The CARE Workshop on Robotics and AI in Medicine, held on December 1, 2025 in Indianapolis, convened leading researchers, clinicians, industry innovators, and federal stakeholders to shape a national vision for advancing robotics and artificial intelligence in healthcare. The event highlighted the accelerating need for coordinated research efforts that bridge engineering innovation with real clinical priorities, emphasizing safety, reliability, and translational readiness with an emphasis on the use of robotics and AI to achieve this readiness goal. Across keynotes, panels, and breakout sessions, participants underscored critical gaps in data availability, standardized evaluation methods, regulatory pathways, and workforce training that hinder the deployment of intelligent robotic systems in surgical, diagnostic, rehabilitative, and assistive contexts. Discussions emphasized the transformative potential of AI enabled robotics to improve precision, reduce provider burden, expand access to specialized care, and enhance patient outcomes particularly in undeserved regions and high risk procedural domains. Special attention was given to austere settings, disaster and relief and military settings. The workshop demonstrated broad consensus on the urgency of establishing a national Center for AI and Robotic Excellence in medicine (CARE). Stakeholders identified priority research thrusts including human robot collaboration, trustworthy autonomy, simulation and digital twins, multi modal sensing, and ethical integration of generative AI into clinical workflows. Participants also articulated the need for high quality datasets, shared test beds, autonomous surgical systems, clinically grounded benchmarks, and sustained interdisciplinary training mechanisms.
Abstract Introduction Existing quantitative studies of violence victimization in Brazil often examine individual demographic and socioeconomic risk factors, limiting insight into how identities can intersect to co-produce vulnerability or resilience. This study uses a nationally representative household survey to investigate how demographic, socioeconomic, and geographic factors intersect to shape the probability of experiencing psychological, physical, and sexual violence among Brazilian adults. Methods Data from the 2019 Brazil National Health Survey was used to created indicators of 12-month experience of three types of interpersonal violence (psychological, physical, and sexual), a measure of any violence and one indicating 2 or more types. Previous literature guided the development of 356 clusters of intersectional identities based on demographic, socioeconomic and other factors. Analyses used the intersectional multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) approach based on multilevel analyses of all 356 intersectional strata in addition to individual-level factors. Results Among Brazilian adults, 18.3% (totaling 27,535,272) reported experiencing interpersonal violence and 3.7% experienced more than one type in the past 12 months. Psychological violence (17.4%) was most frequently reported, followed by physical (4.6%) and sexual (0.8%) violence. MAIHDA models revealed that prevalence and risk varied widely across intersectional strata, but that younger age (< 30), being single, living in an urban area, and living with a long-term illness or disability were consistently found in the strata with highest predicted probability of victimization across all types of violence. Being female, being Black, having a college-level education, and being in the lowest wealth tertile were also commonly found in the highest ranked strata across forms of violence victimization. The overall variance attributable to intersectional (as opposed to individual) effects was between 9.3% and 13.0% across different forms of violence, suggesting that risk of experiencing (or reporting) interpersonal violence in this study accumulates largely in additive rather than multiplicative ways. Conclusions This study found that experiences of psychological, physical, and sexual interpersonal violence were patterned by intersecting social and economic inequalities, with higher risk among women, younger adults, Black or Brown individuals, those who are single, urban residents, and people living with long-term health problems. MAIHDA analyses revealed that risk accumulated across overlapping social positions—particularly among young, single, urban Black women with chronic conditions—highlighting the need for violence prevention strategies that address structural drivers of gender, racial, and socioeconomic inequality. Clinical trial number Not applicable.
