Towards a New Paradigm for Digital Health Training and Education in Australia: Exploring the Implication of the Fifth Industrial Revolution

Featured Application: This paper presents a new, ﬁfth industrial revolution (Industry 5.0)-inspired paradigm for educating and training Australian healthcare professionals and students in the ﬁeld of digital health. By leveraging Industry 5.0-enabling technologies, such as artiﬁcial intelligence, machine learning, blockchain, big data analytics, etc., we can cultivate students to be job-ready for the future of work by providing them with hands-on experience in advanced healthcare technologies. Ultimately, this new training and education paradigm in digital health can help bridge the gap between training and the world of work and prepare students to deliver a more efﬁcient, effective


Introduction
In recent years, the healthcare industry has experienced a revolution driven by advancements in technologies and applications, such as wearable devices, mobile health apps, telehealth and telemedicine, mobile health, electronic health, and health information technology. The use of such technologies and applications in healthcare systems is referred to

Security and Privacy
Security must be considered when a person is using digital technology so that they perceive the tool as safe and secure and know it will protect their personal information [13]. Ensuring the privacy and security of patient data is essential to the successful implementation of these new technologies in healthcare. Therefore, it is necessary for healthcare providers to develop proper staff training and implement secure infrastructure to use these technologies effectively [14]. This can be achieved by using secure, encrypted systems and regular data audits that identify and address potential breaches.

Traceability and Safety
The use of electronic medical records enables the digitization of patient information for easier access and sharing between healthcare providers. Such sharing can improve the continuity of care, reduce medical errors, and improve the efficiency of healthcare systems [15]. However, there are also challenges, such as inter-operability and data security.

Standardisation and Interoperability
There is currently a lack of standardization in the development and implantation of common technical specifications, data formats, and data exchange protocols that enable digital health data to be exchanged and integrated within different systems and platforms [14]. As health data can be obtained from multiple sources (e.g., sensors, devices, apps, tools, etc.), the challenges concerning the inter-operability of the digital health ecosystem can make it difficult for users to share data and collaborate effectively and, more importantly, without compromising patient safety and their data privacy.

Resilience and Sustainability
The resilience and sustainability of digital health solutions are critical factors in their success. Resilience means that the digital health system and technologies are designed and built to withstand and recover from cyber-attacks, database hacking, and the theft of big data. Moreover, sustainability is essential to address the development and implementation of digital health solutions that are financially viable, scalable, and effective and allows for a broad range of user adoption in the longer term [14,16].

Regulatory Policy and Framework
The key regulatory bodies that oversee the digital health sector include the Food and Drug Administration (FDA) in the United States [17], the European Medicines Agency (EMA) in Europe [18], the Medicines & Healthcare Products Regulatory Agency in the United Kingdom [10], and the Therapeutic Goods Administration (TGA) in Australia [19].
Their key mission is to promote and protect public health. Clear and logical regulatory guidelines on the requirements, process, development, deployment, and approval of digital health technologies will be essential and pose significant challenges to inventors and companies operating in the field. The challenges relate to testing, manufacturing, hardware, and software updates [17,20]. Currently, there is a regulatory gap and little-to-no binding regulation to evaluate the quality, safety, and efficacy of digital health technologies and products [10,21].
While the FDA, EMA, and TGA regulatory bodies oversee the safety, efficacy, and quality of medical products, including pharmaceuticals and medical devices, the health technology assessment (HTA) is a multidisciplinary process that systematically evaluates the evaluation of the medical, social, economic, and ethical issues related to the use of new health technologies [22,23]. Given the relatively recent emergence of digital health technologies and solutions, as well as their application in education, there is a lack of international consensus on HTA in these contexts [24,25]. As suggested by [26], very few of the applications of electronic or mobile health data have addressed technology, safety, ethical, and legal issues. As such, by working together and leveraging those guidelines, we could help facilitate the responsible and effective integration of new technologies into healthcare.

