SEARCH · Search PubMed

Results for “expert clinical practice”

Search indexed PubMed citations on genomics, clinical trials, systematic reviews and public health. Explore titles, authors and supplied subject terms, then open the PubMed record.

SourceResearch connectionFrom yearThrough year

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

1,517 records · Page 3Linked to original sources

PubMed2026

Delphi study robot consenso: Strategies for the implementation of robotic surgery in general surgery in the Spanish hospital network.

INTRODUCTION: The implementation of robotic surgery in public hospitals presents multiple logistical, educational, and organizational challenges. In the absence of unified guidelines, a national consensus is required to optimize its safe and efficient adoption. This study aimed to establish a set of consensus-based and measurable recommendations for the implementation of robotic surgery programs in hospitals within the Spanish National Health System, based on the experience of centres with established robotic programs and intended to serve as guidance for hospitals that are initiating or planning their implementation. METHODS: A national Delphi study was conducted with the participation of robotic surgery experts from 26 public hospitals. The expert panel was composed exclusively of digestive surgeons with experience in robotic surgery. Three iterative rounds of expert panel evaluation were conducted between March 2024 and March 2025. The questions were grouped into five thematic blocks. Consensus was defined as an agreement level of ≥66.7%. Kendall's W coefficient was used to assess concordance. RESULTS: High levels of consensus were achieved on key aspects related to infrastructure, structured training, cost evaluation, and quality assurance mechanisms. Areas of disagreement were also identified, such as the need for a dedicated anaesthesiologist, purchase of accessory instruments during the initial phase, and official accreditation pathways. CONCLUSIONS: This study provides a guideline for developing a national robotic surgery strategy focused on patient safety, program sustainability, and standardized training of surgical teams. These recommendations can guide hospitals at different stages of robotic technology adoption. Given that the consensus was reached from an exclusively surgical perspective, the recommendations focus on patient safety, program sustainability, and standardized training of the surgical team, and should be interpreted in an adaptable manner according to each centre's context, case volume, and available resources.

Cirugía Asistida por Robot↗

PubMed2026

How Following Medical Artificial Intelligence Advice Can Mitigate Malpractice Liability: Cross-National Insights from a Randomized Trial.

Artificial intelligence (AI) increasingly influences clinical decision-making, yet its recommendations may diverge from standard care. Although malpractice concerns are thought to discourage physicians from following AI advice, experimental evidence from the United States suggests the opposite: lay jurors are more likely to hold physicians liable when they reject AI recommendations. Whether this pattern extends to systems in which court-appointed experts, not lay jurors, determine liability remains unknown. Methods: To examine how physicians and laypeople in expert-based and lay-juror legal systems evaluate physicians' acceptance or rejection of AI recommendations, particularly when those recommendations deviate from standard care, we designed a randomized vignette study: a 2 × 2 factorial design varying the AI recommendation (standard vs. nonstandard care) and a fictional physician's decision (accept vs. reject). The study was conducted online in 2023 among nationally representative samples of U.S. and German adults and from 2023 to 2024 among German physicians. In total, 387 German physicians, 2291 U.S. adults, and 2283 German adults participated; those not completing the survey or failing attention checks were excluded per preregistered criteria. Participants were randomly assigned to 1 of 4 vignettes, varying the AI recommendation (standard vs. nonstandard care) and physician's decision (accept vs. reject). The reasonableness of the fictional physician's decision was measured, rated by participants on a Likert scale. Results: Analysis, following preregistered exclusion criteria, included 248 German physicians, 1202 U.S. adults, and 1358 German adults. Physicians accepting standard-care AI recommendations were rated more reasonable than those rejecting them (U.S. laypeople: t = 5.36; 95% CI, 0.45-0.97; P < 0.001; German physicians: t = 2.47; 95% CI, 0.14-1.30; P = 0.02; German laypeople: t = 4.14; 95% CI, 0.27-0.76; P < 0.001). Ratings of physicians accepting versus rejecting AI nonstandard-care recommendations were statistically equivalent. Equivalence was tested at an α-value of 0.05 using a two 1-sided tests procedure, reported with 90% CIs per standard convention (U.S. laypeople: t = -4.90; 90% CI, -0.1 to 0.36; P < 0.001; German physicians: t = -1.76; 90% CI, -0.12 to 0.67; P = 0.04; German laypeople: t = 5.35; 90% CI, -0.35 to 0.06; P < 0.001). Conclusion: Across the United States and Germany, samples representative of lay jurors and court-appointed experts viewed accepting standard-care AI advice as more reasonable, whereas accepting or rejecting nonstandard-care AI advice was judged similarly. Contrary to predictions, malpractice liability regimes do not necessarily pose a barrier to AI use in precision medicine.

