搜索结果：Journal of evaluation in clinical practice

Clinical reasoning in contemporary practice often involves ill-structured, poorly defined problems that span the biopsychosocial domain and require reasoning under high relational complexity. Despite sustained scholarly attention to clinical reasoning, few models are both theoretically grounded and usable for clinicians who face this complexity. At the same time, the World Health Organization Family of International Classifications (WHO-FIC) offers a rich but complex ontology that was not designed primarily to support clinical reasoning in practice. To develop a two-stage WHO-FIC-based ontological model of clinical reasoning that is conceptually coherent yet remains cognitively tractable in the face of complexity. A conceptual analysis was undertaken. It integrated three strands: (1) WHO-FIC classification theory, including recent work on harmonisation; (2) empirical and theoretical literature on clinical reasoning; and (3) cognitive theories of bounded rationality, fast-and-frugal heuristics, relational complexity, and framing. These strands were used to derive design constraints for a clinically usable ontology. They were then synthesised into a two-stage, graph-based model designed to manage the complexity-coherence trade-off in clinical reasoning. Stage 1 introduces a parsimonious triad-Body, Activity, and Environment-represented as a complete three-node graph with bidirectional relations. This triad provides an etiologically neutral and cognitively economical starting point for framing complex clinical problems. Stage 2 introduces three emergent constructs-Health Condition, Participation, and Intervention-derived compositionally from Stage 1 relations and aligned with ICD-11, ICF, and ICHI, respectively. The model supports iterative movement between stages through composition and decomposition. It incrementally increases complexity while keeping relational load within cognitively feasible bounds and preserves the value of diagnosis while reducing its tendency to dominate problem framing. A worked case illustrates how the ontology supports reasoning about complex, time-dependent problems through repeated movement between stages. The proposed ontology addresses key ambiguities within WHO-FIC, including the relationship between Activity and Participation and the perceived hierarchical privileging of diagnosis. It offers a more coherent and cognitively usable framework while respecting limits on human reasoning and managing the complexity-coherence trade-off. The model provides a theoretically grounded heuristic scaffold for clinicians and educators who work with complexity. It also contributes to clinical reasoning literature by emphasising reasoning about concepts, not only cases, with implications for interprofessional education and practice.

Prolonged Disorders of Consciousness (PDOC), including unresponsive wakefulness syndrome and minimally conscious state, present persistent challenges in clinical assessment and long-term care. Although behavioral observation remains the primary basis for detecting signs of consciousness, interpretation of such observations often depends on clinical judgment and contextual information provided by caregivers. In some cases, family caregivers may detect subtle signs of recovery in individuals with PDOC; however, these observations are not always incorporated into clinical assessment or diagnostic interpretation due to the inherent ambiguity of behavioral responses. This study explores how implicit biases and microaggressions may influence the interpretation of caregiver observations in PDOC care. Furthermore, it introduces a conceptual framework-the Context-Dependent Diagnostic Sensitivity Model-to illustrate how clinical awareness of bias and improved communication with families may contribute to more accurate diagnostic interpretation. Semi-structured interviews were conducted with seven family caregivers of individuals with PDOC living in home healthcare settings in Japan. Using thematic analysis, the study examined caregivers' experiences of communication and interaction with healthcare professionals. Caregivers frequently reported situations in which their interpretations of patient responses were minimized or reframed as unrealistic expectations. Such interactions sometimes limited the incorporation of caregiver observations into clinical assessment and decision-making processes. These findings suggest that subtle forms of bias embedded in professional communication may influence opportunities for behavioral observation and family participation in care. By integrating qualitative findings with insights from disability studies and research on implicit bias, this study highlights the potential impact of microaggressions on diagnostic sensitivity and clinical interaction in PDOC care. Recognizing and addressing these dynamics may contribute to improved collaboration between healthcare professionals and family caregivers, as well as to the development of more effective clinical practices.