Traditional Chinese Medicine (TCM), as an effective alternative medicine, has been receiving increasing attention. In recent years, the rapid development of large language models (LLMs) tailored for TCM has highlighted the urgent need for an objective and comprehensive evaluation framework to assess their performance on real-world tasks. However, existing evaluation datasets are limited in scope and primarily text-based, lacking a unified and standardized multimodal question-answering (QA) benchmark. To address this issue, we introduce TCM-Ladder, the first comprehensive multimodal QA dataset specifically designed for evaluating large TCM language models. The dataset covers multiple core disciplines of TCM, including fundamental theory, diagnostics, herbal formulas, internal medicine, surgery, pharmacognosy, and pediatrics. In addition to textual content, TCM-Ladder incorporates various modalities such as images and videos. The dataset was constructed using a combination of automated and manual filtering processes and comprises over 52,000 questions. These questions include single-choice, multiple-choice, fill-in-the-blank, diagnostic dialogue, and visual comprehension tasks. We trained a reasoning model on TCM-Ladder and conducted comparative experiments against nine state-of-the-art general domain and five leading TCM-specific LLMs to evaluate their performance on the dataset. Moreover, we propose Ladder-Score, an evaluation method specifically designed for TCM question answering that effectively assesses answer quality in terms of terminology usage and semantic expression. To the best of our knowledge, this is the first work to systematically evaluate mainstream general domain and TCM-specific LLMs on a unified multimodal benchmark. The datasets and leaderboard are publicly available at https://tcmladder.com and will be continuously updated.
Abstract Background Existing evidence indicates that Muslim minorities underutilize mental health services despite a pressing need. Employing the Theory of Planned Behavior (TPB), this study seeks to explore considerations that influence mental health help-seeking by Muslims residing in California and Israel. Methods A qualitative approach involving semi-structured interviews guided by the TPB principles was implemented with 78 Muslim participants. Thematic analysis was conducted to identify key themes. Results Employing both deductive and inductive approaches, four major themes were identified: attitudes (advantages, disadvantages, and the influence of religiosity), subjective norms (the impact of significant others), perceived behavioral control (facilitators and challenges), and intentions toward seeking mental health support (influenced by gender, and prior experience). Common social and cultural norms were identified in both groups within the patterns of the TPB. The family's significance as a supportive resource emerged in both groups, but the extended family had a more profound impact among Muslims in Israel. Stigma as a barrier against seeking mental health help was stronger among Muslims in Israel, while financial barriers and socio-political context were highlighted more by Californian Muslims. Conclusions The findings highlighted the importance of adopting a holistic approach to mental health help-seeking among Muslims due to commonalities in approaches, irrespective of geographical differences. Variance between the two groups primarily stemmed from social factors, particularly stigma and the influence of extended family. The results underscore the universality of common aspects and emphasize the importance of addressing social norms and socio-economic realities to enhance engagement among Muslims in both countries.
Introduction: This article is part of the Focus Theme of METHODS of Information in Medicine on "Managing Interoperability and Complexity in Health Systems". Background: The proliferation of archetypes as a means to represent information of Electronic Health Records has raised the need of binding terminological codes - such as SNOMED CT codes - to their elements, in order to identify them univocally. However, the large size of the terminologies makes it difficult to perform this task manually. Objectives: To establish a baseline of results for the aforementioned problem by using off-the-shelf string comparison-based techniques against which results from more complex techniques could be evaluated. Methods: Nine Typed Comparison METHODS were evaluated for binding using a set of 487 archetype elements. Their recall was calculated and Friedman and Nemenyi tests were applied in order to assess whether any of the methods outperformed the others. Results: Using the qGrams method along with the 'Text' information piece of archetype elements outperforms the other methods if a level of confidence of 90% is considered. A recall of 25.26% is obtained if just one SNOMED CT term is retrieved for each archetype element. This recall rises to 50.51% and 75.56% if 10 and 100 elements are retrieved respectively, that being a reduction of more than 99.99% on the SNOMED CT code set. Conclusions: The baseline has been established following the above-mentioned results. Moreover, it has been observed that although string comparison-based methods do not outperform more sophisticated techniques, they still can be an alternative for providing a reduced set of candidate terms for each archetype element from which the ultimate term can be chosen later in the more-than-likely manual supervision task.
Thomas Savage, Stephen Ma, Abdessalem Boukil
et al.
Large Language Model (LLM) fine tuning is underutilized in the field of medicine. Two of the most common methods of fine tuning are Supervised Fine Tuning (SFT) and Direct Preference Optimization (DPO), but there is little guidance informing users when to use either technique. In this investigation, we compare the performance of SFT and DPO for five common natural language tasks in medicine: Classification with text data, Classification with numeric data, Clinical Reasoning, Summarization, and Clinical Triage. We find that SFT alone is sufficient for Classification with text data, whereas DPO improves performance for the more complex tasks of Clinical Reasoning, Summarization and Clinical Triage. Our results establish the role and importance of DPO fine tuning within medicine, and consequently call attention to current software gaps that prevent widespread deployment of this technique.
