In the fourth industrial revolution, we are witnessing an unprecedent transformation driven by technology, with no sector remaining untouched, and health is one of the sectors where digitalisation could have the greatest impact. Technological advances promise an era of innovations capable of expanding the frontiers of human life, democratize access to care, and personalize medicine like never before (1, 2). In this scenario of revolution, technology is not just a tool, but a vital ally in improving quality of life, health and well-being.

During the COVID-19 pandemic, there has been a significant increase in digital health, including the use of mobile health apps, telemedicine and data analysis to improve healthcare systems (3). As such, it is important to recognise that mHealth has the potential to empower individuals by improving personal health management, offering more immediate and personalised support, which not only improves adherence to treatments but also fosters patients' active involvement when it comes to their long-term well-being (3, 4). In addition, it can provide services in underserved areas (5, 6). However, this technology also places greater responsibility on the individual for the prudent use of health resources. There has been an increase in the use of smart devices for health monitoring, supported by substantial investment, although there are concerns about data privacy. Thus, the growing demand for reliable personal health apps is clear, with the potential to expand as technology continues to evolve (7, 8).

As the use and availability of mobile health apps increases, so does the need for a comprehensive and accessible app evaluation framework (9). Therefore, the search for a suitable and safe mobile health app presents a challenge, as the market offers hundreds of solutions, making it difficult for the user to filter the choice of those that are validated by health professionals (4). In this context, Tabi et al. (4) concluded in their study that of the 328 apps categorised, the majority were developed by the software industry (73%, 11/15), while a minority were co-developed with healthcare professionals (15%, 3/20) or academia (2.1%, 7/328). These data emphasise the importance of involving health professionals in the development of apps to ensure their clinical relevance and validity.

Results from a recent survey indicate that approximately 40% of adults use health apps and 35% use wearable devices, with the majority using these technologies daily (10). This raises concerns about how these data are stored, interpreted, and integrated into clinical decision-making. In fact, although many people already use wearable devices and apps to monitor their health, there is still uncertainty about how this data can be effectively analysed by qualified professionals and converted into useful information for patient care. This highlights the need for interdisciplinary collaboration between doctors, patients and developers to maximise the potential of these technologies (11, 12). Through interviews with 11 healthcare professionals in a previous study (13), it was found that they are aware that it is essential to develop technologies that meet the needs of clinical practice from the outset, led by specialists and with the participation of all stakeholders, to promote interdisciplinary collaboration.

In line with the broader Industry 5.0 vision for healthcare, the literature emphasises that the adoption and meaningful impact of emerging digital solutions depend strongly on user acceptance and inclusive, human-centred design (14). This reinforces the need to understand end users' characteristics and contexts when developing mHealth and wearable-based interventions. The continuous advance of medicine and technology has proved to be a catalyst for population longevity, a global trend that is reflected in the annual increase in the number of elderly citizens in most countries. While technology has provided advances in human life and medical care that have extended life expectancy, it has also intensified other challenges (15).

Between the advances promoted by technology and the increase in life expectancy, a vacuum emerges in which social and medical challenges intensify. This gap is especially visible in the tension between the capacity of health services and the growing demand for care due to an ageing population. In the face of this gap, technology is emerging as an essential link, not only for extending years of life, but also for promoting quality of life. Digital innovations are increasingly being seen as an indispensable resource for providing scalable and effective solutions that can act as a link between healthcare professionals, informal caregivers and patients, improve data communication and promote a process of mutual and continuous learning, contributing to the promotion of patient health and the prevention of risks (diseases) (14, 16).

Therefore, with the demand for care services increasing every year and limited resources to support them, the elderly population urgently needs solutions that promote their autonomy in everyday life (17). In line with the above, studies on the application of technology in the health of the elderly have revealed that apps can help healthcare professionals remotely monitor the health status of older people and improve the self-management of elderly patients in the comfort of their own homes (15, 18).