Artificial Intelligence↗

PubMed2026

The future of precision oncology and artificial intelligence in Belgium: scenarios and policy responses.

PURPOSE: Precision medicine, also known as personalized medicine, enables the provision of tailored health services to patients. In the prevention, early detection, and treatment of cancers, precision medicine is highly promising, given the increasing use of genomic profiling for diagnosis and adapting therapies in several tumor types. Artificial Intelligence (AI) can support this process by analyzing vast amounts of relevant data. However, high-quality data and financial investments in the health system are essential for the implementation of precision medicine and AI solutions in routine cancer care. DESIGN/METHODOLOGY/APPROACH: Building on the quantitative outcomes of a foresight exercise published in another study, this article collects qualitative data to gain more detailed insights into the future of precision oncology in Belgium and discusses the role of AI in this field. It reports the results of a series of expert workshops, focusing on four hypothetical future scenarios that are centered around technological and economic issues that must be overcome for the widespread use of precision oncology in Belgium. FINDINGS: The study concludes that all four scenarios discussed in the workshops would require supportive policy measures in Belgium, which should go beyond mere technological and economic considerations, such as involving patient associations and the public in policy design or creating multi-disciplinary expert groups for precision medicine. ORIGINALITY/VALUE: To the best of our knowledge, this is the first study to employ foresight methodology to illustrate possible future scenarios, scrutinize feasible approaches for implementing precision oncology in Belgium, and discuss the use of AI in this context.

Belgium↗

PubMed2026

Pedagogical Efficacy of LLM-Generated Synthetic Data Versus Real-World Clinical Records: A Randomized Controlled Non-Inferiority Trial.

BACKGROUND: Expert-reviewed clinical cases generated by large language models (LLMs) may supplement case resources in medical education, but their short-term educational performance relative to real-case-derived teaching materials remains uncertain. We compared immediate post-training test performance after teaching with the two types of case materials and assessed non-inferiority against a prespecified margin. METHODS: We conducted a prospective, parallel-group, randomized non-inferiority trial. Through the Wenjuanxing online platform, participants were randomized 1:1 to learn with either real-case-derived teaching cases compiled by clinicians and reviewed by experts or AI-generated clinical cases produced by Gemini 3.0 Pro from fully de-identified matched real cases and reviewed by three senior general surgery specialists with full-professor rank. The primary outcome was the total score on an independent 10-item immediate post-training test (0-10 points), with a prespecified non-inferiority margin of -0.5 points. Secondary outcomes included the training-phase performance score, learning efficiency index, single-item mental effort rating, case realism, and case-source judgment. RESULTS: A total of 403 participants were randomized, of whom 386 were included in the modified intention-to-treat analysis: 192 in the real-case group and 194 in the AI-generated case group. The mean post-training test score was 4.95 (SD, 3.35) in the real-case group and 4.61 (SD, 3.35) in the AI-generated case group. The mean difference (AI-generated minus real-case group) was -0.335 points (95% CI, -1.006 to 0.337). Because the lower bound of the confidence interval was below the prespecified non-inferiority margin of -0.5 points, non-inferiority was not demonstrated (one-sided P = 0.314). No significant between-group differences were observed in the training-phase performance score, learning efficiency index, or single-item mental effort rating. AI-generated cases received lower realism ratings for Level 3 cases. The proportion of participants with at least one high-confidence completely incorrect response was 1.6% in the real-case group and 2.1% in the AI-generated case group. CONCLUSIONS: In this short-term, text-based online case-learning setting, no statistically significant between-group difference was observed in immediate post-training test performance; however, non-inferiority of AI-generated clinical cases relative to real-case-derived teaching materials was not demonstrated.

