Identifying Sociodemographic Factors for a User Engaging Type 2

Diabetes Mellitus Mobile Self-management Application

Kuthethur Sneha Jagannath Das and Felix Janszen

Inpaqt Technology Solutions B.V., 16, Marconistraat, 3029 AK, Rotterdam, The Netherlands

Keywords: Type 2 Diabetes Mellitus, Mobile Health, User Engagement, Sociodemographic Factors, Behavior Change.

Abstract: Type 2 Diabetes Mellitus(T2DM) is a chronic condition affecting the elderly population across the globe.

Self-management from the patient’s side is a key factor for T2DM care. Growth in the information and

communication technology field has paved way for the rise of digital health interventions. Digital health

interventions (DHI) can support self-management behaviors in patients suffering from chronic conditions

through health coaching. Patient Engagement with DHI is crucial for the intervention to be effective on the

patient’s health. This paper discusses user engagement and focuses explicitly on identifying the

sociodemographic factors impacting user engagement with a mobile health intervention (mHealth) in T2DM

patients. The factors along with their interrelations have been identified through expert reviews, feedback

from T2DM patients and their family member through questionnaires and think aloud interview, and the

conduction of a literature study.

1 INTRODUCTION

Type 2 Diabetes Mellitus(T2DM) is a highly prevalent

chronic condition across the globe. By 2040, T2DM is

estimated to be prevalent in 642 million people

globally (den Braber et al., 2019). Prevalence of

T2DM is a risk factor for several comorbidities and

health complications such as obesity, cardiovascular

diseases, renal failure, and blindness to name a few,

and poses a burden on the healthcare system (Pardhan

et al., 2020; Stühmann et al., 2020; Sun et al., 2019).

Immense advancements in medical technology

have led to the growth of telemedicine. Telemedicine

is the crux of mHealth interventions, a subset of DHI

(Shan et al., 2019). Studies have shown that DHI

support the management of chronic conditions in a

home setting (Maresca et al., 2019). mHealth

implemented through smartphone applications (app)

and wearable can be personalized (Shan et al., 2019).

In T2DM management, the goal is to achieve and

maintain the blood glucose level (BGL) within the

optimal range (den Braber et al., 2019; Shan et al.,

2019). Pursuit of sufficient and regular physical

activity (PA), healthy diet, prescribed medication

(insulin doses) intake, sufficient sleep, stress

management and regular BGL monitoring are factors

integral to optimal T2DM management (den Braber et

al., 2019; Grandner et al., 2016; Shan et al., 2019;

Simon et al., 2014). These can be understood as

lifestyle factors (den Braber et al., 2019; Schoeppe et

al., 2016). Studies show that self-management is a

cornerstone for holistic T2DM management (Izahar et

al., 2017). Health coaching can support in facilitating

self-management (Gupta et al., 2018).

Health coaching involves targeting and improving

poor health behaviors such as lack of pursuit of PA,

smoking, and eating an unhealthy meal (Gupta et al.,

2018; Snaith et al., 2018). Previous studies reveal that

mHealth facilitates self-management of T2DM and is

effective in supporting the individual to maintain an

optimal BGL (Boyle., 2017; Kebede & Pischke, 2019;

Murray et al., 2016). Studies also suggest that an

engaging mHealth intervention is a prerequisite for

achieving the health effectiveness (Agarwal et al.,

2019; Yardley et al., 2016).

Despite this significant advantage of mHealth in

T2DM care, T2DM app usage in an individual’s daily

use scenario is not prevalent (Kebede & Pischke,

2019). Findings from literature show that lack of

thorough evidence in the areas of behavior change

models, less clinical focus addressed in the app

development, and minimal integration of T2DM care

functionalities in a single application (app) could be

some possible reasons (den Braber et al., 2019;

Helbostad et al., 2017; Yardley et al., 2016).

254

Das, K. and Janszen, F.

Identifying Sociodemographic Factors for a User Engaging Type 2 Diabetes Mellitus Mobile Self-management Application.