Equity
Digital health equity refers to the ability of individuals, regardless of their socio-economic status, race, ethnicity, or other demographic characteristics, to access and benefit from digital health technologies and services [27]. Therefore, a better understanding of health equity by all stakeholders would help support the design, development, and deployment of digital health tools that actively work to reduce health disparities and promote health equity for socially disadvantaged patient populations [28]. Richardson et al. [27] presented a framework for digital health equity at different determinant levels, e.g., individual, interpersonal, community, and societal. The authors envisaged that the framework could help digital health innovators from various sectors (e.g., industry, health systems operations, and academia) develop and scale their products and services to achieve health equity for all.
A recent study by Kaihlanen et al. [29] suggested some major problems in accessing digital health services. These are related to individuals' access to digital resources, insufficient digital skills or language skills, and a lack of support and training to access and use digital services. Therefore, governments, industries, and universities can play a key role in educating and training individuals to have a greater understanding and knowledge of using digital health technologies effectively.

Education, Training and Awareness
As the use of digital health tools continues to grow, it is essential to ensure that healthcare professionals, patients, and the general public are adequately educated, trained, and aware of the potential benefits and risks of using these technologies. Proper training and education for healthcare providers are essential to ensure they are equipped with the knowledge and skills not only on how to use new technologies but also in understanding how to interpret and integrate data into clinical decision-making. Similarly, patients need to be educated about digital health and ensure that they are trained and capable of using digital health systems properly and can use these tools for their benefit and to mitigate any negative effects. To date, three systematic reviews have critically evaluated 91 studies, each adhering to stringent eligibility criteria, to explore the impact of digital technologies on healthcare professionals' education [30][31][32]. The preliminary findings across several of these studies suggest improvements in outcomes attributable to the use of digital technologies. However, all three reviews concur that further research is required to substantiate these initial observations and confirm a significant effect conclusively. This highlights the necessity for direction and clarity in health education, especially considering the potential impact of technologies arising from Industry 5.0. In order to achieve this, it is essential to facilitate the integration of Industry 5.0 advancements into the sphere of digital health.

An Outlook on the Integration of Industry 5.0 and Digital Health
Digital health is closely related to Industry 5.0 as it relies on the integration of advanced technologies, such as IoT, AI, and ML, to improve healthcare delivery and outcomes. The integration of Industry 5.0 concepts and digital health can have a profound impact on the healthcare industry. By combining the power of human skills with technology, it is possible to create more personalised and effective healthcare solutions that can be tailored to the individual needs of each patient. The concepts of Industry 5.0 and its enabling technologies that support digital health are illustrated in Figure 1 [14,[33][34][35]. 91 studies, each adhering to stringent eligibility criteria, to explore the impact of digital technologies on healthcare professionals' education [30][31][32]. The preliminary findings across several of these studies suggest improvements in outcomes attributable to the use of digital technologies. However, all three reviews concur that further research is required to substantiate these initial observations and confirm a significant effect conclusively. This highlights the necessity for direction and clarity in health education, especially considering the potential impact of technologies arising from Industry 5.0. In order to achieve this, it is essential to facilitate the integration of Industry 5.0 advancements into the sphere of digital health.

An outlook on the Integration of Industry 5.0 and Digital Health
Digital health is closely related to Industry 5.0 as it relies on the integration of advanced technologies, such as IoT, AI, and ML, to improve healthcare delivery and outcomes. The integration of Industry 5.0 concepts and digital health can have a profound impact on the healthcare industry. By combining the power of human skills with technology, it is possible to create more personalised and effective healthcare solutions that can be tailored to the individual needs of each patient. The concepts of Industry 5.0 and its enabling technologies that support digital health are illustrated in Figure 1 [4,14,33,34].

