Toward protocol simplification: Deep learning-based image synthesis in three-phase CT urography.

Mapping digital health initiatives and technological requirements: A proposal from Sao Paulo State for digital maturity assessment.

Beliefs about relationships between symptoms and experiences in daily life: Evidence from experience sampling and self-report in individuals with or without major depression or social phobia.

The design and validation of a complementary yoga therapy module based on patient-reported survey outcomes for migraine headache.

The automation of medical report generation using large language models (LLMs) could significantly reduce physicians' documentation burden while enhancing healthcare efficiency. However, the misuse of generative artificial intelligence in medical reporting can lead to important safety risks for patients. We addressed 2 questions: (1) What is the quality of medical reports generated by LLMs in English and French? and (2) Can we distinguish between human-written and LLM-generated medical reports? We evaluated the quality of reports generated by several multilingual, open-weight LLMs using text similarity metrics on 4212 medical reports in English and French across multiple specialties. A bilingual expert panel of certified physicians (n = 4) and medical residents (n = 5) scored accuracy, fluency, and completeness of generated reports using a 1-5 Likert scale. Experts also completed a Turing-like test, blindly identifying reports as human or machine-generated. Phi-4 achieved the best overall performance (ROUGE-1: 0.70, BERTScore: 0.83). Expert evaluation confirmed high-quality reports in both languages (overall 4.6/5.0). Medical experts performed better than chance but struggled to differentiate human versus machine reports (accuracy: 0.60). Automatic classifiers showed strong performance (accuracy: 0.98). The high quality of LLM-generated reports supports their potential to enhance healthcare efficiency in multilingual settings. However, the discrepancy between human detection difficulty and automated detection success reveals inherent limitations in relying solely on human oversight for quality assurance and misuse prevention. Deployment of LLMs for medical reporting requires combining automated detection tools with human expertise to ensure patient safety. Dataset and code: https://github.com/ds4dh/medical_report_generation.

The utilisation of transoral robotic surgery (TORS) has grown in popularity over recent years with wide applications for both benign and malignant disease. It is important to recognise that the introduction of robotic surgery inserts a new variable into an already error-prone healthcare service that has a high preventable adverse event rate. Surgical safety checklists (SSC) have been well established in recent years and demonstrated to improve outcomes and reduce complications. This study aims to introduce a novel SSC designed for use specifically in operating theatres for cases using TORS. A modified Delphi process was utilised to define consensus for a proposed TORS specific SSC. An initial iteration was devised using a literature search. Experts with significant TORS experience rated each proposed item for potential inclusion using a Likert scale. The process was repeated until consensus was reached for all items. Two rounds were completed with seven experts agreeing on various items to be included in the TORS specific SSC. This novel surgical safety checklist is the first developed specifically for use with TORS. It has been designed using robust Delphi methodology with several TORS experts from high-volume centres across the UK. The aim of the TORS SSC is to be used alongside the WHO SSC and requires ideally long-term and multi-centre adoption in order to validate its implementation.

Annual Summative Feedback Letters are Associated With Improved End-of-Rotation Surgical Faculty Ratings.

Breastfeeding counseling is an effective public health intervention. However, there is a scarcity of studies detailing protocols, especially those applied during the dyad's stay in the Rooming-In Unit. Thus, this research aimed to describe a breastfeeding counseling protocol during the dyad's hospitalization in Rooming-in. A methodological development study was carried out from June to September 2022 in four stages: discovering from a bibliographical survey; defining the target audience, contexts, and answers to the research question; developing from the construction of the instrument; and delivering the final product after content validation by eight experts. The intervention components protocol includes items necessary for execution; intervention script; breastfeeding assessment instrument; adverse situations, solutions, and initial difficulties in breastfeeding; and counseling approach in the face of situations. For each item of the protocol, a Likert scale was applied, and the Content Validity Index was calculated to verify the agreement between the experts. Items with agreement above 80% were considered valid. Content validation was performed in a single evaluation round. The final version of the protocol consisted of 11 sections. It describes in detail the necessary conditions, expected and unexpected procedures, and how to intervene using the counseling approach in the initial difficulties presented during the hospitalization of the dyad in Rooming-in.