Humans↗

PubMed2026

The Impact of Chatbot Type and Normative Messaging on Chatbot Usage Intention Based on the Health Technology Acceptance Model: Randomized Controlled Trial.

BACKGROUND: Digital health tools, such as health chatbots, may improve access to scalable health support, but adoption remains inconsistent. Existing models do not fully integrate technology acceptance factors with health motivation factors relevant to digital health use. OBJECTIVE: This study proposed and tested the health technology acceptance model and examined whether normative message framing and chatbot type were associated with health motivation, technology acceptance, and intention to use a health chatbot. METHODS: In October 2025, we conducted a 4 × 2 between-participants online experiment with 1000 US adults recruited from a nationally representative YouGov panel. Participants were randomized to 1 of 8 conditions varying norm message type (self-oriented, peer-oriented, expert-oriented, or family-oriented) and chatbot type (AI-powered or rule-based) in a cancer prevention and genetic risk information scenario. Outcomes included descriptive norms, injunctive norms, perceived susceptibility, perceived severity, perceived benefits, self-efficacy, perceived ease of use, trust, privacy concerns, and usage intention. Data were analyzed using a multivariate ANOVA with Bonferroni-adjusted post hoc tests and multiple linear regression. RESULTS: Peer-oriented and family-oriented messages produced higher usage intention than expert-oriented messages, and peer-oriented messages also increased descriptive norms, injunctive norms, self-efficacy, and trust. AI-powered chatbots were associated with higher usage intention (P=.02) and greater trust (P=.008) than rule-based chatbots. In regression analyses, the model explained 50.8% of the variance in usage intention. Usage intention was positively associated with descriptive norms (β=0.087; P=.003), injunctive norms (β=0.078; P=.009), perceived susceptibility (β=0.051; P=.03), perceived benefits (β=0.253; P<.001), and trust (β=0.33; P<.001), and negatively associated with perceived severity (β=-0.047; P=.049) and privacy concerns (β=-0.11; P<.001). Perceived ease of use and self-efficacy were not significant predictors. CONCLUSIONS: The health technology acceptance model was a useful framework for explaining the intention to use a health chatbot by combining technology acceptance and health motivation constructs. Both social design features and chatbot design features shaped adoption-related beliefs, with peer-oriented and family-oriented framing and AI-powered chatbots showing particular promise. Trust and privacy concerns remained central determinants of intended use.

Humans↗

PubMed2026

Determinants of Nonspecific Response to Treatment in Randomized Controlled Trials of Major Depressive Disorder: A Narrative Review.

The design, conduct, and interpretation of double-blind randomized placebo-controlled clinical trials in major depressive disorder (MDD) are complicated by determinants of nonspecific response to treatment (NSRT). This narrative review provides a comprehensive overview of the determinants of NSRT in randomized controlled trials (RCTs) for MDD, including the placebo effect, factors related to measurement of the primary endpoint, the inclusion of misdiagnosed patients, the relapsing-remitting course of MDD, and factors related to functional unblinding. Potential strategies to reduce the impact of the determinants of NSRT and to improve the interpretation of RCT outcomes in MDD are also summarized. These strategies include use of centralized rating and standardized rater training, independent diagnostic confirmation, optimized site selection, minimizing financial incentives, exclusion of subjects participating in multiple clinical trials, exclusion of patients with unstable major depressive episode trajectories, and use of active placebo and alternative trial designs. Uniformity among experts in the definitions of determinants of NSRT and related concepts, as well as in strategies to address them, may facilitate progress in the development of novel treatments for MDD.

Humans↗

PubMed2026

Voluntary Knowledge Brokering to Promote Evidence-Based Nursing Practice: A Qualitative Study.