Many advances have been made to identify novel, effective orthopedic care practices. For all that is known about the comparative effectiveness of various clinical decisions in anterior cruciate ligament (ACL) injury care, surprisingly little is known about how surgeons approach decision-making in the face of this evidence. Implementation science models such as Capability, Opportunity, Motivation - Behavior (COM-B) offer a way to organize and comprehensively understand how clinicians make decisions. This evaluation aimed to understand and quantify the factors that influence orthopedic surgeons' decision-making in ACL injury care according to COM-B. This pragmatic evaluation used a sequential exploratory mixed-methods approach combining orthopedic leader discussions and qualitative semi-structured interviews, followed by four rounds of quantitative census surveys to understand the factors influencing four surgeon decision points related to ACL injury care. First, two authors (BN a practicing surgeon with a clinical and research leadership role and MR the director of the affiliated orthopedic research institute) participated in recurring in-person orthopedic leader discussions; then additional selected surgeons were invited to participate in one-time qualitative semi-structured phone interviews; and, finally all surgeons that perform ACL procedures in the health system were invited to participate in four quantitative web surveys. Results were summarized descriptively according to the COM-B model. Two co-authors (BN and MR) participated in the orthopedic leader discussions, five invited surgeons participated in qualitative interviews (100% response rate), and 10-11 surgeons participated in four survey rounds (83%-100% response rate). Factors influencing each of the four selected decision points were identified within each COM-B category. Clinical knowledge (capability) and social influence of patient preferences (opportunity) were identified as highly influential for all decisions. Automatic decision making or habit (motivation) was also highly important for most but not all decisions. Interviews and surveys with surgeons from one Midwest U.S. health system demonstrate the complexity of ACL injury care decision-making. Surgeons reported that capability, opportunity, and motivation were important in all four decisions. The most important factors influencing decisions ranged from their technical ability to perform one surgical technique over another (e.g., hamstring autograft) in selecting what type of surgical graft to use to their patients' preferences for having surgery in deciding whether to recommending surgery. Future research to identify and test intervention strategies like shared decision-making training in alignment with the identified factors like technical ability and social influences have the potential to lead to higher-value orthopedic care by supporting decisions like recommending longer pre-operative rehabilitation.

Modern medicine remains marked by a persistent tension between general scientific knowledge and the singularity of individual patients. Alvan Feinstein's attempt to construct a "science of clinical judgment" offers an important examined response to this problem. This article examines how Feinstein sought to integrate patient singularity into a rigorous epistemological framework and assesses whether his work should be understood merely as a precursor to Evidence-Based Medicine or as an alternative scientific pathway for clinical practice. A narrative review was conducted using a pearl-growing strategy, beginning with Feinstein's primary works and expanding through their conceptual and bibliographic connections. This approach was complemented by targeted searches in PubMed and Scopus and by a historical-philosophical analysis informed by debates in the philosophy and history of medicine. Feinstein transformed clinical judgment from a tacit, individual faculty into a structured, collective, and regulable practice. His project relied on the standardization of observation, refinement of clinical classifications, collective validation, and development of clinically meaningful measurements. Clinimetrics extended this project by making subjective, contextual, functional, and patient-centered phenomena scientifically intelligible without reducing them to biomedical mechanisms or psychometric abstractions. These findings indicate that Feinstein did not simply anticipate Evidence-Based Medicine; he developed a distinct epistemological approach centered on the systematic study of singular clinical realities. Feinstein's work remains relevant because it shows that scientific rigor and attention to patient singularity need not be mutually exclusive. His project provides a critical framework for reconsidering the limits of Evidence-Based Medicine, personalized medicine, and contemporary approaches to clinical measurement.

Mistakes in clinical reasoning are common. Cognitive biases have gained attention as potential sources of error. Over 100 biases have been defined, and over 40 have been identified in clinical reasoning literature. Understanding contextual factors (e.g., clinical setting or emotions) that influence clinical reasoning is a first step towards improving reasoning and reducing errors. Explore the interactions of cognitive biases and distracting contextual factors and their influence on clinical reasoning accuracy. The authors conducted a simulation study. Participants watched video encounters of common conditions with or without added distracting contextual factors (DCFs, e.g., English as a second language or patient anxiety), then completed a post-encounter form and a think-aloud exercise. Reasoning was analyzed with an analytic integrative approach of latent thematic analysis. MANOVA assessed for potential associations of biases and contextual factors on reasoning accuracy, which was followed with univariate ANOVA. Thirteen cognitive biases were identified. Anchoring, availability, and confirmation bias were most common. MANOVA found lower diagnostic reasoning accuracy in cases with DCFs (72% vs. 80%). There was a lower but not statistically significant difference in management reasoning accuracy (70% vs. 73%). Univariate ANOVA found that the number of biases and the cooccurrence of bias and a DCF was associated with lower diagnostic reasoning accuracy. Three themes emerged when exploring biases' influence on reasoning: (1) gestalt from context or error avoidance, (2) optimistic processing, and (3) momentum clouds reasoning in the present and afterward. Two additional themes emerged when exploring the interactions between biases and DCFs: (1) lack of confidence and knowledge deficit, and (2) emphasizing easily available information. Cognitive biases can affect clinical reasoning in multiple ways. DCFs may amplify the negative influence of biases on diagnostic reasoning accuracy. Exploring the interactions of cognitive biases, DCFs, and clinical reasoning, as well as delineating diagnostic reasoning from management reasoning may help future research and interventions improve reasoning accuracy.

