“I Believe in You”: Student Experiences of Faculty Empathy in Health Sciences Education

The Association of Doctoral Programs in Health Sciences (ADPHS) was informally established in November 2019, officially incorporated in August 2021, and is currently a 501(c)(3) nonprofit organization comprised of the directors of member doctoral programs of health sciences. The ADPHS grew from informal discussions among program directors who agreed that a major problem in the field of doctoral education in health sciences was the lack of a clearly defined and easily articulable identity. The discussions led to the drafting of an informal and nonscientific survey used to help clarify the current health sciences education environment, relevant emerging trends, and the educational philosophies adopted by the directors of health sciences doctoral programs nationally. The results of the survey and follow-up discussions revealed a strong consensus among program directors that the field of doctorate education in health sciences is uniformly characterized by its interdisciplinary nature. In this position paper, we provide the rationale for the formal position of the ADPHS that the identity of the field of doctoral education in health sciences is based on its interdisciplinary approach to education.

This article explores the impact and implications of Artificial Intelligence (AI) on Health Sciences and related education. With a focus on medical diagnostics, treatment personalisation, and hospital management, the article highlights how AI has the potential to revolutionize both practice and research in healthcare. Concurrently, the text examines the increasing role of AI in Health Sciences education, addressing its contribution to the personalisation of learning, realistic simulations, and automated assessments. However, the article also draws attention to the inherent challenges of AI implementation, including issues of accuracy, ethics, privacy, and equal access. The concluding remarks offer an ambivalent view, recognizing both the transformative opportunities and the ethical and technical challenges of AI in Health Sciences. The article anticipates the undertaking of a subsequent study, a training needs survey, aimed at exploring how teachers have been utilizing AI in Health Sciences. Based on these insights, a targeted training programme for teachers in the field of health sciences will be developed, whose impact and effectiveness will be carefully evaluated.

Using the Mobile Augmented Reality Acceptance Model, this study examines the motivations of current health science and medical ‎educators to incorporate MAR in their teaching methods. The MARAM augments the Technology Acceptance Model (TAM) by offering ‎proportional benefits, enjoyment, and ease of use, mobile self-efficacy, information seeking, flow, and novelty. Additionally, this study ‎examines MARAM validity. This study aimed to evaluate how well students learnt when the same material was presented in an augmented ‎reality environment. Professors from medical institutes received 370 questionnaires; 325 of them were determined to include information ‎that was appropriate for the study. Structural equation modeling with partial least squares is used to test the relationships among variables. Consumers are much more likely to use mobile augmented reality if they think it will save them time, be convenient, be fun, and ‎give them confidence. Additionally, empirical findings indicate that flow and information-seeking tendencies have a significant impact on ‎usage intention, whereas the role of novelty is comparatively minimal. These findings further emphasize the roles of immersion and perceived usefulness as mediators of the favorable outcomes from AR purchasing.