Enabling Technologies
The ongoing coronavirus pandemic has catalysed the use of digital technologies all over the world. It has accelerated the process of digital transformation from the fourth industrial revolution (4IR) towards Industry 5.0 within different areas of society [35]. The 4IR is driven by technological advances of cyber-physical systems, which focus on integrating the enabling technologies (Table 1) within our daily lives and workplaces [36]. In contrast, the emerging Industry 5.0 seeks to utilise such enabling technologies to prioritise collaboration between humans and machines while maintaining sustainable development and practices [33,37]. State-of-the-art Industry 5.0 technologies, as illustrated in Figure 1, play a critical role in the digital transformation of the healthcare industry. Such transformation is being driven by various technologies, including digital twins, IoT, AI, ML, blockchain technology, and cloud computing. These technologies have produced a digital metamorphosis of the healthcare system [38], with an emphasis on human-centric design, which focuses on the needs and preferences of patients, healthcare professionals, and other stakeholders. By harnessing digital twins, IoT, AI, and ML, healthcare systems can improve their sustainability, human-centricity, and resilience. Table 1 provides a more detailed description of Industry 5.0-enabling technologies that facilitate digital health and

Enabling Technologies
The ongoing coronavirus pandemic has catalysed the use of digital technologies all over the world. It has accelerated the process of digital transformation from the fourth industrial revolution (4IR) towards Industry 5.0 within different areas of society [36]. The 4IR is driven by technological advances of cyber-physical systems, which focus on integrating the enabling technologies (Table 1) within our daily lives and workplaces [37]. In contrast, the emerging Industry 5.0 seeks to utilise such enabling technologies to prioritise collaboration between humans and machines while maintaining sustainable development and practices [33,38]. State-of-the-art Industry 5.0 technologies, as illustrated in Figure 1, play a critical role in the digital transformation of the healthcare industry. Such transformation is being driven by various technologies, including digital twins, IoT, AI, ML, blockchain technology, and cloud computing. These technologies have produced a digital metamorphosis of the healthcare system [39], with an emphasis on human-centric design, which focuses on the needs and preferences of patients, healthcare professionals, and other stakeholders. By harnessing digital twins, IoT, AI, and ML, healthcare systems can improve their sustainability, human-centricity, and resilience. Table 1 provides a more detailed description of Industry 5.0-enabling technologies that facilitate digital health and clinical applications. These issues are being actively discussed within major healthcare professional sectors (see references in Table 1).

Enabling Technology in Industrial Revolution Clinical Applications References
Internet of Things (IoT) and Industrial Internet of Things (IIoT) -real-time data acquisition and analysis from wearable devices in healthcare delivery [40] seamless connectivity between physical devices and objects equipped with sensors and software [41][42][43] promptly collect and respond to vital and physical activities [44] Cloud and Edge Computing -enables healthcare professionals to remotely access and analyse patient data from mobile devices [45] enhances the accessibility, quality, and efficacy of information delivery by minimising the latency of data flow [46] Blockchain Technology for Healthcare -data encrypted and distributed through a decentralised network to improve security [47,48] -Examples are Medicalchain, Hashed Health, Guardtime, and IBM [49] implementation of robust security protocols, such as encryption and access control, to prevent data breaches and cyber-attacks [50] Artificial Intelligent (AI) and Machine Learning (ML) -AI-powered chatbots respond to questions on health, provide diagnoses and treatment advice [51] -[concern:] ethical concerns about ownership, access right, privacy, and security of the use of patient data in AI algorithms [48,52]  optimise the supply chain of pharmaceutical and medical products and affect the efficiency of production [61] Collaborative Robots (Cobots) and Automation -beneficial in delivering different daily services efficiently, such as sterilisation, cleaning, and logistics, in the healthcare domain [62] analyse large amounts of patient data, identify patterns, and make predictions about patient health [63,64] -[concern:] safety of patients and professionals must be prioritised by adhering to strict regulations and guidelines during cobot design and implementation [65]  nanomedicine is one of the emerging issues in biomedical engineering and pharmacy [72,73] Figure 2 further visually illustrates the relationship between, and dynamics within, the technological transformations of each industrial revolution epoch from the first, denoted as 1IR, to the latest (5IR) (now underway) [33] and their impact on healthcare education and training. It serves as a roadmap, highlighting each epoch's technological advancements and the evolving knowledge and skills, abilities, and changes in healthcare education and training for each [74]. Recognising these shifts provides a deeper understanding of the crucial role of embracing and aligning healthcare education with industrial revolutions to equip professionals with the necessary competencies to thrive in the future healthcare environment. noted as 1IR, to the latest (5IR) (now underway) [33] and their impact on healthcare education and training. It serves as a roadmap, highlighting each epoch's technological advancements and the evolving knowledge and skills, abilities, and changes in healthcare education and training for each [71]. Recognising these shifts provides a deeper understanding of the crucial role of embracing and aligning healthcare education with industrial revolutions to equip professionals with the necessary competencies to thrive in the future healthcare environment. Digital health and education, underpinned by relevant enabling technologies (Table  1), presents a transformative opportunity for healthcare disciplines, such as nursing, medicine, and pharmacy. When effectively integrated, these advancements can enhance patient care, streamline healthcare management, and revolutionise health systems worldwide. These technologies have varied levels of adoption and integration into digital health education and practice in countries such as the United States, United Kingdom, Canada, Australia, and New Zealand [30][31][32]. It is generally true that healthcare professionals can exchange and work between the United States, Canada, Australia, the United Kingdom, and some European countries, which are subjected to certain conditions and requirements to address health workforce mobility and shortages [72,73]. Moving forward, we need a Digital health and education, underpinned by relevant enabling technologies (Table 1), presents a transformative opportunity for healthcare disciplines, such as nursing, medicine, and pharmacy. When effectively integrated, these advancements can enhance patient care, streamline healthcare management, and revolutionise health systems worldwide. These technologies have varied levels of adoption and integration into digital health education and practice in countries such as the United States, United Kingdom, Canada, Australia, and New Zealand [30][31][32]. It is generally true that healthcare professionals can exchange and work between the United States, Canada, Australia, the United Kingdom, and some European countries, which are subjected to certain conditions and requirements to address health workforce mobility and shortages [75,76]. Moving forward, we need a more standardised and global approach to digital health and education in order to improve overall professional skills and patient outcomes as well as tackle global shortages of healthcare professional workforce [32,77].

