Understanding the behavioral intention and use of digital health applications: Insights from individuals in a vulnerable position

In an increasingly digitalized society, technology plays a growing role in
promoting (public) health, preventing diseases, and supporting medical
treatment. Digital health applications (DHAs) are examples of such technology.
DHAs are mobile or web-based communication applications that support,
deliver, and promote care in health and health-related fields. DHAs empower
users to monitor and manage their health themselves, offering accessible,
low-threshold, and cost-effective care on demand. With this, DHAs have the
potential to increase accessibility and quality of care. However, not everyone
can e qually b enefit f rom d igital h ealth t echnologies. R elative d istinctions
between individuals influence vulnerability towards exclusion, such as limited
literacy, older age, a low socio-economic position (SEP), a culturally and
linguistically diverse background, (mental) health issues, or homelessness.
People facing these vulnerabilities often also face disproportionate barriers
to digital and healthcare access, potentially exacerbating health disparities.
To ensure equitable access, it is essential to design, develop, and implement
inclusive DHAs that meet the needs of the most vulnerable individuals.
Therefore, this dissertation aims to gain insight into the facilitators and
barriers influencing DHA adoption among individuals in vulnerable positions.
By identifying these factors, this research seeks to increase the accessibility
of DHAs, promoting equitable health access across different (sub)populations.

Chapter 1 provides the background and rationale for this dissertation.
The concept of DHAs is introduced, together with its benefits and pitfalls.
Additionally, the digital divide phenomenon is elaborated upon, including
the vulnerabilities identified by the literature. Accordingly, the Technology
Acceptance Model (TAM) and the Unified Theory of Acceptance and Use of
Technology (UTAUT) are described. The chapter concludes with the aims,
research questions, and outline associated with this dissertation.

Chapter 2 describes a scoping review on the facilitators and barriers to the
adoption and use of autonomous mHealth applications among people with a
low SEP. As they often face health risks and many barriers in the traditional
healthcare system, there is an important role for mHealth. However, the
adoption of mHealth lags among people with low SEP. The review identified
30 factors across intrapersonal, interpersonal, community, ecological, and
app-specific levels. The most prevalent factors that enhance adoption were
infrastructure, stakeholder collaboration, human interaction, tailoring, and
digital literacy.

Chapter 3 describes a cluster analysis of psychosocial profiles associated
with the intention and adoption of the Dutch COVID-19 contact-tracing app
(CTA) during the pandemic. Adoption was particularly low among people in
vulnerable positions, such as people with low SEP or older age, while this part
of the population is more vulnerable to the COVID-19 virus. Hence, the study
aimed to understand the cause of this lagged adoption of CTAs to facilitate
adoption. Using a cluster analysis, five distinct user profiles were identified.
These clusters, along with age and prior adoption behavior, were predictive of
the behavioral intention and adoption of the app. People with more positive
psychosocial profiles were generally older, more highly educated, and more
likely to adopt the app. This provided insight into contact-tracing app adopters
and the way future intention and adoption rates could be predicted and
supported.

Chapter 4 reports an interview study with citizens living in low SEP
neighborhoods and professionals working with them. By this interview study,
insight was gained into the facilitators and barriers to the use of health, wellbeing,
and safety apps (i.e., apps within the domain of positive health), given
the increasing prevalence of such apps and their considerable potential for
prevention and self-help purposes. Over 40 factors were deemed important
in the areas of security and privacy, app content and design, support, and
promotion of apps. Key facilitators included perceived added value, digital
literacy, user-friendly and intuitive design, and support. A distinction emerged
between citizens with a favorable attitude toward digitalization and apps and
those with an unfavorable attitude, underlining the importance of tailoring
strategies to the differing attitudes.

Chapter 5 discusses a survey study performed on the factors associated
with the intention to use electronic mental health (EMH) applications among
migrants with a non-Western background. This population often faces
limited access to digital healthcare, despite their elevated mental health
needs. Therefore, it is important to gain insight into the factors influencing
the intention to use EMH to make mental healthcare more accessible.
A cross-sectional survey indicated that second-generation migrants reported
significantly higher intention, as well as stronger language, health, and digital
literacy levels, compared to first-generation migrants. Higher performance
expectancy, a s tronger b elief t hat t reatment c an b e s tarted a t a n e arlier
stage with EMH allow for earlier treatment initiation, and a higher perceived
personal and cultural understanding by the healthcare professional increased
the intention to use EMH. The findings suggest that DHAs for mental health
seem particularly valuable for providing information and self-help activities
to precede therapy, allowing individuals to start treatment earlier than with
face-to-face treatment only. Here, EMH is found to complement rather than
replace offline therapy.