Robust outcome measurement is central to evaluating clinical training environments and providing timely support to medical students. Burnout during clinical clerkships is common; however, evidence of the capability of instruments to monitor sustained risks and detect meaningful changes remains limited. To evaluate the responsiveness of the 11-item Oldenburg Burnout Inventory-Medical Student version (OLBI-MS-11) and examine the baseline predictors of individuals' sustained burnout during their clerkships. We examined within-person change correlations between the OLBI-MS-11 and domain-matched anchors (Maslach Burnout Inventory-General Survey [MBI-GS] subscales) in a five-wave longitudinal cohort study of Japanese medical students (N = 162). We assessed the instrument's discrimination of MBI-defined burnout caseness and analysed associations between burnout trajectories and clinically relevant constructs, including psychological flexibility, depressive symptoms, perceived stigma, mistreatment, and absence of clerkship. The OLBI-MS-11 demonstrated moderate, domain-concordant correlations in within-person changes with the MBI-GS subscales across adjacent time points and maintained a stable discrimination of burnout caseness (AUC ≈ 0.82-0.84). Changes in burnout were associated with concurrent changes in psychological flexibility and depressive symptoms. Higher baseline psychological flexibility was associated with a reduced risk of sustained burnout, whereas mistreatment predicted persistent burnout. The OLBI-MS-11 showed responsiveness and discriminative validity in clinical clerkships. Its use may facilitate the longitudinal monitoring of medical students' well-being and inform the identification of sustained burnout risk. Continuous-change metrics may provide a more nuanced evaluation of individual trajectories than dichotomous classifications alone.

Post-traumatic stress disorder (PTSD) screening and prediction tools are widely used in veteran and trauma-exposed populations, yet methodological practices show substantial gaps. Rigid threshold application, inconsistent calibration reporting and limited attention to sex-based performance differences, comorbid conditions including traumatic brain injury (TBI) and moral injury and cultural context may introduce inequities and reduce clinical utility. PTSD screening programmes miss cases in some groups while over-referring in others, yet lack practical guidance for addressing these disparities. We provide an implementation framework that operationalizes existing standards (TRIPOD-AI, PROBAST-AI) with concrete, PTSD-specific procedures for calibration assessment, sex-stratified analysis and comorbidity integration. We conducted a systematic scoping review of PTSD screening and prediction studies (2019-2024, n = 75 studies) and synthesized published meta-analytic evidence on TBI-PTSD associations as a worked exemplar of comorbidity integration. We developed a tiered implementation framework (Tier 1: minimum standards; Tier 2: recommended practices; Tier 3: excellence standards) addressing observed heterogeneity. Technical feasibility was demonstrated using synthetic data explicitly matching published PTSD parameters from landmark veteran studies. The scoping review of 75 studies (2019-2024) found that only three studies (4.0%) reported calibration metrics, and only 10.7% provided sex-disaggregated performance metrics. Current reporting practices inadequately address TBI-PTSD comorbidity heterogeneity, moral injury (0% of studies) and cultural adaptation. These findings document substantial methodological gaps and demonstrate framework recommendations target empirically observed heterogeneity. The framework organizes recommendations into three tiers based on feasibility and resource requirements. Tier 1 standards (achievable by all studies) include: precise population definition, pre-specified thresholds, calibration slope reporting, sex-disaggregated performance and missing data documentation. Tier 2 recommendations (feasible for most studies) include: bootstrap internal validation, formal sex-stratified calibration testing with specified interaction thresholds (|β3| > 0.10), decision curve analysis, comorbidity integration and multiple imputation (m ≥ 20). Tier 3 excellence standards (aspirational for well-resourced studies) include: rigorous multi-site external validation, annual calibration monitoring and cultural adaptation for refugee contexts. Synthetic data demonstration (n = 850, matching Bovin 2016 and Wortmann 2016 published parameters: PTSD prevalence = 33%, PCL-5 distributions, TBI prevalence = 35%) confirmed technical feasibility using standard statistical software. Bootstrap validation (500 iterations) yielded optimism-corrected AUC = 0.969 with negligible optimism. Sex-stratified analysis detected meaningful calibration differences (|Δ| = 0.14, exceeding threshold). Comorbidity analysis revealed prevalence stratification (40.4% vs. 30.6%) despite minimal discrimination improvement (ΔAUC = +0.003), clarifying comorbidity's dual role in prediction versus case-finding. Published meta-analyses demonstrate consistent TBI-PTSD associations (2.68× risk overall; 4.18× in military populations) alongside substantial prevalence heterogeneity (I2 = 96%) that current reporting practices inadequately address. Using TBI as a worked exemplar of comorbidity integration alongside sex-stratified validation, moral injury assessment and cultural adaptation, the tiered framework provides PTSD-specific operational guidance for implementing established methodological standards, designed for incremental adoption based on study resources. All Tier 2 components are implementable with standard methods and moderate sample sizes. Prospective validation studies are needed to assess whether framework implementation improves calibration stability, subgroup equity and clinical outcomes compared to standard practice.