Artificial Intelligence (AI) is revolutionizing the field of health sciences, reshaping how we teach, learn, and practice medicine. As AI technologies become increasingly integrated into healthcare systems, their impact on health sciences education cannot be overstated. From personalized learning experiences to advanced diagnostic training, AI is poised to enhance the quality and accessibility of education for future healthcare professionals. However, this transformation also raises critical questions about ethics, equity, and the future role of educators in an AI-driven world. The transformative role of Artificial Intelligence (AI) in health sciences education is increasingly recognized as a pivotal factor in shaping the future of medical training and practice. As AI technologies continue to evolve, their integration into educational curricula presents both opportunities and challenges that must be carefully navigated to enhance the learning experience for future healthcare professionals. One of the most significant contributions of AI to health sciences education is its ability to personalize learning. Traditional teaching methods often follow a one-size-fits-all approach, which can leave some students struggling to keep up while others are not sufficiently challenged. AI-powered platforms, such as adaptive learning systems, analyze individual student performance and tailor content to meet their unique needs. For example, tools like Osmosis and AMBOSS use AI to provide customized study plans, ensuring that students focus on areas where they need the most improvement (Topol, 2019). This personalized approach not only improves learning outcomes but also fosters a more inclusive educational environment. AI is also transforming clinical training by simulating real-world scenarios. Virtual patient simulations, powered by AI, allow students to practice diagnosing and treating conditions in a risk-free environment. These simulations can replicate rare or complex cases that students might not encounter during their clinical rotations. For instance, platforms like Touch Surgery and SimX use AI to create immersive surgical and emergency care simulations, providing students with hands-on experience before they enter the operating room (McGaghie et al., 2011). Such tools bridge the gap between theory and practice, preparing students for the complexities of modern healthcare. Moreover, AI is enhancing the role of educators by automating administrative tasks and providing data-driven insights into student performance. Grading, attendance tracking, and even curriculum design can be streamlined using AI, allowing educators to focus on mentoring and engaging with students. AI-driven analytics can also identify at-risk students early, enabling timely interventions to support their academic success (Wartman & Combs, 2018). By augmenting the capabilities of educators, AI empowers them to deliver more impactful and student-centered teaching. AI's potential to revolutionize health sciences education lies in its ability to personalize learning experiences and improve educational outcomes. For instance, AI-driven tools can facilitate realistic simulations and automated assessments, allowing students to engage in practical scenarios that mimic real-world clinical situations (Santos & Lopes, 2024). This capability not only enhances the learning process but also prepares students for the complexities of patient care in a technology-driven environment (Grunhut et al., 2022). Furthermore, the incorporation of AI into curricula can foster critical thinking and decision-making skills, essential for navigating the ethical dilemmas that arise in medical practice (Grunhut et al., 2022). Despite the promising applications of AI in education, the integration of these technologies into medical curricula has been slow. A scoping review highlighted that many medical schools have yet to adopt AI training, primarily due to a lack of systematic evidence supporting its implementation (Lee et al., 2021). Additionally, concerns regarding data protection and the ethical implications of AI use in healthcare education have been raised, indicating a need for comprehensive AI education that addresses these issues (Veras et al., 2023; Frehywot & Vovides, 2023). Students have expressed a desire for more robust training in AI, emphasizing the importance of understanding its role in healthcare delivery and decision-making processes (Ahmad et al., 2023; Derakhshanian et al., 2024). Moreover, the rapid advancement of AI technologies necessitates continuous curriculum updates to keep pace with emerging trends. As noted in recent literature, the integration of AI into biomedical science curricula should include subjects related to informatics, data sciences, and digital health (Sharma et al., 2024). This approach not only equips students with the necessary skills to utilize AI effectively but also prepares them for the evolving landscape of healthcare, where AI will play an integral role in diagnostics, treatment personalization, and patient management (Santos & Lopes, 2024; Secinaro et al., 2021). However, the implementation of AI in health sciences education is not without challenges. Ethical considerations surrounding AI's impact on healthcare equity and the potential for bias in AI algorithms must be addressed (Frehywot & Vovides, 2023; Han et al., 2019). Ensuring that AI technologies are used responsibly and equitably in education and practice is crucial to avoid exacerbating existing disparities in healthcare access and outcomes (Rigby, 2019). Furthermore, the lack of faculty expertise in AI poses a significant barrier to its integration into medical education, highlighting the need for targeted training and resources for educators (Derakhshanian et al., 2024). However, the integration of AI into health sciences education is not without challenges. Ethical concerns, such as data privacy and algorithmic bias, must be addressed to ensure that AI tools are used responsibly. Additionally, there is a risk of over-reliance on AI, potentially undermining the development of critical thinking and clinical judgment skills. Educators must strike a balance between leveraging AI’s capabilities and preserving the human elements of teaching and learning. Equity is another pressing issue. While AI has the potential to democratize education, access to these technologies remains uneven. Institutions in low-resource settings may struggle to adopt AI-driven tools, exacerbating existing disparities in global health education. Policymakers and educators must work together to ensure that the benefits of AI are accessible to all, regardless of geographic or socioeconomic barriers. In conclusion, AI is a powerful tool that holds immense promise for transforming health sciences education. By personalizing learning, enhancing clinical training, and supporting educators, AI can help prepare the next generation of healthcare professionals to meet the demands of an increasingly complex healthcare landscape. However, its integration must be guided by ethical principles and a commitment to equity, However, the successful integration of AI into educational curricula requires a concerted effort to address ethical concerns, update training programs, and equip both students and faculty with the necessary knowledge and skills. As the healthcare landscape continues to evolve, embracing AI in education will be essential for fostering a new generation of healthcare providers who are adept at leveraging technology to improve patient care. As we embrace this technological revolution, we must remember that AI is not a replacement for human expertise but a complement to it. The future of health sciences education lies in the synergy between human ingenuity and artificial intelligence.

