Search Results (796)

Background: Palliative care addresses not only physical symptoms but also the social, psychological, and spiritual needs of patients. Nurses play a key role in identifying and responding to these needs, yet their perceptions and preparedness may vary. Objectives: This study aimed to explore nurses’ perspectives on the psychological, social, and spiritual needs of palliative patients, assess how well these needs are being met, and examine the influence of nurses’ self-assessed education levels on their evaluations. Methods: A cross-sectional survey was conducted among 237 registered nurses with palliative care experience in Split-Dalmatia County, Croatia. Two validated questionnaires were used to assess the perceived importance of 53 patient needs and the extent to which these needs were satisfied. Results: Findings revealed significant discrepancies between the perceived importance and satisfaction of nearly all psychological, social, and spiritual needs (p < 0.001), particularly regarding fear of death, suffering, and future uncertainty. Only 38.4% of nurses considered themselves adequately trained in palliative care, though most had some educational exposure to it. No statistical differences were found in need assessment based on nurses’ self-rated education. Most nurses reported emotional exhaustion (72.6%) and supported interdisciplinary care (95.8%), while 90.3% noted that responsibility for care often falls on families. Conclusions: Nurses recognize critical unmet needs in palliative patients and feel insufficiently prepared to address them. These findings underscore the need to improve palliative care education, provide emotional support for nurses, and implement systemic healthcare reforms to ensure comprehensive, dignified care. Full article

Background: Maternal mortality in Brazil remains a critical indicator of social and racial inequalities, reflecting structural failures in access to and quality of obstetric care. Black women, particularly those categorized as black or brown, are at a higher risk of dying during pregnancy, childbirth, or the postpartum period. This is the result of the intersection of institutional racism, poverty, and social vulnerabilities. This study aimed to analyze trends and associated factors of maternal mortality among black women in Brazil from 2000 to 2020. Methods: This is a retrospective cohort analytical study using data from the Brazilian Mortality Information System. The sample included women aged 10 to 49 years whose underlying cause of death was classified under ICD-10 codes O00–O99. Descriptive and bivariate analyses were conducted, as well as Poisson and multinomial logistic regressions to estimate adjusted risk ratios according to skin color, education, region, type, and place of death. Results: A total of 40,907 maternal deaths were identified, with 59.2% occurring among black women. The maternal mortality ratio was 39% higher among black women compared to white women and more than double among Indigenous women. Low education, residence in the North and Northeast regions, deaths outside hospital settings, and lack of formal investigation were independently associated with increased risk. Direct obstetric causes accounted for most deaths, with hypertensive disorders and puerperal complications being the leading conditions. Conclusions: Maternal mortality among black women in Brazil reveals deep structural inequalities. Urgent public policies that incorporate an intersectional perspective, addressing race, gender, and class, are necessary to reduce disparities and ensure equitable and dignified maternal healthcare. Full article

Background: The COVID-19 pandemic has put other infectious diseases, especially in children, into a new perspective. Our study focuses on two important viral infections: COVID-19 and influenza, which often present with similar clinical symptoms. Taking into consideration that the pathophysiology and systemic impact of the two viruses are distinct, which can lead to measurable differences in laboratory values, this study aimed to analyze laboratory features that differentiate between COVID-19 and influenza virus infections in pediatric patients. Methods: We statistically analyzed the routinely available laboratory data of 98 patients with influenza virus and 78 patients with COVID-19. Afterwards, the classification and regression tree (CART) method was performed to identify specific clinical scenarios, based on multilevel interactions of different features that could assist clinicians in evidence-based differentiation. Results: Significant differences between the two groups were observed in ALT, eosinophils, hemoglobin, and creatinine. Influenza-infected infants presented significantly higher leukocyte, neutrophil, and basophil counts compared to infants infected with COVID-19. Regarding children (over 12 months), significantly lower levels of ALT and eosinophil counts were observed in those with influenza compared to those with COVID-19. Furthermore, the CART decision tree model identified distinct profiles based on a combination of features such as age, leukocytes, lymphocytes, platelets, and neutrophils. Conclusions: After further refinement and application, such machine learning-based, evidence-driven models, considering the large scale of clinical and laboratory variables, might help to improve, support, and sustain healthcare practices. The differential decision tree may contribute to enhanced clinical risk assessment and decision making. Full article