Pain assessment in infants is difficult due to the lack of verbal communication and the subjective nature of existing methods. Current tools require evaluating multiple indicators separately, which can be time-consuming and variable between observers. Artificial intelligence can enable rapid and standardised direct pain scoring, improving accuracy and clinical efficiency. The limited number of comprehensive studies in this area highlights an important gap in the literature. This research was conducted to develop an application that will evaluate pain in infants in the first 100 days of life using artificial intelligence techniques. This study is an artificial intelligence-based research conducted with 1000 newborns hospitalised in a Neonatal Intensive Care Unit. A data collection form and the Neonatal Pain, Agitation, and Sedation Scale were used as data collection tools. Data analysis was performed using IBM SPSS Statistics 21.0, with descriptive statistics and Cohen's Kappa test applied. A p value of <&#x2009;0.05 was considered statistically significant. Image and audio recordings from all 1000 newborns were independently labelled by the researchers, and these labelled data were used to develop the artificial intelligence model. The labelled image and audio recordings were utilised for model training (80%), validation (10%), and testing (10%). The mean gestational age of infants was determined to be 38.52&#x2009;&#xb1;&#x2009;1.07 weeks, and the postnatal age was determined to be 2.90&#x2009;&#xb1;&#x2009;0.77 days. It was determined that there was no difference between the pain scale scores labelled by the researchers (p&#x2009;>&#x2009;0.05). It was determined that the success rate of the created artificial intelligence model in correctly predicting the presence of pain in newborns was 82%. It was determined that the developed artificial intelligence model was successful in predicting the presence of pain in newborns in the Neonatal Intensive Care Unit.

Implementing evidence-informed healthcare services is typically approached as a structured, time-limited project, focused largely on what to do. Less well understood is how implementation actually unfolds in practice: the ways in which those involved navigate change and generate solutions in diverse community settings. Without understanding how implementation happens in unique contexts, implementation failure may remain poorly understood. The aim was to understand what it means for kidney care team providers, information technology staff, and patients to engage in implementing an evolving virtual kidney care service in a large, sparsely populated rural and remote region. We interviewed eight kidney care service providers, two information technology specialists, and 17 patients in northern British Columbia, Canada, for their experiences in implementing, delivering, and receiving virtual kidney care and how their practices changed with COVID-19. Through an inductive, reflexive process of analysis and hermeneutic interpretation, we identified patterns in how virtual kidney care was implemented. The analysis showed six hermeneutic principles of implementation at work in the everyday practices of the kidney care and information technology teams: acknowledging central concerns, creating new common understandings, collectively acting, surfacing tensions, being responsive to context, and engaging in ongoing dialogue. Rather than discrete, technical, and time-limited, we found implementation to be an ongoing, evolving, relational, generative, and iterative process that is inextricably connected to its context, and that never fully ends. Attending to the how revealed dimensions of implementation practice that are seldom visible in conventional implementation research. A hermeneutic sensibility, marked by openness, humility, and dialogue, with a commitment to understanding, responsiveness, and relationship-building, is key to implementation, especially in the ever-changing contexts of rural and remote areas. The findings point to the value of a hermeneutic approach in implementing, sustaining, and researching innovations in dynamic healthcare systems and rural settings.

