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PubMed2025

Systems Factors Contributing to Racial/Ethnic Disparities in Maternal Health: A Systematic Review.

INTRODUCTION: Despite ongoing efforts to reduce adverse maternal outcomes, including maternal mortality and severe maternal morbidity, racial/ethnic disparities in outcomes persist in high-income countries, including the United States (US) and Canada. Limited research has examined hospital-level factors that may drive disparities and contribute to adverse outcomes. This systematic review summarizes factors within the health system contributing to adverse outcomes and racial/ethnic disparities in the US and Canada to inform future policies and practices. METHOD: We searched SCOPUS, PubMed, EBSCOhost, and ProQuest Healthcare Administration for studies that reported hospital-level factors contributing to adverse maternal outcomes and racial/ethnic disparities. The review followed a two-stage screening process. The risk of bias of the included studies was evaluated using the Mixed Methods Appraisal Tool. The System Engineering Initiative for Patient Safety (SEIPS) 2.0 framework guided the identification and categorization of factors. RESULTS: Of 2441 studies retrieved, 30 met the inclusion criteria. Twenty-eight studies were conducted in the US, and 2 were conducted in Canada. The review included 16 qualitative, 11 quantitative, and 3 mixed-methods studies. We identified 60 factors associated with different system components, including person(s) (12%), tasks (28%), tools and technology (7%), internal environment (10%), organization (28%), and external environment (15%). Shortage of resources, including staffing, poor care coordination, and discriminatory organizational practices, were key factors described in the studies. CONCLUSION: Addressing health system factors in addition to broader societal factors is important to reduce adverse outcomes and promote equity for all women and birthing persons.

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PubMed2026

A Critical Assessment of Evidence-Based Design's Knowledge Base and Inspiration: A Systematic Review.

PurposeThis study examines Evidence-Based Design (EBD) as an epistemological framework for guiding design research and practice, with a particular focus on its reliance on Evidence-Based Medicine (EBM) as a source of methodological inspiration.BackgroundOver the past two decades, EBD has been promoted as a way to strengthen design processes through the systematic use of scientific evidence. Its relationship to EBM, however, remains conceptually ambiguous: EBD draws legitimacy from EBM's hierarchical conception of "best evidence" while at the same time acknowledging the specificities of design practice, which do not easily fit such a model.MethodologyA systematic review was conducted on 31 publications in the design research literature that explicitly address the tension surrounding EBD's conception of "best evidence." The criticisms raised were coded and analyzed by main topics and subtopics.ResultsThe review highlights several reasons why EBM's hierarchical view of "best evidence" is an unsuitable epistemological foundation for EBD. It imposes scientifically inappropriate and practically ineffective methodological standards, devalues important sources of design knowledge, and fails to address central epistemic challenges intrinsic to design processes.ConclusionsBy bringing together critical yet fragmented insights from the literature, this study argues for the development of an updated epistemological framework for EBD. Constructing this framework will require sustained interdisciplinary dialogue between design research and philosophy of science.

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PubMed2026

Effectiveness of an AI-based home exercise app for rehabilitation of rotator cuff-related shoulder pain: A randomized controlled trial.

BACKGROUND: Rotator cuff-related shoulder pain contributes to disability and healthcare use. Although therapeutic exercise is first-line treatment, limited supervision and adherence may reduce its effectiveness; digital rehabilitation with real-time feedback may address these limitations. OBJECTIVES: To evaluate the effectiveness of adding a digital rehabilitation program to standard physiotherapy on pain, function, fear-avoidance beliefs, and healthcare utilization. DESIGN: Single-center, assessor-blinded, randomized controlled trial with two parallel groups. METHOD: Forty-six adults (mean age 59 years) with rotator cuff-related shoulder pain were randomized to 12 weeks of conventional physiotherapy or physiotherapy plus an AI-based digital rehabilitation program using computer vision for real-time feedback and performance monitoring. Outcomes were assessed at baseline and at 2, 4, and 12 weeks. Pain intensity (NPRS) was primary outcome; secondary outcomes included upper limb function (QuickDASH), fear-avoidance beliefs (FABQ), and post-intervention healthcare utilization. Analyses followed an intention-to-treat approach. RESULTS: Pain reduction exceeded the MCID (1.3) at 4 and 12 weeks. Between-group differences favoured the intervention at Weeks 2 and 4 (MD -0.7; 95% CI -1.13 to -0.14 and MD -1.01; 95% CI -1.8 to -0.2, respectively). Upper limb function improved more at Week 4 (MD -7.3; 95% CI -12.3 to -2.2). FABQ scores decreased more at Week 12 (MD -7.6; 95% CI -14 to -0.5). Fewer participants in the experimental group required post-intervention healthcare (3 vs 10; p = 0.02). CONCLUSION: Adding AI-based home exercise app to conventional treatment improve pain and may improve function and reduce healthcare utilization in rotator cuff-related shoulder pain.

