Promoting informed choices: navigating global dental care challenges.

This review article, developed by the EASD Global Council, addresses the growing global challenges in diabetes research and care, highlighting the rising prevalence of diabetes, the increasing complexity of its management and the need for a coordinated international response. With regard to research, disparities in funding and infrastructure between high-income countries and low- and middle-income countries (LMICs) are discussed. The under-representation of LMIC populations in clinical trials, challenges in conducting large-scale research projects, and the ethical and legal complexities of artificial intelligence integration are also considered as specific issues. The development of global research networks and strategies for improved training, standardisation of data and enhanced accessibility to big data analytics to drive innovation and personalised medicine are recommended. With regard to diabetes care, inequalities in access to essential medications, particularly insulin and novel therapies, and disparities in healthcare infrastructure are discussed. Proposed initiatives include international support programmes, improved healthcare provider training and the inclusion of newer diabetes medications in essential drug lists. The importance of global screening programmes, a universal diabetes education curriculum and standardised healthcare checklists is also emphasised. Regarding healthcare organisation, the development of national diabetes registers, benchmarking performance across regions and strengthening international collaborations are highly advised. The role of diabetes specialists as care coordinators and the need for structured assessments to improve early intervention and long-term outcomes are also discussed. Ultimately, the EASD Global Council urges action for a unified, global approach to diabetes research and care to bridge the gap between scientific innovation and clinical practice, ensuring equitable healthcare worldwide.Graphical Supplementary InformationThe online version contains a slideset of the figures for download available at 10.1007/s00125-025-06504-5.

Recruitment and retention of General Practitioners (GPs) is a global challenge in primary care. Traditionally, GPs in the UK have worked as self-employed partners. However, policy changes in England have allowed for salaried GP positions within primary care partnerships. The effects of these different employment models on recruitment and retention remain unclear. This study investigates the impact of partnership vs. salaried employment models on GP job satisfaction, job pressures, and intentions to reduce working hours in England. Data from nine waves of the national GP Worklife Survey (2001-2019) were analysed using multivariate regression models. The analysis adjusted for several GP characteristics, including age, gender, ethnicity, marital status, and number of children. Salaried GPs reported higher satisfaction with working hours but lower satisfaction with income compared to partner GPs. Partner GPs experienced higher job pressures and were more likely to intend to reduce their working hours within five years. Flexible working arrangements, such as salaried positions, may enhance job satisfaction and retention among GPs, helping to address workforce challenges in primary care. Targeted policies are needed to mitigate job pressures and improve satisfaction, particularly among partner GPs.

Background Seeking conventional oral health care for various dental conditions is still a challenge for many worldwide and poses a global public health challenge. It is not until the individual starts experiencing pain and disfigurement of the facial profile that they seek dental care after many self-care interventions have failed. This study sought to determine perceived knowledge, attitude, practice, and satisfaction of dental abscess management among dental abscess patients (DAPs). Methods The research used a cross-sectional design to collect data from patients who visited the Dental Department of Effiduase Government Hospital with dental abscess from 6 May 2020–27 August 2020. A total sample size of 82 was selected from a population of 377. About 76 DAPs who met the inclusion criteria and consented to participate were interviewed. Results About 57% of respondents believed that dental caries caused their abscess. However, 46% sought medical treatment between 0 and 2 weeks after the onset of their dental abscess, while the rest did that after 3 weeks. Close to 64.5% have ever had episode of abscess before current one which they managed with alternative treatment. About 95% of respondents saw the hospital as a good place for dental care. A significant association was established between patient's level of education and influence to seek orthodox treatment (p = 0.015, Fisher's exact test (FET)). Another significant association was established between patient's level of education and the kind of alternative treatment they used (p = 0.016, Fisher's exact test (FET)). Conclusions Most DAPs believe that dental caries was the main cause of dental abscess. DAPs sought late medical care, after they have tried a failed alternative treatment. DAPs expressed satisfaction with reception, equipment and materials, and medicines used. Majority of the patients rated the cost of dental care in the facility as affordable.

Premature birth remains a significant global health challenge, contributing to high rates of neonatal morbidity and mortality. This retrospective study analyzes the key characteristics, risk factors, complications, and predictive outcomes affecting preterm infant outcomes. Utilizing established theoretical frameworks—including the Developmental Origins of Health and Disease (DOHaD), the Bioecological Model, and the Neurodevelopmental Framework this research examines the interplay of prenatal, perinatal, and postnatal influences on neonatal health. A comprehensive analysis of neonatal morbidity trends from 2018 to 2020 highlights both advancements and persistent challenges in neonatal care. By integrating clinical data with theoretical insights, this study provides a refined understanding of the factors influencing preterm infant health. The findings offer valuable implications for improving neonatal risk assessment models, optimizing clinical interventions, and enhancing long-term developmental outcomes for preterm infants.