This study aims to determine the development of social media that has changed marketing strategies by promoting highly attractive influencers to influence consumer behavior, particularly in the increasingly competitive beauty industry as Gen Z's interest in skincare products grows. The sampling method used was Non-Probability Sampling with Purposive Sampling technique with a sample size of 100 respondents. Data collection was conducted using a questionnaire distributed via Google Form using a Likert scale. The results were analyzed using multiple linear regression analysis, classical assumption tests, hypothesis testing, and data processing using SPSS 30. The results showed that influencer appeal and brand image had a positive and significant effect on purchasing decisions, both partially and simultaneously. These findings confirm that the synergy between attractive influencers and strong brand image can increase consumer purchasing decisions. The practical implications underscore the importance of selecting influencers that are in line with the brand identity and consistently building a positive image on social media.

Best practices for critically ill patients boarding in the emergency department: A Delphi study.

Post-Finasteride Syndrome: Survey of Dermatologists From the Spanish Hair and Nail Disorders Group.

People with rheumatic and musculoskeletal diseases (RMDs) can acquire disabilities that affect their participation in work and school. Generative artificial intelligence (genAI) may reduce documentation time, providing a tool for providers to efficiently write letters for accommodation and maximally advocate for people with disabilities. Therefore, fellows-in-training (FITs) must develop skills in disability advocacy and genAI for clinical care. We created an online module and simulation activity in which FITs wrote letters for accommodation using genAI. We aimed to improve FITs' confidence implementing these skills and to identify areas needing further instruction. FITs completed an online module and simulation activity engineering genAI prompts for letters for accommodation. Educators scored FITs' skills against a rubric. FITs measured their confidence conducting these skills in retrospective pre-post Likert scales that we compared with Wilcoxon signed rank tests. Twenty-three FITs participated; 18 FITs (78.6%) completed the Likert scales. On average, FITs scored 83.83% against the rubric. The strongest skill was engineering genAI prompts (95.45%), and the lowest was differentiating the scope of practice between rheumatology providers and disabilities professionals coordinating accommodations (74.55%). FITs' confidence significantly improved across all objectives, most notably in engineering genAI prompts and finalizing letters drafted with genAI (P < 0.0001). Our educational materials teach FITs to incorporate genAI into writing letters for accommodation and addressing disparities from medical disabilities. Such skill development prepares FITs to enter the rheumatology workforce confident in their abilities to integrate genAI into clinical activities and deliver care to people with disabilities from RMDs.

This study examines the effect of job satisfaction on employees’ marketing performance in the digital era. Increasing business competition and rapid technological changes require marketing employees to adapt quickly in order to maintain organizational performance. However, many companies still face challenges related to inconsistent marketing performance caused by low employee satisfaction. This research aims to analyze whether job satisfaction significantly influences marketing performance in a digital work environment. A quantitative associative approach was applied in this study. Primary data were collected through questionnaires distributed to 134 marketing employees using a Likert scale. The data were analyzed using simple linear regression with SPSS software. The findings indicate that job satisfaction has a positive and significant effect on marketing performance. The regression coefficient value of 0.675 and significance level of 0.000 confirm that higher job satisfaction contributes to better marketing performance. In addition, the coefficient of determination (R²) of 0.402 shows that job satisfaction explains 40.2% of the variation in marketing performance, while the remaining percentage is influenced by other factors outside the study. These results highlight the importance of improving employee satisfaction to support marketing effectiveness in the digitalization era.

Network-level disruption effects familiar face processing via cortical nodes connected to occipito-limbic and tempora-frontal networks.