Knowledge brokering is a process of connecting knowledge producers with users to facilitate evidence-based practice through relationship building and information sharing. This descriptive qualitative study aimed to clarify knowledge brokering by nurses in Japanese hospitals. Twelve registered nurses in Japanese hospitals participated. They had over 5 years' clinical experience, including experience in conducting research, particularly staff research, and education. Data were collected through semi-structured individual interviews and analyzed using qualitative content analysis. The analysis revealed a central theme: continuous efforts to foster empathy among colleagues and spontaneously promote evidence-based practice: multifaceted brokering activities by clinical nurses. Findings identified 10 categories categorized into four interconnected gears: establishing the foundational ground, assessing clinical needs and staff readiness, tailoring and diffusing evidence, and sustaining and evolving evidence-based practice. Even nurses without formal titles voluntarily bridged the research-practice gap, providing new insights into informal brokering. Brokers communicated considerately, balanced evidence with clinical context, negotiated practical compromises, and fostered staff research competency.

Humans↗

PubMed2026

Final-year nursing students' clinical practice experiences: a reflection study.

OBJECTIVES: This study aimed to explore the most impactful clinical practice experiences of final-year nursing students and the future-oriented actions developed in response to these experiences. METHODS: A retrospective descriptive qualitative design was used. Following reflection training in the internship practice course, 134 final-year nursing students were asked to describe the experience that affected them most during clinical practice. A total of 123 written reflections were analyzed using content analysis. RESULTS: Three themes emerged: near-miss events, incivility behaviors, and positive preceptoring roles. Negative experiences were mainly related to patients, relatives, and nurses and often led students to feel fear and inadequacy. Students reported action plans focused on effective communication, safe patient care, and becoming positive role models. CONCLUSIONS: These findings highlight the importance of supportive clinical learning environments and positive professional socialization during the transition from student to nurse. IMPLICATIONS FOR INTERNATIONAL AUDIENCE: Nursing students worldwide may encounter incivility and near-miss events during clinical practice, potentially adversely affecting their learning experiences and professional development.

Humans↗

PubMed2026

Assessing comorbidities and predicting risk: A primer for APRNs.

Today's clinical environments are rife with tools designed to comprehensively account for medical complexity and comorbidities while predicting risk for a host of adverse health-related outcomes. Therefore, it is imperative that advanced practice registered nurses (APRNs) understand the structure and function of these tools, their similarities and differences, their limitations, and strategies for appropriate incorporation into practice. This article offers a practical overview for APRNs, emphasizing clinical implications and guidance for aligning assessment tools with the clinical population of interest to improve care delivery, quality, and patient outcomes.

Humans↗

PubMed2026

Practical Saudi Guidelines on management of moderate-to-severe psoriasis: 2026 update.

BACKGROUND: Psoriasis is a chronic, immune-mediated inflammatory skin disease that affects approximately 5.3% of the population in the Kingdom of Saudi Arabia (KSA). Thus, we aim to develop updated evidence-based clinical practice guidelines for the management of adults and pediatric patients with moderate-to-severe plaque psoriasis in the KSA. METHODS: These guidelines followed the "Grading of Recommendations, Assessment, Development, and Evaluation" (GRADE) methodology. We conducted a systematic literature review of PubMed, EMBASE, and the Cochrane Library for high-quality evidence published between 2020 and 2026. The panel developed 31 PICO questions that address key treatment considerations for moderate-to-severe psoriasis. RESULTS: We established 27 evidence-based recommendations and 4 good-practice statements addressing key aspects of moderate-to-severe psoriasis management. These guidelines strongly recommend adopting the Psoriasis Area and Severity Index (PASI) 90 as the primary treatment goal over PASI 75. For adult patients, the guidelines recommend biologic therapies, including interleukin (IL)-17 inhibitors, IL-23 inhibitors, IL-12/23 inhibitors, and tumor necrosis factor (TNF)-α inhibitors, for better disease control. For pediatric patients, the guidelines recommend early initiation of biologic therapy, with etanercept, secukinumab, ixekizumab, and adalimumab as preferred options. CONCLUSION: These Saudi national guidelines offer a comprehensive, evidence-based framework for managing moderate-to-severe psoriasis in adults and pediatric patients.

Humans↗

PubMed2026

The value of international collaborations for supporting neuroanesthesia practice, education, and research in resource-constrained settings.

