Healthcare最新文献

{"title":"Gender-Based and Sexualized Behaviors in Perioperative Workplaces in Türkiye: An Exploratory Cross-Sectional Survey.","authors":"Semin Turhan, Sibel Önen Özdemir, Selçuk Kayır, Güvenç Doğan, Özgür Yağan, Volkan Hancı","doi":"10.3390/healthcare14193271","DOIUrl":"10.3390/healthcare14193271","url":null,"abstract":"<p><strong>Background/objectives: </strong>Evidence on gender-based and sexualized conduct in perioperative workplaces in Türkiye is limited. This exploratory study described 12-month self-identified personal exposure, behavior encounters, reporting, organizational climate, impacts, and prevention priorities in a self-selected sample.</p><p><strong>Methods: </strong>An anonymous web survey used open non-probability recruitment from 8 June to 31 July 2026. Eligible respondents worked in operating-room or anesthesia services. Sample proportions were reported with Wilson 95% confidence intervals (CIs), and sex comparisons were performed.</p><p><strong>Results: </strong>Of 183 submissions, 179 were eligible (111 women; 68 men). Self-identified personal exposure to either gender-based or sexual harassment was reported by 15/176 respondents (8.5%, 95% CI 5.2-13.6): 13.8% of women and 0% of men (<i>p</i> < 0.001). Overall, 63.1% reported experiencing or witnessing at least one specified behavior; this secondary outcome was not a measure of personal harassment prevalence. Among 75 respondents routed through the context items to the reporting question, 74.7% selected 'No' or 'Considered reporting but did not'; the item did not identify which specific behavior was being considered. Lower exploratory climate scores and higher impact scores accompanied personal exposure. Managerial sanctions and retaliation protection were rated the highest.</p><p><strong>Conclusions: </strong>Within this self-selected sample, the observed conduct, sex differences, and limited use of reporting pathways within the routed subgroup warrant organizational attention. Results should not be interpreted as nationally representative prevalence estimates.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13664897/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Response Quality of AI-Generated Answers to Orthodontic Patient Concerns Across Empathy, Accuracy, Comprehensiveness, Personalisation, Safety, and Patient-Centeredness: A Cross-Model, Bilingual Evaluation of Claude, GPT-4o, and Gemini.","authors":"Mustafa Ozcan, Ferdi Allaf","doi":"10.3390/healthcare14193281","DOIUrl":"10.3390/healthcare14193281","url":null,"abstract":"<p><strong>Background: </strong>Patients now consult large language models (LLMs) for orthodontic concerns, but most evaluations sit in English and focus on factual accuracy. We compared three current LLMs (Claude Opus 4.5, GPT-4o, Gemini 2.5 Flash) on patient-facing responses in English and Turkish, and tested whether model differences held up after adjusting for response length.</p><p><strong>Methods: </strong>Sixty standardised patient scenarios were prompted in both languages to each model via stateless single-turn API calls with identical token limits, yielding 360 responses. Three blinded orthodontists scored every response on empathy, accuracy, comprehensiveness, personalisation, safety, and patient-centeredness (1-5 Likert). Primary between-model contrasts used mixed-effects linear models with scenario as a random effect to accommodate the paired scenario structure, with length-adjusted specifications adding response word count as a covariate; one-way ANOVA and ANCOVA on the balanced English sample were reported concordantly as descriptive checks. Reliability was assessed with ICC(2,3) and Krippendorff's α.</p><p><strong>Results: </strong>Forty-eight Turkish Gemini outputs (80%) were truncated mid-generation and were excluded, leaving 312 successfully completed responses. Between-model ranking is therefore reported on the balanced English cell (<i>n</i> = 60 per model). Unadjusted, Gemini scored highest on the English cell (total 4.04 vs. 3.86 GPT-4o, 3.85 Claude). But response length correlated strongly with scores (r = 0.75 total; r = 0.84 comprehensiveness), and mean Gemini English length (547 words) was roughly double Claude's (265) and GPT-4o's (288). After length adjustment, Gemini's advantage on empathy, comprehensiveness, and personalisation disappeared (all <i>p</i> > 0.10), the total-score coefficient reversed (β = -0.065, <i>p</i> = 0.017), and Gemini scored lower on patient-centeredness (β = -0.153, <i>p</i> = 0.021). English scored substantially higher than Turkish on every dimension (3.92 vs. 3.51; d = 2.71), and patient-centeredness was the weakest dimension overall (3.27).</p><p><strong>Conclusions: </strong>Rubric-based scoring of LLM outputs is strongly associated with response length; unadjusted between-model comparisons may mainly reflect length differences rather than architectural differences. The English-Turkish gap and the Turkish Gemini truncation are robust to length adjustment. Per-language quality assurance-for both completeness and length-normalised content quality-is a prerequisite for patient-facing LLM deployment; English-only evaluation is not a safe proxy.