DOI: 10.5220/0011062800003188

In Proceedings of the 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2022), pages 254-260

ISBN: 978-989-758-566-1; ISSN: 2184-4984

Hence, our goal in this project is to develop an

engaging mHealth app that is science-based,

evidence-based, and artificial intelligence (AI) driven,

supporting T2DM patients to self-manage their

condition in a remote setting. This paper solely

focuses on addressing the question of what

sociodemographic factors contribute to developing a

user engaging mHealth app that would support T2DM

patients in maintaining their BGL within the target

range.

In the beginning of this project, during the

conduction of an expert stakeholder analysis, the

possibility of sociodemographic factors affecting the

user engagement with the app was addressed. Hence,

that was taken as one of the problem statements in the

pursuit of this project. To solve this, a thorough

literature study was conducted followed by interaction

with T2DM patients and caregivers through

questionnaires and think aloud interview.

2 BACKGROUND

Diabetes education is closely related to the self-

management of T2DM as it induces self-care

behaviors in the individual (Kebede & Pischke, 2019;

Weston et al., 2015). Diabetes education includes

equipping the patient with knowledge about T2DM,

complications of T2DM, and the patient’s progress in

T2DM management (Weston et al., 2015). Education

about the health condition and self-awareness about

the progress is an integral part of health coaching

process. And this is associated with positive

engagement with the DHI and thus effectiveness on

the individual’s health (Weston et al., 2015; Yardley

et al.,2016) Enabling the patient with relevant and

timely health information is an essential benefit seen

in mHealth app adoption (Shan et al., 2019).

One aspect of engagement is related to the user’s

interaction with the digital intervention and is defined

as the “quality of user’s experience with technology”

(O’Brien & Cairns, 2015; O'Brien & Toms, (2008).

To address this definition of engagement, some

aspects such as feedback, awareness, aesthetics,

attention, interactivity, and challenge are considered

in building an engaging technology (O’Brien &

Cairns, 2015; O'Brien & Toms, (2008).

Another aspect of engagement with digital health

interventions focuses on the patient’s engagement

with the process of achieving behavioral and

physiological change (Yardley et al., 2016). Here,

engagement with a DHI is considered similar to

engaging with face-to- face intervention (Yardley et

al., 2016).

3 METHODS

In this project, the CeHReS roadmap (

Van Velsen et

al., 2013)

is being adopted for developing this T2DM

mHealth app. The initial set of designs were explicitly

focused on the content design of the app. This has

been done by taking into account the various

attributes of health coaching. We will not be

discussing about the app design process further since

it lies outside the scope of this paper.

Figure 1: Outline of the steps taken in identifying the

sociodemographic factors affecting user engagement.

As shown in Figure 1, three steps were taken in

identifying the sociodemographic factors influencing

user engagement with the T2DM app. Expert

evaluation on the initial set of designs, literature study

and, questionnaire response by patient and family

caretaker are the three steps. These steps are

described below.

3.1 Expert Stakeholder Evaluation

The initial set of designs were created and as a part of

stakeholder evaluation, a qualitative evaluation with

a group of experts was conducted. In total, five

experts participated in this evaluation. The expert

panel consisted of an mHealth specialist, Artificial

Intelligence (AI) expert, knowledge in the area of

behaviour change, diabetes and pharmacology

specialist, software developer along with a regular

non diabetic fitness app user. To conduct this

evaluation, a short video explaining the core

functionalities of the content design was pre-recorded

and sent to the expert panel prior to the expert session.

This was done one week before the expert session.

Identifying Sociodemographic Factors for a User Engaging Type 2 Diabetes Mellitus Mobile Self-management Application

255

During the expert meet up, the questions related to

engagement aspect were posed and discussed. The

questions discussed are as follows:

1. Do you think the app is engaging to the user?

2. How is sustained engagement affected in

this?

3. What factors can be addressed to make the

app engaging in terms of long-term user

engagement?

3.2 Literature Study

Based on the feedback received in this expert

evaluation session, a decision to update the current

designs based on a revised literature study was taken.