Background/Objectives: Mobile health (mHealth) interventions can enhance chronic disease management, but their integration into public healthcare systems remains complex. DiabeText is the first SMS-based intervention in Spain delivering personalized diabetes self-management support using electronic health record data. This study explored perceived barriers and facilitators to the implementation of DiabeText in the Spanish public health context from the perspective of key stakeholders. Methods: A qualitative study was conducted using semi-structured interviews with 14 purposively selected stakeholders involved in digital health, diabetes care, data protection, and healthcare management across several Spanish regions. Interviews were thematically analyzed using Braun and Clarke’s approach and guided by the Implementation Research Logic Model. Results: Participants reported several barriers, including concerns regarding data protection, uncertainty about long-term sustainability, insufficient training and engagement of healthcare professionals and low digital literacy among certain patient groups. Facilitators included favorable institutional momentum for digital innovation, funding availability, perceived clinical utility and scalability of DiabeText, and growing patient familiarity with digital tools. Recommended strategies included integration into existing healthcare systems and workflows, professional training and use of familiar communication platforms. Conclusions: Effective implementation of DiabeText requires addressing regulatory, organizational, and equity-related barriers while leveraging institutional support and readiness for innovation. Early involvement of healthcare professionals, robust data governance, and investment in digital literacy are essential to ensure sustainable and equitable adoption. These findings provide actionable insights to support the integration of mHealth tools into chronic disease care in Spain and similar settings. Full article

People living in rural communities are typically underserved by public transportation services and face challenges in accessing healthcare, jobs, stores, and other destinations. Understanding the lived experiences of people who use public transportation in rural communities can help to inform a more equitable transportation system. This qualitative study gathered the perspectives of community health center employees about the public bus system for Hawai‘i Island, a rural county in the United States. Using a community-engaged research approach, the evaluation team interviewed 10 employees through either in-person small group interviews or online individual interviews between April and July 2023. Transcripts were coded and analyzed using a thematic analysis approach. While all study participants were selected for their interest in commuting to work by bus, most believed the bus was not a reliable or convenient option. Participants shared their experiences about not being able to rely on the bus schedule, feeling unsafe while walking to bus stops or waiting for the bus, and other barriers to using the bus system. Participants also shared their insights about how a reliable bus system would benefit community health center patients who needed transportation to more than just their medical appointments, but also to places like pharmacies, laboratory services, and grocery stores. These findings can be used to initiate discussions around the ways that community health centers can further address transportation as a social determinant of health and inform transportation providers about how to best plan and invest in transportation infrastructure and services to meet the needs of rural populations. Full article

The emerging field of dermatogenomics, which examines visible dermatologic phenotypes alongside their polygenic factors, offers insights for early disease recognition and initiation of preventative measures. This review explores key dermatologic manifestations serving as clinical markers of systemic diseases, emphasizing cardiovascular, autoimmune, neuropsychiatric, metabolic/endocrine, and cancer-related conditions. Importantly, the pathogenesis of certain skin conditions including psoriasis, atopic dermatitis, vitiligo, and hidradenitis suppurativa is linked to systemic disease through shared genetic and epigenetic mechanisms. The diagnostic markers for these integumentary diseases are discussed alongside their shared mechanisms to systemic diseases, highlighting the clinical manifestation typically seen in primary care settings. This narrative review integrates dermatology with genomics, primary care, preventative care, public health, and internal medicine perspectives, underscoring the importance of an interdisciplinary and collaborative approach to patient care. Lastly, this review advocates for standardized dermatogenomic screening thresholds, inclusivity and expansion of genomic datasets, and the leverage of artificial intelligence and multi-omic technologies in preventative healthcare. Full article

Background/Objectives: In the context of evolving healthcare systems, effective communication represents a fundamental skill for ensuring quality care and addressing the psychosocial needs of oncology patients. In line with the new challenges of nursing education, this study explores communication between nurses and oncology patients, analyzing facilitating and hindering factors from the nurses’ perspective within the hospital setting. Methods: A descriptive qualitative study was conducted using one-on-one semi-structured interviews. The interviews lasted from 15 to 30 min. The study population consisted of nurses working in the Medical Oncology units of the Regina Elena Institute in Rome (IRE). Data were analyzed using the Framework Analysis method by Ritchie and Spencer. Results: The sample consisted of 20 nurses with an average age of 33.5 years. Six main themes emerged: communication as the pillar of the care relationship between technical and human aspects, the need for a balance between closeness and personal protection, the influence of language and personalized approaches on communication, the stimulation of specific training needs, and barriers to nursing communication. Conclusions: Nurses recognize communication as an integral part of the care process and as a key competency for addressing the complex needs of oncology patients. However, inadequate training, time constraints, and staff shortages represent significant barriers, highlighting the need to invest in specific training programs and organizational strategies to improve the quality of care. Full article