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665484/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149192401","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Critical Methodological Review of Clinical Scores, Machine Learning, and Large Language Models for the Diagnosis and Management of Pediatric Appendicitis.","authors":"Marko Bašković, Zenon Pogorelić","doi":"10.3390/healthcare14193269","DOIUrl":"10.3390/healthcare14193269","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Acute appendicitis is the most common surgical emergency of childhood, yet its diagnosis remains difficult because presentations are atypical, inflammatory markers are nonspecific, and the consequences of error run in both directions, from negative appendectomy to missed perforation. Over the past two decades, a large body of work has tried to support this decision with clinical scores, and more recently with machine learning, deep learning, and large language models. <b>Methods:</b> This critical methodological review synthesises that literature across the whole care pathway rather than the single question of binary diagnosis, using a reproducible search and a transparent study-level appraisal, and it therefore covers severity stratification, prediction of non-operative treatment response, imaging stewardship, and the postoperative course. We evaluate this evidence through the lens of contemporary methodological standards, in particular the Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis, updated for artificial intelligence (TRIPOD+AI), and the Prediction model Risk Of Bias Assessment Tool, updated for artificial intelligence (PROBAST+AI). <b>Results:</b> We describe the main families of models, from the Alvarado and Pediatric Appendicitis scores to random forests, gradient boosting, convolutional networks applied to ultrasound, and emerging generative models. Reported performance is dominated by discrimination while calibration, clinical utility, external validation, fairness, and reproducibility are reported inconsistently and are often absent. We argue that the recurring pattern of very high reported accuracy reflects methodological fragility more than clinical readiness. <b>Conclusions:</b> We offer a practical checklist for the critical appraisal of appendicitis prediction studies together with a research agenda aimed at closing the gap between a high area under the curve and safe use at the bedside.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665171/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149192616","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Association of Bone-Specific Physical Activity with Bone Mineral Density and Arterial Stiffness in Premenopausal Women: A Cross-Sectional Study.","authors":"Sung-Woo Kim, Myong-Won Seo, Hyun Chul Jung","doi":"10.3390/healthcare14193287","DOIUrl":"10.3390/healthcare14193287","url":null,"abstract":"<p><p><b>Background:</b> This cross-sectional study investigated the associations of bone-specific physical activity (PA), assessed using the Bone-Specific Physical Activity Questionnaire (BPAQ), with bone mineral density (BMD) and arterial stiffness in premenopausal women. <b>Methods:</b> A total of 270 premenopausal women participated. Continuous total BPAQ (tBPAQ) was analyzed as the primary exposure in the revised analyses, while tertile-based analyses were retained as secondary analyses. BMD was measured by dual-energy X-ray absorptiometry, and arterial stiffness was assessed using brachial-ankle pulse wave velocity (baPWV). BMD models were adjusted for age, fat-free mass (FFM), and BMI, and the mean bilateral baPWV model was adjusted for age, mean arterial pressure, and BMI. <b>Results:</b> Higher tBPAQ was positively associated with whole-body, femoral neck, total femur, and lumbar spine BMD after false-discovery-rate correction (all q < 0.001). The forearm association was weaker (B = 0.0040 g/cm² per 10 tBPAQ points; q = 0.019) and was not retained in the log1p-transformed sensitivity analysis (<i>p</i> = 0.162) or the adjusted tertile comparison (<i>p</i> = 0.062). There was no evidence of an adjusted linear association between tBPAQ and mean bilateral baPWV (B = 5.1 cm/s per 10 points; 95% CI, -4.6 to 14.7; <i>p</i> = 0.301; q = 0.301). Exploratory quadratic models suggested possible nonlinearity for femoral neck BMD and mean bilateral baPWV, but these findings were hypothesis-generating. <b>Conclusions:</b> Higher cumulative bone-specific PA was associated with higher BMD, particularly at weight-bearing skeletal sites, whereas the forearm finding was less consistent across analyses. No adjusted linear association with arterial stiffness was identified. Longitudinal and interventional studies are needed to clarify temporality and possible nonlinear relationships.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665021/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149192847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Ageism and LGBTIQA+ Phobia: A Scoping Review of Barriers in Healthcare.","authors":"Andrea Paz-Lorenzo, Francisco Javier Castro-Molina, Jesús Manuel García-Acosta","doi":"10.3390/healthcare14193276","DOIUrl":"10.3390/healthcare14193276","url":null,"abstract":"<p><strong>Introduction: </strong>Population ageing and increasing recognition of sexual and gender diversity have highlighted health inequalities affecting older LGBTIQA+ people. Ageism and LGBTIQA+ phobia intersect, creating specific barriers to healthcare.