Prospects, Issues, and Challenges for the Healthcare Workforce
The working environment in digital health is constantly evolving, and new technologies are being developed at a rapid pace. Therefore, a new training paradigm is required for the workforce to work well with those technologies. As educators, we need to consider how to prepare the workforce of the future. However, educators are constantly faced with many possibilities and complex decisions as they design learning and teaching content, assessment tasks, and instructions focused on the knowledge and skills learners need to be successful in this fast-changing world. In order to stay ahead in this complex environment, it is necessary to understand how the future of work will evolve in the years ahead with the advancement of Industry 5.0 technologies [8,78,79].
The idea of the future of work comprises three elements: the workplace, the actual work carried out, and the workforce ( Figure 3) [79,80]. Workplace refers to where and when work is carried out. Work presupposes that it is inevitable that future employees will be collaborating with analytic software, chatbots, and robotics to get carry out work efficiently and innovatively. This magnifies the need for targeted interventions funded by national governments and other stakeholders to bridge the skills gaps precipitated by advanced technological change. Workforce focuses on the people who do the work. New Industry 5.0 technologies are increasingly replacing manually repetitive labour tasks. Employers must prepare their workforce for moving into, within, or out of an organization due to the changing skill requirements caused by advances in technology. ernments and other stakeholders to bridge the skills gap nological change. Workforce focuses on the people who technologies are increasingly replacing manually repetit prepare their workforce for moving into, within, or o changing skill requirements caused by advances in tech Although big data usage and analytics, AI, and M in the future, it is less clear how these should be integrat ula to ensure that the relevance of graduates' skills focu and personalized and sustainable healthcare. It has been and training methods may be unable to keep up with the and may fail to prepare students for the future digital Commission notes [4,7] that the future of work is shifti elements are focused on human-centricity, sustainabili urgent for all levels of government, economy, and socie training to enable workers to adapt to a shifting job ma work [4,7]. Australia provides a useful example of these Although big data usage and analytics, AI, and ML will become fundamental skills in the future, it is less clear how these should be integrated into existing education curricula to ensure that the relevance of graduates' skills focuses on human-centric technology and personalized and sustainable healthcare. It has been argued that traditional education and training methods may be unable to keep up with the rapid changes and advancements and may fail to prepare students for the future digital health workforce. The European Commission notes [5,7] that the future of work is shifting to Industry 5.0, where its core elements are focused on human-centricity, sustainability, and resilience. It is becoming urgent for all levels of government, economy, and society to support education and skills training to enable workers to adapt to a shifting job market and the nature of healthcare work [5,7]. Australia provides a useful example of these dilemmas.