To evaluate whether a two-step, 'stage-gated' reporting approach could improve the positive predictive value (PPV) of biparametric (bp)MRI for prostate cancer (PCa) screening compared to conventional Likert/PI-RADS scoring. This retrospective secondary analysis utilised data from IP1-PROSTAGRAM-a prospective, population-based study of men aged 50-69 years who underwent PCa screening with bpMRI, ultrasound and prostate-specific antigen (PSA) testing between October 2018 and May 2019 at two centres (NCT03702439). MRI scans from IP1-PROSTAGRAM were retrospectively evaluated using the 'stage-gated' approach: three radiologists independently reviewed limited MRI sequences (axial T2-weighted and b1500 diffusion-weighted images) and classified scans as positive or negative; if positive, the remaining bpMRI images were reviewed and a hypothetical "decision-to-biopsy" made. The PPV of 'stage-gated' reading was compared to PI-RADS and Likert scores ≥ 4 from the original IP1-PROSTAGRAM bpMRI reports. The reference standard was IP1-PROSTAGRAM biopsy results with grade group (GG) ≥ 2 cancer considered significant. Of 408 participants (median age 57 years [IQR 53, 61]), 405 had MRI scans available for secondary analysis. The prevalence of GG ≥ 2 cancer was 4% (17/405). The 'stage-gated' reporting approach achieved a PPV of 53% (95% CI: 30, 75; 8/15), compared to 29% (95% CI: 15, 47; 8/28) and 30% (95% CI: 17, 46; 11/37) for Likert and PI-RADS ≥ 4 pathways, respectively. The 'stage-gated' approach halved the number of recommended biopsies while maintaining similar cancer detection rates. The 'stage-gated' reporting approach, using limited sequences for the initial read, may improve the PPV and benefit-to-harm ratio of MRI-based screening. Question The PPV of MRI in PCa screening is low, likely because conventional assessment systems are not optimised for low disease prevalence populations. Findings A two-step, 'stage-gated' reading approach achieved a PPV of 53% (8/15), compared to 29% (8/28) for Likert and 30% (11/37) for PI-RADS scores ≥ 4. Clinical relevance The 'stage-gated' reporting approach, which uses limited sequences for the initial read, may improve the PPV and benefit-to-harm ratio of MRI-based screening by reducing unnecessary biopsies. Prospective evaluation is needed to confirm these findings in real-world screening settings.

There is a recognised desire to teach amongst GP trainees yet limited formal opportunities to do this. There are known benefits of near-peer teaching to both teacher and learner, but minimal research investigating the role of GP trainees as teachers in a clinical setting. This study aims to evaluate the views of GP trainees participating in a teaching scheme piloted at the University of Manchester. This mixed-methods study was conducted over a three-year period. In years one and three, evaluation was undertaken using questionnaires comprising Likert scale items and free-text responses (n = 11). In the second year, qualitative data was collected via a focus group with GP trainees following their teaching experiences (n = 8). Subsequently, a thematic analysis was conducted. GP trainees reported benefits including improved clinical skills, job satisfaction and development of leadership skills. There was a noted impact on their teaching skills, as GP trainees demonstrated their ability to be adaptable to learners' needs and develop interactive, structured teaching sessions. The main challenges identified were organisation and time management, balancing responsibilities and adapting to student needs. Trainees unanimously felt the scheme allowed them to meet their portfolio requirements, develop their teaching skills and made them more likely to consider pursuing medical education as part of their future careers. All participants expressed a desire to continue with teaching and reported improved job satisfaction. Participation in a near-peer teaching scheme can have significant positive impacts on GP trainees' personal and professional development. Despite some challenges, trainees reported numerous benefits from undertaking the scheme. Formal teaching opportunities for GP trainees could contribute to the development of a skilled and motivated future workforce of clinician-educators in general practice.

An international survey on current practices of management of neonatal catheter-associated venous thromboembolism: communication from the ISTH SSC Subcommittee on Pediatric and Neonatal Thrombosis and Hemostasis.

RadTranslateGPT: An Improved AI-Based System for Translation and Simplification of Structured Radiology Reports.

Emotional Impact of Patient Death and Associated Psychological Distress in Cardiac Physicians.

Nonverbal behaviours are social tools, used to signal our intentions and feelings to our social partners. Successful communication should therefore depend upon our 'readability': how interpretable these nonverbal signals are. However, while children's ability to reliably interpret their social partners has been well researched, there is a lack of research into the development of readability. To address this gap, 36 typically developing 5- to 11-year-old children were covertly video recorded interacting with a researcher. This captured their naturalistic responses to four different social scenarios. Five-second, silent video clips of each child's reactions to each scenario were created and shown to 27 adult perceivers. These perceivers were then asked to infer which of the four potential scenarios each child was reacting to in each clip, allowing us to measure how 'readable' each child was. Perceivers were further asked to rate how expressive they felt each child was against a five-point Likert scale. This study was pre-registered on the OSF. This is the first study to demonstrate that children between 5 and 11-years-old are readable social actors. Contrary to our expectations, we found no significant effect of age on target readability. On the other hand, target's expressivity was significantly associated with their readability. These results have implications for our understanding of how children become successful communicators and suggest that readability might be a stable trait over this age range - varying between individuals in a similar manner to that previously observed in facial expressivity.