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PubMed2026

Power as equal ability, knowledge and resistance: Systematic review of experiences of adults with noncommunicable diseases.

PURPOSE: To analyse subjective experiences of power of adults with noncommunicable diseases in relationships with healthcare practitioners as well as underlying facilitators and barriers of these experiences. METHODS: Systematic review (4 databases) of experiences using reflexive thematic analysis underpinned by critical realist approach. The analysis was conducted with an abductive reasoning using previous theories on social power as well as retroduction. RESULTS: Based on 24 studies, we formed three themes, which depict experiences of power as 1) the position, equal ability and freedom to make one's own choices and (re)negotiate within shared dialogue, 2) the ability to use knowledge to claim one's rights, 3) resistance. Facilitators were connected to acknowledgement as an equally valuable individual, positive healthcare practitioner attitudes and actions towards patient activity and views, safety in the relationship as well as to sufficient, clear and varied information. Main barriers were experiences of dehumanisation, negative healthcare practitioner attitudes and actions, perceived or assumed practitioner domination in interactions, lack of or incomprehensible knowledge and testimonial smothering. CONCLUSION: Results suggest that adults with noncommunicable diseases may experience power primarily as a positive power: being acknowledged as having legitimate position to make decisions and being in possession of varied knowledge through which they can gain agency to protect and claim their rights, by resisting, if necessary. Healthcare practitioners are in key position to support these experiences through positive transforming actions, while knowledge asymmetries, persistent inequality and paternalistic structures continue to hinder it.

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PubMed2026

The effectiveness of digital health interventions for type 2 diabetes in underserved populations: A systematic review and meta-analysis.

This systematic review and meta-analysis of 12 randomized controlled trials (1835 participants) evaluated whether digital health interventions (DHIs) improve glycemic control among underserved adults with type 2 diabetes (T2D), including racial/ethnic minority, low-income, Medicaid-insured, rural, and low-health-literacy populations. Searches of PubMed, Embase, and the Cochrane Central Register of Controlled Trials from inception to December 20, 2025 identified eligible parallel-group randomized controlled trials reporting change in hemoglobin A1c (HbA1c). Two reviewers independently screened studies, extracted data, and assessed risk of bias using the revised Cochrane Risk of Bias 2 tool. Random-effects meta-analysis showed that DHIs produced a modest but statistically significant HbA1c reduction versus control (mean difference, -0.37 %age points; 95% CI, -0.44 to -0.30; P < .0001; equivalent to -4.0 mmol/mol). Heterogeneity was moderate-to-substantial (I² = 69.9%). Subgroup analyses suggested directionally similar effects by population group and intervention modality, but interpretation was limited by study-level data and the small number of trials. Funnel-plot inspection and Egger's test (P = .31) did not suggest major small-study effects, although power was limited. Overall certainty for HbA1c was moderate. DHIs may support more equitable diabetes care when implemented with cultural tailoring, language access, digital-literacy support, and technology-access safeguards.

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PubMed2026

Failure modes and effects analysis for clinical implementation of online adaptive radiotherapy: A systematic review.