Australian Educational Context in Digital Health
The Australian higher education system has a long history of quality assurance and accreditation. As such, all the degrees meet the rigorous Australia Qualifications Framework [81], meaning that graduates are well-prepared for the workforce. In order to address the need for digital health, many universities in Australia have started offering various digital health-related degrees. In this context, we assessed and compared Australian universities that offer digital health degrees in terms of pedagogy and technological competencies (software, hardware, resources, infrastructure, etc.), assessments, and industry collaborations to provide insight into the strengths and weaknesses of the degrees in preparing students for Industry 5.0 in the field of digital health ( Table 2).  As noted in Tables 2 and 3, most digital health degrees are offered at the graduate certificate level in the Australian context. They are designed to cater to the needs of professionals who are already working in healthcare and want to upskill or reskill in the digital health field. Graduate certificates seem to offer a shorter and more flexible pathway for professionals to acquire the knowledge and skills necessary to advance their careers without committing to a full-time postgraduate degree. Appendix A provides detailed information about the entry requirements for each graduate certificate, as well as the courses or topics covered and the learning outcomes that students can expect to achieve upon the completion of the degrees. According to the analysis in Table 3, most degrees lack industry partnerships that can provide students with real-world exposure so that they can apply their knowledge in practice and gain experience. Australian universities have their own core curriculum and vary in terms of how they address key issues related to digital health, such as security, privacy, standardisation, and interoperability, as well as regulatory policy. Table 4 presents a thorough review of how each university addresses the key issues related to digital health and Industry 5.0 in order to equip their graduates with the skills and knowledge essential to success in the ever-evolving and complex world of digital health.    It is important to note that the comparison in Tables 2-4 might not be simple, as diverse degrees may have distinct objectives, intended audiences, and pre-requisites. Furthermore, it is important to consider the context in which these degrees are being designed and offered, such as accessible resources and local industry needs. Therefore, a visual representation through histograms capturing the prevailing trends in the adoption of the three key principles: sustainability, human centricity, and resilience in digital health curriculum design is presented in Figure 4. The distribution of the data in Table 4 has been mapped to the histograms, indicating the extent to which the programs emphasise these key principles. By segmenting the results into high, median, and low categories, we can effectively identify trends, gaps and potential areas for improvement in the educational offerings within this field. As shown in Figure 4a, merely about 10% of the programs strongly incorporate the two key digital health principles of sustainability and human centricity. Similarly, as illustrated in Figure 4b, the emphasis on both human centricity and resilience is given low priority in the majority of the programs. Figure 4c reveals that most programs exhibit a high-to-medium focus on the resilience principle, combined with a medium-to-low emphasis on the sustainability principle in their digital health curriculum. The purpose of the comparison is not to provide an exhaustive list but rather to offer insights for students, educators, policymakers, and universities to better understand the delivery of digital health and improve the quality of learning and teaching. Appl It is important to note that the comparison in Tables 2-4 might not be simple, as diverse degrees may have distinct objectives, intended audiences, and pre-requisites. Furthermore, it is important to consider the context in which these degrees are being designed and offered, such as accessible resources and local industry needs. Therefore, a visual representation through histograms capturing the prevailing trends in the adoption of the three key principles: sustainability, human centricity, and resilience in digital health curriculum design is presented in Figure 4. The distribution of the data in Table 4 has been mapped to the histograms, indicating the extent to which the programs emphasise these key principles. By segmenting the results into high, median, and low categories, we can effectively identify trends, gaps and potential areas for improvement in the educational offerings within this field. As shown in Figure 4a, merely about 10% of the programs strongly incorporate the two key digital health principles of sustainability and human centricity. Similarly, as illustrated in Figure 4b, the emphasis on both human centricity and resilience is given low priority in the majority of the programs. Figure 4c reveals that most programs exhibit a high-to-medium focus on the resilience principle, combined with a medium-to-low emphasis on the sustainability principle in their digital health curriculum. The purpose of the comparison is not to provide an exhaustive list but rather to offer insights for students, educators, policymakers, and universities to better understand the delivery of digital health and improve the quality of learning and teaching.  We also noticed that the information about the infrastructure, resources, and technologies used in these programs is often not well documented. Such information is essential to help students make informed decisions about their education and career paths, help educators design and deliver effective courses, help policymakers shape policies to support digital health initiatives and help universities enhance their degrees and partnerships with industry to meet the needs of the rapidly evolving digital health landscape.
It is clear that the fifth industrial revolution requires us to change our education and training for healthcare professionals, and our findings to date indicate that much needs to We also noticed that the information about the infrastructure, resources, and technologies used in these programs is often not well documented. Such information is essential to help students make informed decisions about their education and career paths, help educators design and deliver effective courses, help policymakers shape policies to support digital health initiatives and help universities enhance their degrees and partnerships with industry to meet the needs of the rapidly evolving digital health landscape.
It is clear that the fifth industrial revolution requires us to change our education and training for healthcare professionals, and our findings to date indicate that much needs to be carried out to develop a new paradigm for digital health education.