Generative artificial intelligence (AI) has brought revolutionary innovations in various fields, including medicine. However, it also exhibits limitations. In response, retrieval-augmented generation (RAG) provides a potential solution, enabling models to generate more accurate contents by leveraging the retrieval of external knowledge. With the rapid advancement of generative AI, RAG can pave the way for connecting this transformative technology with medical applications and is expected to bring innovations in equity, reliability, and personalization to health care.
Krystian Strzałka, Szymon Mazurek, Maciej Wielgosz
et al.
This paper explores the innovative use of simulation environments to enhance data acquisition and diagnostics in veterinary medicine, focusing specifically on gait analysis in dogs. The study harnesses the power of Blender and the Blenderproc library to generate synthetic datasets that reflect diverse anatomical, environmental, and behavioral conditions. The generated data, represented in graph form and standardized for optimal analysis, is utilized to train machine learning algorithms for identifying normal and abnormal gaits. Two distinct datasets with varying degrees of camera angle granularity are created to further investigate the influence of camera perspective on model accuracy. Preliminary results suggest that this simulation-based approach holds promise for advancing veterinary diagnostics by enabling more precise data acquisition and more effective machine learning models. By integrating synthetic and real-world patient data, the study lays a robust foundation for improving overall effectiveness and efficiency in veterinary medicine.
One of the major barriers to using large language models (LLMs) in medicine is the perception they use uninterpretable methods to make clinical decisions that are inherently different from the cognitive processes of clinicians. In this manuscript we develop novel diagnostic reasoning prompts to study whether LLMs can perform clinical reasoning to accurately form a diagnosis. We find that GPT4 can be prompted to mimic the common clinical reasoning processes of clinicians without sacrificing diagnostic accuracy. This is significant because an LLM that can use clinical reasoning to provide an interpretable rationale offers physicians a means to evaluate whether LLMs can be trusted for patient care. Novel prompting methods have the potential to expose the black box of LLMs, bringing them one step closer to safe and effective use in medicine.
Monte Carlo (MC) techniques are currently deemed the gold standard for internal dosimetry, since the simulations can perform full radiation transport and reach a precision level not attainable by analytical methods. In this study, a custom voxelized particle source was developed for the TOPAS-MC toolkit to be used for internal dosimetry purposes. The source was designed to allow the use of clinical functional scans data to simulate events that reproduce the patient-specific tracer biodistribution. Simulation results are very promising, showing that this can be a first step towards the extension of TOPAS-MC to nuclear medicine applications. In the future more studies are needed to further ascertain the applicability and accuracy of the developed routines.
Abstract Background Polycystic ovary syndrome (PCOS) is known to be associated with chronic low-grade inflammation and endometrial dysfunction. Chronic endometritis (CE) is a type of local inflammation that can contribute to endometrial dysfunction in infertile women. Some clinicians recommend screening for CE in women at high risk, such as those with endometrial polyps. However, it is still uncertain whether there is a relationship between PCOS and CE, as well as whether women with PCOS require enhanced screening for CE. This study was to assess the incidence of CE among infertile women with PCOS by hysteroscopy combined with histopathology CD138 immunohistochemical staining of endometrium. Methods A total of 205 patients in the PCOS group and 4021 patients in the non-PCOS group from July 2017 to August 2022 were included in this retrospective study. After nearest-neighbor 1:4 propensity score matching (PSM), 189 PCOS patients were matched with 697 non-PCOS patients. Basic information was recorded. The CE incidence was compared. The risk factors affecting CE incidence were also analyzed. Results No significantly higher CE incidence in infertile women with PCOS were found either in total analysis or after PSM (P = 0.969; P = 0.697; respectively). Similar results were discovered in the subgroup of Body Mass Index (BMI) (P = 0.301; P = 0.671; P = 0.427; respectively) as well as the four PCOS phenotypes (P = 0.157). Intriguingly, the incidence of CE increased as BMI increased in the PCOS group, even though no significant differences were found (P = 0.263). Multivariate logistic regression showed that age, infertility duration, infertility type, PCOS, and obesity were not the independent risk factors affecting CE incidence. Conclusion The incidence of CE in PCOS patients did not significantly increase compared to non-PCOS patients. Similarly, no significant differences in the incidence of CE were observed among different PCOS phenotypes. The current evidence does not substantiate the need for widespread CE screening among PCOS women, potentially mitigating the undue financial and emotional strain associated with such screenings.
