and Sivapalan, S.

(2021). Mobile app–based self-report questionnaires

for the assessment and monitoring of bipolar disor-

der: Systematic review. JMIR Formative Research,

5:e13770.

de Figueiredo, B. Q., da Silva, T. M., de Almeida Franc¸a,

L., de Sousa, J. M., Boavista, R. T. T. M., and Borges,

Y. J. (2022). Transtorno bipolar: desaﬁos etiol

ogicos,

ınicos e terap

euticos. Research, Society and Devel-

opment, 11:e120111436224.

A Study on mHealth Adherence for Bipolar Disorder: A Case Study with the BraPolar2 Application

819

Gelinas, L., Morrell, W., and Bierer, B. E. (2023). Terms

and conditions apply: an ethical analysis of mobile

health user agreements in research. Journal of Law

and the Biosciences, 10.

Glise, K., Wiegner, L., and Jonsdottir, I. H. (2020).

Long-term follow-up of residual symptoms in patients

treated for stress-related exhaustion. BMC Psychol-

ogy, 8:26.

Grande, S. W., Longacre, M. R., Palmblad, K., Montan,

M. V., Berquist, R. P., Hager, A., and Kotzbauer,

G. (2019). Empowering young people living with

juvenile idiopathic arthritis to better communicate

with families and care teams: Content analysis of

semistructured interviews. Jmir mhealth and uhealth.

Grau-Corral, I., Jans

a, M., Gascon, P., Lozano-Rub

ı, R.,

Pantoja, P. E., Roca, D., Miguens, V. A., Hidalgo-

Mazzei, D., and Escarrabill, J. (2020). Mobile health

projects in a high-complexity reference hospital: Case

study. Jmir mhealth and uhealth.

Hajesmaeel-Gohari, S., Khordastan, F., Fatehi, F.,

Samzadeh, H., and Bahaadinbeigy, K. (2022). The

most used questionnaires for evaluating satisfaction,

usability, acceptance, and quality outcomes of mobile

health. BMC Medical Informatics and Decision Mak-

ing, 22:22.

Jakob, R., Harperink, S., Rudolf, A. M., Fleisch, E.,

Haug, S., Mair, J. L., Salamanca-Sanabria, A., and

Kowatsch, T. (2022). Factors inﬂuencing adherence to

mhealth apps for prevention or management of non-

communicable diseases: Systematic review. Journal

of Medical Internet Research, 24:e35371.

Lazar, J., Feng, J., and Hochheiser, H. (2017). Research

Methods in Human-Computer Interaction. Elsevier

Science.

Manzano-Monfort, G., Paluzie, G., D

ıaz-Geg

undez, M.,

and Chabrera, C. (2023). Usability of a mobile appli-

cation for health professionals in home care services:

a user-centered approach. Scientiﬁc Reports, 13:2607.

Misra, S., Socherman, R., Park, B. S., Hauser, P., and

Ganzini, L. (2008). Inﬂuence of mood state on ca-

pacity to consent to research in patients with bipolar

disorder. Bipolar Disorders, 10:303–309.

Mond

ejar, A. G., Silva-Calpa, G. F. M., Barbosa Raposo,

A., and Mograbi, D. C. (2020). An m-health appli-

cation for remote monitoring of people with bipolar

disorder through digital phenotyping and smartphone

dependency. Proceedings - IEEE Symposium on

Computer-Based Medical Systems, 2020-July:388–

391.

Mond

ejar, A. G., Silva-Calpa, G. F. M., Raposo, A. B., and

Mograbi, D. C. (2019). BraPolar: an m-health ap-

plication for remote monitoring of people with bipo-

lar disorder. In 2019 IEEE 7th International Confer-

ence on Serious Games and Applications for Health

(SeGAH), pages 1–8. IEEE.

Mond

ejar, A. G., Silva-Calpa, G. F. M., Raposo, A. B., and

Mograbi, D. C. (2024). Redesign of an m-health ap-

plication for individuals with bipolar disorder: A strat-

egy for user adherence and effective data collection. In

2024 IEEE 12th International Conference on Serious

Games and Applications for Health (SeGAH), pages

1–9.

Muro-Culebras, A., Escriche-Escuder, A., Martin-Martin,

J., Rold

an-Jim

enez, C., De-Torres, I., Ruiz-Mu

noz,

M., Gonzalez-Sanchez, M., Mayoral-Cleries, F., Bir

A., Tang, W., Nikolova, B., Salvatore, A., and Cuesta-

Vargas, A. I. (2021). Tools for evaluating the content,

efﬁcacy, and usability of mobile health apps according

to the consensus-based standards for the selection of

health measurement instruments: Systematic review.

JMIR mHealth and uHealth, 9:e15433.

Mustafa, N., Saﬁi, N. S., Jaffar, A., Sani, N. S., Mohamad,

M. I., Rahman, A. H. A., and Sidik, S. M. (2021).

Malay version of the mhealth app usability question-

naire (m-mauq): Translation, adaptation, and valida-

tion study. JMIR mHealth and uHealth, 9:e24457.

Patoz, M.-C., Hidalgo-Mazzei, D., Pereira, B., Blanc,

O., de Chazeron, I., Murru, A., Verdolini, N., Pac-

chiarotti, I., Vieta, E., Llorca, P.-M., and Samalin, L.

(2021). Patients’ adherence to smartphone apps in the

management of bipolar disorder: a systematic review.

International Journal of Bipolar Disorders, 9:19.

Sajatovic, M., Velligan, D. I., Weiden, P. J., Valenstein,

M. A., and Ogedegbe, G. (2010). Measurement of

psychiatric treatment adherence. Journal of Psycho-

somatic Research, 69:591–599.

Siegel-Ramsay, J. E., Sharp, S. J., Ulack, C. J., Chiang,

K. S., di Scalea, T. L., O’Hara, S., Carberry, K.,

Strakowski, S. M., Suarez, J., Teisberg, E., Wallace,

S., and Almeida, J. R. C. (2023). Experiences that

matter in bipolar disorder: a qualitative study using

the capability, comfort and calm framework. Interna-

tional Journal of Bipolar Disorders, 11:13.

Tondo, L., Miola, A., Pinna, M., Contu, M., and

Baldessarini, R. J. (2022). Differences between bipo-

lar disorder types 1 and 2 support the dsm two-

syndrome concept. International Journal of Bipolar

Disorders.

ohringer, P. A., Barroilhet, S. A., Amerio, A., Reale,

M. L., Alvear, K., Vergne, D., and Ghaemi, S. N.

(2013). Cognitive impairment in bipolar disorder and

schizophrenia: A systematic review. Frontiers in Psy-

chiatry, 4.

Woldeyohannes, H. O. and Ngwenyama, O. K. (2017).

Factors inﬂuencing acceptance and continued use of

mhealth apps. In Nah, F. F.-H. and Tan, C.-H., editors,

HCI in Business, Government and Organizations. In-

teracting with Information Systems, pages 239–256,

Cham. Springer International Publishing.

Zhou, L., Bao, J., Setiawan, I. M. A., Saptono, A., and Par-

manto, B. (2019). The mhealth app usability ques-

tionnaire (mauq): Development and validation study.

JMIR mHealth and uHealth, 7:e11500.

HEALTHINF 2025 - 18th International Conference on Health Informatics

820