Health 4.0 promotes a health service delivery model that is coherent with the fundamental principles of Society 5.0, emphasising a vision for a new societal model to achieve a human-centred society (16). In this scenario, when considering the care landscape for the elderly population, the social determinants of health (SDH) take centre stage, highlighting the need to go beyond mere medical care (19, 20). These determinants, which encompass economic, social, cultural and environmental factors, have a decisive influence on living conditions and, consequently, the health of older people (21). Therefore, when developing technological solutions, it is essential to incorporate an understanding of these factors to promote not only autonomy but also equity in access to health. The strategic use of technology within the context of social determinants has the potential to mitigate disparities, contributing to healthy ageing and a more inclusive and just society (22).

A previous study based on interviews with 11 health professionals, offered a twofold possibility regarding the influence of technology on the elderly population:

On the one hand, it can lead to greater isolation and contribute to a disparity in access to technological innovations and their benefits, which is also mentioned in the literature (23). However, other authors point out that technology can prevent social isolation (24).

This study is motivated by the significant challenges presented by the growing ageing population, which affect both older individuals and their caregivers (this motivation derives from both previous literature and previous studies carried out by the authors). Given the gap between existing needs and the accessibility of solutions, it is crucial to develop technologies that respond to these specific challenges. Therefore, this study aims to create and present a preliminary proof of concept of an innovative digital tool (prototype of a mobile app) to support older people to live more independently and safely, promoting self-care and personal empowerment, while facilitating communication and coordination between the older person, caregivers and health professionals. This solution represents an innovative digital tool for monitoring the elderly, designed with the involvement of a group of users (the elderly), their caregivers and some health professionals. In addition, through these functionalities were designed considering SDH as a rationale and may potentially support inclusion and equitable access to healthcare, as well as reducing isolation.

Finally, a targeted literature review was conducted to frame the problem space and inform the initial design directions of the prototype; the key themes identified are synthesised in Section 2 (Theoretical Background).

The integration of digital health technologies into the care of older adults has considerable potential to enhance quality of life, reduce social isolation, and improve the efficiency of healthcare delivery. Yet these benefits largely depend on how such technologies are designed and implemented (30). Humanisation in digital health seeks to ensure that technology does not reduce patients to data points but instead acknowledges and respects individual needs and lived experiences (31). While this concern applies across contexts, it is particularly relevant in ageing populations, as many older adults live with multimorbidity, increased vulnerability and, in some cases, social isolation—factors that may heighten anxiety when engaging with digital tools (30, 32). In this sense, digital health should complement care rather than replace it, supporting communication, decision-making and timely responses (33).

To translate this humanised vision into practice, User-Centred Design (UCD) is essential (34). UCD places end users at the core of development by involving them from the early stages to understand their needs, tasks and contexts of use. It relies on iterative cycles of prototyping and usability testing, allowing solutions to be refined progressively through feedback and observation of real-world use (35–37). Practically, this may involve simplifying and clarifying language, reducing the number of steps, optimising icons and visual elements, and improving readability through appropriate font size and contrast. UCD also helps address a recurring limitation in research and technological development: the tendency to treat older adults as a homogeneous group, often automatically associated with cognitive decline, frailty and dependency. Ageing, however, is highly heterogeneous, and overlooking this diversity can result in poorly fitted and less inclusive solutions (30). In older populations, this is closely linked to accessibility: simple interfaces, legible text, good contrast, clear feedback and low cognitive load can increase trust and sustained use (38–40). Accordingly, Gomez-Hernandez et al. (38) propose two “golden rules” for designing mobile applications for older users: simplify, and increase the size and spacing of interactive controls.

Even so, anxiety related to digital technology use is common among older adults and may be shaped by low digital literacy, fear of damaging devices, and previous negative experiences (41, 42). Therefore, inclusive design is not only a usability matter: it can also reduce digital literacy barriers and help prevent innovation from widening inequalities in access to healthcare, namely the digital divide (43–45).

Finally, aligning humanisation, ageing, UCD and digital health requires careful attention to trust, privacy and data sharing, since many real-world solutions involve multiple users with different needs and levels of access (46). A humanised approach should ensure transparency (what data are collected and why), control (who can access what), and simple, clear rules for risk alerts, balancing safety with autonomy (47–49). This balance is particularly critical in ageing populations and, when embedded from the outset of design and implementation, tends to make technologies more acceptable, safer, and better aligned with person-centred care, supporting higher-quality ageing (50).