‘Future Global Goals and Challenges in Alternative Care’-A Discussion on Interventions and Solutions for Children without Parental Care

Hepatitis B remains a significant global health challenge, contributing to substantial morbidity and mortality. Approximately 254 million people worldwide live with Chronic hepatitis B (CHB), with the majority of cases occurring in sub-Saharan Africa and the Western Pacific regions. Alarmingly, only about 13.4% of the individuals infected with this disease have been diagnosed, and awareness of hepatitis B virus (HBV) infection status is as low as 1% in sub-Saharan Africa. In 2022, CHB led to 1.1 million deaths globally. The World Health Organization (WHO) has set a target of eliminating hepatitis B as a public health concern by 2030; however, this goal appears increasingly unattainable due to multiple challenges. These challenges include low vaccination coverage; a large number of undiagnosed cases; a low proportion of patients eligible for treatment under current guidelines; limited access to healthcare; and the costs associated with lifelong treatment. Treatment of HBV can yield significant clinical benefits within a long window of opportunity. However, the benefits of therapy are markedly diminished when the disease is detected at the advanced cirrhosis stage. This editorial aim to highlight the current challenges in hepatitis care and the necessary steps to achieve the WHO's hepatitis elimination goals for 2030.

How Public Health Crises Expose Systemic, Day-to-Day Health Inequalities in Low- and-Middle Income Countries - An Example From East Africa

Depression is a global key challenge in mental health care. The implementation of effective, low-risk and cost-effective interventions to reduce its disease burden is a necessity. The aim of this study was to investigate the efficacy of the new Meditation-Based Lifestyle Modification (MBLM) program, a "second-generation" mindfulness-based intervention, in depressive outpatients. Eighty-onepatients with mild to moderate depression were randomized into three groups: intervention group (MBLM), control group (CONTROL), and treatment as usual group (TAU). The primary outcome was the change of depressive symptoms as administered by the Beck Depression Inventory-II (BDI-II) after 4 and 8 weeks. Secondary outcome variables included the Brief Symptom Checklist-18 and the Perceived Stress Scale-10. A 6-month follow-up was conducted. A greater reduction of depressive symptoms was found in MBLM participants compared to CONTROL (p < .001, ηp2 = 0.11, d = 0.70)and TAU ( ) with a 13.15 points reduction of BDI-II score versus 1.71 points (CONTROL) and 3.34 points (TAU) after 8 weeks. Between-group post hoc tests for all secondary outcomes and at follow-up also yielded significant between-group differences with medium to large effect sizes in favor of MBLM. Study results showed beneficial effects of MBLM in depressed outpatients. Further high-quality controlled clinical studies including qualitative research are needed to investigate the specific and unspecific effects of the MBLM program in depression and other medical conditions.

Background/introductionOne of the key recommendations for the new WHO global strategy for oral health is inclusion of disadvantaged populations and their engagement in policy dialogues such that their needs and views are addressed in policy decisions.ObjectivesThis study explored oral health perceptions, practices and care-seeking experiences of slum residents in Ibadan, Nigeria.MethodFocus group discussions (FGD) were conducted with family health-decision makers in an urban slum site. Oral health perceptions, practices, and care-seeking experiences were discussed. FGDs were recorded, transcribed, and translated. ATLAS.ti qualitative research software was deployed for analysis using thematic analysis.ResultsSix FGD sessions, divided by gender and age, were conducted between September–October 2019, (N = total 58 participants, aged 25 to 59 years). Common dental ailments mentioned were dental pain, tooth sensitivity, bleeding gums, tooth decay, mouth odor, gum disease, and tooth fracture. Perceived causes of dental conditions included poor dental hygiene and habits, sugary diets, ignorance, and supernatural forces. Mouth cleaning was mostly done once daily using toothbrush and paste. Other cleaning tools were ground glass, wood ash, charcoal, “epa Ijebu” (a dentrifice), and “orin ata” (a type of chewing stick). Remedies for relieving dental pain included over-the-counter medicines, warm salted water, gin, tobacco (snuff/powdered), cow urine/dung, battery fluid, and various mixtures/ concoctions. Visits to the dentists were mentioned by a few but this was usually as last resort. Main barriers to accessing care from dental care facilities were unaffordability of service charges and fear of extreme treatment measures (extraction). Suggested measures to improve timely access to dental health care included reducing/subsidizing costs of treatments and medications, offering non-extraction treatment options, and oral health education programmes.ConclusionThe slum residents experience various forms of dental ailments mostly pain-related. The residents perceived formal dental clinics as unaffordable, thereby engaging in self‐care remedies and harmful oral health practices before seeking professional help. Policymakers and decision-makers may leverage this empirical evidence for the people’s education on early dental care and address challenges to affordable, available, and acceptable oral healthcare services among slum residents to improve access to care facilities.

