Junior Doctors Research Articles

The ‘Epidemic’ of violence against junior doctors in Baghdad: reasons, impact and consequences

ABSTRACT Violence against heath care workers in Iraq has reached an ‘epidemic’ level. It affects health care providers, receivers of care and the health system as a whole. This study aims to explore the reasons and impact of violence against junior doctors in Baghdad city. A sample of 223 junior doctors from 12 General and Teaching hospitals in Baghdad/Iraq were included in this survey. A semi-structured questionnaire was adopted that enquires about demographic and work characteristics, and details of workplace violent attacks. The results showed that 82% of the participants were either exposed to or witnessed workplace violence. The highest prevalence was among young newly graduated house officers. The source was mostly the patients’ companions/relatives, and mainly attributed to work overload and lack of medicines/supplies. A significant positive association was found between exposure to WPV and all domains of burnout score. High emotional exhaustion was found in 79.1% of those exposed to WPV in comparison to 35.1% of those not exposed (p < 0.001). In addition, 39.1% of the participants met the criteria for potential risk of PTSD, while 11.2% showed the symptoms of a full PTSD diagnosis. Urgent practical interventions need to be undertaken by all those with influence and responsibility to control and reduce this behaviour.

Junior Doctors’ Specialty Choice: Stated and Revealed Preferences over More Than a Decade

Junior Doctors’ Specialty Choice: Stated and Revealed Preferences over More Than a Decade

Establishing a novel score system and using it to assess and compare the quality of ChatGPT-4 consultation with physician consultation for obstetrics and gynecology: A pilot study.

In the current study, we aimed to establish a quantified scoring system for evaluating consultation quality. Subsequently, using the score system to assess the quality of ChatGPT-4 consultations, we compared them with physician consultations when presented with the same clinical cases from obstetrics and gynecology. This study was conducted in the Women and Children's Hospital of Chongqing Medical University, a tertiary-care hospital with approximately 16 000-20 000 deliveries and 8500-12 000 gynecologic surgeries per year. The detailed data from obstetric and gynecologic medical records were analyzed by ChatGPT-4 and physicians; the consultation opinions were then generated respectively. All consultation opinions were graded by eight junior doctors using the novel score system; subsequently, the correlation, agreement, and comparison between the two types of consultation opinions were then evaluated. A total of 100 medical records from obstetrics and 100 medical records from gynecology were randomly selected. Pearson correlation analysis suggested a noncorrelation or weak correlation between consultations from ChatGPT-4 and physicians. Bland-Altman plot showed an unacceptable agreement between the two types of consultation opinions. Paired t tests showed that the scores of physician consultations were significantly higher than those generated by ChatGPT-4 in both obstetric and gynecologic patients. At present, ChatGPT-4 may not be a substitute for physicians in consultations for obstetric and gynecologic patients. Therefore, it is crucial to pay careful attention and conduct ongoing evaluations to ensure the quality of consultation opinions generated by ChatGPT-4.

Clinical leadership education-A scoping review protocol.

Leadership is a key skill for physicians, but studies show that many junior doctors feel unprepared for the role as a leader. In recent years, there has been increasing interest and research into the training and development of clinical leadership, revolving around leadership in situations with direct patient care and as opposed to the administrative leadership of a department. However, the lack of consensus on how best to teach leadership, how the education should be structured, as well as a standardized definition and measure for good leadership, complicates training, assessment, and comparison of approaches in both research and education. The aim of this study is to map out the existing body of research on leadership education for physicians and medical students and identify any gaps in this literature. The scoping review will follow the Arksey and O'Malley (Arksey and O'Malley, Int J Soc Res Methodol. 2005; 8(1):19-32) framework, Joanna Briggs Institute methodology (JBI Manual for Evidence Synthesis-JBI Global Wiki) and PRISMA_ScR (Tricco et al., Ann Intern Med. 2018; 169(7):467-473). A systematic search will be conducted across the following databases: PubMed, Cochrane, Embase, Ebsco, Medline, and Google scholar. Two independent reviewers will screen titles and abstracts, then review the full texts of articles. Data will be extracted and presented in line with the review questions. The study will use a structured approach, as guided by Arksey and O'Malley and JBI methodology. Studies not written in English, Danish, German, Swedish, and Norwegian will be translated using available software. This review will not include a formal assessment of the study quality or meta-analysis, as it is a scoping review.