Chapter 6 describes a survey study among clinical patients, informal
caregivers, and healthcare professionals of a hospital examining the empirical
factors influencing their digital literacy, self-efficacy, and support needs, as
these factors appeared important in the healthcare context. The findings show
a strong positive interrelationship between self-efficacy, digital literacy, and
enthusiasm for digital developments. Additionally, the way people seek support
(i.e., support patterns) when having inadequate skills appears important, as
well as age and type (patient/caregiver or professionals’ job title). In general,
respondents who seek help from family and friends rather than solving issues
independently reported lower digital literacy and higher support needs.
The study emphasizes the importance of focusing support strategies on
individuals with lower digital literacy and self-efficacy, a help-seeking support
pattern, and higher age.

Chapter 7 describes another survey study in the health care setting,
concentrated on the explanatory factors related to the behavioral intention
and use of telemonitoring apps among patients with Chronic Obstructive
Pulmonary Disease (COPD). Although telemonitoring apps offer significant
benefits for COPD self-management (e.g., reducing the probability of
hospitalizations and exacerbations), their use remains limited. Therefore,
this study explored the explanatory factors of behavioral intention and use
among both app users and non-users. Users showed significantly higher
digital literacy, performance expectancy, and fewer symptoms compared to
non-users. Users also experienced significantly higher importance of social
influence and alignment with norms and values than non-users. Performance
expectancy, self-efficacy, and alignment with personal norms and values
were explanatory for the behavioral intention. Self-efficacy, social influence,
personalization, and intention to use explained the use of telemonitoring apps.
The study further emphasizes the need for ongoing support infrastructure
(especially in the onboarding phase) and hybrid care models that combine
telemonitoring with traditional healthcare.

Chapter 8 reports a validation study of the “Experienced Usability and
Satisfaction with Self-monitoring in the Home Setting” (GEMS) questionnaire
among COPD patients using a telemonitoring app, extending the validation
from a nephrology sample to the COPD sample. By psychometric analyses,
the study confirmed the two-factor structure (usability and satisfaction)
with satisfactory reliability. One item showed cross-loading, suggesting
that for older, less educated, and less digitally skilled patients, usability and
satisfaction may be closely intertwined. The findings confirm the robustness
and applicability of the GEMS across different clinical contexts.

Chapter 9 comprises the discussion of the main findings, along with a
reflection on the methodological strengths and limitations of this dissertation,
and implications for future research and practice. The exploratory findings
provide indications that the psychosocial factors performance expectancy,
digital literacy, self-efficacy, general attitude, and support play an important
role in the behavioral intention and use of DHAs among individuals in a
vulnerable position, with digital literacy and self-efficacy appearing particularly
relevant within the concept of effort expectancy. These results contribute
to a developing field and validate components of the UTAUT and TAM
frameworks. To address barriers, three forms of support are recommended: 1)
DHA introduction by professionals, 2) digital training, and 3) ongoing technical
support. Moreover, the results seem to provide support for a blended care
model that combines online and offline healthcare. Nonetheless, the research
highlights the influence of context, such as the distinction between wellnessand
health condition management apps, and between apps that are used
voluntarily versus those that are advised, prescribed, or mandated. Future
research is recommended on the meso- and macro-level factors (e.g., public
health services, policy makers, and app developers), the sustained use of DHAs,
additional contexts and populations, and the ethical and governance aspects
of DHA implementation.

In conclusion, this dissertation provides a broad understanding of the
facilitators and barriers influencing the behavioral intention and use of DHAs
among individuals in vulnerable positions. Addressing these factors, together
with support and blended care models, could enhance DHA adoption and
reduce disparities. Hence, this work provides an important first step toward
understanding the challenges and opportunities involved in making sure that
no one is left behind in the digital transformation of healthcare.