As mentioned above, mobile health apps are emerging as powerful tools to support self-care, particularly relevant for the elderly population. These applications offer a diverse range of functionalities and stand out for their ability to: allow patients to self-manage their health; provide users with relevant information about their state of health; promote real-time communication between patients and health professionals; enable a rapid response to significant changes in the patient's health condition, among others (51, 52). To help design technological solutions that are passive and accepted by the elderly, Wilson et al. (53) highlight in their study the barriers and facilitators to the use of technologies by the elderly population.

Regarding the health of the elderly, the literature proposes various apps designed to monitor and improve various aspects of the health and well-being of this age group in a specific way. Table 1 shows some of these apps.

The impact of mHealth on SDH is significant and multifaceted, with the potential to transform and improve public health practices (19, 20). The literature identifies different areas in which SDH can be impacted by mHealth, emphasising the following:

Improving access to healthcare: mHealth can improve access to healthcare services, especially in remote or underserved areas, by enabling remote consultations, health monitoring and delivery of health information. This can help reduce geographical and economic barriers and motor disabilities, allowing for more equitable access to healthcare (19, 20, 54, 67, 68).

In addition, Paglialonga et al. (5) introduce the concept of the “digital divide”, which highlights disparities in access to and use of digital technologies, such as mobile health (mHealth) apps and devices. These disparities can be influenced by various factors, including, age, location, socioeconomic status, education and digital literacy. The concept therefore emphasises the importance of measures to ensure that technologies are accessible to all, to reduce health inequalities and ensure that advances in healthcare benefit the entire population equally.

The literature review was followed by the user research stage, where the needs and requirements of both parties (elderly people and their caregivers, as the application has 2 different users) concerning the app were collected and understood so that it could be better aligned with the demands and expectations of the end users. As Gomathi & Mishra (14) point out, the success of digital health technologies depends largely on user acceptance. It is crucial to understand the profile of users and professionals to integrate technology inclusively. To carry out the user research, questionnaires were initially carried out for the elderly and their caregivers. However, it was concluded that this would not be the best instrument, as the language might not be easy to interpret for all elderly people and caregivers, even if it were adapted. The decision was therefore made to conduct informal interviews with both parties involved in the app. These interviews, with both parties (senior + caregivers), followed two different scripts, each based on the same three fundamental axes: initially, demographic information was collected to contextualise the responses within the variables of age, location and preference for health institutions. Next, the preferences and usage habits of health apps were analysed, seeking to understand which functionalities were most appreciated and how regularly they were used. Finally, the identification of specific functionalities desired by the users was explored in depth, including their relevance and suitability to their daily needs, with the aim of optimising health and well-being support through digital technology.

Prior to the interviews, participants received information about the study aims and how the data would be used. Written informed consent was obtained, and participation was voluntary. Participants were recruited through convenience sampling based on accessibility and willingness to take part and included older adults and caregivers with relevant experience. Interviews were informal semi-structured, and data were captured through researcher field notes (no audio-recordings). Confidentiality and anonymity were ensured; no directly identifiable personal data were collected, and notes were anonymised prior to analysis in line with GDPR requirements. The same information and consent procedures were applied to the usability testing sessions, with informed consent obtained prior to testing and no identifiable data recorded. Ethical review and approval were not required for this study in accordance with local legislation and institutional requirements.

The analysis was conducted by the first author using an inductive thematic synthesis approach appropriate for formative UCD studies. Interview data were synthesised to develop personas and requirements that guided the design and development of the application. Field notes were reviewed iteratively across participants to identify recurring needs, barriers, preferences, and desired functionalities, which were clustered into broader themes (e.g., medication adherence support, ease of navigation, reassurance/monitoring, and caregiver coordination). Personas (older adult and caregiver; Section 4.1.1.1) were derived by consolidating recurring participant characteristics (goals, motivations, frustrations, context of use, and digital confidence). Themes were translated into functional and non-functional requirements (Table 2) and mapped to the user scenarios/use cases (Section 4.1.1.2), supporting the definition of the app's functionalities and attributes. Given the small, early-phase sample and single-researcher synthesis, the personas and requirements should be interpreted as preliminary design inputs to guide prototyping rather than as exhaustive or generalisable user profiles.