Benefits of a near-peer program from the tutors’ perspective: a survey of Australian junior doctors in a regional teaching program

BackgroundNear-peer teaching has been shown to provide diverse benefits for both tutees and tutors in senior medical student and junior trainee settings. However, junior trainees may face more obstacles in teaching including competing clinical priorities and time management. We sought to investigate the challenges and benefits of engaging in near-peer teaching for junior trainees within our local context. Our Near-Peer Medical Teaching (NPMT) teaching program is designed and facilitated by junior doctors for medical students at the Central Coast Clinical School (University of Newcastle) of the Joint Medical Program.MethodsCurrent and past NPMT tutors participated in an online survey from October 2022 to April 2023. Tutors were asked about feasibility of teaching within a work environment, perceived benefits from their experience and attitudes towards medical education.ResultsTeaching experience appears to be influenced by competing clinical priorities and convenience of session times, but it does not appear to exert considerable stress on tutors likely due to self-selection of tutors with prior enjoyable teaching experience. Furthermore, this study indicates that junior doctors derived enjoyment and developed clinical skills and professional qualities, which are important factors in increasing job satisfaction and ameliorating burn-out in this cohort.ConclusionsJunior doctors appear to benefit from engaging in near-peer programs in the Australian teaching hospital setting. Further research should include qualitative methodologies to explore the perspectives of Australian junior doctors’ more deeply.

A Local Training Program to Increase Awareness of Emerging Extended Reality Technologies Among Health Care Professionals: Development Study

Abstract Background Demands on health care services can greatly outweigh capacity. Multifactorial causative factors present great challenges, forcing the National Health Service (NHS) to increase efficiency and adaptivity. Concurrently, digital advancements are excelling and long-term plans for NHS sustainability are focusing on the use of technological interventions to benefit patients. As a result, integration of extended reality (XR) technology has become an important focus of health care research. However, models of how the digital literacy of health care workforces can be developed and how frontline staff can be actively involved in the design and development of creative digital interventions are lacking. Such programs are essential to allow the development and upscaling of digital innovation within the NHS for the benefit of the patients. Such a program has been developed in the Digital Futures research lab at Torbay and South Devon NHS Foundation Trust, representing one of the first immersive digital technologies research spaces embedded within the NHS. A “Digital Deep Dive” training program has been developed, allowing local health care workers to recognize the possibilities of digital health care technologies and supporting them in the evolution of ideas for potential bespoke digital solutions appropriate to their own patient groups and care pathways. Objective This paper aims to explain the development of this unique XR Deep Dive program and present the evaluation that informed future directions for its ongoing development. Methods The Deep Dive sessions were designed according to relevant pedagogic principles, including experiential, active, and contextual learning theories. Voluntary pilot sessions were held for local clinical teams comprised of junior doctors, consultants, nurses, and allied health professionals. Self-selection sampling was used. Participants completed an anonymous postsession feedback form, which was used to conduct a service evaluation. Data were analyzed using descriptive statistics (quantitative) and thematic analysis (qualitative). Results In total, 21 completed questionnaires were analyzed. Overall, the sessions were positively received: all participants reported increased awareness of the potential for digital health care innovation postsession and most found it useful and relevant to their clinical careers. Participants valued the sessions being grounded in a context relevant to local practice with opportunities to interact with the technology through the lens of use cases. Conclusions We have developed a unique training initiative providing contextually relevant XR technology awareness training for health care professionals locally. Despite the growing pace of digital health care innovation, we recognized a knowledge gap in our local workforce regarding the potential of XR technologies within health care. We responded by developing a training program grounded in the concept of digital co-creation—working with staff and service users to develop bespoke solutions integrated within patient pathways. The results from this paper will help to inform future directions for developing digital awareness training in our trust and have implications for wider NHS digital literacy training.