PURPOSE OF REVIEW: Neuroanesthesia practice in low- and middle-income countries is constrained by workforce shortages, limited infrastructure, and variability in clinical practice. Growing global interest in collaboration makes it timely to evaluate how international partnerships can address these gaps and improve equity in care, education, and research. RECENT FINDINGS: Recent literature highlights substantial variability in neuroanesthesia practice and limited access to context-appropriate guidelines and advanced technologies. International collaborations, including training partnerships, scholarship programs, and research networks, have improved knowledge exchange, workforce development, and the adoption of standardized practices. Evidence suggests that specialized training is associated with improved clinical outcomes. However, persistent inequities in research participation, authorship, and leadership, as well as concerns regarding sustainability and 'parachute research', remain. SUMMARY: International collaboration is a key strategy for advancing neuroanesthesia in resource-constrained settings. Sustainable, equitable partnerships that prioritize local ownership, capacity building, and contextual adaptation are essential to improving clinical practice, strengthening education, and enhancing global research representation.

Humans↗

PubMed2026

Understanding and Usefulness of Effect Size and Certainty of Evidence: A Cross-Sectional Survey of Evidence-Based Practice Competencies Among US Registered Dietitians.

INTRODUCTION: Understanding of absolute and relative effect estimates, and determining effect size and certainty of evidence corresponding to effect estimates, represent fundamental evidence-based practice competencies that promote informed clinical decision-making. While research has been conducted in the medical profession, based on our literature review there is no published research on these competencies in the nutrition and dietetics profession. METHODS: Among registered dietitians, our main objectives were to assess (1) their understanding and perceived usefulness of three absolute and two relative effect estimate approaches to determine effect size, (2) their perceived usefulness of certainty of evidence, and (3) factors influencing their understanding and perceived usefulness. We conducted a web-based, cross-sectional survey by recruiting dietitians from the Academy of Nutrition and Dietetics (United States). Participants received effect estimates based on hypothetical dietary interventions vs. usual diet for reducing myocardial infarction risk. RESULTS: Of the 11,050 dietitians who received the survey link, 210 participated, and only completers (n = 114) were included in our analysis. Participants demonstrated a similar understanding of the relative (27.6%) and absolute (27.5%) effect estimates, with Risk Difference being the best understood approach and Number Needed to Treat being the least (30.7% vs. 24.6% correct responses). While perceived usefulness scores were similar between five approaches, they were highest when data was presented as Relative Risk [mean (SD): 4.82 (1.50)]. Dietitians rated the usefulness of certainty of evidence favorably [mean (SD): 5.07 (1.83), on a 7-point scale], and no factors were associated with correct understanding. CONCLUSION: Dietitians may have limited understanding of effect size thresholds presented in our survey, a finding mostly consistent with surveys of other health professionals. To optimize informed decision-making between dietitians and clients, dietetic programs and continuing education platforms should consider additional training on effect estimate approaches (relative and absolute), and determining effect sizes and certainty of evidence for effect estimates.

Clinical nutrition↗

PubMed2026

Comparing Traditional Motor Speech Practice to Contextualized Speech Practice in Preschoolers With Childhood Apraxia of Speech.

PURPOSE: The aim of this study was to compare retention of real-word targets across practice conditions (contextualized vs. motor-only) within a modified integral stimulation treatment for preschoolers with childhood apraxia of speech (CAS). METHOD: A single-subject experimental design with alternating treatments was used with matched target sets randomly assigned to contextualized practice, motor-only practice, or no treatment. Three preschoolers with CAS completed 18 therapy sessions, each consisting of two 25-min blocks: one contextualized practice and one motor-only practice. Order of practice was randomized each visit. Changes in percent phonemes correct (PPC) and lexical stress accuracy, derived from blinded transcription, were explored with visual analysis and effect sizes (standardized mean difference, d statistic). RESULTS: Meaningful improvements (d > 1) were observed in PPC across words treated in contextualized practice for all three children immediately posttreatment and for two of three children at the 1-month follow-up. Meaningful improvements in the motor-only condition were observed in two of three children immediately posttreatment and at follow-up. No meaningful changes were observed in lexical stress across any conditions in any participant. CONCLUSIONS: This study provides preliminary support for the feasibility of a modified integral stimulation therapy that incorporates elements of linguistically grounded therapies (linguistic retrieval, recasts, expansions) that may facilitate target retention in some preschoolers with CAS. However, other elements should be explored in conjunction with integral stimulation to maximize clinical outcomes. SUPPLEMENTAL MATERIAL: https://doi.org/10.23641/asha.33228981.

