Search Results (233)

Background/Objectives: This cross-sectional observational study investigated factors associated with emergency room (ER) utilization for dental pain in a rural inland region of Portugal. The main objective was to examine the relationship between access to dental care, sociodemographic characteristics, oral health behaviors, and clinical outcomes with the use of emergency room services for dental problems. Methods: The study sample comprised 423 participants from the districts of Bragança and Vinhais, in Trás-os-Montes, aged 4 to 90 years, who attended their first dental medicine consultation. Participants completed a structured questionnaire addressing sociodemographic characteristics, general health, oral health behaviors, and dental prosthetic use, and underwent oral examination for assessment of the Decayed, Missing, and Filled Teeth (DMFT) index. Associations with reported ER utilization due to toothache were analyzed using Fisher’s exact test and the Mann–Whitney U test. Results: Overall, 28.4% of participants reported having visited the ER due to dental pain, and most cases were managed with medication followed by discharge. ER utilization was significantly associated with behavioral risk factors such as smoking, as well as poorer oral hygiene practices, including less frequent tooth brushing. In addition, participants who sought ER care presented higher DMFT scores, indicating a greater burden of untreated dental decay and tooth loss. Conclusions: These findings suggest that limited preventive dental care and unfavorable oral health behaviors are associated with to avoidable ER visits for dental pain in rural settings. This study reinforces the need to strengthen access to preventive oral health services and to advance the integration of dental care into Portugal’s National Health Service (SNS), particularly in underserved inland regions. Full article

Early clinical exposure (ECE) has been associated with increased confidence, professionalism, and career exploration in undergraduate medical education. Student-run free clinics (SRFCs), such as the Health Outreach Project (HOP) at Drexel University College of Medicine, provide opportunities for preclinical students to engage in patient care and community outreach. This qualitative study explored medical students’ perceptions of participation in HOP. Fourteen third- and fourth-year medical students with prior HOP experience participated in four semi-structured focus groups conducted virtually over Zoom. Data were analyzed using an inductive thematic analysis approach. Four major themes emerged: (1) early clinical exposure and clinical skills development, (2) community engagement and patient-centered perspectives, (3) professional identity formation and career exploration, and (4) opportunities, limitations, and emotional challenges of outreach work. Participants described HOP as an important source of authentic clinical exposure that increased confidence in patient interactions and broadened awareness of social determinants of health and underserved populations. Students also reflected on the influence of HOP on professional identity formation, career interests, and perspectives on patient-centered care, while acknowledging frustrations related to systemic barriers and limited resources. These findings suggest that students perceive SRFCs as valuable experiential learning environments that support clinical preparedness and professional development early in medical training. Full article

Background/Objectives: We aimed to evaluate the relationship between lens thickness (LT) and postoperative outcomes following cataract surgery versus combined cataract–glaucoma procedures in a predominantly Black and Caribbean population, and to assess the utility of LT and the Laroche Glaucoma Risk Calculator in predicting intraocular pressure (IOP) reduction. Methods: This retrospective cohort study included 187 eyes from patients aged ≥50 years that underwent cataract surgery alone or combined cataract–glaucoma surgery (goniotomy or Ahmed retrobulbar/intraconal tube) at a single center in Queens, New York. Preoperative and ≥3-month postoperative data included IOP, visual acuity (logMAR), medication burden, visual field mean deviation, and anterior segment biometry. Patients were stratified by surgical type, diagnosis, and glaucoma risk. Associations between LT and postoperative IOP reduction were analyzed. Results: Mean LT was 4.53 mm. Greater LT was associated with increased postoperative IOP reduction across all groups. Eyes with LT ≥4.5 mm showed greater IOP reduction compared to LT ≤4.2 mm (2.63 vs. 1.19 mmHg). Combined procedures yielded greater IOP reduction than cataract surgery alone, with the largest decrease in the Ahmed group (−4.56 mmHg). Cataract surgery alone produced smaller but significant reductions (−1.58 mmHg) and the greatest visual acuity improvement. Medication burden decreased substantially in the combined groups. Patients with angle-closure glaucoma had the highest LT. High-risk patients demonstrated greater IOP reduction than low-risk patients. Conclusions: Increased LT may serve as a predictive biomarker for postoperative IOP reduction. Incorporating LT and the Laroche Glaucoma Risk Calculator into preoperative planning may enhance surgical decision-making and outcomes, particularly in underserved populations. Full article