Comparison of a Novel Machine Learning-Based Clinical Query Platform With Traditional Guideline Searches for Hospital Emergencies: Prospective Pilot Study of User Experience and Time Efficiency.

Emergency and acute medicine doctors require easily accessible evidence-based information to safely manage a wide range of clinical presentations. The inability to find evidence-based local guidelines on the trust's intranet leads to information retrieval from the World Wide Web. Artificial intelligence (AI) has the potential to make evidence-based information retrieval faster and easier. The aim of the study is to conduct a time-motion analysis, comparing cohorts of junior doctors using (1) an AI-supported search engine versus (2) the traditional hospital intranet. The study also aims to examine the impact of the AI-supported search engine on the duration of searches and workflow when seeking answers to clinical queries at the point of care. This pre- and postobservational study was conducted in 2 phases. In the first phase, clinical information searches by 10 doctors caring for acutely unwell patients in acute medicine were observed during 10 working days. Based on these findings and input from a focus group of 14 clinicians, an AI-supported, context-sensitive search engine was implemented. In the second phase, clinical practice was observed for 10 doctors for an additional 10 working days using the new search engine. The hospital intranet group (n=10) had a median of 23 months of clinical experience, while the AI-supported search engine group (n=10) had a median of 54 months. Participants using the AI-supported engine conducted fewer searches. User satisfaction and query resolution rates were similar between the 2 phases. Searches with the AI-supported engine took 43 seconds longer on average. Clinicians rated the new app with a favorable Net Promoter Score of 20. We report a successful feasibility pilot of an AI-driven search engine for clinical guidelines. Further development of the engine including the incorporation of large language models might improve accuracy and speed. More research is required to establish clinical impact in different user groups. Focusing on new staff at beginning of their post might be the most suitable study design.

Leadership and Healthcare Management Needs and Inclusion in the Undergraduate Medical Education Curriculum in Nigeria

Background: Leadership and management skills are considered essential for high-quality patient care at all levels of the health system. This study aimed at identifying the leadership and healthcare management (LHM) needs of junior medical doctors (JMDs) and possible modes of inclusion into the undergraduate medical education (UME) curriculum. Methodology: This study is a cross-sectional study with stratified random sampling technique. It was conducted at the College of Health Sciences and Teaching Hospital of Ladoke Akintola University of Technology (LAUTECH), Osogbo, Nigeria and State Specialist Hospital, Osogbo, Nigeria, between November and December 2018. Seventy-four (74) Nigerians comprised of medical students, junior doctors, nurses, administrators, lecturers, and hospital/college of health sciences executives (stakeholders) were assessed. Participants completed an eight-item self-administered leadership and healthcare management questionnaire with a Likert scoring scale of 1 to 5. Statistical analyses were carried out using the IBM SPSS Software, with significant p-value put at P&lt;.05. Results: Seventy-four (74) participants were studied, 45 males and 29 females. Out of 35 skills/competencies listed, three inclusions: Patient Safety, Judgment and Decision making, and Legal Issues in Medical Practice, were unanimously rated important or very important by all study participants. Participants slightly preferred that LHM be taught in the clinical years, and 12 weeks duration of training was the most popular choice. Among the commonly suggested methods of training, only the use of didactic lectures had statistical significance (c2 = 25.767; P = .01). The preferred trainers were the Hospital/College of Health Sciences-based management experts (c2 = 22.308; P = .03). The top envisaged barriers/challenges were time constraints and a lack of LHM lecturers. Overwhelmingly, the study participants agreed that LHM training will benefit JMDs and improve healthcare delivery. Conclusion: The study has revealed very strong support for LHM training and identified the LHM competencies/skills needed by JMDs in Nigeria. More work is needed to refine this essential inclusion in the UME curriculum.