IUBMB/PSBMB 2019 Conference/Plenary: Mentoring in postgraduate training and the role of Organization for PhD Education in Health Sciences in European System.

This article presents health science educators and researchers with an overview of standardized testing in educational measurement. The history, theoretical frameworks of classical test theory, item response theory (IRT), and the most common IRT models used in modern testing are presented. A narrative overview of the history, theoretical concepts, test theory, and IRT is provided to familiarize the reader with these concepts of modern testing. Examples of data analyses using different models are shown using 2 simulated data sets. One set consisted of a sample of 2000 item responses to 40 multiple-choice, dichotomously scored items. This set was used to fit 1-parameter logistic (PL) model, 2PL, and 3PL IRT models. Another data set was a sample of 1500 item responses to 10 polytomously scored items. The second data set was used to fit a graded response model. Model-based item parameter estimates for 1PL, 2PL, 3PL, and graded response are presented, evaluated, and explained. This study provides health science educators and education researchers with an introduction to educational measurement. The history of standardized testing, the frameworks of classical test theory and IRT, and the logic of scaling and equating are presented. This introductory article will aid readers in understanding these concepts.

Working within a scholarship of teaching and learning (SoTL) perspective requires a rigorous approach based on conceptual frameworks in order to build on previous developments. Nevertheless, in health sciences education, the development, implementation, and evaluation of many educational innovations are carried out without an underlying conceptual framework, partly due to a lack of knowledge about any such applicable framework. The objective of this research was to catalogue conceptual frameworks mentioned in recently published health sciences education articles and to classify them according to their use in various SoTL contexts. A literature review in health sciences education from the January, 2011 to March, 2016 period was carried out using the Pubmed, CINAHL, Embase, ERIC, and PsychINFO databases and based on the following terms: (a) theories and models; (b) education; and (c) health professionals. The titles and abstracts of articles were reviewed for purposes of including research articles, innovation reports, and synthesis articles using or discussing theories or models. Data extraction followed the SoTL classification contexts provided by Simpson et al. (2007). A total of 471 articles were selected, retrieving 324 conceptual theories and models, classified according to Simpson’s classification in one or more categories: Teaching (n=294), Curriculum development (n=182), Mentoring (n=12), Leadership/administration (n=16), and Learner assessment (n=78). In conclusion, this literature review identified conceptual theories and models mentioned in articles published in health sciences education from 2011 to 2016. This repertory highlights the importance of conceptual frameworks in health science education. It should encourage faculty members to work from a SoTL perspective by making it easier to identify conceptual frameworks pertaining to the educational innovations they are addressing.

The role of health science education in creating awareness of malaria predisposing factors among secondary school students in Owerri Education Zone I of Imo State Nigeria was examined using survey design. A survey research design was adopted for the study. Two research questions and two hypotheses guided the study. A sample size of 399 Health Science Education students was selected as the sample size in line with Taro Yamane formula and cluster random sampling technique. Rating scale titled “Health Science Education and Malaria Predisposing Factors Awareness Rating Scale” (HSEMPFARS) designed by the researcher was used for data collection. Using Cronbach alpha statistics, the HSEMPFARS' dependability coefficient was 0.86. Mean scores and standard deviation were used to answer the research questions, and the one sample t-test and independent samples t-test were used to evaluate the hypothesis. Findings showed that exposure to health science education helps students to a high extent to be aware of malaria predisposing factors and preventive measures; no significant difference was observed in the responses of students on their awareness of predisposing factors based on gender. In light of these findings, the researcher recommended that Health science education instructors should be consistent in their teaching about malaria predisposing factors and awareness as this would help sustain continuous students’ awareness about the disease and that topics like malaria in health education should not be taught with special reference to a particular gender since both male and female students have similar levels of malaria predisposing factors awareness through health science education.