Background/Objectives: Persistent inequities in healthcare experiences and outcomes among marginalized racial/ethnic groups and sexual and gender minority (SGM) populations have been well documented. However, disparities in perceptions of discrimination and bias between patients and health providers remain insufficiently understood. This review synthesizes the current evidence on how these groups differently perceive discrimination, how bias manifests in clinical encounters, and how intersecting identities shape healthcare experiences. Methods: A comprehensive review using SANRA guidelines examined racial/ethnic discrimination, SGM-related bias, provider implicit attitudes, minority stress processes, and structural determinants of inequity in healthcare settings. Articles were identified through systematic search strategies across major databases, and their conceptual, methodological, and theoretical contributions were analyzed. Results: Across studies, marginalized patients consistently reported discrimination, stigma, and mistrust in healthcare, whereas providers often underestimated the prevalence and impact of these experiences. Evidence indicates that implicit pro-White biases among providers influence communication quality, clinical decision-making, and patient comfort. Structural racism and intersecting minority statuses further compound disparities, contributing to delayed care, unmet health needs, and poorer outcomes. Limited alignment between patient and provider perceptions suggests a gap in recognition of inequitable treatment and its drivers. Conclusions: Healthcare inequities arise from interconnected, interpersonal, and structural mechanisms. Addressing these disparities requires multilevel interventions targeting provider training, institutional policy reform, and system-level barriers. Integrating both patient and provider perspectives is essential for developing equitable, affirming models of care and improving health outcomes for racial/ethnic and SGM populations. Full article

Knowledge-sharing is a deliberate exchange of information to enhance accessibility and reuse which is critical for improving healthcare delivery. This study assessed knowledge-sharing practices among dentists, pharmacists, and allied health professionals (AHPs) in nine public hospitals in South Africa’s Eastern Cape Province. A cross-sectional survey was conducted using purposive and stratified random sampling to recruit 99 participants. Data were collected via a validated questionnaire and analysed with SPSS v.22.0 using descriptive statistics. Respondents were predominantly female (77.6%) and aged 21–35 years (63.6%); AHPs comprised 65.7% of the sample. The results show a statistically significant association between profession and encouragement to adopt a global perspective (p = 0.017), while significant differences were observed between profession and encouragement to seek inter-team solutions (p = 0.020), and access to leadership-driven opportunities for interdisciplinary knowledge-sharing (p = 0.016). Despite observable patterns in the descriptive results, no other statistically significant differences by profession were observed for all other items. Collaboration with external communities and leadership-driven knowledge-sharing opportunities were also highest among dentists but limited overall. Adoption of information systems for knowledge exchange was low, particularly among pharmacists and AHPs. Participation in professional development and recognition of long-term knowledge-sharing strategies followed similar patterns. These findings highlight the need to strengthen leadership-driven opportunities for interdisciplinary knowledge-sharing and to develop targeted interventions to address specific gaps between professions. Full article

The management strategies in resectable non-small cell lung cancer (NSCLC) have changed over the last few years. Despite advancements in surgical techniques and conventional chemotherapy, patients with resectable NSCLC remained at high risk of future recurrence. Clinical trials have demonstrated improvements in response rates, pathological outcomes, and survival with the perioperative approach. Considering the findings of these landmark trials, there is a pressing need to contextualize and incorporate these global developments into the national practice framework. This review outlines key developments from recent clinical trials, with a focus on perioperative strategies in early-stage operable NSCLC from a Canadian perspective. We discuss the integration of checkpoint inhibitors in the perioperative setting for patients without actionable genomic alterations, adjuvant targeted therapies for EGFR and ALK mutant disease, and emerging tools such as ctDNA based minimal residual disease monitoring. The article also addresses the practical challenges of implementing these advances within the Canadian healthcare system, including systemic therapy approvals, barriers, and importance of multidisciplinary care to guide clinicians in optimizing patient outcomes. Full article