Do we have a lost generation of junior doctors: Effects of the COVID-19 pandemic on junior doctors’ resilience status, medical knowledge and medical skills

BackgroundAt the onset of the COVID-19 pandemic, strict measures suspended face-to-face teaching at German universities, posing significant challenges for medical education. Practical, patient-centered training couldn’t be fully replaced by online formats, leading to skill deficits and increased stress among students. To date, no study has examined the impact of COVID-19 on the resilience and the competence of medical graduates so far. This study aims to address this knowledge gap by investigating the pandemic impact on resilience, medical competence, communication skills, and research competence of medical graduates.MethodsThe study employed data from the “Bavarian Graduate Study of Medicine” (MediBAS), a cross-sectional evaluation survey conducted in cooperation with Bavarian universities and the Bavarian Institute for higher education research and planning. It targeted medical, dental, and veterinary graduates. The data were collected in two waves (2018/19 and 2022/23), with 1.114 human medicine graduates participating. The questionnaire assessed among others resilience, medical expertise, communication skills, and research competence. Statistical analysis involved descriptive statistics, correlation analysis, and Mann-Whitney-U tests due to non-normal data distribution.ResultsThe study analyzed self-assessed resilience, medical expertise, communication, and research skills of medical graduates from two waves. The findings demonstrated through descriptive statistics a decline in all competencies except research skills, which exhibited an increase. Correlation analysis revealed significant relationships between variables. Mann-Whitney-U tests revealed no significant differences between the waves in resilience (p =.079, r =.06), medical expertise (p =.117, r =.05), communication skills (p =.053, r =.07), or research competence (p =.106, r =.05).ConclusionThe study examined the impact of COVID-19 on medical graduates’ resilience, medical expertise, communication skills, and research competence. While there was a slight decline in resilience, medical expertise, and communication skills between the waves, there was an improvement in research competence. None of these changes were statistically significant. The findings suggest that the pandemic may have contributed to these trends by limiting practical experiences. No major negative impacts were found, suggesting no “lost generation” of doctors. The long-term effects of the changes remain uncertain due to the cross-sectional design and require further research.

The influence of the hidden curriculum on the risk of burnout in junior doctors in a palliative medicine rotation – a qualitative exploratory study

BackgroundPalliative Care (PC) provides person-centred care for patients with life-limiting diseases and their families. Studies have shown that healthcare professionals delivering PC are predisposed to moral distress and burnout due to constant exposure to death and dying and aspects of the hidden curriculum (HC) through which culture and values are transmitted implicitly. However, there are limited studies focusing on the latter through the lens of junior doctors. Using the Ring Theory of Personhood (RToP) and the Krishna-Pisupati Model (KPM), which categorize and map conflicts between personal and professional values, beliefs, and principles within the four domains of personhood, this study investigates the impact of palliative care experiences on the risk of burnout in junior doctors.MethodsThis qualitative exploratory study was conducted at the Division of Supportive and Palliative Care in the National Cancer Centre Singapore, involving medical residents who had completed at least one month with the division between 2020 and 2022. 13 participants were recruited for individual semi-structured interviews carried out by an independent research assistant. Acknowledging HC and burnout as sociocultural constructs, we adopted a constructivist ontological position and a relativist epistemological lens to guide thematic analysis of the data.ResultsThe themes identified were: (1) The Nature of PC (2), Moral Distress, and (3) Impact of Environment on Wellbeing. Junior doctors saw the value of the philosophy of care in PC and felt compelled to adopt values espoused by the discipline. However, compounded by consistent exposure to death and dying and limitations to manpower and time, elements of the HC, such as staff support measures, proved to be significant stressors—contributing to burnout and moral distress.ConclusionThis is the first study on the effects of the HC on burnout for junior doctors in a PC rotation. It provides unique insights into the impact of complex clinical, personal, social, ethical and organizational factors on burnout and suggests that all factors need to be addressed in tandem for any attempts at staff support to be successful. This study can guide current and future research and programs that support wellbeing for junior doctors.