Humans↗

PubMed2026

Satisfaction with clinical practice environments among early-career health professionals in South Africa: Findings from the WiSDOM cohort study.

BACKGROUND: The work or practice environments of health professionals play a central role in their retention in the healthcare system and their ability to provide quality patient care. The aim of the study was to examine and compare the satisfaction of early-career health professionals in the WiSDOM (Wits longitudinal Study to Determine the Operation of the labour Market among its health professional graduates) study with their clinical practice environments (CPEs) in South Africa, and the factors influencing their satisfaction. METHODS: WiSDOM, a prospective longitudinal cohort study, consists of eight health professions: clinical associates, dentists, doctors, nurses, occupational therapists, oral hygienists, pharmacists, and physiotherapists. Every year we collect information on the cohort's involvement in direct patient care, their perceived workload, availability of medicines and equipment for patients in their care, and their satisfaction with the clinical practice environment (CPE).We used Stata®19 for analysis. We used panel linear regression to investigate factors associated with the cohort's satisfaction with their clinical practice environments from 2018 to 2024, and logistic regression to evaluate the association between CPE and intention to leave in 2024. RESULTS: In 2024, the mean age of the cohort was 30.9 (± 2.0), the majority were female (74.4%) and working in urban areas (92.7%). In 2024, 59.7% of the overall cohort reported a heavy workload compared to 69.2% in 2018. Over the follow-up period, reported problems with the availability of medicines or equipment were worse in the public sector and in rural areas, compared to the private sector and urban areas respectively.The cohort's satisfaction score with the CPE was 6.7 out of 10 in 2018 and 6.9 in 2024. The predictors of CPE were year of follow-up, health profession, employment sector, and geographic location. Nurses (β=-1.2; 95% CI -1.7, -0.7; p < 0.001), and pharmacists (β=-0.7; 95% CI -1.1, -0.4; p < 0.001) scored their CPE significantly lower compared to the other professional groups. Health professionals in the public sector (β=-1.1; 95% CI -1.3, -0.9; p < 0.001) and in rural areas (β=-0.6; 95% CI -0.9, -0.3; p < 0.001) were less satisfied with their CPE compared to those in the private sector and urban areas respectively. Dissatisfaction with the CPE was significantly associated with intention to leave the workplace and the profession. CONCLUSION: The study findings underscore the need for positive clinical practice environments for early-career health professionals in South Africa both as a health workforce and patient safety imperative.

South Africa↗

PubMed2026

Deimplementation of inappropriate feeding practices in early care and education: a Hybrid Type 3 cluster-randomized trial.

BACKGROUND: The science of deimplementation-reducing harmful or ineffective practices-has focused almost exclusively on clinical prescribing, with no studies conducted in community or educational settings. Early care and education (ECE) settings offer a strategic venue for shaping eating behaviors, with children consuming up to 500 meals annually in these environments. However, ECE educators routinely use feeding practices that undermine self-regulation, including pressuring children to eat, rushing mealtimes, and offering food as reward. These practices contribute to food aversions, diminished self-regulation, and obesity risk. METHODS: We will conduct a Hybrid Type 3 cluster-randomized trial evaluating a co-designed deimplementation strategy package (WISE Words) across 88 ECE sites in Arkansas and Louisiana. Sites will be randomized 1:1 to WISE Words or usual practice, with usual practice sites receiving the intervention after two years (waitlist design). WISE Words includes six strategies: dynamic training using improvisation methods, peer learning collaboratives with goal setting, external facilitation, audit and feedback, environmental reminders, and tailored educational materials. The primary outcome is de-adoption of inappropriate feeding practices measured via direct mealtime observation (Table Talk). Secondary outcomes include adoption of evidence-based practices, acceptability, appropriateness, and sustainability at 12- and 24-months post-intervention. Child outcomes include Body Mass Index, skin carotenoid levels (Veggie Meter) willingness to try new foods (observed) and food neophobia (teacher and caregiver report). An explanatory sequential mixed methods design will test mechanisms of change derived from the Implementation Trust Building Theory of Change examining whether trust mediates strategy effects on outcomes. DISCUSSION: This trial extends deimplementation science into community settings by targeting culturally embedded behavioral practices rather than clinical prescribing behaviors. Results will inform approaches to shifting entrenched practices in ECE and similar settings while testing trust as a deimplementation mechanism. Sustainability assessments will address a notable gap, as few studies have examined whether deimplementation effects persist. TRIAL REGISTRATION: NCT07101321, July 20, 2025.