</p><p><strong>Objective: </strong>To map and synthesize evidence on healthcare barriers affecting older LGBTIQA+ people and their consequences from a nursing perspective.</p><p><strong>Methods: </strong>A scoping review was conducted following PRISMA-ScR and Joanna Briggs Institute guidance. The review question was developed using the PCC framework. Searches were performed in PubMed, CINAHL, Scopus, and the Cochrane Library. Nineteen sources were included.</p><p><strong>Results: </strong>Structural barriers included inadequate professional training, cisheteronormativity, and limited inclusive policies. Interpersonal barriers comprised discriminatory attitudes, identity invisibility, misgendering, and fear of disclosure. Social barriers included stigma, isolation, and socioeconomic disadvantages. These barriers were associated with delayed care-seeking, reduced service utilization, and poorer physical, mental, and social health outcomes.</p><p><strong>Discussion: </strong>The findings indicate that inequalities cannot be explained by age or LGBTIQA+ identity alone, but by their interaction with socioeconomic and psychosocial vulnerabilities across the life course. Community networks may provide protection, although their availability is unequal. Nursing education, identity-affirming protocols, inclusive organizational policies, and accountability mechanisms are therefore required.</p><p><strong>Conclusions: </strong>Older LGBTIQA+ people experience cumulative barriers within healthcare and long-term care. Longitudinal and intervention research is needed to evaluate effective strategies for culturally safe and equitable care. The protocol was registered in the Open Science Framework on 8 July 2026.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665186/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149192852","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Algorithmic Bias in AI-Based Diagnostic Models: A Systematic Review and Lifecycle Framework for Fairness Auditing and Governance in Healthcare.","authors":"Reyadh Alluhaibi","doi":"10.3390/healthcare14193293","DOIUrl":"10.3390/healthcare14193293","url":null,"abstract":"<p><p><b>Background:</b> Artificial-intelligence-based diagnostic systems increasingly influence healthcare delivery, yet strong aggregate performance can coexist with clinically meaningful disparities across demographic subgroups. Such disparities raise not only model-development concerns but also health-equity, implementation, and governance challenges for healthcare organizations. <b>Methods:</b> We conducted a systematic review reported in accordance with PRISMA 2020 of literature published from January 2019 through August 2026. The search identified 1842 records; 87 records were retained in the overall evidence corpus and 46 underwent structured quantitative extraction. The corpus included primary empirical/model-evaluation evidence together with secondary or adjacent methodological evidence used for qualitative contextualization. We also developed FRCS-10, a ten-item descriptive reporting-completeness index derived from established reporting and governance guidance, and applied it to the full corpus. <b>Results:</b> Peer-reviewed primary sources reported baseline true-positive-rate gaps of 0.062-0.281 across sex, age, and race on CheXpert and MIMIC-CXR, while a contextual dermatology meta-analysis reported AUROC values of 0.89 for Fitzpatrick I-III and 0.82 for Fitzpatrick IV-VI. These values were synthesized as source-reported estimates and were not independently re-analysed from patient-level data. Data representation was the most frequently coded bias source (38%), followed by algorithmic design (21%) and label or annotation bias (19%). The descriptive FRCS-10 mean was 4.6/10; only 7 of 87 records described post-deployment fairness monitoring. Five primary empirical studies with sufficiently explicit estimands were assessed for compatibility; their disparity definitions were not commensurable, so no pooled effect size was computed. <b>Conclusions:</b> We propose the Equity-Aware Bias Detection and Mitigation Framework (EA-BDMF), a literature-derived, implementation-oriented lifecycle specification for healthcare AI. It links data auditing, prevalence-aware preprocessing, fairness-constrained training, calibration and threshold governance, and post-deployment monitoring. The framework is accompanied by a Lifecycle Equity Debt (LED) accounting measure, checkpoint documentation, a Bias Provenance-Mitigation Traceability Matrix, and descriptive regulatory mapping. The complete framework has not yet been validated end to end, and its clinical and organizational utility requires prospective evaluation in real-world healthcare settings.