Healthcare disparities are widespread across the U.S. Mobile health programming is designed to dismantle systemic healthcare barriers for medically underserved communities. The purpose of this study was to assess the effectiveness of two southeastern U.S. mobile primary care programs. Guided by the Social Determinants of Health framework, this descriptive study examines the programs’ patient populations to determine reach and patient medical data to ascertain patients’ connection to the medical system and long-term primary care. Data were collected via electronic health record (EHR) and analyzed in Power BI and R. Basic descriptive, crosstab and chi-square statistics were conducted to assess the patient population and explore patient healthcare engagement prior to and following their initial mobile primary care visit. The results indicate that mobile primary care programs are utilized by systemically underserved groups, with both program A and B’s patient population identifying primarily as Latin/Hispanic (69.6% and 41.3% respectively), uninsured (99.1% and 59.8%), and Spanish-speaking (64.4% and 42.3%). Additionally, each program demonstrates an ability to engage patients in long-term primary care utilization via repeat utilizers (65.5% and 25.9%). McNemar’s chi-square results show that participation in either of the mobile primary care programs has a statistically significant, non-random measurable effect on patient primary care enrollment. Differences in program structure and findings are explored, and recommendations for future practice, research, and policy are discussed. Full article

Background: Artificial Intelligence (AI) and Machine Learning (ML) technologies, such as conversational agents, are becoming increasingly essential tools across multiple industries, particularly in healthcare. This paper presents a scoping review (PRISMA-ScR) of conversational agents (CAs) in mobile health coaching systems (MHCS). It examines existing applications of MHCS, focusing on development strategies, usage contexts, impacts on users, benefits, and research gaps, emphasizing the ability of explainable artificial intelligence (XAI) in making health guidance and decision-support recommendations transparent, trustworthy, and interpretable, if properly integrated. This scoping review identifies opportunities to maximize the use of conversational agents, explainable AI, and mobile technologies to make mobile health coaching systems more accessible and trustworthy, as well as further research gaps worth exploring. Objective: This scoping review maps the evidence on CAs and XAI-enabled technologies in MHCS, identifies trust-related design criteria, categorizes reported outcomes, and highlights opportunities for explainable conversational agents (XCA) in a mobile health context, especially in tackling general medical conditions pertinent in underserved settings. Eligibility criteria: Reported eligible resources evaluated, designed, or conceptually analyzed existing CAs, XAI techniques, and MHCS, AI-supported medical dialogue systems, e-coaching systems, and mobile health applications. We considered sources only relevant to healthcare, health coaching, trust, explainability, or patient engagement that were published between 2006 and 2025. Sources of Evidence: Searches were conducted in IEEE Xplore, Google Scholar, Springer, ScienceDirect/Elsevier, ProQuest, and ACM Digital Library, supplemented by targeted web searches and backward citation checks. Charting methods: Data were charted by system type, communication mode, health context, operational mode, technology used, XAI/trust features, degree of automation, study designs and outcome classification. We applied a revised outcome classification: generated desired outcome (GDO) and partially generated desired outcome (P-GDO), and did not generate desired outcome (DN-GDO). Results: A total of 201 resources were collected. Charted studies clustered around CAs in health, MHCS for chronic diseases and stress management, XAI methods such as LIME, SHAP, Prospector, and counterfactual explanations, and trust-related elements such as voice quality, communication style, appearance, social intelligence, privacy, and performance quality. Most health CAs and MHCS addressed chronic diseases, mental health, or behavior change; fewer addressed general medical diagnosis or autonomous mobile-based primary care support. Conclusions: Existing evidence suggests that CAs and MHCSs can support engagement, coaching, education, and selected decision-support tasks, but evidence for safe, autonomous, explainable general practice functionality remains limited. Future work should prioritize clinically supervised XCA designs, core safety assessment, interfaces with transparent explanation, data protection, culturally and linguistically responsive implementation, and future-oriented review in underserved mobile health settings. Full article