Before health science can play its expected role, health science education needs to be looked at critically and revamped. This area of education needs immediate attention for positive and effective change. This paper is based on observations, deliberations, and supportive findings across the US system of science education. However, with globalization, a lot of it is applicable to other countries. Health science education has been categorized into three categories: Health Science Education in School; in College; And, Beyond College. The paper raises more questions that we need to find workable answers to. It does not, in anyway, claim to provide the best solution, the only answer, or the end to all discussion and development for improvement.

BackgroundRecently, much attention has been given to e-learning in higher education as it provides better access to learning resources online, utilising technology – regardless of learners’ geographical locations and timescale – to enhance learning. It has now become part of the mainstream in education in the health sciences, including medical, dental, public health, nursing, and other allied health professionals. Despite growing evidence claiming that e-learning is as effective as traditional means of learning, there is very limited evidence available about what works, and when and how e-learning enhances teaching and learning. This systematic review aimed to identify and synthesise the factors – enablers and barriers – affecting e-learning in health sciences education (el-HSE) that have been reported in the medical literature.MethodsA systemic review of articles published on e-learning in health sciences education (el-HSE) was performed in MEDLINE, EMBASE, Allied & Complementary Medicine, DH-DATA, PsycINFO, CINAHL, and Global Health, from 1980 through 2019, using ‘Textword’ and ‘Thesaurus’ search terms. All original articles fulfilling the following criteria were included: (1) e-learning was implemented in health sciences education, and (2) the investigation of the factors – enablers and barriers – about el-HSE related to learning performance or outcomes. Following the PRISMA guidelines, both relevant published and unpublished papers were searched. Data were extracted and quality appraised using QualSyst tools, and synthesised performing thematic analysis.ResultsOut of 985 records identified, a total of 162 citations were screened, of which 57 were found to be of relevance to this study. The primary evidence base comprises 24 papers, with two broad categories identified, enablers and barriers, under eight separate themes: facilitate learning; learning in practice; systematic approach to learning; integration of e-learning into curricula; poor motivation and expectation; resource-intensive; not suitable for all disciplines or contents, and lack of IT skills.ConclusionsThis study has identified the factors which impact on e-learning: interaction and collaboration between learners and facilitators; considering learners’ motivation and expectations; utilising user-friendly technology; and putting learners at the centre of pedagogy. There is significant scope for better understanding of the issues related to enablers and facilitators associated with e-learning, and developing appropriate policies and initiatives to establish when, how and where they fit best, creating a broader framework for making e-learning effective.

BackgroundSocial media is an asset that higher education students can use for an array of purposes. Studies have shown the merits of social media use in educational settings; however, its adoption in health science education has been slow, and the contributing reasons remain unclear.ObjectiveThis multidisciplinary study aimed to examine health science students’ opinions on the use of social media in health science education and identify factors that may discourage its use.MethodsData were collected from the Universitas 21 “Use of social media in health education” survey, distributed electronically among the health science staff and students from 8 universities in 7 countries. The 1640 student respondents were grouped as users or nonusers based on their reported frequency of social media use in their education.ResultsOf the 1640 respondents, 1343 (81.89%) use social media in their education. Only 462 of the 1320 (35.00%) respondents have received specific social media training, and of those who have not, the majority (64.9%, 608/936) would like the opportunity. Users and nonusers reported the same 3 factors as the top barriers to their use of social media: uncertainty on policies, concerns about professionalism, and lack of support from the department. Nonusers reported all the barriers more frequently and almost half of nonusers reported not knowing how to incorporate social media into their learning. Among users, more than one fifth (20.5%, 50/243) of students who use social media “almost always” reported sharing clinical images without explicit permission.ConclusionsOur global, interdisciplinary study demonstrates that a significant number of students across all health science disciplines self-reported sharing clinical images inappropriately, and thus request the need for policies and training specific to social media use in health science education.