BACKGROUND: The accuracy of radiotherapy is limited by anatomical variations occurring over time scales ranging from sub-seconds to days. Online Adaptive Radiotherapy (OART) addresses this by enabling daily plan adaptation based on real-time imaging. While OART offers improved dose conformity, its dynamic, time-constrained workflow introduces novel failure modes that challenge traditional quality assurance protocols. PURPOSE: This study aims to synthesize the existing literature on Failure Modes and Effects Analysis (FMEA) for OART to systematically catalog risks and identify mitigation strategies. METHODS: A systematic literature search was conducted to identify studies applying FMEA to OART workflows. Eleven studies were included, covering MR-guided (ViewRay MRIdian, Elekta Unity), CBCT-guided (Varian Ethos), and MR-enhanced C-arm linac systems. To address heterogeneity in risk scoring methodologies (e.g., TG-100 10-point scales vs. 5-point rankings), extracted failure modes were harmonized into a standardized three-tier risk classification system (Class I: Low, Class II: Intermediate, Class III: High). RESULTS: A total of 300 unique failure modes were identified, with 49.6 percent classified as high-risk (Class III). Analysis revealed that the majority of high-risk failures were concentrated in the online treatment delivery phase, specifically within human-computer interactions and anatomical contouring steps. CONCLUSIONS: This study supports the development of tailored, robust QA frameworks that prioritize human factors and process consistency to guide safe implementation in diverse clinical settings.

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PubMed2025

Artificial Intelligence in Diagnosing Depression Through Behavioural Cues: A Diagnostic Accuracy Systematic Review and Meta-Analysis.

AIM: To synthesise existing evidence concerning the application of AI methods in detecting depression through behavioural cues among adults in healthcare and community settings. DESIGN: This is a diagnostic accuracy systematic review. METHODS: This review included studies examining different AI methods in detecting depression among adults. Two independent reviewers screened, appraised and extracted data. Data were analysed by meta-analysis, narrative synthesis and subgroup analysis. DATA SOURCES: Published studies and grey literature were sought in 11 electronic databases. Hand search was conducted on reference lists and two journals. RESULTS: In total, 30 studies were included in this review. Twenty of which demonstrated that AI models had the potential to detect depression. Speech and facial expression showed better sensitivity, reflecting the ability to detect people with depression. Text and movement had better specificity, indicating the ability to rule out non-depressed individuals. Heterogeneity was initially high. Less heterogeneity was observed within each modality subgroup. CONCLUSIONS: This is the first systematic review examining AI models in detecting depression using all four behavioural cues: speech, texts, movement and facial expressions. IMPLICATIONS: A collaborative effort among healthcare professionals can be initiated to develop an AI-assisted depression detection system in general healthcare or community settings. IMPACT: It is challenging for general healthcare professionals to detect depressive symptoms among people in non-psychiatric settings. Our findings suggested the need for objective screening tools, such as an AI-assisted system, for screening depression. Therefore, people could receive accurate diagnosis and proper treatments for depression. REPORTING METHOD: This review followed the PRISMA checklist. PATIENTS OR PUBLIC CONTRIBUTION: No patients or public contribution.

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PubMed2026

Evaluation of one-step amplicon-based targeted enrichment for SARS-CoV-2 whole-genome sequencing using the Midnight amplicon scheme.

Genomic surveillance proved invaluable during the COVID-19 pandemic for tracking SARS-CoV-2 variants and guiding outbreak responses, underscoring the ongoing need to reduce whole-genome sequencing (WGS) costs and improve workflow efficiency to ensure accessibility in resource limited settings. Here, we evaluated a one-step reverse transcription polymerase chain reaction (RT-PCR) approach using the Midnight V2 primer scheme for targeted amplification of the SARS-CoV-2 genome, assessed its compatibility with Illumina sequencing, and compared its performance to a well-established two-step method. Initially, we determined optimal RT-PCR reaction conditions using the Midnight V2 primer panel for the one-step RT-PCR kit and scaled reaction volumes for both RT-PCR and library preparation. Clinical specimens (n = 53) that had undergone routine WGS for surveillance purposes using the established two-step RT-PCR method were compared using the one-step RT-PCR assay. For samples with genome completeness greater than 70%, both methods gave comparable results with similar sequence coverage and 100% concordance for lineage assignment. Further investigation revealed a higher percentage of reads aligning to the SARS-CoV-2 genome with a greater depth of coverage using the one-step method compared to the two-step method. Finally, analysis of scaled one-step and library reaction volumes revealed significant cost savings for samples undergoing WGS. Overall, the results presented here verify the accuracy and reproducibility of one-step targeted amplification and offer an efficient and cost-effective workflow for routine SARS-CoV-2 genomic surveillance.

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PubMed2026

Effects of acute resistance exercise on prefrontal oxygenation and task-switching performance: Considerations of loading strategies and blood flow restriction.