As individuals age, physiologic alterations take place in the oral cavity, and are thought to be a regular component of the ageing process. However, pathological developments that are not harmless, and that need professional care, are frequently encountered. The line between physiological ageing and actual pathological changes is not clear in all cases. The wellbeing of the oral cavity can be compromised with the initiation of tooth loss, soft tissue lesions such as oral carcinoma, neglected grossly carious teeth, neglected severe periodontitis, and orofacial neuralgia. For adequate oral health to be retained in older ages, oral diseases must be prevented and/or treated with emphasis in younger ages. Proper self-management measures—like brushing of teeth with a fluoridated toothpaste, dental flossing, and consuming nutrient-dense and balanced meals which have less refined carbohydrate are crucial preventive practices to be incorporated in daily life by people of all ages which includes the elderly. Dental care professionals can play a major role in prevention of dental problems and avoidance of more damage of oral tissues in older people. Professional activities comprise head, neck, and intraoral assessment of teeth and surrounding tissues for presence of oral manifestations of systemic illnesses, oral neoplasms, carious teeth, periodontitis, and impaired function and esthetics. Other measures for prevention comprise prophylaxis, dental care guidance, fluoride varnish provision, and proper therapy via restorations and reconstructions. Since the effects of dental conditions accrue as time passes, the necessity for sooner establishment of a preventive routine in life is vital for healthy ageing intraorally. Further, dental care for the geriatric population initiates in the younger ages through a stress on management of oral health issues early on, and from that point through an elaborate preventive plan moving ahead.

Depression is a major global health care challenge, causing significant individual distress but also contributing to a substantial global burden. Timely and accurate diagnosis is crucial. To help future clinicians develop these essential skills, we trained a generative pretrained transformer (GPT)-powered chatbot to simulate patients with varying degrees of depression and suicidality. This study aims to evaluate the applicability and transferability of our GPT-4-powered chatbot for psychosomatic cases. Specifically, we aim to investigate how accurately the chatbot can simulate patients exhibiting various stages of depression and phases of suicidal ideation, while adhering to a predefined role script and maintaining a sufficient level of authenticity. Additionally, we want to analyze to what level the chatbot is suitable for practicing correctly diagnosing depressive disorders in patients, as well as assessing suicidality stages. We developed 3 virtual patient role scripts depicting complex, realistic cases of depression and varying degrees of suicidality collaboratively with field experts and aligned with mental health assessment guidelines. These cases were integrated into a GPT-4-powered chatbot for practicing clinical history-taking. A total of 148 medical students, with an average age of 22.71 years and mostly in their sixth semester, interacted individually with one of the randomly assigned virtual patients through chat. Following this, they completed a questionnaire assessing their demographics and user experience. Chats were analyzed descriptively to assess diagnostic accuracy and suicidality assessments, as well as the role script adherence and authenticity of the artificial intelligence (AI). This was done to gain further insight into the chatbot's behavior and the students' diagnostic accuracy. In over 90% (725/778) of the answers, the chatbot maintained its assigned role. On average, students correctly identified the severity of depression in 60% (81/135) and the phase of suicidality in 67% (91/135) of the cases. Notably, the majority either failed to address or insufficiently explored the topic of suicidality despite explicit instructions beforehand. This study demonstrates that a GPT-powered chatbot can simulate patients with depression fairly accurately. More than two-thirds of participants perceived the AI-simulated patients with depression as authentic, and nearly 80% (106/135) indicated they would like to use the application for further practice, highlighting its potential as a training tool. While a small proportion of students expressed reservations, and the overall diagnostic accuracy varied depending on the severity of the case, the findings overall support the feasibility and educational value of AI-based role-playing in clinical training. AI-supported virtual patients provide a highly flexible, standardized, and readily available training tool, independent of real-life constraints.