In the sustainability of quality systems, monitoring patient safety and satisfaction from the patients' perspective contributes to improving the quality of care and providing care in line with the needs and expectations of patients. This study aimed to explore the relationship between patients' perceptions of individualized care, patient safety, their experiences with adverse events, and satisfaction with nursing care, and the sequential mediating role of patient safety perception and adverse event experience in the relationship between individualized care and satisfaction with nursing care. A total of 660 patients from the inpatient units of a public hospital in T&#xfc;rkiye were included in this cross-sectional study. Data collection was conducted between April and July 2024 using the Individualized Care Scale-Patient version, the Patient Measure of Safety-30, a question assessing the experience of adverse events, and the Newcastle Satisfaction with Nursing Care Scale. Data were analysed using descriptive and correlation analysis, and the hypothesis model was tested using structural equation modeling. The findings show that individualized care is associated with higher levels of patient satisfaction with nursing care and more positive patient safety perceptions, while also contributing to a lower experience of adverse events. In the final model, it was determined that the patient safety perception mediated the effect of individualized care on nursing care satisfaction among both those who experienced adverse events and those who did not. These results suggest that healthcare institutions should place greater emphasis on strengthening individualized care practices by supporting nurses in planning and delivering care tailored to patients' specific needs. In addition, integrating an individualized care approach into nursing education programs and broader healthcare policies may play a key role in improving patient safety and satisfaction with nursing care.

Clinical ethics scholarship on deepfakes has focused primarily on patients as targets of synthetic deception, in which fabricated audiovisual material alters patient beliefs about clinicians and care. This focus neglects the reverse epistemic vulnerability: clinicians themselves as recipients of synthetic, adversarially generated clinical information. To develop a conceptual analysis of clinician-facing deepfakes and their implications for clinical epistemology, diagnostic reasoning, and institutional trust. Normative and conceptual analysis drawing on virtue epistemology, philosophy of testimony, diagnostic error theory, automation bias research, and socio-technical systems theory. Clinician-facing deepfakes constitute a distinct epistemic risk category producing three primary harms: (1) diagnostic error cascades, (2) testimonial contamination of clinical knowledge transmission, and (3) institutional epistemic fragility. We introduce the concept of epistemic role reversal, defined as the systematic decoupling of perceptual reliability from epistemic justification under adversarially generated clinical inputs, resulting in the collapse of expert perceptual advantage in bounded domains. Clinical ethics must address both sides of the epistemic encounter in medicine. Clinician-facing deepfakes are not merely a symmetrical extension of patient-facing deception but a structurally distinct class of epistemic threat. While empirical prevalence remains unknown, evidence from adjacent literatures supports their plausibility. A precautionary framework of clinical epistemic hygiene is therefore warranted, combining institutional verification infrastructure, workflow-level safeguards, and professional epistemic norms adapted to adversarial information environments.

Limited evidence exists on the long-term impact of Clinical Decision Support Systems (CDSS) on potassium safety in middle-income countries, with most studies focusing on short-term outcomes in resource-rich settings. This study evaluates the long-term effectiveness of a CDSS in reducing potassium-related adverse events in a Brazilian tertiary-care hospital from 2006 to 2023. This retrospective observational study analysed all potassium-containing prescriptions (oral and intravenous) at a Brazilian tertiary-care teaching hospital. The study compared the pre-implementation (2006-2014) and post-implementation (2014-2023) phases of a CDSS that monitors and blocks prescriptions exceeding predefined safety limits for potassium concentration, infusion rate, and daily dose. Near misses were retrospectively identified by applying the same CDSS-defined rules to completed prescriptions-both before and after CDSS implementation. Trends in adverse events and blocked prescription attempts were analysed using Prais-Winsten regression. Data were obtained directly from hospital databases, without coding or transformation. The study adhered to the RECORD statement and received ethical approval. Of 9,308 drug-related adverse events recorded between 2013 and 2023, 64 (0.7%) involved potassium salts. Despite an increase in overall drug-related events (p&#x2009;<&#x2009;0.001), the proportion involving potassium decreased from 2.8% in 2013% to 0.2% in 2023 (p&#x2009;=&#x2009;0.008). After CDSS implementation, 90,741 potassium prescriptions were submitted, of which 38,961 (42.9%) triggered CDSS blocked attempts, showing a consistent upward trend (&#x3b2;&#x2009;=&#x2009;20.4, p&#x2009;<&#x2009;0.001). Most blocked attempts were due to violations of intravenous concentration (60%) and infusion rate (18%) limits. Near-miss prescriptions remained proportionally high [median 27.4% (IQR: 17.5-32.2)] throughout the post-CDSS phase. This study demonstrates the long-term effectiveness of a potassium-specific CDSS in reducing adverse drug events in a middle-income setting. However, persistent increases in blocked attempts and near misses suggest potential issues related to alert fatigue, overreliance on CDSS, and override practices, highlighting the need for ongoing system refinement and staff training.