Although acute resistance exercise (RE) has been proposed to influence cognitive flexibility and underlying neural mechanisms, it remains unclear whether these effects vary across loading strategies and whether exercise-induced prefrontal hemodynamic responses translate into cognitive outcomes. The present study examined (1) prefrontal cortex (PFC) oxygenated hemoglobin (O2Hb) responses across exercise sets and conditions, (2) the effects of low-load (LL), LL with blood flow restriction (BFR), and high-load (HL) RE on task-switching performance, and (3) whether exercise-related PFC O2Hb responses were associated with pre- to post-exercise changes in task-switching performance. Thirty physically active adults completed three randomized, counterbalanced RE conditions consisting of four sets of barbell squats. LL was performed at 30% one-repetition maximum (1RM) with and without BFR, whereas HL was performed at 70% 1RM. Cognitive flexibility was assessed pre- and post-exercise using a modified Stroop task, indexed by switch-cost reaction time (RT) and accuracy. PFC O2Hb was assessed using functional near-infrared spectroscopy during exercise and expressed as changes from the resting baseline for each set (Sets 1-4). PFC O2Hb increased across sets, rising from Set 1 to Set 3 before plateauing, with no differences observed across conditions. Switch cost RT and accuracy did not improve from pre- to post-exercise, and no differences across conditions were detected. PFC O2Hb during the final set was not associated with changes in switch cost. These findings suggest that although acute RE elicits robust increases in prefrontal hemodynamic activity, such responses may not translate into acute improvements in cognitive flexibility.

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PubMed2026

Leading with Innovation: Maternal Health Transformation in New York City Health + Hospitals.

New York City's (NYC) maternal health crisis drew close attention in the late 2010s, driven by alarming data: Approximately 30 women died annually during childbirth in NYC, Black non-Hispanic women were 12 times more likely to die than white women, and more than 3,000 women experienced life-threatening birth complications each year. In response, NYC committed $12.8 million in July 2018 to reduce maternal mortality and eliminate racial disparities.NYC Health + Hospitals (H+H)-the nation's largest public health system, serving 1.1 million patients annually with roughly 15,000 births per year-became the primary vehicle for this initiative. With 80 percent of the system's deliveries covered by Medicaid and a patient population that is 51.2 percent Hispanic and 27.1 percent Black, H+H is uniquely positioned to lead the fight against maternal health inequity.Three flagship programs anchor H+H's response to the city's maternal mortality rate. The OB Simulation Program, launched in 2012 and expanded in 2018, was the first in the nation to use mannequins of color to train thousands of providers in obstetric emergencies. The Maternal Home Program, piloted at H+H's Kings County Hospital in 2019 and scaled system-wide by 2021, has served more than 10,341 patients, generating more than 33,000 referrals for social, behavioral health, and community resources. The Cardio-Obstetrics Program located at Kings County Hospital targets cardiovascular disease-the leading cause of maternal death among Black women-through screening, education, and community outreach. These programs are a health equity imperative, made more urgent by impending federal Medicaid cuts resulting from the H.R.1 One Big Beautiful Bill Act (passed on July 4, 2025).

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PubMed2026

Analysis of deep learning techniques in computer-aided diagnosis for meniscus injuries: a systematic literature review.

Meniscus informatics is a growing subject of study in the healthcare industry. One of the major hindrances to the healthcare system's transformation is obtaining knowledge and meaningful information from complicated, high-dimensional and diverse sources. Modern biomedical research, for instance, has seen an increase in the use of complex, dissimilar, poorly documented, and generally unstructured electronic health records, imaging, sensor data and text, even after many current techniques have been used to extract more robust and useful elements from the data for analysis. New efficient standards for building end-to-end learning models from complex data are therefore needed. Therefore, the current study aims to examine the most recent research on the use of deep learning techniques for diagnosing meniscus tears and recommend creating comprehensive and meaningful interpretable structures that might benefit the healthcare industry. We also draw attention to shortcomings and the need for better technique development, and we provide new perspectives about this exciting new development in the field.

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PubMed2026

The influence of organizational culture on medication safety practices and associated risk factors in the community setting: A systematic review.