Background/Objectives: Unmet healthcare needs, driven by structural and patient-level barriers, are particularly critical in chronic obstructive pulmonary disease (COPD). However, limited research has examined how academic themes on this topic connect and evolve over time. This study analyzed the structure and temporal shifts in research trends on unmet healthcare needs in COPD to identify key concepts and topics and policy implications. Methods: We systematically searched PubMed, Embase, and CINAHL (12–15 March 2025) to identify English-language abstracts on unmet healthcare needs in COPD. Eligible studies were peer-reviewed articles with an English-language abstract that examined unmet healthcare needs from the patient perspective. In total, 451 abstracts were analyzed using text network analysis and Latent Dirichlet Allocation. Topic distributions before and after the coronavirus disease pandemic were assessed using chi-square tests, and findings were interpreted within Penchansky and Thomas’s 5A healthcare access framework. Results: Six topics emerged: socioeconomic disparities, early diagnosis and symptom management, guideline-based information and technology use, integrated care for advanced COPD, access to pulmonary rehabilitation, and equitable medication availability. These topics mapped onto all five access dimensions, underscoring the multidimensional nature of unmet healthcare needs. Network analysis identified management, diagnosis, symptoms, exacerbation, and other related terms as central hubs in the discourse. Post-pandemic, research shifted toward digital information delivery, technology adoption, and equitable pharmacotherapy. Conclusions: Findings suggest that reducing unmet healthcare needs in COPD requires integrated systems that address both disease complexity and access barriers. Targeted, multidisciplinary, and policy-driven interventions in highly central domains are needed to reduce disparities and improve outcomes. This study also confirmed a post-pandemic shift in research priorities, emphasizing the need for equitable and adaptive healthcare policies. Full article

Deep learning for semantic segmentation has made significant advances in recent years, achieving state-of-the-art performance. Medical image segmentation, as a key component of healthcare systems, plays a vital role in the diagnosis and treatment planning of diseases. Due to the fractal and scale-invariant nature of biological structures, effective medical image segmentation requires models capable of capturing hierarchical and self-similar representations across multiple spatial scales. In this paper, a Recurrent Neural Network (RNN) is explored within the Convolutional Neural Network (CNN) and Vision Transformer (ViT)-based hybrid U-shape network, named RCV-UNet. First, the ViT-based layer was developed in the bottleneck to effectively capture the global context of an image and establish long-range dependencies through the self-attention mechanism. Second, recurrent residual convolutional blocks (RRCBs) were introduced in both the encoder and decoder to enhance the ability to capture local features and preserve fine details. Third, by integrating the global feature extraction capability of ViT with the local feature enhancement strength of RRCBs, RCV-UNet achieved promising global consistency and boundary refinement, addressing key challenges in medical image segmentation. From a fractal–fractional perspective, the multi-scale encoder–decoder hierarchy and attention-driven aggregation in RCV-UNet naturally accommodate fractal-like, scale-invariant regularity, while the recurrent and residual connections approximate fractional-order dynamics in feature propagation, enabling continuous and memory-aware representation learning. The proposed RCV-UNet was evaluated on four different modalities of images, including CT, MRI, Dermoscopy, and ultrasound, using the Synapse, ACDC, ISIC 2018, and BUSI datasets. Experimental results demonstrate that RCV-UNet outperforms other popular baseline methods, achieving strong performance across different segmentation tasks. The code of the proposed method will be made publicly available. Full article

While large language models (LLMs) such as ChatGPT, Claude, and DeepSeek are evaluated based on their accuracy and truthfulness, “hallucinations” betray underlying structural limitations. These results are not simply incorrect answers, but statistical resonances; they are instances where models stabilize into statistically significant (though semantically unfounded) response patterns. Current frameworks fail to accommodate contextual semantics, experiential time, and intentionality as key dimensions for effective experience-based decision-making in complex digital spaces. This article presents an integration paradigm offered by the theory of uncertainty and incompleteness of information, extended by the Sophimatics approach with 2D complex time (t = t + i·t₀) and Super Time Cognitive Neural Network (STCNN) that provides both memory management, imagination enhancement, and creativity generation as computational primitives. By integrating probability with plausibility, credibility, and possibility, our model reconsiders the issue of evaluating the reliability of LLM results as a problem that goes beyond traditional probabilistic approaches. Accepting that hallucinations are an emerging phenomenon of resonance between statistical distributions, we suggest an extended probability method in which these resonances can be mitigated and directed towards a coherent cognitive understanding. The paper places this approach in the broader perspective of digital transformation at the information systems level and its implications for AI reliability, explainability, and adaptive decision-making in post-generative AI. Intuitive scenarios are described, based on the inclusion of complex time and Sophimatics in theoretical modelling, illustrating how prediction, historical-contextual adoption, and resistance to paradoxical or contradictory information are strengthened. The results point to this paradigm as a springboard for reliable, human-aligned AI capable of enabling digital transformation in sectors such as healthcare, finance, and governance. Full article