The Fifth Industrial Revolution and a New Teaching Paradigm for Digital Health
Students need to be able to work effectively alongside machines and technology while also being able to communicate and collaborate with their colleagues. As new technologies emerge, students need to learn and upskill continuously throughout their careers. We propose a new learning and teaching framework that integrates pedagogical methods, technologies, and assessment strategies to deliver a skilled workforce in the future ( Figure 5).

Learning Content and Source
Industry 5.0 will present significant challenges and demands to contemporary learning and the education approaches that help learners to leverage human/technology cooperation to solve future problems [34,79]. It is incumbent upon educational institutions that they provide students with exposure to emerging technologies and educational situations in which students interact with technology and learn to apply it. In order to stay relevant and build a competitive advantage for graduates and universities, higher education should consider how Industry 5.0 and digital health can interact with the learning and teaching context, at the same time answering the overarching questions about what kind of learning models, content, program planning, digital credentials, and good practice are needed to improve and reshape educational approaches [80].

Infrastructure, Resources and Technologies
Despite growth in the use of Industry 5.0 technologies that support the entire teaching and learning process [37], most educational institutions still focus on ensuring students develop familiarity with the tools used within simulated work scenarios [81] rather than incorporate authentic, real-world problems that involve multiple stakeholders, including patients, clinicians, industry partners, etc. Additionally, the barriers to, and enablers of, the successful adoption and implementation of Industry 5.0 technologies to support learning and teaching activities have so far been ignored or not well documented.
The information and communications technology (ICT) infrastructure refers to the essential hardware, software, networks, and other technologies that facilitate communication and data management. ICT infrastructure is important for network connectivity and computing devices and provides collaboration and organisational platforms to inte-

Learning Content and Source
Industry 5.0 will present significant challenges and demands to contemporary learning and the education approaches that help learners to leverage human/technology cooperation to solve future problems [34,82]. It is incumbent upon educational institutions that they provide students with exposure to emerging technologies and educational situations in which students interact with technology and learn to apply it. In order to stay relevant and build a competitive advantage for graduates and universities, higher education should consider how Industry 5.0 and digital health can interact with the learning and teaching context, at the same time answering the overarching questions about what kind of learning models, content, program planning, digital credentials, and good practice are needed to improve and reshape educational approaches [83].