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665230/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149192888","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Nursing Role in the Management of Major Ambulatory Surgery Units: A Scoping Review.","authors":"Lidia María Herrera-Aguiar, Jesús Manuel García-Acosta, Johan Gregorio Reyes-Quesada, Chaxiraxi Bacallado-Rodríguez, Silvia Elisa Razetto-Ramos, Elena Herrera-Aguiar, Francisco Javier Castro-Molina, Mª Mercedes Novo-Muñoz, Natalia Rodríguez-Novo","doi":"10.3390/healthcare14193289","DOIUrl":"10.3390/healthcare14193289","url":null,"abstract":"<p><p><b>Background:</b> Major Ambulatory Surgery is an increasingly common care model, but evidence on nurses' specific organizational roles remains limited. <b>Objectives:</b> To identify and map evidence on nursing roles in the organization, management, and optimization of MAS units. <b>Methods:</b> A scoping review was conducted according to Joanna Briggs Institute methodology and PRISMA-ScR guidelines. Embase, MEDLINE ALL (Ovid), CINAHL Complete, and Web of Science Core Collection were searched on 30-31 July 2025. Following an exploratory phase, the eligibility period was set from January 2000 to July 2025. Observational, qualitative, interventional, and review studies published in English or Spanish were included. <b>Results:</b> Of 922 records identified, 18 sources were included: 16 primary studies and two literature reviews, the latter analyzed separately as contextual evidence. The primary studies most frequently documented nursing roles in preoperative assessment, patient education, discharge preparation, postoperative follow-up, continuity of care, and care-process coordination. Six primary studies measured a service-level indicator (day-of-surgery cancellations, waiting times, or theatre utilization), all with uncontrolled before-after or descriptive designs; only one study addressed management, staffing, leadership, or organizational planning. Direct evidence on managerial, strategic, and organizational-planning roles was scarce. <b>Conclusions:</b> The central finding is the scarcity of evidence on nurses' managerial, strategic, and organizational-planning roles, in contrast with the well-documented roles in preoperative assessment, patient education, postoperative follow-up, and care coordination. Because methodological quality was not appraised, the findings do not establish the effectiveness or comparative superiority of specific nursing models. Future research should define and evaluate nursing competencies and organizational models in MAS using robust comparative, qualitative, and mixed-methods designs.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665532/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193184","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Monitoring Digital Health Equity Across the Digital Front Door: U.S. Trends in Broadband Access, Portal Offers, and Patient IT Use in 2017-2020.","authors":"Rehab A Rayan, Salman Kimiagari","doi":"10.3390/healthcare14193268","DOIUrl":"10.3390/healthcare14193268","url":null,"abstract":"<p><p><b>Background/Objectives</b>: Patient portals and patient-facing information technologies are now routine channels for healthcare delivery, but healthcare organizations need practical ways to monitor whether these channels are equitably accessible and used. This study examined U.S. national trends in digital health equity from 2017 to 2020 using three Healthy People/HINTS indicators representing an access-offer-use pathway: broadband access, being offered online access to medical records, and using information technology to track or communicate about care. <b>Methods</b>: We conducted a repeated cross-sectional analysis of publicly available aggregate Healthy People 2030 indicator data based on the Health Information National Trends Survey. National trends were summarized for HC/HIT-05, HC/HIT-06, and HC/HIT-07. Education- and income-related inequalities were assessed using the Slope Index of Inequality and Relative Index of Inequality. Subgroup variation was examined using precision-adjusted funnel monitoring with overdispersion adjustment. Sensitivity analyses assessed alternative overdispersion specifications, weighting approaches, and confidence-interval diagnostics. <b>Results</b>: From 2017 to 2020, broadband access declined from 55.9% to 41.5%, while portal offers increased from 61.4% to 72.0% and patient IT use increased from 80.0% to 83.3%. Socioeconomic inequalities persisted across the pathway. Education-related gradients widened for broadband access and portal offers, whereas education and income gradients narrowed for downstream patient IT use. Funnel monitoring indicated subgroup heterogeneity beyond expected sampling variation, supporting the need for equity monitoring beyond aggregate national trends. <b>Conclusions</b>: Digital health performance should not be evaluated using overall uptake alone. Monitoring access, organizational offering, and patient use as separate but connected stages can help healthcare organizations, payers, and policymakers identify where inequities occur and target connectivity screening, portal-offer workflows, digital navigation support, and low-bandwidth service design.