Contemporary healthcare institutions are increasingly organised through technocratic forms of governance in which auditability, standardisation and metric certainty function as primary indicators of quality and accountability in clinical practice. While these mechanisms aim to enhance safety and transparency, their institutional dominance can reshape the moral-epistemic architecture of professional practice. When what is auditable becomes what is treated as accountable, justificatory practice is displaced by record-making, and reflective judgement becomes structurally costly rather than institutionally protected. This paper conceptualises technocratic rationality as an institutional epistemic regime in which epistemic legitimacy becomes subordinated to auditability, thereby reshaping which forms of knowledge count as credible, which reasons are admissible, and which kinds of judgement become institutionally speakable. It also advances epistemic leadership as a normative orientation for healthcare institutions. The paper develops a conceptual analysis using the Leadership-Structure-Culture framework as an organising architecture. Nursing is examined as a paradigmatic case through which the institutional effects of technocratic rationality become visible within contemporary healthcare systems. A causal-normative chain is proposed: dominant audit logic reshapes epistemic legitimacy; altered legitimacy narrows reason-giving; constrained justificatory practice weakens professional moral accountability. The analysis shows how technocratic rationality becomes embedded within organisational structures and identifies where leadership must intervene to safeguard the conditions that sustain responsible clinical judgement. Epistemic leadership is understood as the stewardship of the conditions necessary for truth-seeking in institutional life. It protects reason-giving, interpretive dialogue and justificatory integrity in professional practice. The paper concludes that healthcare institutions must not only measure practice but also preserve the moral-epistemic conditions under which responsible clinical judgement can be exercised and defended.

Chronic psychological suffering may persist despite adequate diagnosis, evidence-based treatment and preserved cognitive insight. In clinical practice, this persistence is often interpreted as treatment resistance, symptom severity or insufficient adherence. However, such explanations may fail to capture the structural organization through which suffering becomes stabilized over time. This theoretical article proposes an alternative conceptualization of psychopathological chronicity as a structural mode of organization sustained by recursive affective-symbolic loops, rather than by the mere persistence of symptoms. It aims to explain the paradox of insight without recovery and to clarify how chronic suffering may acquire a homeostatic function. The article integrates concepts from clinical psychopathology, phenomenology, affective neuroscience and predictive processing. It also draws on converging evidence from clinical domains in which psychological status, perceived health and self-regulatory appraisals modify relationships among symptom reports, objective findings, functional impairment and somatic outcomes. Clinical vignettes are used to illustrate the proposed model. The proposed framework suggests that cognition may become functionally recruited in the stabilization of chronic suffering. Within this organization, chronicity can operate as a form of "pathological health", protecting the subject from greater psychic fragmentation while simultaneously maintaining distress. The model also highlights how therapeutic interactions may inadvertently reinforce recursive loops when interventions remain confined to cognitive insight, reassurance or premature disruption. Psychopathological chronicity may be better understood as an affective-symbolic architecture that organizes symptoms, self-appraisal, embodiment and relational patterns. Structural change may therefore require embodied and transferential interventions capable of disrupting the recursive core, together with operational markers for distinguishing timely therapeutic destabilization from premature disruption. This model is primarily applicable to adult and older adolescent populations and may contribute to a more nuanced evaluation of chronicity in clinical practice.