Gynecology and obstetrics, Public aspects of medicine
Objective: This study was aimed to determine the level of knowledge of reproductive rights and related factors among youths of Bule Hora town, 2021. Methods: A Community-based cross-sectional study was carried out among youths of Bule Hora Town from February 1 to 30, 2021. A systematic random sampling method was used to select 407 youths. A pretested face-to-face interview of a structured questionnaire was used to collect the data. The data entry was performed by using EPI-DATA Version 3.1 and transferred to SPSS version 23 for analysis. Bivariable and multivariable logistic regression analysis was done to find the factors related to knowledge of reproductive rights. Adjusted odds ratios (AOR) with 95% CI at a p-value <0.05 were assessed to measure the strength of associations and statistical significance. Results: More than half 241(59.2%), [95% CI (54.4, 63.9)] of the respondents had adequate knowledge about reproductive rights. Educational status of being primary [AOR = 4.75(1.60, 14.14)], secondary [AOR = 3.69(1.26, 10.79)] and college and above [AOR = 3.43(1.09, 10.74)], Counseled for reproductive health matters [AOR = 1.67(1.04, 2.69)], ever joined in reproductive health clubs [AOR = 2.10(1.34, 3.28)] and ever discussed reproductive health matters [AOR = 1.83(1.17, 2.87)] were significantly associated with knowledge of reproductive rights. Conclusion: The level of knowledge about the reproductive right of the youths is found to be inadequate. Being primary, secondary, college and above, counseled about reproductive health matters, joined in reproductive health clubs, and discussed reproductive matters were factors affecting knowledge of reproductive rights.
Abstract Background The COVID-19 pandemic has impacted medical professionals’ job satisfaction and was a call to adopt telemedicine. Finding out how far medical professionals are satisfied and ready to use telemedicine would be important to improve medical practice. Methods Data was collected from 959 medical professionals from both the governmental and private health sectors in Egypt in 2021 using a specifically designed online questionnaire, to evaluate job satisfaction, perception of telemedicine, and propose solutions to improve medical practice. Results The study revealed low to moderate job satisfaction at governmental (27.2%) and private (58.7%) sectors. Underpayment was the most reported challenge at both sectors (37.8% and 28.3%, respectively). Dissatisfaction with government salary was independently predicted by working at the Ministry of Health and Population (OR = 5.54, 95%CI = 2.39,12.8; p < 0.001). Wage increase (46.10%), medical training of professionals (18.1%), and management of non-human resources (14.4%) were the most proposed solutions to improve medical practice in Egypt. During the COVID-19 pandemic, 90.7% of medical professionals had practiced telemedicine with moderate level of perception of its benefits (56%). Conclusions During the COVID-19 pandemic, medical professionals reported low to moderate job satisfaction and a moderate level of perception of telemedicine. It is recommended to analyze the healthcare financing system and provide continuous training of medical professionals to improve medical practice in Egypt.
Arctic medicine. Tropical medicine, Public aspects of medicine
S. Tilghman, B. Alberts, Daniel A. Colón-Ramos
et al.
Any barrier to entry weakens science and its societal impact The recent events that precipitated the resurgence of the Black Lives Matter movement and the disproportionately devastating impact of COVID-19 on many communities of color are stark reminders of the pernicious effects of systemic racism on all aspects of our society, including science, medicine, and public health. The lack of diversity in the scientific and health professions—a longstanding manifestation of racism—can no longer be ignored, excused, or attributed to uncontrollable factors. We write at this moment of reckoning to explain what is lost by a lack of diversity; to describe some promising efforts to achieve it; and to propose urgent, larger-scale actions that political and institutional leaders, educators, and scientists can take to redress the inequities that pervade our professions.
Xue-Yan Zhang, Hao-Jie Huang, Donglin Zhuang
et al.
