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 ble