BACKGROUND: Increasing attention has been given to the role of organizational culture in influencing medication safety practices across healthcare settings. The lack of widely accepted standardized instrumentation makes operational measurement of organizational culture and medication safety challenging. The purpose of this systematic review was to examine the impact of organizational culture on medication safety within community healthcare settings. METHODS: MEDLINE, CINAHL, Scopus, and Nursing & Allied Health were searched in August 2025 using keywords, subject terms, field codes, and Boolean operators to identify papers relevant to the review question; bibliographies of included studies were also reviewed. Screening and full-text review were completed independently by two reviewers with a third to adjudicate conflicts. The Critical Appraisal Skills Programme was used for quality assessment. The PRISMA statement guided the development and implementation of the review. RESULTS: Thirteen articles were included representing various community settings. Most studies reported on untoward medication events, but few measured systematically collected safety data before and after an intervention. Organizational culture was seldom defined or operationalized. Most studies were methodologically sound, but the overall level of evidence was weak to moderate. CONCLUSION: Organizational culture influences medication safety through aspects such as communication channels, teamwork, training, and an environment that allows error and near-miss reporting. Few studies explicitly evaluate the causal impact of culture interventions on measurable medication safety outcomes in community healthcare settings. Further research should incorporate standardized measurement tools and intervention-based, pre-post designs to better understand how organizational culture influences medication safety in community healthcare settings.

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PubMed2026

Orofacial Cleft Disparities in American Indian and Alaska Native Populations: A Systematic Review and Meta-Analysis.

ObjectiveTo evaluate the prevalence, access to care, and health outcomes of orofacial clefts (OFCs) among American Indian and Alaska Native (AI/AN) populations through a systematic review and meta-analysis.DesignSystematic review and meta-analysis performed in accordance with PRISMA 2020 guidelines and registered with PROSPERO (CRD420251035364).SettingUS-based population registries, hospital databases, and institutional or community-level retrospective studies involving AI/AN populations.Patients and ParticipantsAI/AN individuals with OFCs compared with non-Hispanic White patients.InterventionsPrimary cleft lip and palate repair, secondary cleft-related procedures, and multidisciplinary cleft care.Main Outcome Measure(s)Prevalence of OFCs, timing of cleft surgery, discharge disposition, access to specialists, and qualitative determinants of disparities.ResultsEighteen studies including more than 1985 AI/AN patients were identified. Meta-analysis of 5 studies estimated a pooled OFC prevalence of 15 per 10 000 live births (95% confidence interval: 5-49), with substantial heterogeneity (I2 = 99.8%). Individual studies reported significantly higher OFC prevalence in AI/AN populations compared to non-Hispanic Whites (odds ratio range: 1.44-2.68). Geographic maldistribution of craniofacial-trained surgeons, increased odds of nonhome discharge, and delayed cleft palate repair were consistently observed barriers. Qualitative analyses highlighted structural inequities, perceived racism, and lack of culturally responsive care as major contributors to disparities.ConclusionsAI/AN populations face a disproportionately high burden of OFCs alongside structural barriers to timely, culturally competent care. Addressing these disparities requires community-engaged, multidisciplinary interventions that improve geographic access and integrate culturally responsive approaches to care.

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PubMed2025

Feasibility, Acceptability, and Preliminary Effectiveness of Family Navigation for Low-income Ethnoracially Diverse Preschoolers with Developmental Concern.

OBJECTIVE: To assess for feasibility, acceptability, and preliminary effectiveness of an ethnoracially-matched family navigation intervention aimed at reducing barriers to developmental evaluations for preschoolers with developmental concern attending Head Start. METHODS: Fifty-eight parents of Head Start preschoolers who were identified as at risk for developmental delay were assigned using stratified block random sampling to the family navigation intervention (n = 28) and 30 controls (usual care). Key outcomes included the percentage of children who completed the planned intervention visits, satisfaction with the intervention, and the proportion of children guided by family navigators who completed developmental evaluations. RESULTS: Of the 28 families, 21 parents completed the family navigation intervention visits. The intervention sample was diverse, including 57% Black, 24% White, and 19% Latino(a) parents. Ninety percent of Head Start educators (n = 18) and 100% of healthcare providers (n = 6) were satisfied with the intervention. Parents qualitatively reported that they valued the advocacy support from the family navigators and navigators (n = 7) valued their role in "giving back." Sixty-six percent of the intervention group were seen by a healthcare provider to discuss developmental concerns showing preliminary effectiveness for completion of healthcare evaluations. However, there was no significant difference between those in the intervention and control group completing Head Start recommended evaluations, and over half of all participants were not referred for educational evaluations. CONCLUSION: Results support the feasibility, acceptability, and preliminary effectiveness of an ethnoracially matched family navigation intervention to reduce barriers to developmental healthcare evaluations for preschoolers at risk for developmental delays. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT03499405; Date of Registration: April 9, 2018.