Background The outbreak of coronavirus disease 2019 (COVID-19) has caused a public catastrophe and global concern. The main symptoms of COVID-19 are fever, cough, myalgia, fatigue and lower respiratory tract infection signs. Almost all populations are susceptible to the virus, and the basic reproduction number ( R 0 ) is 2.8–3.9. The fight against COVID-19 should have two aspects: one is the treatment of infected patients, and the other is the mobilization of the society to avoid the spread of the virus. The treatment of patients includes supportive treatment, antiviral treatment, and oxygen therapy. For patients with severe acute respiratory distress syndrome (ARDS), extracorporeal membrane oxygenation (ECMO) and circulatory support are recommended. Plasma therapy and traditional Chinese medicine have also achieved good outcomes. This review is intended to summarize the research on this new coronavirus, to analyze the similarities and differences between COVID-19 and previous outbreaks of severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) and to provide guidance regarding new methods of prevention, diagnosis and clinical treatment based on autodock simulations. Methods This review compares the multifaceted characteristics of the three coronaviruses including COVID-19, SARS and MERS. Our researchers take the COVID-19, SARS, and MERS as key words and search literatures in the Pubmed database. We compare them horizontally and vertically which respectively means concluding the individual characteristics of each coronavirus and comparing the similarities and differences between the three coronaviruses. Results We searched for studies on each outbreak and their solutions and found that the main biological differences among SARS-CoV-2, SARS-CoV and MERS-CoV are in ORF1a and the sequence of gene spike coding protein-S. We also found that the types and severity of clinical symptoms vary, which means that the diagnosis and nursing measures also require differentiation. In addition to the common route of transmission including airborne transmission, these three viruses have their own unique routes of transmission such as fecal-oral route of transmission COVID-19. Conclusions In evolutionary history, these three coronaviruses have some similar biological features as well as some different mutational characteristics. Their receptors and routes of transmission are not all the same, which makes them different in clinical features and treatments. We discovered through the autodock simulations that Met124 plays a key role in the efficiency of drugs targeting ACE2, such as remdesivir, chloroquine, ciclesonide and niclosamide, and may be a potential target in COVID-19.
Background: The activities of traders and visitors in the market have potential hazards that pose safety and health risks. Thus, understanding the risks and the threats is a necessity.
Objective: This study aimed to identify hazards, analyze safety and health risks, and design risk control efforts that market managers can apply.
Methods: This research was qualitative research with an observational approach. The informants were selected purposively: the head of the Siteba Market Technical Implementation Unit, security officers, traders, and visitors at the Siteba Market, Padang City, Indonesia. The instruments used were checklists and interview guides. Risks were analyzed manually based on the AS/NZS 4360 standard matrix.
Results: The research results using the elicitation method identified ten potential safety and health hazards in Siteba Market. The safety and health risks for traders and visitors to Siteba Market consisted of seven high risks and three medium risks. Potential high risks were accidents, pickpockets, fatigue, slipping, falling, and jostling during emergencies and fires. Meanwhile, the potential risks consisted of traffic jams, indigestion, and scattered merchandise.
Conclusion: Traders and visitors were potentially exposed to safety and health. Community organizing efforts through the occupational health business post need to be activated by the health centers to carry out preventive and promotive measures for safety and health in the market.
Philip Spinhoven, Garazi Zulaika, Elizabeth Nyothach
et al.
<h4>Background</h4> Adolescents in sub-Saharan Africa often report low levels of quality of life (QoL) and well-being, but reliable data are limited. This study examines which sociodemographic, health, and behavioral risk factors and adverse adolescent experiences are associated with, and predictive of, QoL in Kenyan secondary schoolgirls. <h4>Methods and findings</h4> 3,998 girls at baseline in a randomised controlled trial in Siaya County, western Kenya were median age 17.1 years. Subjectively perceived physical, emotional, social and school functioning was assessed using the Pediatric Quality of Life (QoL) Inventory-23. Laboratory-confirmed and survey data were utilized to assess sociodemographic, health and behavioral characteristics, and adverse adolescent experiences. We identified a group of girls with Low QoL (n = 1126; 28.2%), Average QoL (n = 1445; 36.1%); and High QoL (n = 1427; 35.7%). Significantly higher scores on all well-being indicators in the LQoL compared with HQoL group indicated good construct validity (Odds Ratio’s (ORs) varying from 3.31 (95% CI:2.41–4.54, p < .001) for feeling unhappy at home to 11.88 (95%CI:7.96–17.74, p< .001) for PHQ9 defined possible caseness (probable diagnosis) of depression. Adverse adolescent experiences were independently statistically significant in the LQoL compared to the HQoL group for threats of family being hurt (aOR = 1.35,1.08–1.68, p = .008), sexual harassment out of school (aOR = 2.17,1.79–2.64, p < .001), and for menstrual problems like unavailability of sanitary pads (aOR = 1.23,1.05–1.44, p = .008) and stopping activities due to menstruation (aOR = 1.77,1.41–2.24, p < .001). After 2-years follow-up of 906 girls in the LQoL group, 22.7% persisted with LQoL. Forced sex (aOR = 1.56,1.05–2.32, p = .028) and threats of family being hurt (aOR = 1.98,1.38–2.82, p < .001) were independent predictors of persistent LQoL problems. <h4>Conclusions</h4> Persistent QoL problems in Kenyan adolescent girls are associated with adverse physical, sexual and emotional experiences and problems with coping with their monthly menstruation. A multi-factorial integral approach to reduce the rate of adverse adolescent experiences is needed, including provision of menstrual hygiene products. <h4>Trial registration</h4> ClinicalTrials.gov:NCT03051789.