Infrastructure, Resources and Technologies
Despite growth in the use of Industry 5.0 technologies that support the entire teaching and learning process [38], most educational institutions still focus on ensuring students develop familiarity with the tools used within simulated work scenarios [84] rather than incorporate authentic, real-world problems that involve multiple stakeholders, including patients, clinicians, industry partners, etc. Additionally, the barriers to, and enablers of, the successful adoption and implementation of Industry 5.0 technologies to support learning and teaching activities have so far been ignored or not well documented.
The information and communications technology (ICT) infrastructure refers to the essential hardware, software, networks, and other technologies that facilitate communication and data management. ICT infrastructure is important for network connectivity and computing devices and provides collaboration and organisational platforms to integrate processes and people [85]. It is also crucial for the development and implementation of Industry 5.0. However, ICT infrastructure often presents a challenge in low-income or resource-poor countries [14,86].
Hashim et al. [87] emphasised that, in addition to budgetary allotments, universities need to formulate agile, realistic, and scalable digital transformation strategies for the adoption of new technologies. Universities can leverage open-source software and technologies, which will radically reduce the fixed costs of investing in digital technologies for supporting educational practice [87][88][89]. Although it can be used free of charge, open-source software presents challenges related to security, support, compatibility, and governance, which need to be carefully considered [11].

Strategies to Reinvent Education Pedagogy
Recent studies [8,90] have reported on the third wave of automation and have predicted that by 2030, approximately 90% of jobs may be replaced by autonomous robots. As a result, there will be increased demand for knowledge-based (cognitive) occupations, driven by a continuing shift from routine manual skills to non-routine, metacognition-based skills, such as problem-solving, collaboration, and leadership. However, education researchers have noted that the current research on preparing students for the future of work is still in its infancy [84,91,92]. Despite many of the digital technologies already existing in the higher education system [84,91,92], these are becoming less relevant in addressing the complex future labour market in the context of Industry 5.0. Hence, educational institutions require a comprehensive overhaul of their existing curricula and learning and teaching strategies to help students in becoming lifelong learners who know how to identify and define the right problems for complex systems that need solving and working collaboratively to achieve the desired outcomes. Some examples of how Industry 5.0 technologies can be applied to learning and teaching pedagogy may include the following.

Experiential Learning in Project-Based Learning
An experiential learning approach means students are given a set of problems, and while trying to solve them, they not only need to search for information but also implement the theoretical concepts that they have learned [93]. One popular experiential learning approach is project-based learning (PBL) [88]. PBL involves students working on realworld projects that allow them to apply their knowledge and skills in a practical and meaningful way. In the context of digital health and Industry 5.0, PBL could involve working on projects, such as developing a health application, designing an AI-powered medical diagnosis tool, or creating a virtual reality training program for industrial workers.

Collaborative Learning
Some studies [16,94] have suggested that to implement digital solutions and competencies successfully to solve real-world clinical and public health problems, there must be multidisciplinary collaboration between medical science and science and technology disciplines. However, collaboration can be challenging, as it involves two or more people interacting with each other [95]. We believe that the available tools and resources, together with a systematic approach to teamwork and communication skills, can play a relevant role in preparing the next generation of workers for the challenges of the future [96].

Transdisciplinary Learning
Digital health is a multidisciplinary field that includes health sciences, engineering, computer science, and information technology. Embracing transdisciplinary processes in research and education [97] and sharing knowledge has become an important aspect of new teaching paradigms and was reported as helpful [94] in equipping students with a thorough education that covers all aspects of digital health. A recent study by Broo and colleagues [97,98] highlighted the importance of transdisciplinary working environments for a sustainable future. The authors suggested the complex problems of the fifth industrial revolution (i.e., Industry 5.0) cannot be adequately tackled by an individual from a single discipline but require the consideration of individuals and experts from different disciplines or areas to work together to address complex, real-world problems. Therefore, the authors urged higher education institutions to introduce transdisciplinary environments combined with new frameworks, such as blending systems and design thinking, in the teaching and learning programs.