The digital competence of health sciences educators is important for the delivery and development of modern education and lifelong learning. The aim of the study was to assess the appearance of digital competence in the work of Finnish health sciences educators and to determine whether educators' background factors are related to the areas of digital competence appearance. The European Framework for the Digital Competence of Educators was used as a theoretical background. The participants were Finnish health sciences educators (n = 388). Data were collected by quantitative survey and statistically analyzed. Results show that health sciences educators had participated in continuing education to develop their expertise and used a variety of digital methods and materials. Educators need more competence to improve healthcare students' ability to use digital technology. In the area of Teaching and Learning, educators younger than 40 years rated the appearance of digital competence as better than did those between the ages of 40 and 49 years. In the future, health sciences educators' basic and continuing education could take into account the competence requirements for digital competence, and educators' expertise must be increased in areas where digital competence does not appear strong.

BACKGROUND:Simulation debriefing influences learning from healthcare simulation activities. Health sciences educators must be competent in conducting simulation debriefing for healthcare students. A structured faculty development intervention for health sciences educators must be informed by educator needs to enhance its utility. This paper describes the needs of health sciences educators regarding simulation debriefing at a faculty of health sciences.MATERIALS AND METHODS:A parallel convergent mixed methods study design was applied on a selected population of 30 health sciences educators at the University (x) who integrate immersive simulation for first- to final-year students in their undergraduate programs. The Objective Structured Assessment of Debriefing tool underpinned observations which informed the quantitative strand of the study, while semi-structured interviews were conducted as part of the qualitative strand. Descriptive statistics and thematic analysis were used to analyze the data.RESULTS:Health sciences educators struggled to establish the learning environment for simulation (median 1), facilitate learning (median 3), and evaluate their debriefing activities. However, they were able to apply an appropriate approach toward simulation (median 4). They identified the need to be educated on the fundamentals of simulation-based education.CONCLUSION:A continuing professional development program must be developed aimed at transforming approaches toward facilitating learning, explaining the fundamentals of simulation-based education, modeling of best-practices related to debriefing, and applying appropriate strategies for evaluating debriefing activities.

Health Sciences Online: Eight+ Revolutions and Ten+ Brief Analyses

Introduction An essential attribute of competent health sciences educators (HSEs) is the integration of disciplinary and pedagogical knowledge. However, many HSEs receive little or no formal educational training, raising concerns about their teaching approaches. This study addresses this issue by examining the perceptions of HSEs without formal pedagogical training regarding two central aspects: teaching and learning methods and the roles they assign to themselves and their students. Methods The research employs a qualitative phenomenological case study involving nine HSEs from diverse fields—medical education, nursing, and podiatry—who collaborated in the observation and discussion of their own teaching practices. Discussions held around these observations were inductively analyzed to identify interpretive dimensions related to the participants’ conceptualizations of their own roles, their students’ roles, and their use of teaching and learning methods. Results The findings indicate that, although participants valued methods beyond traditional lectures and acknowledged the importance of aligning teaching with assessment, they simultaneously upheld a lecture format where students primarily act as passive listeners and attributed to external factors—senior faculty or students—the difficulties in implementing more participatory strategies. Regarding their own role, participants emphasized sharing professional experience and serving as role models over content delivery. They perceived their responsibility for student motivation and success in the course as limited, approaching success through grades rather than learning. In terms of the student role, participants expected learners to assume responsibility for their own learning, demonstrated through independent study and in-class participation, distinguishing this from a focus on passing a course and grades. Discussion The study reveals that while HSEs without educational training may express views aligned with educational literature, their interpretations often lack depth, remain teacher-centered, overlook pedagogical nuances, externalize difficulties, and exhibit unacknowledged inconsistencies. These findings highlight the importance of formal educational development programs to foster reflective practice and pedagogical growth among HSEs.