Vaccines are one of the most effective interventions used by public health services to reduce infectious diseases. However, individuals' attitudes toward vaccines are also crucial to vaccine effectiveness. Experiences with vaccines and trust in healthcare services can guide future vaccination decisions. The aim of this study was to examine the relationship between COVID-19 vaccine regret, distrust of the healthcare system, and future vaccination intentions. In this cross-sectional study with a qualitative component, data were obtained through face-to-face interviews (n&#x2009;=&#x2009;402). Data were collected using the Decision Regret Scale (DRS), the Health System Distrust Scale (HCSDS), and open-ended questions regarding the reasons for COVID-19 vaccine regret. To ensure clarity of the findings, quantitative and qualitative data were integrated. Of the participants in the study, 87.1% did not experience any adverse effects from the COVID-19 vaccine. 56.2% of participants regretted getting the COVID-19 vaccine. Additionally, 35.8% reported being 'undecided' about accepting a new vaccine in the future. Among participants, it was found that experiencing a side effect after the COVID-19 vaccine increased distrust in the healthcare system (p&#x2009;<&#x2009;0.05). A weak positive correlation was found between participants' HCSDS and DRS scores (r&#x2009;=&#x2009;0.282, p&#x2009;<&#x2009;0.001). Qualitative analyses showed that participants' regrets regarding the COVID-19 vaccine were mainly grouped around two themes: (1) 'Concern about long-term effects', (2) 'Perception that the vaccine is unnecessary'. Based on these findings, it can be said that the phenomenon of COVID-19 vaccine regret and the level of distrust in the healthcare system will make it even more difficult to control future pandemics and infectious diseases. In addition, the findings highlight the need for communication strategies aimed at increasing trust in vaccines and the healthcare system.

The National Health Service, UK, has recently implemented a new patient safety strategy, replacing root cause analysis (RCA) incident investigation with systems-based approaches. It is unknown if this change will optimise learning and improve care outcomes. We aimed to analyse safety recommendations/actions/improvements/solutions from comprehensive incident investigations by comparing those that adopted root cause analysis with systems-based approaches. The evaluation adopted a sequential multi methods design. Reports were extracted between January 2022 and January 2023. The quality of the incident investigation was graded using a validated tool (Learning Response Review and Improvement Tool). Investigation identified solution types were organised using qualitative content analysis, adopting inductive and deductive orientations. These were then classified into system factors and the effectiveness of the solution scored. Descriptive statistics were computed to investigate differences between incident investigation type. Grading the quality of reports demonstrated that the expectations set out within the change in safety strategy were mostly being realised in practice. A total of 135 solutions were extracted from systems-based and 57 from RCA reports, where the type of solutions identified were similar between each investigation approach. Organisational system factors were the most frequent for systems-based whilst task system-work factors were most frequent for RCA reports. For both investigation types, most of these solutions were deemed to fall in the least effective category: administrative controls. The evaluation provides important insights into how the shift to systems-based investigations are shaping the quality of investigations and the recommendations that aim to prevent a recurrence of harm. Changing from RCA to systems-based investigations led to more patient/carer/family involvement and systems-focussed solutions, however weaker administrative recommendations remained prominent. Policy, practice and research need to ensure that the change in conceptual thinking and investigative orientation also contributes to improvements in learning and the development of stronger controls or barriers that prevent harm.