An interpretable machine learning model assists in predicting induction chemotherapy response and survival for locoregionally advanced nasopharyngeal carcinoma using MRI: a multicenter study.

To develop and validate an interpretable and generalized machine learning model using MRI for the individualized prediction of induction chemotherapy (ICT) response and survival in locoregionally advanced nasopharyngeal carcinoma (LANPC). A total of 1368 patients who underwent MRI examinations before ICT from three hospitals were retrospectively enrolled and divided into training, internal validation, external validation, and cross-field strength validation cohorts. Significant radiomics and clinical features were selected from coarse to fine. An interpretable genetic algorithm-enhanced artificial neural network (GNN) was applied for models' development and validation. The performance of junior and senior doctors in predicting ICT response with and without model aid was evaluated. The interpretable GNN model achieved good generalization performance in predicting ICT response, with areas under the curve (AUCs) ranging from 0.808 to 0.864 across all cohorts. Survival analysis demonstrated that low-risk patients defined by GNN-radiomics signature and clinical factors had better progression-free survival than high-risk patients in all cohorts (hazard ratio ranging from 3.231 to 12.787, p < 0.05). The predictive performance of junior and senior doctors for ICT response significantly improved with model assistance (AUCs: 0.686 vs. 0.785 and 0.736 vs. 0.836, p < 0.05). An interpretable, applicable, and generalized GNN model based on multi-center databases achieved superior performance in predicting ICT response and survival in LANPC patients, which may contribute to the personalized treatment of LANPC. Question Currently, there is a lack of accurate methods for predicting and evaluating the efficacy and prognosis of nasopharyngeal carcinoma (NPC). Findings Genetic algorithm-enhanced artificial neural network model excels in predicting induction chemotherapy response and survival outcome of NPC, providing valuable assistance to doctors in clinical practice. Clinical relevance This model can identify patients likely to benefit from induction chemotherapy, promoting individualized treatment and optimizing clinical management.

Using ChatGPT for writing hospital inpatient discharge summaries – perspectives from an inpatient infectious diseases service

BackgroundHospital discharge summaries are important tools for communication between healthcare professionals. They convey events that occurred during hospitalisation, as well as the subsequent follow-up plans. Artificial intelligence models can be used to summarise information succinctly from large amounts of raw data input. We explored ChatGPT’s ability to generate effective discharge summaries to assist junior doctors in writing these documents.MethodsWe constructed three hypothetical scenarios of inpatient encounters, with three different outcomes: i) discharge home with follow-up with a general practitioner, ii) discharge to a stepdown facility for further physical rehabilitation, iii) transfer to a tertiary centre for more advanced care. ChatGPT was used to generate discharge summaries for these three scenarios. The quality of the responses provided were evaluated.ResultsChatGPT was able to provide an effective framework for discharge summaries. It processed large volumes of text, summarising pertinent issues and communicating follow-up plans clearly. It is a potentially useful tool for documentation for clinicians. However, pitfalls remain, where close reading is still required to ensure the veracity of the output provided.ConclusionsChatGPT was able to synthesize patient information from a long prosaic format to provide a structured discharge summary. Future prospective study could evaluate if this framework provided by ChatGPT is helpful to aid junior doctors in learning about and writing discharge summaries more efficiently.