As corona virus disease 2019 (COVID-19) is a rapidly growing public health crisis across the world, our knowledge of meaningful diagnostic tests and treatment for severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) is still evolving. This novel coronavirus disease COVID-19 can be diagnosed using RT-PCR, but inadequate access to reagents, equipment, and a nonspecific target has slowed disease detection and management. Precision medicine, individualized patient care, requires suitable diagnostics approaches to tackle the challenging aspects of viral outbreaks where many tests are needed in a rapid and deployable approach. Mass spectrometry (MS)-based technologies such as proteomics, glycomics, lipidomics, and metabolomics have been applied in disease outbreaks for identification of infectious disease agents such as virus and bacteria and the molecular phenomena associated with pathogenesis. Matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF/MS) is widely used in clinical diagnostics in the United States and Europe for bacterial pathogen identification. Paper spray ionization mass spectrometry (PSI-MS), a rapid ambient MS technique, has recently open a new opportunity for future clinical investigation to diagnose pathogens. Ultra-high-pressure liquid chromatography coupled high-resolution mass spectrometry (UHPLC–HRMS)-based metabolomics and lipidomics have been employed in large-scale biomedical research to discriminate infectious pathogens and uncover biomarkers associated with pathogenesis. PCR-MS has emerged as a new technology with the capability to directly identify known pathogens from the clinical specimens and the potential to identify genetic evidence of undiscovered pathogens. Moreover, miniaturized MS offers possible applications with relatively fast, highly sensitive, and potentially portable ways to analyze for viral compounds. However, beneficial aspects of these rapidly growing MS technologies in pandemics like COVID-19 outbreaks has been limited. Hence, this perspective gives a brief of the existing knowledge, current challenges, and opportunities for MS-based techniques as a promising avenue in studying emerging pathogen outbreaks such as COVID-19.
The legacy of colonial rule has permeated into all aspects of life and contributed to healthcare inequity. In response to the increased interest in social justice, medical educators are thinking of ways to decolonise education and produce doctors who can meet the complex needs of diverse populations. This paper aims to explore decolonising ideas of healing within medical education following recent events including the University College London Medical School’s Decolonising the Medical Curriculum public engagement event, the Wellcome Collection’s Ayurvedic Man: Encounters with Indian Medicine exhibition and its symposium on Decolonising Health, SOAS University of London’s Applying a Decolonial Lens to Research Structures, Norms and Practices in Higher Education Institutions and University College London Anthropology Department’s Flourishing Diversity Series. We investigate implications of ‘recentring’ displaced indigenous healing systems, medical pluralism and highlight the concept of cultural humility in medical training, which while challenging, may benefit patients. From a global health perspective, climate change debates and associated civil protests around the issues resonate with indigenous ideas of planetary health, which focus on the harmonious interconnection of the planet, the environment and human beings. Finally, we look further at its implications in clinical practice, addressing the background of inequality in healthcare among the BAME (Black, Asian and minority ethnic) populations, intersectionality and an increasing recognition of the role of inter-generational trauma originating from the legacy of slavery. By analysing these theories and conversations that challenge the biomedical view of health, we conclude that encouraging healthcare educators and professionals to adopt a ‘decolonising attitude’ can address the complex power imbalances in health and further improve person-centred care.