Background/Objectives: Multidisciplinary care is the gold-standard approach for delivering comprehensive pediatric healthcare. For children undergoing cochlear implant (CI) evaluation, multiple appointments are required to assess candidacy, set realistic expectations, and counsel families on rehabilitation and the psychosocial impact of hearing loss. Established pediatric CI users also need coordinated follow-up to address ongoing auditory, educational, and psychosocial needs. This study evaluated the satisfaction and family perspectives of the implementation of a virtual, team-based multidisciplinary model for both CI candidates and established CI users. Methods: Thirty-nine children and their families participated in discipline-specific telehealth consultations, including audiology, listening and spoken language (LSL) therapy, psychology, and educational services, followed by a 60 min multidisciplinary team meeting. Team meetings occurred during pre-implantation and at six months post-activation for CI candidates. Team meetings for established CI users were scheduled following completion of individual consultations. Providers summarized findings from their individual visits before transitioning to a caregiver-led discussion. Post-visit surveys assessed satisfaction and perceived benefit from the multidisciplinary model. Results: Thirty-nine dyads were enrolled (11 Pre-CI; 28 Established CI). Caregivers were predominantly mothers (89.7%), most identified as Hispanic (55.3%) and White (71.1%). Over half of children identified as Hispanic (59%) and White (71.8%); most were diagnosed with hearing loss at birth (55.9%). Satisfaction with the virtual model was uniformly high: 100% of caregivers were satisfied or very satisfied, and most rated care quality as “very good” or “excellent.” LSL therapy was most frequently rated as the most beneficial visit (70% Pre-CI; 45% Established CI). Caregivers strongly preferred ongoing team-based care, with 55–80% reporting that they would like it to occur every six months and 95–100% preferring remote meetings. Conclusions: A virtual multidisciplinary model offers a high-quality, family-centered approach for both CI evaluations and ongoing management of established CI users. By integrating simultaneous team-based sessions, this model not only supports the ‘whole child’ but also strengthens the family system by improving communication, streamlining care, and reducing the burden of multiple in-person appointments. Families consistently report high levels of satisfaction with the convenience, clarity, and collaboration provided through virtual team visits. Incorporating routine check-ins with families is essential to ensure their needs are addressed, reinforce progress, and guide timely, targeted interventions that maximize each child’s developmental outcomes. Full article

Background: In response to the growing emotional support needs of patients in oncology, peer support was introduced into clinical teams in Quebec, Canada, in 2018. These peers, called accompanying patients (APs), are former cancer patients who use their experiential knowledge to provide support to patients during their oncology journey. This paper aims to identify APs’ perceptions of the program by including a diversity of perspectives. We include inexperienced and experienced APs, APs in different facilities, and APs in different cancer programs. Methods: We conducted a qualitative study based on 12 semi-structured interviews of APs between June and August 2024 in Quebec, Canada. We explored four themes, building on the Practice Change Model for qualitative analysis: APs’ sources of motivation, influences and environmental factors, resources available for AP integration, and the program’s effects. Results: 12 APs from 5 facilities participated in an interview. All the APs, both experienced and inexperienced, were highly motivated to participate in the program. Their motivations included a desire to give back to society, to help people and to give meaning to their illness. Both experienced and inexperienced APs were confident in their ability to accompany others. They were aware of their responsibilities and its limits regarding their role as an AP. They pointed out the program’s positive impact on their own emotional well-being and that of the patients. The program also benefited the clinical team, by limiting unhelpful demands from patients and saving time for clinicians. However, experienced APs did not feel well integrated into the healthcare team. Conclusions: We concluded that APs are highly motivated to be in the program. They perceived a need for the program in the current health system. They noted its beneficial effects on patients, on themselves, and on the clinical team. However, more resources need to be directed toward integrating APs into healthcare teams. Full article