Background: Out-of-hospital cardiac arrest is a major cause of mortality, and survival depends heavily on rapid defibrillation. Automated external defibrillators (AEDs) can significantly improve outcomes when used before emergency medical services (EMS) arrive, yet access to and use of these devices remain uneven across communities. This study investigates racial and geographic disparities in AED use during EMS encounters in the United States, evaluating differences across racial groups, geographic settings, cardiac arrest status, and patient acuity, irrespective of whether a bystander or EMS personnel applied the device. Methods: This descriptive study used aggregated data from the National Emergency Medical Services Information System (NEMSIS) Public Release Data Cube to compare AED use across racial, geographic, cardiac arrest, and acuity categories. AED use was defined as any documented application during the EMS encounter. Results: The dataset included 106,246 EMS encounters across six racial and ethnic groups. AEDs were applied in 16,688 encounters (15.7%), with substantial variation across demographic and geographic categories. Asian, American Indian or Alaska Native, and Black or African American patients had the highest rates of AED use, while White patients had the lowest rate despite representing the largest share of encounters. Urban areas accounted for most AED deployments, whereas suburban and frontier regions showed markedly lower use, while rural AED use was similar to urban rates. AED application was strongly associated with cardiac arrest and high patient acuity, yet racial differences persisted even within these clinically severe categories. Conclusions: AED use generally aligns with clinical indicators such as cardiac arrest and critical acuity, but meaningful racial and geographic differences were observed, reflecting descriptive patterns rather than confirmed disparities. These patterns should be interpreted cautiously, as the aggregated nature of the dataset limits the ability to determine whether differences reflect inequities, incident characteristics, or EMS system factors. These findings highlight the need for targeted strategies to expand AED access, improve device placement, and strengthen community readiness in underserved areas. Integrating AED availability into broader EMS planning and community outreach may help reduce inequities and create conditions that support improved survival outcomes. Further research using individual-level data and geospatial methods is needed to clarify the drivers of these observed differences and inform equitable prehospital care policies. Full article

Objective: Describe a mobile health clinic program led by pharmacists to provide services in a primary care shortage area. Methods: ONU HealthWise is a comprehensive pharmacy service offered by Ohio Northern University Raabe College of Pharmacy with a mobile clinic initiated in 2015. ONU HealthWise is located in an HRSA-designated medically underserved and primary care shortage area and the mobile health clinic visits 11–18 locations monthly plus additional sites for screening or vaccinations. Medical residents from a health-system attend some locations and collaborative practice agreements allow pharmacists to initiate and adjust medications. Student pharmacists rotate through the mobile clinic to gain experiential training toward their Doctor of Pharmacy. The mobile clinic is an integral part of the learning and precepting for ONU HealthWise PGY-1 residents. Results: Over a 12-month period (July 2024–June 2025), the mobile clinic held 148 clinics across 7 rural counties in northwest Ohio. A total of 1265 screenings were conducted at 713 patient encounters (604 unique patients). Of the screenings, 38.1% of blood glucose, 21.6% of cholesterol, and 60.1% of blood pressures were abnormal. All abnormal tests resulted in either a medication adjustment, scheduled follow-up at future mobile clinic, or referral to a provider. Student pharmacists spent more than 3670 h on the mobile health clinic in experiential education. Conclusion: Pharmacists can be an integral healthcare provider by increasing access to primary care services through a mobile health clinic in a medically underserved area. The service provides learners with vital patient experiences. Full article

Background: During the early years of the coronavirus disease 2019 (COVID-19) pandemic, many schools found their staff, specifically teachers, adapting their roles to address social and health challenges, such as food insecurity and health literacy. Given the challenges these school-based communities faced, and continue to face, a clear gap was exposed during these early years of the public health crisis: a lack of community-centered professionals who can assist with social health factors impacting health and well-being. Methods: In this descriptive report, we examine the process and implementation of training two teachers to become community-centered professionals, specifically community health workers (CHWs), to serve schools located in socioeconomically challenged neighborhoods of urban regions. We explore their training and how these CHW–teachers prescribed social health interventions across four major domains: (a) access to medical and environmental equipment, (b) mental health challenges, (c) food insecurity, and (d) health literacy. We describe the specific interventions they implemented and the potential economic value and practicality of the overall initiative. Outputs: In less than one year, two teachers were successfully trained as CHWs in and for underserved communities. These CHW–teachers conducted informal surveys based on objectives of health themes that aligned with absenteeism. Both the process and implementation of the CHW training and CHW-led school-based interventions proved cost-effective and practical. Conclusions: Having CHW–teachers in schools is practical, may offer economic value, and is likely to complement additional health initiatives at schools (e.g., school nurses). As a small-scale pilot initiative, further studies should evaluate CHW–teacher impact on school-based goals, such as attendance rates, while this report focuses on early implementation processes. Full article