For the literature study, scientific papers from JMIR

(open access journal) were found through the

combination of the following keywords: T2DM,

diabetes, user engagement, mHealth, eHealth,

telemedicine, self-management and social

demographics. This literature study was conducted in

December 2020.

3.3 T2DM Patient and Family

Caretaker Questionnaire

Based on the expert evaluation feedback and

conclusions of the literature study, a decision to

collect insights from the T2DM patients and their

family caretakers was taken. Here, T2DM patients

and family caretakers of T2DM patients were

recruited to participate in a short questionnaire

survey. Two different questionnaires were made. One

was for the T2DM patient and the other was for the

family caretaker. The purpose of the questionnaire

was to understand the interest of the patients and

family in the scope of the app with emphasis on the

role of T2DM care education in remote self-

management and the possible involvement of a

family member as a caregiver in T2DM management.

13 people filled the questionnaire. 4 of them were

patients and 9 of them were family members. In

addition, 1 family member did a think aloud session

for 20 minutes discussing about the designs. The

patients were recruited through acquittances of the

people conducting this research.

With the expert evaluation feedback, the content

analysis results of the literature study and the

questionnaires results along with the think aloud

session, the current designs were further optimized.

In this paper, as illustrated in Figure 1, we report the

findings explicitly focusing on the engagement

dependent on sociodemographic aspect for an optimal

T2DM management.

4 RESULTS

From the methods discussed in the previous section,

three sets of results are obtained. These are discussed

in this section.

4.1 Expert Evaluation

Through the expert evaluation, the scope of user

engagement with the mHealth app was elaborately

explored. All the experts reinforced the point of the

current set of designs being engaging and effective

for the user in T2DM self-management. However, a

strong recommendation was provided by all the

experts to look into the long-term or sustained

engagement aspect. The expert panel felt that factors

such as age, ethnicity, education status, health

literacy, and digital skills could affect user

engagement.

In order to address this, the experts suggested

exploring the possible role of sociodemographic

factors in adopting and engaging with mHealth

technology for successful T2DM self-management.

4.2 Literature Study

For the literature study, ten articles from JMIR were

selected. The ten articles selected focused on T2DM

management via mHealth and eHealth (web-based)

solutions and had at least one barrier listed which

focused on the lack of engagement aspect. The

articles selected are based on studies conducted on

T2DM management through ICT in diverse

geographic locations such as the USA, Canada,

Norway, China and India. In this literature study, ten

barriers affecting the engagement have been

identified. Figure 2 provides an outlook of the

sociodemographic factors identified in the literature

study implementation.

Five articles identified low health literacy as a

barrier affecting the user engagement (Alvarado et

al., 2017; Desveaux et al., 2018; Williams &

Schroeder, 2015; Zhang et al., 2019). When

compared to patients with high health literacy,

patients with low health literacy dropped out of

mHealth and eHealth studies (Alvarado et al., 2017;

Williams & Schroeder, 2015).

Five articles identified ethnicity of the patient as a

barrier in engaging with the developed eHealth and

mHealth solutions for T2DM management (in the

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256

context of this paper, ethnicity can be understood as a

sense of belonging to a particular cultural or social

group) (Huang et al., 2019; Mold et al., 2018;

Muralidharan et al., 2017; Tatara et al., 2019;

Williams & Schroeder, 2015, 2015).

Figure 2: List of barriers affecting T2DM care engagement

of the patient (with their frequency of occurrence).

Four articles identified that age of the patients

affect their engagement with the T2DM care solution.

Elderly people face difficulty in this aspect (Agarwal

et al., 2019; Huang et al., 2019; Peters et al., 2017;

Williams & Schroeder, 2015).

Four articles have identified language as a barrier

in engaging with the T2DM solution (Alvarado et al.,

2017; Mold et al., 2018; Tatara et al., 2019; Williams

& Schroeder, 2015). A study conducted in the U.S.A

identified Latino population residing in the U.S.A had

issues in adopting the eHealth solution as the solution

was in English (Williams & Schroeder, 2015).

Four articles have identified digital or technical

illiteracy as a barrier for a successful engagement

with the T2DM services (Alvarado et al., 2019;

Huang et al., 2019; Peters et al., 2017; Tatara et al.,

2019). T2DM patients with lower digital skills have

dropped out of investigative studies faster in

comparison to patients with higher digital skills.