Informed consent is a cornerstone of modern medicine, yet the extent to which patients truly understand surgical information in the perioperative setting remains uncertain, particularly among older and vulnerable populations. Orthopaedic surgery represents a particularly challenging context, as trauma pathways are often characterized by urgency, pain, and emotional stress, whereas elective procedures allow greater opportunity for structured communication. To assess real-time patient comprehension of surgical informed consent immediately before orthopaedic surgery and to compare understanding between elective and trauma pathways. We conducted a prospective observational study at a single tertiary referral hospital in Northern Italy between January 2023 and December 2024. Approximately 870 adult orthopaedic surgical patients were screened for eligibility. After exclusion of patients with cognitive impairment, severe psychiatric illness, language barriers, refusal to participate, or incomplete questionnaires, 750 consecutive patients were included in the final analysis (460 elective, 290 trauma). All patients had received standard preoperative explanations and completed institutional informed consent procedures. In routine clinical practice, consent discussions generally involved both an orthopaedic resident and the supervising attending surgeon. Comprehension was assessed immediately before transfer to the operating room using a brief standardized four-item tool evaluating understanding of the planned procedure, risks, benefits, and therapeutic alternatives. Responses were independently categorized as absent, vague/partial, or adequate. Overall, 488 patients (65.1%) demonstrated absent comprehension, 188 (25.1%) vague or partial comprehension, and only 74 (9.9%) adequate comprehension. Trauma patients showed significantly lower overall comprehension than elective patients, with fewer patients demonstrating at least partial comprehension (28.3% vs. 39.1%; p&#x2009;=&#x2009;0.003). Adequate comprehension remained low in both groups (8.3% vs. 10.9%; p&#x2009;=&#x2009;0.30). Older age and lower educational attainment were associated with poorer comprehension in exploratory analyses. Mean questionnaire completion time was 3.5&#x2009;&#xb1;&#x2009;1.2&#x2009;min. Despite repeated explanations and signed consent forms, most patients entered the operating room without meaningful understanding of the planned procedure, risks, benefits, or alternatives. The observed deficit was present in both elective and trauma settings, suggesting a systemic limitation of routine consent processes rather than solely a physician-specific communication issue. Informed consent in orthopaedic surgery frequently fails to ensure patient comprehension. Consent should be reframed as a dynamic verification process rather than a purely administrative requirement, incorporating structured communication pathways, simplified language, and teach-back-based strategies tailored to both elective and trauma settings.

The integration of ambient artificial intelligence (AI) scribes into the OpenNotes environment presents a profound governance crisis in healthcare. While patient access to medical records was designed as a transparency reform, the introduction of machine-generated text introduces novel vulnerabilities regarding record integrity, liability, and patients' trust. This study investigates how clinicians discursively negotiate the systemic risks and accountability challenges of patient-facing, AI-assisted documentation. Employing a netnographically informed qualitative design, the research conducted a reflexive thematic analysis of 484 relevant comments across 120 threads from eight clinician-oriented subreddits spanning October 2020 to February 2026. The analysis revealed five distinct governance challenges. First, an accountability vacuum exists where the mandatory clinician signature functions merely as a legal shock absorber for institutional AI liability. Second, clinicians frame AI hallucinations as a mathematically inevitable epistemic risk rather than a correctable technical bug. Third, a "dual-audience" problem emerges, as algorithmic optimization compromises both the individual clinical voice needed for peer communication and the empathetic clarity required for patient readers. Fourth, existing privacy frameworks are structurally inadequate to manage commercial data extraction during patient encounters. Finally, institutional productivity demands and AI-driven over-documentation severely threaten the fiscal credibility of the medical record through inadvertent upcoding. The prevailing regulatory assumption-that a physician's digital signature combined with passive patient visibility guarantees documentation accountability-is a fragile fiction. To protect clinical truth, health systems must transition from models of passive disclosure toward contingent transparency. This requires establishing authoritative, enforceable mechanisms for provenance tracking, error contestation, and vendor accountability.

Learning from medical errors prevents their recurrence. This study examined the management of safety incidents and medical errors, as well as the learning process. A semi-structured interview was conducted with NHS practitioners involved in invasive procedures. An inductive thematic analysis was followed to create descriptive themes. Analytical themes have been identified based on the descriptive themes. The interviews included 15 participants (11 consultants, two senior trainees, and two senior theatre nurses). Many are unfamiliar with the definitions and classification of medical errors. Concerns are raised about under-reporting important incidents and over-reporting futile incidents. There was a clear division in reporting near misses. The majority have a pathway for managing medical errors in their organisations. However, the main concern was the lack of feedback. The majority believe M&M meetings provide the best platform to discuss medical errors, though there are concerns about the meetings' length, case selection, and the absence of anonymised discussions. The participants believe central reporting could lead to change, but the lack of horizontal dissemination of lessons learned is a significant defect. Confidentiality, the reputation of trust, fear of public opinion and politicians, and the negative role of the media all hinder the publication of medical errors and the learning of lessons. There is a lack of formal support for the second victim and a prevalence of defensive medicine. There are concerns related to the process and purpose of incident reporting. M&M meetings are the preferred forum for clinicians to discuss and learn from errors. The main problems are the lack of feedback and the horizontal dissemination of learning lessons. Publishing about medical errors is a sensitive subject influenced by many factors. There is a need for a formal programme across the NHS to support the second victim. Defensive medicine is the new norm.