Among the elderly participants interviewed (n = 4), participants were aged between 72 and 78, with an equal geographical distribution between the Centre and North regions of Portugal. Regarding access to healthcare, there is a tendency to use public services, with half of the interviewees using them exclusively. Among the caregivers interviewed (n = 4), participants were aged between 47 and 60 years, and the group includes caregivers from the Centre and North regions of Portugal. Their experience in caring for the elderly ranges from 7 to 12 years, demonstrating considerable commitment to their profession.

This phase was conducted as an early-stage exploratory User-Centred Design activity. Therefore, a small convenience sample was intentionally used to obtain initial qualitative insights and inform personas, scenarios, and the first prototype iteration, rather than to achieve demographic representativeness.

The subsequent phase focused on drawing up wireframes and workflows, graphic representations of the path to show the user's interaction flow within the application. An agile, iterative and incremental methodology was adopted at this stage of the model's development, allowing it to be implemented while users evaluate the tool and add requirements. This prototype is a mockup created using Figma design software.

Accessibility was treated as an essential design requirement related to the age of future users, which may affect interaction with mobile technologies (e.g., reduced visual acuity, cognitive load, motor skills, and digital literacy). Based on the information gathered about the requirements, the interface prioritised a simple and clear layout, with large font, high-contrast visual elements and the use of colour as a supporting cue rather than the sole carrier of meaning. In addition, multimodal interaction was considered important: data informed the inclusion of voice-based interaction and different alert modalities (visual, audible, and vibratory) to support medication routines and emergency situations. Finally, a voice-operated virtual assistant was incorporated to align with the usability, support, and companionship needs expressed during the requirements-gathering phase. These choices were informed by interview findings and direct observation, which guided the selection of colour and voice-based interaction elements for the prototype.

After the first cycle, we carried out a preliminary evaluation that revealed key areas to adjust in order to improve the usability and acceptance of the app. Feedback for these cycles came from three caregivers participating in the evaluation, who provided valuable insights into the interface and functionality. After implementing the improvements suggested in the first cycle, a second cycle was required for further refinement and to ensure that all concerns were adequately addressed. The same caregiver participants from the interview phase participated in both prototype-testing cycles, ensuring continuity of feedback and enabling verification that the refinements implemented after Cycle 1 addressed the issues identified.

Following these two iterative cycles and the finalisation of the prototype, usability tests were carried out individually, with the aim of assessing the application's acceptance by the two types of users, validating all the requirements defined in the user research and measuring the application's usefulness. Users were asked to complete a series of specific tasks, while being observed as they carried them out, to analyse the ease of use and efficiency of the application.

Tasks were selected to reflect key and safety-relevant use-cases identified during the requirements-gathering phase (e.g., medication confirmation, checking health status and contacting the caregiver, setting a medication routine, and reviewing adherence history). Sessions were conducted in participants' homes, lasted approximately 30 min, and used an interactive, moderated task-based procedure on a smartphone prototype. Participants interacted with the prototype while the moderator observed performance and asked brief clarification questions when needed. At the end of the session, participants completed a short ad hoc post-task usability questionnaire developed for this formative evaluation (i.e., not a standard instrument such as SUS). The questionnaire used Likert-style ratings with an “NA” option and included two sets of items: (1) overall opinion about the application (e.g., ease of orientation, findability, perceived slowness, pleasantness, coherence/consistency, and need for help); and (2) interface-specific aspects (e.g., readability/font size, emphasis of important information, adequacy of information layout across screens, icon intuitiveness, and ease of navigation). Open-ended questions were also included for additional comments.

The first author acted as moderator/observer, providing standardised task instructions and recording difficulties during task completion (e.g., hesitations, navigation errors, misunderstandings, and requests for help). Below are some examples of tasks performed, focused on functionalities for the elderly:

Imagine that you need to check that your health figures are in order, to understand whether you need to call the caregiver or not. Is everything OK or do you need to call the caregivers?

A total of 13 usability test sessions were conducted. Of these, eight focused on the older-adult user flow: three were performed by older adults (70–80 years), and five were performed by caregivers to assess the usability of the older-adult interface. The remaining five sessions focused on the caregiver flow and were performed by five participants aged 40–60, comprising the four caregivers previously interviewed plus one registered nurse, who also tested the caregiver interface.