Dementia is recognised as one of the major global health and social care challenges of present times. When the onset of dementia occurs in midlife, there is an increased possibility that there are children and young adults involved who are dependent on the parent concerned. The aim of the study was to describe health and social care professionals’ experiences of identifying and supporting children and young adults with a parent with dementia. A qualitative descriptive approach was carried out with individual interviews of health and social care professionals, using a semistructured interview guide. Thirteen participants in rural and urban areas in Sweden were interviewed. The overarching theme, advocating a forgotten group with three categories were identified. They combine and reflect health and social care professionals’ experiences of identifying and supporting children and young adults with a parent with dementia. Health and social care professionals who encountered children and young adults with a parent with dementia described how they were not sufficiently trained in supporting this group and identified a general shortage of available appropriate support services. The children and young adults were also described as a forgotten and overlooked group in need of affirmation and support in a more systematic way.

Global health care challenge: Indian experiences and new prescriptions

S ubstantial progress has been made in the medical management of patients with metastatic cancer of the bone, and patients are living longer with their cancers more than ever before. Still, metastatic bone disease remains a major source of morbidity and mortality for patients afflicted with advanced cancers of the breast, prostate, lung, kidney, thyroid, myeloma, and more. As the population in the United States ages, the prevalence of cancer is expected to rise. Presently, the prevalence of cancer is about 5 million cases per year. In 2015, more than 1.2 million people will receive a cancer diagnosis, most of whom will be older than 40 years of age. Approximately half of these newly diagnosed cases will involve the skeleton. As of 2007, the cost of treating metastatic bone cancer in the United States reached USD 12.6 billion, making up almost 20% of all societal cancer costs, as estimated by the NIH [6]. These numbers will continue to rise as the population ages, and are not restricted to the United States. Metastatic bone disease is a major global health care challenge [5]. Janssen and colleagues attempt to answer whether allogeneic blood transfusions are associated with worse survival after surgery in patients with pathologic long bone fractures. The current study poses a clear clinical question, which it tries to answer with a relatively large and homogeneous patient population while reviewing a robust number of clinical variables. This work is commendable for the volume of patients and clinical factors it evaluates. Additionally, it demonstrates statistically significant information apart from the primary objective that would be consistent with expectations. By their own admission, the work by Janssen and colleagues is underpowered to definitively demonstrate a lack of correlation between perioperative transfusions and patient survival. Still, it is hard to imagine a much larger or more thorough This CORR Insights is a commentary on the article ‘‘Are Allogeneic Blood Transfusions Associated With Decreased Survival After Surgery for Long-bone Metastatic Fractures? by Janssen and colleagues available at: DOI: 10.1007/s11999-015-4167-3. The author certifies that he, or a member of his immediate family, has no funding or commercial associations (eg, consultancies, stock ownership, equity interest, patent/ licensing arrangements, etc) that might pose a conflict of interest in connection with the submitted article. All ICMJE Conflict of Interest Forms for authors and Clinical Orthopaedics and Related Research editors and board members are on file with the publication and can be viewed on request. The opinions expressed are those of the writers, and do not reflect the opinion or policy of CORR or the Association of Bone and Joint Surgeons. This CORR Insights comment refers to the article available at DOI: 10.1007/s11999-0154167-3. R. L. Randall MD (&) Sarcoma Services, Center for Children’s Cancer Research, Huntsman Cancer Institute, University of Utah, 2000 Circle of Hope, Suite 4260, Salt Lake City, UT 84112-5550, USA e-mail: lor.randall@hci.utah.edu CORR Insights Published online: 7 March 2015 The Association of Bone and Joint Surgeons1 2015

chronic kidney disease (CKD) is a progressive organ disorder that is a global health care challenge. Diagnosis Models available today do invasive examinations and rely upon static laboratory values, without consideration for CKD being a dynamic process. In this new study, an innovative artificial intelligence (CKDI) and Internet of Medical Things (IoMT) based real-time prediction framework will be created to clinically address CKD changes over time. The study in this paper proposes a predictive model built upon IoMT and advanced machine learning algorithms to address CKD predictive diagnosing. The study centered on increased CKD predictive diagnosis quality and accuracy. The framework utilizes Adaptive Neuro-Fuzzy Inference Systems(ANFIS) to mitigate uncertainties within medical data, Echo State Networks(ESN) to ensure temporal feature detection, CNN-LM modules to detect spatial-sequential features, and Fuzzy-Rough Set Optimization (FRSO) for feature selection optimization. Sensors probe patient data, with data being monitored in real-time and using cloud processing. In addition, a weighted ensemble learning framework assures predictions will be reliable and accurate. The model offered over 90 percent accuracies, 93.9 percent early diagnoses, and latencies under 50 milliseconds for prediction, all of which exceeds a traditional CKD study. Powered by IoMT, the AI model offers a reliable, low-cost, and transparent diagnostic system for CKD. Its ability for real-time analysis and proactive intervention has the potential to be an industry game-changer in healthcare automation.