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665087/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Emerging Applications of Virtual Reality and Artificial Intelligence in Schema Therapy: A Scoping Review.","authors":"Flavia Salomoni Mansano, Karen Priscila Del Rio Szupszynski, Carmen Moret-Tatay, María José Beneyto-Arrojo, Margareth da Silva Oliveira","doi":"10.3390/healthcare14193292","DOIUrl":"10.3390/healthcare14193292","url":null,"abstract":"<p><p>Digital tools have become increasingly integrated into contemporary psychological practice, responding to the growing demand for accessible, scalable, and experiential mental health interventions. Within this evolving landscape, Schema Therapy represents a promising field for technological enhancement due to its emphasis on experiential techniques, mode work, and the restructuring of deeply rooted cognitive-emotional patterns. <b>Objectives:</b> This study aimed to map and characterize how Virtual Reality and Artificial Intelligence technologies are currently being used or proposed to support innovation in the application of Schema Therapy. <b>Methods:</b> A scoping review was conducted with searches performed across five major databases. Search strategies were adapted to each database, and records were screened according to inclusion/exclusion criteria. <b>Results:</b> Four records met eligibility criteria, revealing an emerging yet limited body of work dedicated to theoretical and experimental innovation in this area. Virtual Reality and metaverse-based interventions were proposed to create immersive, ecologically valid environments that facilitate emotional reprocessing, mode restructuring, and reductions in self-criticism, key mechanisms within ST. AI tools have demonstrated potential for large-scale identification of Early Maladaptive Schemas, enabling new forms of assessment and case conceptualization within online mental health contexts. <b>Conclusions:</b> No current evidence is sufficient to establish the efficacy of combining digital technologies such as Virtual Reality or Artificial Intelligence with Schema Therapy. The available literature remains limited and includes different stages of research development, from conceptual proposals and protocols to empirical studies. The identified applications primarily use these technologies as tools to support established Schema Therapy procedures rather than to modify its theoretical concepts or techniques. Although the findings indicate possible directions for technologically supported interventions, the current evidence is insufficient to establish their clinical effectiveness. Further empirical research is needed to evaluate their effects, feasibility, and clinical use within Schema Therapy.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665133/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193017","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Orthopedic and Trauma Physicians' Ability to Identify Selected SUT Reimbursement Amounts in Türkiye: A Cross-Sectional Survey.","authors":"Ahmet Yiğitbay, Serhat Yıldırım, Nezih Ziroğlu","doi":"10.3390/healthcare14193284","DOIUrl":"10.3390/healthcare14193284","url":null,"abstract":"<p><p><b>Background:</b> The Turkish Social Security Institution Health Implementation Communiqué (SUT) specifies administrative reimbursement tariffs that are distinct from actual healthcare delivery costs. Physicians' familiarity with these tariffs can be examined across different areas of orthopedic practice. <b>Objective:</b> To assess orthopedic and trauma physicians' ability to identify selected SUT reimbursement amounts and to describe their responses to hypothetical clinical scenarios. <b>Methods:</b> This cross-sectional online survey included 102 orthopedic and trauma physicians practicing in Türkiye, recruited voluntarily through a national professional society e-mail group. Analyses included demographic and professional information, previous healthcare-cost education, 18 single-response multiple-choice tariff questions, and three hypothetical clinical scenarios. Each correct tariff response received one point, yielding an unweighted total of 0-18. Questions had two to four response options with nonuniform monetary intervals; some options were individual amounts. Scenario responses were treated as descriptive rather than measures of individual decision change. <b>Results:</b> The mean tariff-response score was 6.02 ± 2.38, with a median of 6 (IQR, 4-8). Overall, 614 of 1836 responses were correct (33.4%). Assuming one correct option per question and uniform random selection, the theoretical expected accuracy was 31.5%. Accuracy ranged from 22.1% for outpatient procedures to 52.9% for implants, although differences in response formats limit comparisons between categories. Six participants (5.9%) reported previous healthcare-cost education. Non-equivalent scenario response formats and internally inconsistent response combinations prevented valid assessment of individual decision changes. <b>Conclusions:</b> Participants selected the reference-matching response for approximately one-third of the tariff questions. Interpretation is limited by heterogeneous response options, the possibility of correct answers through guessing, and the voluntary, nonrepresentative sample. The findings concern selected administrative reimbursement amounts and do not measure actual healthcare costs or comprehensive health-economic knowledge. The hypothetical scenario responses do not establish effects of tariff information on clinical behavior, appropriateness, utilization, expenditure, or patient outcomes.</p>","PeriodicalId":12977,"journal":{"name":"Healthcare","volume":"14 19","pages":""},"PeriodicalIF":3.4,"publicationDate":"2026-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13665003/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149193140","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}