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PubMed2026

A bimodal large language model reduces misalignment in patient education: A double-blinded randomized trial.

BACKGROUND: Effective patient education requires accurate communication aligned with patients' emotional and semantical needs. Text-based large language models (LLMs) lack access to non-verbal cues, which may contribute to misaligned responses. METHODS: We evaluated emotional and semantic misalignment in a text-based LLM using 64,200 utterances from 16,583 patient education cases across six departments and three centers. Dolphin was developed integrating text and audio cues and evaluated through emotion recognition, semantic consistency assessment, branch-level ablations, and a double-blinded randomized trial against a matched text-based LLM comparator (Chinese Clinical Trial Registry: (ChiCTR2500095933). FINDINGS: The text-based LLM showed emotional misalignment in 36.7% of responses and semantic misalignment in 28.3% of cases, with higher misalignment under greater burden. Dolphin outperformed the text-based LLM in emotion recognition accuracy (0.886 vs. 0.713) and semantic consistency (84.9% vs. 82.1%; both adjusted p < 0.001). Ablations supported contribution of audio branches. Dolphin received higher expert ratings than the text-based LLM and human educators (all p < 0.001). In 555 patients, Dolphin was associated with greater patient satisfaction (98.6% vs. 93.8%), suggestion acceptance (76.1% vs. 58.9%; p < 0.001), proactive disclosure (44.6% vs. 26.5%; p < 0.001), and fewer 7-day unplanned recontact (12.9% vs. 22.9%; p = 0.002). No unsafe recommendations or safety events were identified. CONCLUSIONS: Compared with text-based LLM, Dolphin improved emotional-semantic alignment and patient-education outcomes, supporting bimodal alignment as a strategy for reducing misalignment-driven communication failures. FUNDING: National Natural Science Foundation of China, State Key Laboratory Special Fund, and Chinese Academy of Medical Sciences Innovation Fund.

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PubMed2026

Disparities in guideline-adherent cardiovascular preventive care for people with diabetes: A systematic review and meta-analysis.

BACKGROUND: Clinical practice guidelines offer guidance on delaying the progression of cardiovascular disease in people living with diabetes. We sought to determine whether guideline-recommended cardiovascular preventive care for people living with diabetes differs according to sociodemographic indicators, globally. METHODS: We conducted a systematic review of studies that compared the sociodemographic characteristics of people diagnosed with type 1 or 2 diabetes who received cardiovascular preventive care as recommended by guidelines to those who did not. Sociodemographic predictors were defined by PROGRESS+ (an equity framework). We searched MEDLINE, EMBASE, and APA PsychInfo from 2010 to January 21, 2026. Studies were screened independently by two people. One person assessed the risk of bias and extracted data, and another verified. We pooled results using a random-effects model and assessed the certainty of evidence using GRADE. RESULTS: Twenty-five studies were included. Meta-analyses showed female, Black, and Hispanic individuals had slightly lower odds of receiving guideline-recommended prescriptions for lipid-lowering medication compared to Male, and White individuals, respectively (OR:0.89, 95%CI:0.79,1.00, moderate certainty; OR:0.78, 95%CI:0.74,0.81, high certainty; OR:0.86, 95%CI:0.59,1.26, low certainty). Individuals aged 18-45 years had moderately lower odds (OR:0.33, 95%CI:0.19,0.57, moderate certainty), no observed association for Asian individuals. Asian individuals had moderately lower odds of antihypertensive medication prescription (OR:0.42, 95%CI:0.38,0.46, high certainty). Evidence suggests likely no association between HbA1c testing and sex/gender or between sex/gender and lipid panel testing. CONCLUSIONS: Some disparities in guideline-recommended cardiovascular preventive care among people living with diabetes were found. These results are consistent with previous reviews and highlight the need to ensure guidelines consider equity and with improved dissemination.

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PubMed2026

Tele-Oncology in the Post-Pandemic Era: Clinical Integration, Access Disparities and Medico-Legal Accountability.