P-1817. Reducing The Use of Piperacillin/Tazobactam for Common Infections – A Danish Quality Improvement Study

Abstract Background During a 4-year period we noticed a doubling of Piperacillin/Tazobactam (PIT) consumption in our hospital, which was not supported by the local antibiotic guideline. This quality improvement study aimed to study prescription behavior. We hypothesized that an intervention might increase guideline adherence, thus decreasing the use of PIT as first line treatment for common infections. Methods Baseline data on PIT consumption were collected from April 2022 to March 2023 as defined daily doses (DDD)/100 bed-days. We collected baseline data on guideline adherence from January to March 2023 and performed an audit by reviewing patient charts. A multifaceted intervention was carried out from April 1st to December 31st, 2023, consisting of teaching sessions, feedback to prescribers, discouraging use of urinary dipsticks, creating pocket guidelines, and revision of the antibiotic guideline. Inclusion criteria: Immuno-competent patients ≥ 18 years being prescribed PIT for community-acquired infections. Patients with immunosuppression or at risk of hospital-acquired infection were excluded. We compared the number of PIT prescriptions between baseline and intervention by using unpaired t-tests. Change in adherence to guidelines was tested using the Chi-squared test. The primary outcome was reduction in PIT use and secondary outcome was increased guideline adherence. Results Three-hundred and sixty-nine patients were included. During the intervention, we observed a 26% decrease in PIT use (DDD/100 bed days) and 41% reduction in the number prescribed PIT doses/week. Correctly prescribed PIT doses increased from 49.6% to 53.8% after the intervention. The correct prescriptions were differentiated between senior (75%), junior (57.7%) and locum doctors (43.5%). Conclusion By using a multifaceted intervention strategy to encourage prescribers to follow local guidelines, we observed a substantial reduction in the use of PIT for community-acquired infections in immuno-competent patients. Forming a formal antimicrobial stewardship team may play an important role in maintaining vigilance towards antibiotic prescribing behavior. Disclosures All Authors: No reported disclosures

Assistance of Artificial Intelligence in Diagnosis of Vitreoretinal Lymphoma on Optical Coherence Tomography

Vitreoretinal lymphoma (VRL) remains a diagnostic challenge due to its scarce prevalence, and delayed diagnosis usually results in blindness and even fatal outcomes. Herein, an artificial intelligence (AI) system is developed to identify VRL among 16 retinal diseases and conditions on optical coherence tomography (OCT) images with the cross‐subject meta‐transfer learning (CS‐MTL) algorithm. Extensive experiments of few‐shot VRL recognition tasks prove the robustness of our model on 1‐, 3‐, and 5‐shot scenarios, achieving an F1 score of 0.8697 to 0.9367. The superiority of the model is shown with a higher F1 score (0.9310) compared with other state‐of‐the‐art algorithms (0.5487–0.9018) and three doctors whose clinical experiences range between 3 to 10 years without the help of the CS‐MTL (0.7773–0.8949). AI assistance significantly improves the F1 scores of doctors by 6.16–14.46% (p &lt; 0.001). Moreover, the F1 scores of AI‐assisted senior doctor and retinal specialist (0.9414 and 0.9500), but not the junior doctor (0.8897), exceed that of the CS‐MTL (0.9310). This study presents a promising approach for aiding in the diagnosis of VRL on retinal OCT images and may provide a novel insight into the collaboration of doctors with AI techniques, resulting in reducing the risk of diagnostic delays of rare diseases.

N51 How to guide, for selecting and managing High Cost Drugs in Inflammatory Bowel Disease (IBD)