Three articles have identified educational level as

a barrier in adopting T2DM digital interventions

(Alvarado et al., 2019; Tatara et al., 2019; Williams

& Schroeder, 2015). Educational level has affected

the self-management aspect of T2DM causing lower

engagement in low level educated groups (Alvarado

et al., 2019).

Three articles have identified income level as a

barrier in T2DM ICT-based care (Alvarado et al.,

2019; Mold et al., 2018; Peters et al., 2017). Other

factors include specific lack of knowledge of medical

terms (Mold et al., 2018), cultural awareness

(Alvarado et al., 2019) and place of residence of the

patient (Mold et al., 2018).

Belief in the benefit of the solution (Agarwal et

al., 2019; Desveaux et al., 2018; Huang et al., 2019),

referral of the solution by the clinician team (Agarwal

et al., 2019; Huang et al., 2019) and continuous

interaction between the clinician team and patient

(Agarwal et al., 2019) have also been identified as

barriers for engagement.

Figure 2 shows the list of ten barriers identified in

the ten articles during the implementation of the

literature study. In Figure 2, cultural awareness has

been combined with ethnicity, specific lack of

medical terminology knowledge has been combined

with health illiteracy and the barriers listed in relation

to the clinician and patient engagement have been

grouped under clinician presence.

4.3 Patient and Family Caretaker

Questionnaire

13 participants filled in the questionnaire survey. 4

participants were T2DM patients and 9 participants

were family caretakers of T2DM patients. All the 13

participants were of the Indian origin.

Among the T2DM patients, 3 men and 1 woman

filled in the questionnaire. 2 of the participants have

indicated their age group. One person belonged to the

age group of 50 to 60 and another between 60 to 70

years.

Among the family members who filled in the

questionnaire, two participants were Indians based

out of Germany and the Netherlands. 4 men and 5

women filled in the questionnaire. 3 people were less

than 30 years, one person belonged to the age group

of 30 to 40, 4 of them belonged to the age group of 50

to 60 and one person to the age of 60 to 70.

Out of the 4 T2DM patients, 3 have indicated that

they have good knowledge about T2DM care and 1

patient has indicated that they want to have T2DM

care knowledge. All 4 have indicated that they like

Identifying Sociodemographic Factors for a User Engaging Type 2 Diabetes Mellitus Mobile Self-management Application

257

their family members being involved in the care. Out

of 9 family caretakers, only 2 have indicated that they

have good knowledge about T2DM care, 4 gave a

neutral response and 3 have indicated they don’t have

any knowledge about T2DM care. 7 family caretakers

have indicated that they want to have T2DM care

knowledge. All 9 participants have indicated that they

like to be involved in their family member’s T2DM

care.

One female family member participated in the

think aloud session. She is from India and belonged

to the age group of 50 to 60 years. Her spouse has

T2DM. During the session, she reinforced the idea of

the app was good and needed in T2DM management.

Further, she provided insights into how the health

information can be conveyed better to a potential user

based on the current content design of the app.

5 DISCUSSION

From the feedback received in the expert panel

discussion for the initial set of T2DM mHealth app

designs, the literature study implementation and the

interaction with T2DM patients and family caretakers

through questionnaires and interview,

sociodemographic factors which influence the user

engagement were identified.

Some of the factors identified during the expert

panel discussion are concurrent to the factors

identified during the implementation of the literature

study. These were the factors of age, education level,

health illiteracy, and digital illiteracy.

From the results of the literature study, it can be

understood that the factors are related to each other.

For instance, the article by (Williams& Schroeder,

2015) identified health illiteracy, age, language,

ethnicity and education level as barriers to the user

engagement. The article by (Alvarado et al., 2017)

identified health illiteracy, language, digital literacy,

education level, and cultural awareness as factors of

barrier for the user engagement. Articles by (Tatara et

al., 2019; Williams& Schroeder, 2015) reveal that

immigrant populations who form the minority ethnic

groups and Hispanic population in the U.S.A. face the

concerns of health illiteracy.