The elderly completed 6 tasks, the aim being to ensure that the interface was intuitive and easy to use, considering possible technological or cognitive limitations common in this age group. On the other hand, the caregivers completed 7 tasks related to the part of the application aimed at them, and these tasks were designed to assess how the application can help in their caring responsibilities, ensuring that the functionalities offered are practical and efficient for supporting the elderly. In addition, as mentioned above, the caregivers also carried out the 6 tasks for the elderly. This was done to capture a support perspective and anticipate how caregivers might assist older adults during adoption and daily use.

Between August and September 2024, we additionally conducted four informal online interviews with a separate group of registered nurses (generalist and geriatric-specialist), mainly from the Aveiro and Porto regions. These participants did not take part in the caregiver/user usability sessions. Their feedback informed refinements to both the prototype features and the underlying data structure (e.g., how medication- and health-related information were organised and represented), supporting validation of the proposed approach. In addition, these expert inputs helped shape the future work directions outlined in the manuscript, particularly regarding clinical validation and further refinement of data representation.

Based on the feedback gathered from all of these participants, final adjustments were made, culminating in the final version of the SeniorHealth Tracker app prototype presented in Section 4.1.2.

Figure 1 summarizes the steps of the methodology used in this study.

This subsection is divided into two specific parts. The first (4.1.1.) presents the requirements for developing the solution, which came from the user research. The second (4.1.2.) presents the final version of the app prototype with the adjustments made according to the comments from the usability tests.

The importance of the SDH in mHealths cannot be underestimated, as these determinants significantly influence the health and well-being of the population. Incorporating a thorough understanding of SDH into the development and implementation of mHealth solutions is essential to ensure that these technologies not only promote autonomy and improve access to healthcare but also mitigate existing disparities. By considering these factors, it is possible to create more equitable and inclusive interventions, in line with the principles of a human-centred society (19, 20, 22).

The SeniorHealth Tracker app prototype was developed with a human-centred approach, motivated by the SDH to address the needs of the elderly population. Thus, based on the prototype developed, it has the preliminary potential to support SDH related needs by making it possible to:

Access to services (potential use-case): SeniorHealth Tracker technology is intended to facilitate access to medication delivery services, transport to local services and home care, which may support the independence and quality of life of older people, especially those living far from urban centres, in areas considered remote. This topic is in line with the literature that highlights mHealth as a powerful tool for improving access to healthcare in remote or under-served areas, reducing geographical barriers and promoting equity in access (19, 20, 54, 67, 68).

The interviews revealed that not all older people are able to use 100% of the app's functionalities, which could end up catalysing the “digital divide” highlighted by Paglialonga et al. (6). Hendl & Shukla (68) emphasise that the implementation of technology must be accompanied by policies that promote equity in access, something that must be considered in the development and expansion of SeniorHealth Tracker. In summary, the integration of SDH into SeniorHealth Tracker is presented here as a design rationale and longer-term aspiration for a more holistic and equitable use of mHealth technologies for older adults, rather than as a demonstrated outcome of the present study.

The article discusses the critical intersection between technological innovation and the human touch, emphasising that while technology provides powerful tools to improve the quality of life of the elderly, it is the human element that transforms these tools into effective solutions. It is important to emphasise that an app for monitoring the elderly must be more than a set of digital functionalities, although these are essential; it must be a gateway to a caring and responsive human service.

The article presents the essential features of an elderly health monitoring app, such as real-time health monitoring, medication management and virtual assistance, the panic/alert button with GPS (allows quick responses in the event of an emergency), mapping of local services, and health and wellbeing tips for the elderly. These features emerged from user research carried out with both caregivers and the elderly themselves, and the app was tested with users, and in this small evaluation participants generally perceived the prototype as useful and easy to use. Given the small, convenience-based sample and the prototype nature of the solution, these findings are preliminary and should not be generalised. Once again, it is necessary to emphasise the value of the human accompaniment behind the technology: health professionals who analyse the data collected, respond to alerts and offer personalised support.

In addition, this technology (app + wearable) can be adapted so that it can be used by people with specialised care needs, further extending its reach and potential for a positive impact on the health and well-being of a variety of populations.