Background: Spasticity significantly impairs functional recovery after severe acquired brain injury. Current management methods predominantly rely on pharmacological interventions, which can cause substantial side effects or require invasive medical procedures in refractory cases. Focal muscle vibration, a noninvasive technique that applies mechanical vibrations to muscle–tendon units and alters spinal and cortical excitability via proprioceptive pathways, has been effective in reducing spasticity in subjects with stroke. However, there is limited data to support focal muscle vibration as a viable option for improving functional recovery in patients with severe acquired brain injury. Objectives: To evaluate the clinical effects of adding focal muscle vibration to standard physiotherapy compared with standard physiotherapy alone in patients with severe acquired brain injury and spastic hypertonia. Methods: Twenty-four patients were randomly assigned to receive focal muscle vibration in addition to standard care (n = 12) or standard care alone (n = 12) for 3 weeks. Assessments were conducted at baseline, immediately after physiotherapy, and 3 weeks after physiotherapy. The outcomes assessed included the Modified Ashworth Scale, Disability Rating Scale, Modified Barthel Index, and three pain measures. Results: A significant reduction in spasticity was observed in the focal muscle vibration group, as indicated by the Modified Ashworth Scale scores (p = 0.014). Disability Rating Scale scores demonstrated a statistically significant decrease in disability ratings at the end of treatment (p = 0.002) and during the follow-up phase (p = 0.002). Between-group comparisons of change scores revealed a statistically significant improvement in disability ratings in the focal muscle vibration group during the treatment phase (p = 0.011). Significant functional gains were noted on the Disability Rating Scale, which persisted at the follow-up evaluation. Conclusions: Focal muscle vibration reduces muscle spasticity and improves functional status in patients with severe acquired brain injury during inpatient rehabilitation. Future studies with larger sample sizes, blinded assessments, and stratified randomization are needed to verify these findings and develop standardized treatment protocols for this underserved population. Full article

Cataracts represent the leading cause of blindness worldwide, particularly in older adults, and constitute a significant public health challenge. Although cataract surgery is generally associated with a high safety profile, both patients and healthcare providers often face significant challenges due to age-related physiological changes and the high prevalence of comorbidities, which are directly linked to cataractogenesis and other systemic diseases that can complicate both the surgical procedure and postoperative recovery. This narrative review aimed to assess the epidemiological characteristics of age-related physiological and pathological comorbidities in older adults with cataracts, evaluating their impact on preoperative assessment, surgical outcomes, and public health planning. Articles were identified through non-systematic searches of PubMed, EMBASE, and Scopus using a combination of medical subject headings (MeSH) terms and free-text keywords. Among the multiple non-ocular comorbidities, carotid artery disease (CAD) and hypertension (HTN) are among the cardiovascular diseases (CVDs) with the highest correlations with cataract. Diabetes, dyslipidemia, and metabolic syndrome are also highly prevalent and significantly influence surgical outcomes, as poor glycemic control increases intraoperative risks and postoperative complications. Additionally, neurological conditions such as stroke, Parkinson’s disease, and epilepsy often complicate anesthesia administration, contribute to postoperative delirium, and affect adherence to treatment protocols. Given these complexities, a multidisciplinary approach and targeted preoperative screening may offer personalized care to improve safety and outcomes. Despite advances in clinical care, disparities in access to cataract surgery, especially in underserved populations, continue to exist. Thus, a coordinated public health strategy that promotes early detection, equitable access, and the integration of innovations such as teleophthalmology and artificial intelligence is essential to optimize care for older adults with cataracts worldwide. Full article

As modern society grows increasingly complex, access to essential services such as healthcare, legal aid, tailored education, and psychological support remains heavily gated by socio-economic, neurological, and systemic barriers. This paper explores the transformative potential of Large Language Models (LLMs) and Generative Artificial Intelligence not merely as industrial productivity enhancers, but as vital “social scaffolds” capable of fostering a more inclusive society. Crucially, we propose a paradigm shift in the concept of Ethical Computing—moving from a passive defensive framework of non-maleficence (“do no harm”) to an active mandate of beneficence, where AI systems are explicitly developed to serve marginalized and un(der)served populations. Through this expanded ethical lens, we systematically analyze the democratizing impact of AI across four primary axes of inclusivity: socio-economic (providing zero-cost medical triage and legal translation for undocumented populations), neurospicy (acting as a non-judgmental communicative bridge for individuals with Autism Spectrum Disorder), pedagogical (delivering hyper-personalized executive function support for Special Educational Needs), and psychological (serving as an accessible, first-level triage system for mental health crises). By framing LLMs as a modern social safety net, we outline a clear trajectory for future research, advocating for an “ethical-by-design” development paradigm that explicitly prioritizes equity, accessibility, and the active dismantling of historical barriers for the digitally and socially disenfranchised. Full article

Background and Objectives: Shortages of dermatologists create significant barriers to care, particularly for inflammatory and history-dependent conditions where image-only artificial intelligence (AI) classifiers have limited applicability. Current teledermatology solutions largely focus on single-task, morphology-based neoplasm classifiers, leaving the vast majority of dermatologic presentations underserved. This study evaluated the diagnostic accuracy and management plan quality of Dermflow (Prava Medical, Delaware, USA), a proprietary dermatology-focused Multimodal Image-and-Data Assistant (MIDA) that autonomously gathers dermatology-specific history, integrates data with patient-submitted images, and outputs structured differential diagnoses and management summaries. Materials and Methods: Two AI systems, Dermflow and Claude Sonnet 4 (Claude, a leading vision–language model), analyzed 87 clinical images from the Skin Condition Image Network and Diverse Dermatology Images databases, representing 10 inflammatory dermatoses and 9 neoplastic conditions stratified across Fitzpatrick Skin Tone (FST) categories (I–II, III–IV, V–VI). For the diagnostic comparison, Dermflow received images and autonomously gathered clinical history, while Claude received identical images without history. For the management plan comparison, both systems received the correct diagnosis and the clinical histories gathered by Dermflow. The primary outcome was diagnostic accuracy. The secondary outcome was management plan quality, assessed by two blinded dermatologists across eight clinical dimensions using 5-point Likert scales. Chi-square tests compared diagnostic accuracy between models; t-tests and ANOVA compared management quality scores. Results: Dermflow achieved markedly superior diagnostic accuracy compared to Claude (86.2% vs. 24.1%, p < 0.001). Both models maintained consistent diagnostic performance across FST categories without significant within-model differences (Dermflow p = 0.924; Claude p = 0.828). Management plan quality showed no significant overall differences between models. However, composite management quality scores declined significantly for darker skin tones across both systems: Dermflow scored 4.20 (FST I–II), 3.99 (FST III–IV), and 3.47 (FST V–VI); Claude scored 4.35, 3.97, and 3.44, respectively (p < 0.001 for most pairwise FST comparisons within each model). Conclusions: Multimodal AI integrating targeted history with image analysis achieves substantially higher diagnostic accuracy than image-only approaches across both inflammatory and neoplastic dermatologic conditions. Autonomous history gathering addresses fundamental limitations of morphology-only classifiers and enables scalable, patient-facing triage across the full spectrum of dermatologic disease. However, both models demonstrated reduced management plan quality for darker skin tones despite receiving the correct diagnosis, suggesting persistent training data limitations that require targeted bias-mitigation strategies beyond domain-specific instruction. Full article

Accurate radiation biodosimetry is urgently needed for medical management after large-scale radiation exposure. Partial-body irradiation with 5% bone marrow sparing (PBI/BM5) provides a realistic radiation model. The current study specifically focused on the high-dose lethality window (12–16 Gy), where survival transitioned from 100% to 0%, representing a clinically distinct and underserved scenario requiring dedicated biodosimetry tools. We defined the survival profile of male C57BL/6 mice after PBI/BM5 and found that doses of 13.5–14.0 Gy were nonlethal within 12 days, whereas 15.0–15.5 Gy caused 100% mortality within 12 days, with a calculated LD_50/12 of 14.68 Gy. A separate cohort of 14.0 Gy showed 100% survival up to 90 days post-radiation. To develop serum cytokine-based biodosimetry in high-dose radiation exposure, mice were exposed to 12.0–16.0 Gy PBI/BM5, and serum was collected on days 1, 3, and 7. A multiplex cytokine assay was used to quantify 70 total cytokines/chemokines. After the exclusion of 4 targets outside detection limits, 66 markers were utilized for downstream analysis. PCA, clustering and heatmaps, and LASSO classification revealed that cytokine signatures can classify radiation groups/status/doses. A 4-cytokine panel (IL-7, GDF-15, IL-16 and FLT3L) could distinguish naïve vs. irradiated mice on all study days. A 24-cytokine signature panel distinguished radiation survivors vs. non-survivors, and another 34-cytokine panel separated radiation doses (12–16 Gy); the prediction was better on day 7 compared to earlier time points. This exploratory study was specifically designed to define the systemic inflammatory response in a high-dose window where survival transitions from 100% to 0% (the ‘lethality threshold’) in a clinically relevant partial-body irradiation model. These findings show that serum cytokines have strong potential for high-dose triage, survival prediction, and dose discrimination within the near-lethal exposure range in a clinically relevant PBI/BM5 model. Extension to lower dose ranges is an important direction for future work. Full article

Background: Timely prehospital management is critical for survival after traumatic injury. In rapidly growing metropolises, emergency medical service (EMS) systems often struggle to provide equitable care amid urban sprawl and traffic congestion. This study investigated spatiotemporal inequalities in trauma-related EMS response in a rapidly expanding capital city (Astana, Kazakhstan) to inform healthcare optimization and urban health equity. Methods: We analyzed a five-year population-based dataset of 26,073 trauma-related EMS calls recorded between 2020 and 2024. Spatial patterns were examined using Kernel Density Estimation (KDE) and Getis–Ord Gi* hotspot analysis. Road-network modeling assessed accessibility at 3, 5, and 10 min thresholds using a GIS-based network analyst framework. Results: Males accounted for 60.1% of utilization and had higher clinical severity (hospitalization rate: 45.5% vs. 40.3%, p < 0.001). Demand peaked at 20:00, coinciding with peak traffic. The mean total response time was 21.63 min, and only 16.9% of calls met the 10 min benchmark. Significant accessibility gaps were found in the Baikonur district (61.4% delay rate). Conclusions: The findings demonstrate that while the EMS system provides broad geographic coverage, it suffers from systemic spatiotemporal bottlenecks. Targeted infrastructure expansion in underserved peripheral districts and the implementation of dynamic deployment models are necessary to enhance urban health equity and reduce preventable mortality in expanding metropolitan areas. Full article

Universities play a strategic role in advancing the Sustainable Development Goals (SDGs) through community engagement, particularly within medical education. This study examines medical students’ involvement in volunteering activities and evaluates how such engagement contributes to SDG 3 (Good Health and Well-being) and SDG 4 (Quality Education). A cross-sectional survey was conducted among 499 students from the Victor Babeș University of Medicine and Pharmacy in Timișoara, using a structured questionnaire assessing perceived community impact, soft skills development, motivation for volunteering, sustainability orientation, and institutional support. Results indicate a high level of availability and prior participation in volunteering, reflecting strong internalization of public health and social responsibility values. While no significant differences were observed between volunteers and non-volunteers regarding perceived community impact (SDG 3), volunteer experience was significantly associated with higher levels of soft skills development and motivation (SDG 4). Strong positive correlations were identified between perceived community impact and motivational, educational, and sustainability related dimensions. The intensity of involvement was modestly associated with sustainability orientation and institutional support. Despite high motivation, students reported limited structured institutional frameworks for sustained engagement. The findings suggest that medical volunteering functions as a dual mechanism, strengthening professional competencies while reinforcing community health orientation. Institutionalizing structured outreach programs, particularly in underserved areas, could enhance long-term impact and align medical education more effectively with the 2030 Sustainable Development Agenda. Full article