Humans↗

PubMed2026

A systematic review of international/national guidelines for the management of nasopharyngeal carcinoma: Convergence and divergence of recommendations.

Increasing numbers of clinical practice guidelines have been published by international/national groups for nasopharyngeal carcinoma (NPC), providing valuable references for clinicians in making evidence-based decisions on treatment. However, there are substantial discrepancies in various recommendations, leading to uncertainties in choosing the optimal strategies. The authors systematically searched databases and organizational websites for NPC guidelines published between January 2000 and November 2025. All identified guidelines underwent quality appraisal; in total, 26 clinical practice guidelines rated recommended for use were included. The recommendations covering all management aspects (diagnosis, staging, radiotherapy, systemic therapy, follow-up surveillance, biomarkers, and salvage of recurrent/metastatic diseases) were summarized and comparatively analyzed for consistency and disparities. Strong consensus exists for diagnostic workup, staging systems, and induction chemotherapy plus concurrent chemoradiotherapy for advanced disease, whereas marked disparities exist on radiotherapy details, particularly target volume delineation, elective coverage extent, and dose specifications. Although systemic therapy strategies for different stage groups were mostly consistent, substantial disparities exist in alternative options and treatment details. This first comprehensive systematic synthesis of international NPC guidelines provides a practical reference for clinicians to understand all recommendations and select optimal options based on local resources and expertise while identifying current controversies that demand future research for further standardization and harmonization.

Humans↗

PubMed2026

Genomic science and the nurse educator's role: Promoting integration from curriculum to clinical practice.

BACKGROUND: Registered nurses and nurse educators play a critical role in preparing future clinicians to translate genomic discoveries into practice. However, emerging evidence suggests that both groups may lack sufficient knowledge and confidence in genomics, potentially limiting their ability to teach, mentor, and apply genomics in real-world settings. This gap is especially concerning in Aotearoa New Zealand, where the genomic literacy of nurse educators and clinicians remains underexplored. OBJECTIVE: This study aims to: (1) assess nurse educators' genomic literacy and confidence in teaching genomics; and (2) evaluate registered nurses' knowledge and confidence in applying and teaching genomics in clinical practice. DESIGN: Exploratory descriptive qualitative. SETTING: This study was conducted in the greater Auckland area. PARTICIPANTS: A total of 17 participants were recruited using purposive sampling to ensure a diverse range of perspectives across varying levels of teaching experience, disciplinary backgrounds, and exposure to genomic content. METHODS: Data were collected using semi-structured focus group interviews, a method well-suited for generating in-depth discussion and facilitating interaction among participants with shared professional interests. The collected data were analysed using thematic analysis methods. RESULTS: The findings offer insight into the preparedness of New Zealand's nursing workforce to engage with genomic-informed healthcare and inform strategies for integrating genomics into nursing curricula and continuing professional development. Given the interdisciplinary nature of genomic healthcare, these insights may also be relevant to other health professionals-including midwives, pharmacists, and allied health practitioners-who increasingly encounter genomic information in clinical practice and require foundational competencies to support patient care. CONCLUSION: Addressing this educational gap is critical to ensuring that nurses-key facilitators of patient care and public health-are equipped to deliver safe, equitable, and evidence-based genomic healthcare.

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↗