Lifelong Learning
Lifelong learning, which is defined as an ongoing, voluntary, and self-motivated pursuit of knowledge [97], has been increasingly promoted in recent decades. It involves a shift away from traditional lecture-based instruction towards a more hands-on and student-centred approach to teaching and learning. With such an approach, students take responsibility for their education by participating in real-world case studies, interactive activities, and group projects and discussions. This student-centred approach focuses on cultivating critical thinking and collaboration, and through hands-on laboratories, students gain practical experience in the application of advanced technologies. Furthermore, this approach can be customised to adapt to the needs of students by incorporating real-world scenarios, simulated patient cases, and personalised instruction.
By using a lifelong learning approach, educators can better prepare healthcare students for success in their future careers by developing critical thinking skills, teamwork abilities, and a deeper understanding of applied skills. These skills are particularly important in the context of Industry 5.0, where professionals must be able to think creatively and work effectively with others and understand patient information flows in these technologies. However, it is still unknown how well the higher education system's education and training approaches help students develop agility in response to fast-changing technologies and also maintain motivation and capacity for learning in the longer term.

Assessment Model
In order to transform a healthcare professional from an aspiring learner to an expert who masters independent thinking, efficient problem-solving, and has the capacity to adapt their abilities to previously unencountered problems and tasks [15,[99][100][101], the following assessment methods have been proposed:

•
Standardised assessments, such as hands-on laboratory work and structured clinical assessments; • Reflective learning, involving self-analysing of a person's own experiences and learning from past behaviours in order to maintain up-to-date knowledge and skills; • Capstone projects; • Electronic examination that contains different written examination formats, including short-answer, multiple-choice questions as an option.

Guided by Ethics
Longo et al. [102] emphasised that ethics is expected to fuel a symbiotic relationship between humans and the cyber-physical world in Industry 5.0. Ethics principles can be related to (i) the design and development of digital technologies, (ii) the technologies themselves, and (iii) the use of digital technologies. However, there is currently still a lack of a robust framework that teaches ethical conduct and professional accountability for learners to engage with and deepen their understanding of the ethical issues related to digital health.

Conclusions
Industry 5.0 emphasises the importance of human-centric design and aims to create a more equitable and sustainable future by balancing the benefits of technology with the needs of people. Industry 5.0 can help address equity issues in health, for example, by ensuring that digital health solutions are accessible, affordable, and culturally sensitive. This can be achieved by involving diverse stakeholders, including patients, caregivers, healthcare providers, and community organisations in the design, development, and implementation of digital health solutions. Hence, this project aimed to identify how educators can move to integrate Industry 5.0 technologies into pedagogical interventions that support students in developing sophisticated and transferable skills in the new worlds of work they will be entering. In order to help educators better understand the potential of these technologies for improving students' learning outcomes, the proposed learning and teaching framework highlights the importance of pedagogical methods, technologies, and assessment strategies that support a skilled workforce of the future. Life-long learning, with its focus on hands-on experience, critical thinking, and collaboration, is an effective approach for equipping healthcare students with the skills and knowledge necessary for success in this rapidly evolving industry. However, there is a need for a comprehensive overhaul of existing academic curricula and learning and teaching strategies to ensure that students are prepared for the complex challenges of Industry 5.0.
Further research is needed to explore strategies for embedding Industry 5.0 technologies into academic curricula and for developing a robust framework for teaching ethical conduct and professional accountability in the context of digital health. The ultimate goal is to create healthcare solutions that are both sustainable and resilient and prioritise the needs of patients and the larger community. This could include research on the use of virtual and augmented reality in education, the development of personalised learning experiences, and the impact of Industry 5.0 technologies on student outcomes. Additionally, further research could explore the ethical implications of using these technologies in education and the role of educators in preparing students for the ethical challenges posed by Industry 5.0.

Acknowledgments:
We would like to acknowledge the support of RMIT University and Deakin University for providing resources and facilities to conduct this research.

Conflicts of Interest:
The authors declare no conflict of interest.

Appendix A
Appendix A provides a comprehensive overview of the graduate certifications related to digital health offered by Australian universities. Table A1 provides detailed information on the entry requirements for each degree, the subjects and topics that will be covered, and the learning outcomes. This comprehensive overview will help potential students determine which program is the best fit for their career goals.  Bachelor's degree (or higher qualification) in any discipline or diploma in any discipline followed by at least three (3) years professional experience, including at least one year in a supervisory or leadership role in any field Complete all of the following: