SEARCH · PubMed Health

Results for “Healthcare”

Explore indexed PubMed citations for clinical trials, systematic reviews and public health research. Read source abstracts and follow each citation to its original PubMed record.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 recordsLinked to original sources

PubMed2026

Healthcare-facility-based SARS-CoV-2 genomic surveillance in Brazil: experience from the global action in healthcare network.

UNLABELLED: Genomic sequencing is essential to effectively monitor the SARS-CoV-2 evolution and spread of its lineages. Healthcare-facility-based SARS-CoV-2 genomic surveillance has been proposed as a valuable strategy, considering the characteristics of its target population. As part of the Centers for Disease Control and Prevention's Global Action in Healthcare Network program, this study aimed to describe the distribution and frequency of SARS-CoV-2 lineages in two tertiary-care hospitals in Brazil, where the genomic sequencing capacity is limited. Whole-genome sequencing of SARS-CoV-2 samples obtained from 993 healthcare workers (75.4%) and inpatients (24.6%) was analyzed between February 2023 and August 2024. In total, 113 distinct lineages were identified. Notably, we observed a temporal replacement of predominant lineages corresponding to three distinct epidemic waves: the first wave dominated by XBB.1.5 and XBB.2.3 (February 2023 to June 2023), the second by GK.1.1 and JD.1.1 (September 2023 to December 2023), and the third by JN.1 and JN.1.9 (January 2024 to April 2024). JN.1.9 was the only lineage with a significantly higher prevalence among healthcare workers compared to inpatients. Additionally, we identified cases of co-infection with genetically distinct variants, underscoring the potential for healthcare-based monitoring to capture events relevant to viral evolution. Overall, our findings were consistent with those observed across Brazil, suggesting that this strategy may be valuable for SARS-CoV-2 genomic surveillance. They also indicate a clear temporal pattern of lineage replacement, reflecting successive waves driven by emerging variants and rapid global dissemination. IMPORTANCE: Genomic surveillance of SARS-CoV-2 remains essential for identifying emerging variants with increased transmissibility, immune escape, or pathogenicity. While most genomic surveillance efforts focus on community-based sampling, a healthcare-facility-based strategy may offer a complementary approach. In this study, we describe SARS-CoV-2 lineage dynamics over an 18-month period among healthcare workers and hospitalized patients in southern Brazil. Our findings align closely with regional and national trends, supporting the value of healthcare-facility-based SARS-CoV-2 genomic surveillance for documenting the local genomic landscape and demonstrating the feasibility and value of this approach in settings with limited genome sequencing capacity. Additionally, this approach may be applicable to other respiratory viruses in healthcare settings; however, further studies would be needed to confirm this.

Humans↗

PubMed2026

From Infection Control to Healthcare System Resilience: Lessons Learned from SARS-CoV-2 Research in Healthcare Workers.

The COVID-19 pandemic placed unprecedented pressure on healthcare systems and exposed healthcare workers (HCWs) to biological hazards, organizational pressures, and psychological strain. Evidence generated during the emergency shows that HCW protection cannot rely on isolated measures, but requires an integrated framework combining epidemiological surveillance, contact tracing, infection prevention and control, vaccination, occupational health, and workforce support. Contact tracing helped identify occupational exposures and clarify how duration, proximity, and inadequate use of personal protective equipment jointly shaped infection risk. Subsequent studies of reinfection showed that susceptibility reflected the interaction of viral circulation, individual immunity, and vaccination status. Vaccination reduced the clinical impact of SARS-CoV-2 and supported service continuity, although uptake depended on trust, communication, and management of adverse event concerns. The pandemic also highlighted substantial economic consequences and a high burden of psychological distress and burnout among HCWs. Building on this evidence, future preparedness should translate these lessons into permanent, adaptable infrastructure rather than temporary emergency arrangements, integrating interoperable, AI-assisted surveillance capable of combining occupational, diagnostic, vaccination, and genomic data to detect emerging risks early, while ensuring robust data governance and human oversight. Equally central is the need to address long-term workforce vulnerabilities, including Long COVID, attrition, and burnout, through early identification, rehabilitation, flexible return-to-work models, and sustained psychosocial support. Achieving this requires structured multidisciplinary collaboration among occupational medicine, infection control, epidemiology, mental health, and digital health specialists, moving from fragmented infection-control protocols to an integrated, proactive, and learning-oriented preparedness strategy. Protecting HCWs is therefore not only an occupational safety priority but a foundational prerequisite for safe, equitable, and sustainable healthcare delivery during future infectious threats.

Humans↗

PubMed2026

Experiences of stigma, bias, and communication challenges among pregnant healthcare workers: A systematic review of qualitative evidence.

BACKGROUND: Healthcare work environments are fraught with occupational hazards that can impact pregnant healthcare workers' health as well as patient care. Despite the feminization of healthcare globally, systematic discrimination against pregnant workers persists across diverse healthcare settings and cultural contexts. The intersection of stigma, bias, and communication challenges creates substantial barriers to career advancement and wellbeing. However, no systematic review has synthesized qualitative evidence on how these three constructs interact across healthcare professions and cultural contexts using an integrated theoretical framework. OBJECTIVE: To systematically review and synthesize qualitative evidence on experiences of stigma, bias, and communication challenges among pregnant healthcare workers across different healthcare settings and cultural contexts using an integrated theoretical framework. DESIGN: Systematic review of qualitative studies following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines with thematic synthesis. DATA SOURCES: Seven databases were searched from inception to January 2026. REVIEW METHODS: Included qualitative studies were appraised using the Critical Appraisal Skills Programme (CASP) checklist and synthesized through theory-guided thematic synthesis. Confidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation-Confidence in the Evidence from Reviews of Qualitative research (GRADE-CERQual) approach. RESULTS: Fourteen studies encompassing 1223 participants across 17 countries revealed four major themes: (1) professional identity stigma and workplace discrimination through systematic labeling and stereotyping; (2) gender-based institutional bias rooted in masculine organizational logic; (3) multilevel communication failures creating fear-based climates; and (4) individual and collective resistance strategies developed despite constraints. Occupational hazards specific to pregnancy included exposure to infectious diseases, imaging, physical tasks, cleaning products, patient violence, and medication administration. Support from coworkers and supervisors was identified as the most critical facilitator for avoiding hazards and making necessary modifications, while the desire to be 'supernurses' and fear of consequences emerged as significant barriers. These patterns were consistent across healthcare professions, settings, and cultural contexts, with specialty culture and healthcare system type moderating discrimination intensity. Confidence in core findings was rated high using GRADE-CERQual. CONCLUSIONS: Pregnant healthcare workers globally experience interconnected stigma, bias, and communication challenges that are systematically embedded within healthcare organizational structures. These challenges operate synergistically, requiring comprehensive multilevel interventions beyond policy compliance. Healthcare organizations must implement evidence-based strategies addressing stigma reduction, bias interruption, and communication transformation simultaneously to retain skilled workers and ensure quality patient care.

Female↗

PubMed2026

Factors influencing the enhancement of the new iron triangle in healthcare organisations.

PURPOSE: A new paradigm, "healthcare's new iron triangle," has been developed to emphasise the technological perspective of healthcare delivery, focusing on automation, value and empathy. The study aims to build a conceptual model and to identify factors for the enhancement of the new iron triangle in healthcare organisations. DESIGN/METHODOLOGY/APPROACH: The healthcare organisation is the primary focus point of the current study. To determine the factors, a survey of the literature and healthcare experts' opinions was conducted. The healthcare professionals validated the identified factors. Data for this study were gathered using a closed-ended questionnaire and scheduled interviews. The study employed "Total Interpretive Structural Modeling methodology and Matriced' Impacts Croise´s Multiplication Appliqué´ a UN Classement/Cross-Impact Matrix Multiplication Applied to a Classification (MICMAC) analysis" to address the "why" and "how" the factors interact and prioritise the identified factors. FINDINGS: The study found that organisational structure (F8), artificial intelligence (F1), innovation (F2) and human resources (F5) are the driving or key factors of the study. RESEARCH LIMITATIONS/IMPLICATIONS: The study primarily focused on identifying factors for the enhancement of a new iron triangle in healthcare organisations. The scope could eventually be expanded to explore more areas. PRACTICAL IMPLICATIONS: Academics and other stakeholders will have a better understanding of the key drivers for the enhancement of the new iron triangle in healthcare organisations. ORIGINALITY/VALUE: In this study, total interpretive structural modeling and cross-impact MICMAC analysis are proposed as an innovative approach to address the new iron triangle in healthcare organisations.

Humans↗

PubMed2026

Driven toward care, avoiding the end: A systematic review and meta-analysis of the relationship between death anxiety and healthcare utilisation.

Both overuse and underuse of the healthcare system have been recognised as significant problems. Relatedly, growing research has recognised the key role of death anxiety in driving various health-relevant behaviours. However, the relationship between death anxiety and healthcare utilisation has not yet been systematically explored. The current systematic review and meta-analysis addressed this gap. In total, 987 papers were screened for inclusion, of which 63 were included in the final review (Ntotal = 21,271). This included 33 quantitative studies, 27 qualitative studies and 3 mixed-methods designs. In total, 17 studies contained sufficient data to be meta-analysed. Overall, the included studies highlighted a significant relationship between death anxiety and healthcare utilisation; in particular, positive associations with desire for life-prolonging treatments and contact with hospitals and medical professionals. By contrast, a negative association was found with other aspects of healthcare utilisation, including hospice use and end-of-life communication. The sample type emerged as a significant moderator, suggesting that the relationship between death anxiety and healthcare usage was strongest in non-medical samples. The current findings suggest that death anxiety plays a key role in utilisation of the healthcare system. The fear of death may need to be targeted in psychological interventions, in order to ensure maximal effectiveness of health services, and improve outcomes for healthcare users.

Humans↗

PubMed2026

CAUSAL artificial intelligence and data-driven decision intelligence in personalized medicine: a review of healthcare informatics systems.

This review examines the integration of causal artificial intelligence (AI) and data-driven decision intelligence within healthcare informatics systems to advance personalized medicine and clinical decision-making. A narrative review methodology was employed, synthesizing interdisciplinary literature from major databases, including PubMed, Scopus, Web of Science, IEEE Xplore, and ScienceDirect. Studies focusing on causal inference, decision intelligence, and healthcare informatics applications in personalized medicine were included. Data were extracted on methodological approaches, healthcare settings, analytical techniques, and clinical applications, followed by thematic synthesis. Findings indicate that causal AI enhances clinical decision support by enabling estimation of treatment effects and simulation of intervention outcomes at the individual patient level. Integration of multimodal health data such as electronic health records, genomic data, and real-time monitoring improves prediction accuracy and supports tailored treatment strategies. Additionally, causal models improve interpretability, fostering clinician trust and facilitating transparent decision-making. Robust healthcare informatics infrastructures, including interoperable systems and data warehouses, were identified as critical enablers of causal analytics. Overall, causal AI represents a transformative advancement in healthcare analytics, supporting more informed, individualized, and evidence-based clinical decisions. Its integration within healthcare informatics systems has significant potential to improve patient outcomes and guide the future of intelligent, personalized healthcare delivery.

Precision Medicine↗

PubMed2026

Validation of a Turkish Translation of the Stress in Emergency Healthcare Professionals: The Stress Factors and Manifestations Scale.

AIM: The primary duties of emergency healthcare professionals (EHPs) are to provide emergency patient care to acutely ill and injured individuals. Due to the nature of their work, EHPs operate under constant stress, often requiring rapid decision-making, swift action, and the delivery of necessary medical care in life-or-death situations, sometimes under inadequately safe conditions. Therefore, the aim of this study is to determine the validity and reliability of the Emergency Healthcare Professional Stress Factors and Symptoms (SEHP:SFMS) Scale in Turkish for identifying stress factors and symptoms in emergency medical care professionals providing emergency patient care services. DESIGN: A methodological study design was used in this study. METHODS: The study was conducted with the participation of 211 EHPs from employees working in emergency care institutions affiliated with the Muğla Provincial Health Directorate between November 2023 and June 2024. Data were collected via a face-to-face survey. Data were analysed using Lawshe content validity ratio, Kaiser-Meyer-Olkin coefficient, Bartlett test, exploratory factor analysis, principal component analysis, Varimax factor rotation method, confirmatory factor analysis, Cronbach's α internal consistency coefficient, convergent validity, discriminant validity, test-retest, and Spearman correlation coefficient tests. RESULTS: The linguistic translation and cultural adaptation of the SEHP:SFMS showed strong performance. The scope validity index of the scale is 0.83. The item-total correlation values of the scale were found to be between 0.486 and 0.794, and the factor loadings were between 0.474 and 0.816. Confirmatory factor analysis fit indices: χ2 = 248.727; df = 101; n = 211; p = 0.000; χ2/df = 2.463; RMSEA = 0.083; CFI = 0.914, SRMR = 0.052, which was found to be compatible and acceptable with the proposed 3-factor model. The Cronbach's α reliability coefficient of the scale was 0.931, and the total variance was 61.97%. CONCLUSIONS: SEHP:SFMS is a valid and reliable tool to assess stress factors and symptoms of Turkish emergency healthcare professionals. Its use improves the quality of emergency care. PATIENT OR PUBLIC CONTRIBUTION: These study findings have been used to create a tool with Turkish validity and reliability that allows for the examination of stress factors among healthcare professionals working in emergency and critical services. Identifying and reducing stress factors among healthcare professionals is crucial for the delivery of quality healthcare services. It can also be used to develop targeted interventions and ongoing strategies to facilitate improved clinical supervision and mentoring. IMPLICATION FOR NURSING PRACTICE: Nurses in emergency departments, which are among the most stressful, dynamic, intense, life-saving, and critical environments in healthcare institutions, and where life-saving treatment is administered, are at high risk of experiencing psychological trauma. Trauma experienced in the work environment is a significant problem for nursing. The consequences of trauma negatively affect nurses and institutions. Studies show that post-traumatic stress, anxiety, depression, and burnout are commonly observed in emergency department nurses. In this sense, understanding the stress and stress factors experienced by nurses can guide future interventions. The results of this study are considered important in making visible the stress and stress factors experienced by nurses in the emergency department, and also in guiding managers and nurses working in this field in terms of preventive and protective measures.

Humans↗

PubMed2026

Determinants of private health insurance uptake and its association with healthcare utilization in Gulf Cooperation Council countries: a systematic review.

All Gulf Cooperation Council (GCC) countries have a multi-payer healthcare system that comprises governmental health coverage (GHC), funded by the government, and private health insurance (PHI), mainly sponsored by employers and purchased by individuals. Both are expected to influence healthcare utilization and contribute to system efficiency and patient well-being. This systematic review explored the determinants of PHI uptake and its association with healthcare service utilization in the presence of GHC in GCC countries. We systematically searched CINAHL, PubMed, Scopus, Web of Science, and Cochrane Library for peer-reviewed studies published between January 2012 and October 2022. Study quality was assessed using the Critical Appraisal Skills Programme (CASP) checklists for both quantitative and qualitative studies, following PRISMA guidelines. Twenty-six studies met the inclusion criteria. Determinants of PHI uptake were mapped to Andersen's Behavioral Model of Health Services Use (BMHSU) and categorized into (1) predisposing factors (sex, age, marital status, and education), (2) enabling factors (employment/income and health system-related factors such as access and perceived service quality), and (3) need factors (health status, including chronic noncommunicable diseases). PHI uptake was positively associated with being male, married, highly educated, employed with a high income, and having chronic diseases. PHI was positively associated with healthcare utilization, particularly routine check-ups, preventive services, and the use of prescribed medicines. In GCC countries, PHI uptake is influenced by sociodemographic and socioeconomic characteristics, health status, and perceived service quality. PHI is also associated with higher healthcare utilization, underlining the need for evidence-informed policies that enhance equity and expand coverage.

Humans↗

PubMed2026

Assessing AI literacy and attitudes among medical students: implications for integration into healthcare practice.

PURPOSE: This study aims to assess AI literacy and attitudes among medical students and explore their implications for integrating AI into healthcare practice. DESIGN/METHODOLOGY/APPROACH: A quantitative research design was employed to comprehensively evaluate AI literacy and attitudes among 374 Lusaka Apex Medical University medical students. Data were collected from April 3, 2024, to April 30, 2024, using a closed-ended questionnaire. The questionnaire covered various aspects of AI literacy, perceived benefits of AI in healthcare, strategies for staying informed about AI, relevant AI applications for future practice, concerns related to AI algorithm training and AI-based chatbots in healthcare. FINDINGS: The study revealed varying levels of AI literacy among medical students with a basic understanding of AI principles. Perceptions regarding AI's role in healthcare varied, with recognition of key benefits such as improved diagnosis accuracy and enhanced treatment planning. Students relied predominantly on online resources to stay informed about AI. Concerns included bias reinforcement, data privacy and over-reliance on technology. ORIGINALITY/VALUE: This study contributes original insights into medical students' AI literacy and attitudes, highlighting the need for targeted educational interventions and ethical considerations in AI integration within medical education and practice.

Students, Medical↗

PubMed2026

Healthcare Access and Safety Training Gaps Among H-2 A Visa Agricultural Workers in Georgia.

The H-2 A Temporary Agricultural Workers Program, which supplies seasonal labor essential to U.S. food security, has grown over 230% in the past decade but is excluded from the National Agricultural Workers Survey. Although safety training is federally mandated and H-2 A workers are eligible for Affordable Care Act (ACA) marketplace coverage, compliance and healthcare access among these workers remain poorly documented. The aim of this pilot study was to assess workplace safety training, heat acclimatization practices, health insurance awareness and enrollment, and healthcare utilization among H-2 A workers in Georgia. In summer 2024, bilingual research assistants orally administered a cross-sectional Spanish-language survey to 51 H-2 A workers at a South Georgia laundromat, in partnership with the Latino Community Fund Georgia. The survey assessed demographics, occupational characteristics, safety training, heat acclimatization, health insurance awareness and enrollment, and healthcare utilization. Findings are self-reported. Among participants, 41% reported not receiving federally mandated pesticide safety training, and 59% received heat illness prevention training. Heat acclimatization was inadequate for 53% (29% received none). Additionally, 53% did not know the nearest hospital, 43% reported having health insurance, and 25% were unsure of their health insurance status. Overall, 71% had never visited a doctor's office, and of 22 insured workers, only 1 (2%) had used benefits this season. Substantial gaps in workplace safety training, heat acclimatization, and healthcare access were observed in this pilot study, consistent with prior evidence of persistent disparities in this population. Community-based outreach, bilingual health navigation, and market-based labor accountability models warrant further investigation to improve protections for H-2 A workers.

Agricultural workers↗

PubMed2025

Artificial intelligence in healthcare and medicine: clinical applications, therapeutic advances, and future perspectives.

Healthcare systems worldwide face growing challenges, including rising costs, workforce shortages, and disparities in access and quality, particularly in low- and middle-income countries. Artificial intelligence (AI) has emerged as a transformative tool capable of addressing these issues by enhancing diagnostics, treatment planning, patient monitoring, and healthcare efficiency. AI's role in modern medicine spans disease detection, personalized care, drug discovery, predictive analytics, telemedicine, and wearable health technologies. Leveraging machine learning and deep learning, AI can analyze complex data sets, including electronic health records, medical imaging, and genomic profiles, to identify patterns, predict disease progression, and recommend optimized treatment strategies. AI also has the potential to promote equity by enabling cost-effective, resource-efficient solutions in low-resource and remote settings, such as mobile diagnostics, wearable biosensors, and lightweight algorithms. Successful deployment requires addressing critical challenges, including data privacy, algorithmic bias, model interpretability, regulatory oversight, and maintaining human clinical oversight. Emphasizing scalable, ethical, and evidence-driven implementation, key strategies include clinician training in AI literacy, adoption of resource efficient tools, global collaboration, and robust regulatory frameworks to ensure transparency, safety, and accountability. By complementing rather than replacing healthcare professionals, AI can reduce errors, optimize resources, improve patient outcomes, and expand access to quality care. This review emphasizes the responsible integration of AI as a powerful catalyst for innovation, sustainability, and equity in healthcare delivery worldwide.

Humans↗

PubMed2025

Identifying healthcare transmission routes of nontuberculous mycobacteria with whole genome sequencing: a systematic review.

OBJECTIVE: To enumerate and describe the effect of whole genome sequencing (WGS) on epidemiological investigations of healthcare-associated transmission of nontuberculous mycobacteria (NTM). DESIGN: Systematic review. METHODS: We performed a literature search using targeted search terms to identify articles meeting inclusion criteria. Data extraction of study characteristics and outcomes was performed by two independent researchers. The primary outcome was the author interpretation of WGS utility in the investigation of suspected healthcare-associated transmission of NTM. The secondary outcome was whether a transmission route was identified through WGS. RESULTS: Thirty-one studies were included in the final analysis with 28 (90%) concluding that WGS was helpful in transmission investigations and in 19 of these 28 (68%) WGS aided in identifying a transmission route. The most common identified transmission routes were water-borne point sources (10), heater-cooler units (6), patient-to-patient (4), and a healthcare worker (1). CONCLUSION: WGS is an informative tool in investigating healthcare transmission of NTM.

Humans↗

PubMed2026

Public health, public protest: The role of health burdens and healthcare access in protest mobilisation.

Health and politics are intertwined, yet few studies have examined the association between health and protest. This study examined whether population health burdens were associated with protest incidence and whether healthcare access modified these associations. Analysis was based on an unbalanced 2004-2023 country-year panel, combining protest counts from ACLED with rates for 22 GBD causes. Mixed-effects negative-binomial models estimated incidence-rate ratios (IRRs) with interactions for healthcare access (±1 SD). Two-way fixed-effects Poisson models were estimated as a benchmark to distinguish cross-national associations from within-country dynamics. Health burdens were systematically, but heterogeneously, associated with protest. Rates for several non-communicable burdens were associated with protest, notably musculoskeletal disorders (IRR 1.72, 95% CI 1.37-2.15), neoplasms (1.24, 1.06-1.44), substance-use disorders (1.32, 1.12-1.56) and HIV/AIDS and other STIs (1.24, 1.12-1.38). Higher healthcare access generally attenuated health-protest associations. Fixed-effects models confirmed several associations (e.g. HIV/AIDS, neoplasms) but revealed that others (e.g. maternal/neonatal disorders, enteric infections) were driven primarily by cross-national differences. Population health burdens were associated with cross-national variation in protest mobilisation. Chronic, non-communicable burdens were associated with heightened protest, whereas poverty-linked and early-life burdens were associated with lower mobilisation. Healthcare access was associated with attenuation of these relationships.

Humans↗

PubMed2026

The application of artificial intelligence in healthcare practice: A mapping review of systematic reviews.

Artificial intelligence (AI) is rapidly transforming healthcare practice, with growing evidence supporting its use in diagnosis, prognosis, treatment planning, and operational decision-making. The proliferation of systematic reviews in recent years underscores the need for an updated synthesis of the literature to inform research, policy, and practice. We searched PubMed, Web of Science, Scopus, IEEE Xplore, and CINAHL for systematic reviews and meta-analyses published between 2019 and February 2026. Eligible reviews focused on AI applications in healthcare practice, were peer-reviewed, and written in English. A total of 368 reviews met the inclusion criteria. Publication volume increased steadily, peaking in 2025. AI research was concentrated in high-density domains, such as radiology, oncology, and critical care. Across reviews, diagnostic imaging, electronic health record (EHR) data, and biomarkers/laboratory results accounted for 68% of training data sources, though newer data types, such as wearable device and sensor data, emerged from 2022 onward. Diagnosis, prognosis, and treatment comprised over 80% of AI applications, with novel uses emerging in recent years, such as AI-assisted clinical documentation (e.g., ambient documentation tools) and patient education. Ethical concerns were reported in 78.5% of reviews, with privacy, model accuracy, data and algorithmic bias, and explainability as recurrent themes. The proportion of reviews reporting ethical concerns increased from 2021 to 2025. AI applications in healthcare are expanding in scope, diversifying in data sources, and evolving toward novel clinical and operational uses. The human-centered AI or augmented intelligence paradigm, integrating computational precision with clinical expertise, holds significant promise but will require parallel advances in governance, regulatory frameworks, and ethical oversight to ensure safe adoption.

Artificial Intelligence↗

PubMed2026

Status of dementia care among healthcare practitioners in Nigerian tertiary hospitals: a cross-sectional study.

BACKGROUND/OBJECTIVES: Dementia is an escalating public health concern globally. This study evaluated the knowledge, attitudes, practices, and perceived barriers to dementia care among healthcare practitioners in Nigerian tertiary hospitals, aiming to identify practitioner-related sociodemographic predictors and systemic barriers affecting dementia care delivery. METHODS: We collected data from May 2024 to May 2025 for this cross-sectional study in 12 purposively selected tertiary hospitals across Nigeria's six geopolitical zones. Participants included physicians, nurses, pharmacists, and other professionals involved in geriatric psychiatric care. Using multistage and convenience sampling, 394 respondents were recruited (response rate: 99.5%). Data were collected via a validated Dementia Care Practice Questionnaire (Cronbach's α = 0.84) and analyzed with SPSS v22. Descriptive statistics, Chi-square tests, and odds ratios (ORs) identified associations (significance: p ≤ 0.05). RESULTS: Of 394 respondents, 51.5% were aged ≥40 years, and 54.8% were female. While 62.9% demonstrated adequate knowledge, negative perceptions (51.3%) and attitudes (56.9%) were common. Despite this, 71.3% reported engagement in dementia care, and 75.6% demonstrated appropriate professional help-seeking behaviour when confronted with dementia care challenges. Practitioner-reported barriers included limited training opportunities, geographical barriers affecting patient access to dementia services, and inadequate staffing. Predictors of desirable care practices among healthcare practitioners included age ≥40 years, female gender, Christian affiliation, and ≥5 years of professional experience. CONCLUSION: Although many healthcare practitioners are involved in dementia care, gaps in perceptions, attitudes, and structural support persist. Interventions should focus on targeted training, system strengthening, and policy reform to improve dementia care outcomes.

Barriers to care↗

PubMed2026

Privacy, security, and reliability risks of artificial intelligence in healthcare: a systematic review of empirical evidence.

BACKGROUND: Artificial intelligence (AI) is increasingly integrated into healthcare information systems, supporting clinical decision-making, imaging analysis, and predictive modeling. While these applications offer operational and clinical benefits, they also introduce emerging risks to patient privacy, data security, and system reliability. OBJECTIVE: To systematically review empirical evidence on privacy breaches, security vulnerabilities, and misuse associated with AI applications in healthcare settings. METHODS: PubMed, Embase, Web of Science, Scopus, IEEE Xplore, and ACM Digital Library were searched for empirical studies published between January 2015 and November 2025 that evaluated AI use or misuse in clinical diagnosis, treatment, or decision-making. Two reviewers independently screened studies and extracted data using a standardized form. Findings were synthesized narratively due to heterogeneity in study designs, AI methods, and reported outcomes. RESULTS: Of 7,285 records identified through database searches and 205 through citation screening, 22 empirical studies met the inclusion criteria, spanning multiple clinical domains and data modalities, predominantly medical imaging applications. Five recurring threat categories were identified: patient re-identification, membership inference, unauthorized access and adversarial exploitation, input manipulation, and misuse or overinterpretation of AI outputs. Across studies, AI models were shown to encode latent biometric signals across diverse data types, limiting the effectiveness of traditional anonymization and synthetic data approaches. Adversarial attacks and input manipulation were also shown to compromise diagnostic performance and system integrity. CONCLUSION: This systematic review provides empirical evidence suggesting that contemporary AI systems in healthcare introduce privacy and security risks that may challenge traditional assumptions about data protection. These findings underscore the need for privacy- and security-by-design approaches and governance frameworks that address risks across the AI lifecycle.

Humans↗

PubMed2026

Non-motor symptoms and healthcare utilization before diagnosis of myasthenia gravis: a nationwide cohort study.

BACKGROUND: Non-motor symptoms have been reported prior to myasthenia gravis (MG) diagnosis. However, the temporal patterns of non-motor symptoms and healthcare utilization before MG diagnosis remain unclear. METHODS: We conducted a retrospective, population-based cohort study using the Korean National Health Insurance Service (KNHIS) database from 2011 to 2021. Incident MG cases were identified using the International Classification of Diseases, Tenth and Rare Intractable Disease codes. Individuals younger than 20  years or with missing health screening data were excluded. Each MG case was matched 1:10 by age, sex, and index date to controls. Non-motor symptoms and healthcare utilization were defined using operational criteria derived from KNHIS claims data. Rate ratios (RRs) and 95 % confidence intervals (CIs) were estimated across four prespecified intervals (0-1, 1-2, 2-5, and 5-10  years) before MG diagnosis. RESULTS: We included 8,355 MG patients and 83,550 controls (mean age, 53.7  years; male, 44 %). MG patients had higher rates of any non-motor symptoms over 10  years(RR 1.34; 95 % CI 1.30-1.39), with the sharpest increase in the year before diagnosis. Depression, anxiety, migraine, constipation, and insomnia consistently showed higher RRs across all intervals. Hospitalizations (RR 1.66; 95 % CI 1.61-1.71) and outpatient clinic visits (RR 1.10; 95 % CI 1.04-1.17) were consistently higher across 10  years, peaking during the 0-1 year before MG diagnosis. CONCLUSION: Non-motor symptoms and healthcare utilization increased years before MG diagnosis. Earlier recognition of these symptom patterns may facilitate timelier evaluation for MG and improve diagnostic pathways.

Humans↗

PubMed2026

Knowledge on the Haemophilia Care Among Healthcare Providers in Tanzania: A Multicenter Cross-Sectional Study.

BACKGROUND: Haemophilia is a rare inherited bleeding disorder associated with recurrent bleeding, disability, and mortality when diagnosis and management are delayed. In low- and middle-income countries, limited diagnostic capacity, access to treatment and gaps in Healthcare Providers' (HCPs') knowledge are major contributors to morbidity and mortality. In Tanzania, the recent improvement in haemophilia services highlights the need for systematic evaluation of HCPs' knowledge and clinical practices. OBJECTIVE: The study assessed the knowledge of haemophilia care among healthcare providers in Tanzania. METHODS: A multicenter hospital-based cross-sectional study was conducted among HCPs in tertiary and regional hospitals in Tanzania. A structured self-administered questionnaire assessed knowledge on haemophilia, including the pathophysiology, clinical features, diagnosis, treatment, and complications. Data were analyzed using IBM SPSS statistics version 27. RESULTS: Among 799 HCPs assessed (50.9%) aged 20-29 and (59.2%) males. Nurses were the majority (31.8%), and 75.2% had ≤5 years' experience. Overall haemophilia knowledge was high (median 83.3%, IQR: 75.9-88.9), strongest performance in general knowledge and weakest in treatment (68.2%, IQR: 54.5-77.3). Most respondents identified haemophilia as inherited (95.6%), non-infectious (93.7%), and recognized prolonged bleeding after injury or circumcision as key-symptoms (>90%). Knowledge varied by cadre, department, and experience (p<0.05); physicians and specialists scored higher than nurses, while health attendants scored lower. CONCLUSION: Healthcare providers demonstrated fairly adequate general knowledge of haemophilia. However, gaps remain in understanding genetic inheritance, acquired haemophilia, and modern treatment strategies, with knowledge variation by cadre, department, and experience, highlighting the need for targeted education across all HCPs groups.

Tanzania↗