From the expert panel discussion, it was realized

design in terms of aspects such as aesthetics, feedback

or challenge alone would not be sufficient in

engaging the user. From literature, it can be

understood that these aspects arise from the definition

of engagement that is inclined towards the quality of

the user experience with the digital intervention and

focus on the initial reaction of the user to the digital

intervention (O’Brien & Cairns, 2015; O'Brien &

Toms, (2008).

The panel discussion yielded a strong conclusion

that inclusion of sociodemographic elements and

clinician presence to the existing design which

already focused on the areas of aesthetics and

feedback would benefit the part of user engagement.

The findings from the literature study implemented

also concurs with this.

In the work of (Yardley et al.,2016), “engagement

is understood as a dynamic process which involves a

trigger, followed with an initial use by the patient,

which may further lead to a sustained engagement,

disengagement or maybe a shift to another

intervention”. Thus, it can be realized that for

engagement to be effective, it should satisfy the

criterion of engagement with technology and

engagement with the behavior change pursuit

(O’Brien & Cairns, 2015; Yardley et al.,2016).

From the previous sections, it can be understood

that self-management is crucial for successful T2DM

management and diabetes education is an important

part of self-management as it plays a role in inducing

self-care behaviors in the patient.

The article by (Yardley et al., 2016) emphasizes

that digital health interventions need to address the

target group of people with low health literacy and

include design solutions to alleviate health illiteracy.

Health literacy focuses on the aspects of applying

knowledge and the ability to access, understand and

apply health-related information.

Interaction with subjects is an inherent component

of CeHReS roadmap as it is based on human centred

design. In the expert session, the experts strongly

recommended to address countries in Asia and Africa

as it would give a global perspective in the project.

Hence, as an initial step, the patient interaction took

place with the Indian patients and family members.

Although the number of participants were less, the

feedback from the participants concurred with the

expert evaluation feedback and literature study. The

insights from the questionnaire response of T2DM

patients and family caretakers also indicate that

knowledge of T2DM care would support optimal

T2DM self-care. These responses concur with the

feedback of expert session and literature study.

From the conclusions of the expert session, the

conduction of literature study and, responses of

T2DM patients and family caretakers, we realize the

role of health literacy in T2DM management. Hence,

in this paper, we come to the conclusion of health

illiteracy about T2DM being the most crucial factor

among the list of sociodemographic factors

ICT4AWE 2022 - 8th International Conference on Information and Communication Technologies for Ageing Well and e-Health

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identified, which affects the user engagement with the

T2DM mHealth app intervention.

In the next phase of our project, we are optimizing

the initial set of designs by modelling the

sociodemographic factors into an Artificial

Intelligence model to drive the app content and

explicitly focus on addressing the T2DM education

aspect through chatbots and avatars (Das et al., 2019).

From the questionnaire, it was understood that family

caretaker also forms an important stakeholder group

and hence they would be included in the mHealth

intervention along with the physician team. The

designs would be developed into a functional

prototype and would be tested as a part of iterative

longitudinal studies with T2DM patients, their family

caretakers and clinician for aspects of usability,

sustained user engagement, and T2DM management

effectiveness.

6 CONCLUSIONS

The objective of this paper was to identify the

sociodemographic factors affecting user engagement

of a T2DM patient with an mHealth T2DM

intervention. Health illiteracy, digital literacy,

education level, age, ethnicity, language, place of

residence, income level, cultural awareness and

patient clinician interaction were found to be the

barriers for an effective user engagement with the

mHealth intervention.

Health illiteracy was identified as a crucial factor

in affecting the user engagement as it is closely linked

to diabetes education, an integral feature of self-

managing T2DM. These engagement barriers were

identified through an expert panel discussion,

followed with a literature study implementation and

questionnaire responses from T2DM patients and

family members.

ACKNOWLEDGEMENTS

We thank the participants of the expert session and

the T2DM patients and family caretakers who

interacted with us on the scope of this mHealth

intervention through questionnaire and think aloud

session.

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