PURPOSE OF THE REVIEW: Tele-health has evolved from a marginal tool confined to rural populations and selected follow-up programs into a structurally integrated component of modern cancer care. Prior to COVID-19, its adoption was constrained by regulatory fragmentation, non-uniform reimbursement, and licensure barriers. This narrative review evaluates the evolutionary integration of tele-health in oncology post-COVID-19, examines digital disparities across patient populations, and addresses the medico-legal implications of this integration, with the objective of providing a comprehensive and clinically actionable framework for the governance of virtual oncology care. RECENT FINDINGS: The pandemic acted as a global catalyst, driving telehealth to over 50% of oncology outpatient encounters in some settings, before stabilising post-pandemic at approximately 10-20% of consultations within hybrid care models. Evidence supports meaningful clinical benefits - improved access to specialist services, reduced travel burden, and sustained continuity of care - with outcomes comparable to in-person care in postoperative follow-up, symptom monitoring, and survivorship. However, persistent disparities in device availability, connectivity, and digital literacy disproportionately affect older, rural, and socioeconomically disadvantaged patients, raising the risk that geographic inequalities are replaced by technological ones. From a medico-legal standpoint, the remote modality does not modify the applicable standard of care, yet restricted physical examination and reliance on patient-reported data introduce risks of diagnostic delay and incomplete clinical assessment, with direct implications for professional liability, data protection under HIPAA and GDPR, cross-border licensure, and multi-party accountability across physicians, institutions, and technology providers. Tele-oncology has become a permanent structural feature of modern cancer care, offering demonstrable benefits in access, continuity, and patient satisfaction. Yet its integration has been uneven, its governance remains fragmented, and its medico-legal landscape is still evolving. Realising the full potential of virtual oncology care - equitably and safely - requires coherent regulatory frameworks, sustained investment in digital infrastructure, and explicit attention to the populations at greatest risk of being left behind.

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PubMed2026

From fear to empowerment: the impact of employees AI awareness on workplace well-being - a new insight from the JD-R model.

PURPOSE: The primary purpose of the study was to explore the impact of health workers' awareness of artificial intelligence (AI) on their workplace well-being, addressing a critical gap in the literature. By examining this relationship through the lens of the Job demands-resources (JD-R) model, the study aimed to provide insights into how health workers' perceptions of AI integration in their jobs and careers could influence their informal learning behaviour and, consequently, their overall well-being in the workplace. The study's findings could inform strategies for supporting healthcare workers during technological transformations. DESIGN/METHODOLOGY/APPROACH: The study employed a quantitative research design using a survey methodology to collect data from 420 health workers across 10 hospitals in Ghana that have adopted AI technologies. The study was analysed using OLS and structural equation modelling. FINDINGS: The study findings revealed that health workers' AI awareness positively impacts their informal learning behaviour at the workplace. Again, informal learning behaviour positively impacts health workers' workplace well-being. Moreover, informal learning behaviour mediates the relationship between health workers' AI awareness and workplace wellbeing. Furthermore, employee learning orientation was found to strengthen the effect of AI awareness on informal learning behaviour. RESEARCH LIMITATIONS/IMPLICATIONS: While the study provides valuable insights, it is important to acknowledge its limitations. The study was conducted in a specific context (Ghanaian hospitals adopting AI), which may limit the generalizability of the findings to other healthcare settings or industries. Self-reported data from the questionnaires may be subject to response biases, and the study did not account for potential confounding factors that could influence the relationships between the variables. PRACTICAL IMPLICATIONS: The study offers practical implications for healthcare organizations navigating the digital transformation era. By understanding the positive impact of health workers' AI awareness on their informal learning behaviour and well-being, organizations can prioritize initiatives that foster a learning-oriented culture and provide opportunities for informal learning. This could include implementing mentorship programs, encouraging knowledge-sharing among employees and offering training and development resources to help workers adapt to AI-driven changes. Additionally, the findings highlight the importance of promoting employee learning orientation, which can enhance the effectiveness of such initiatives. ORIGINALITY/VALUE: The study contributes to the existing literature by addressing a relatively unexplored area - the impact of AI awareness on healthcare workers' well-being. While previous research has focused on the potential job displacement effects of AI, this study takes a unique perspective by examining how health workers' perceptions of AI integration can shape their informal learning behaviour and, subsequently, their workplace well-being. By drawing on the JD-R model and incorporating employee learning orientation as a moderator, the study offers a novel theoretical framework for understanding the implications of AI adoption in healthcare organizations.

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