Abstract Background We developed this guide as our gastroenterology consultants requested a tool which summarise biologics/small molecules guidelines to help with decision making in regards to starting, escalating or switching treatment, without requiring extensive research. This would allow junior doctors to be familiar with these IBD drugs. This guide is being used by consultants, in teaching sessions with junior doctors and distributed on the wards. To assess the benefits, we aim to use a questionnaire so we can improve. Methods This started in March 2024 and a first copy was distributed with doctors in April 2024. The document was developed to be concise and made in 2-pages. As requested, includes drug class, brand, administration route, induction, maintenance, option to escalate dose, pre-screening and routine bloods, contraindications, common side effects and age range. Most doctors are aware of the drug but not on administration route or monitoring which can influence the choice. We noted during IBD clinics that sometimes the biologic suggested does not fit patients’ lifestyle, which requires re-discussion with consultant for a more suitable option, which delays treatment. To evaluate this project, we are taking verbal feedback and aim to use a questionnaire among experienced consultants and junior doctor. Results The guide is being used during teaching session given by IBD lead to junior doctors and they say this is a resourceful tool for their knowledge development and consolidation. We do not have results from questionnaires but we aim to collect and analyse. One gastroenterology consultant emailed “Great initiative and very practical guide!” Doctors discuss with patients the options accurately and when attending IBD clinic they are aware of the options allowing an informed decision for a drug which suits their lives, and start as soon as possible. On the wards, teams are aware of some IBD treatments, this allows them to arrange the necessary pre-screening while waiting IBD review. Conclusion For this to continue to be updated, we will follow the latest studies. Some individuals have concerns because of the lack of experience. If they have the main guideline available, this will bring more confidence and allows space for treatments to be compared. Administration route, blood monitoring and socioeconomic factors can affect the medication that we chose for patients, it is essential that when counselling, doctors are also aware of this. Most recently, patients are referred to IBD team with a clearer plan and more aware of the implications. Following positive feedback, we are planning other guides for mesalazine and corticosteroids. This can be shared with other departments with IBD patients, such as endoscopy and surgical wards.

Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis.

Enhancing AI reliability: A foundation model with uncertainty estimation for optical coherence tomography-based retinal disease diagnosis.

An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs

PurposeDistal radius fractures (DRFs) are often initially assessed by junior doctors under time constraints, with limited supervision, risking significant consequences if missed. Convolutional Neural Networks (CNNs) can aid in diagnosing fractures. This study aims to internally and externally validate an open source algorithm for the detection and localization of DRFs.MethodsPatients from a level 1 trauma center from Adelaide, Australia that presented between 2016 and 2020 with wrist trauma were retrospectively included. Radiographs were reviewed confirming the presence or absence of a fracture, as well as annotating radius, ulna, and fracture location. An internal validation dataset from the same hospital was created. An external validation set was created with two other level 1 trauma centers, from Groningen and Rotterdam, the Netherlands. Three surgeons reviewed both sets for DRFs.ResultsThe algorithm was trained on 659 radiographs. The internal validation set included 190 patients, showing an accuracy of 87% and an AUC of 0.93 for DRF detection. The external validation set consisted of 188 patients, with an accuracy and AUC were 82% and 0.88 respectively. Radial and ulnar bone segmentation on the internal validation was excellent with an AP50 of 99 and 98, but moderate for fracture segmentation with an AP50 of 29. For external validation the AP50 was 92, 89 and 25 for radius, ulna, and fracture respectively.ConclusionThis open-source algorithm effectively detects DRFs with high accuracy and localizes them with moderate accuracy. It can assist clinicians in diagnosing suspected DRFs and is the first radiograph-based CNN externally validated on patients from multiple hospitals.

Strategic tips to successfully undertake research: a comprehensive roadmap for medical trainees.

Engaging in research during medical training is crucial for fostering critical thinking, enhancing clinical skills, and deepening understanding of medical science. Despite its importance, the shortage of physician-scientists lingers with many trainees and junior doctors encountering challenges navigating the research process. Drawing on current literature, this article provides a comprehensive roadmap, categorising 12 actionable strategies into five themes, to help medical trainees overcome common obstacles and optimise their research experience. The strategies include early planning, research conduct and integrity, productivity and time management, collaboration and dissemination, and personal growth and development. By implementing these evidence-based recommendations, derived from current literature and expert insights, medical trainees can refine their research skills, produce high-quality outputs, and contribute meaningfully to the scientific community, ultimately enriching their medical training and future careers.

Understanding influences on psychiatry specialty selection in Victoria's Medical workforce.

Australia faces a psychiatrist shortage, making it crucial to understand factors influencing specialty choice and workforce retention. An online cross-sectional survey was conducted among medical doctors in their prevocational and vocational stages working in Victoria, Australia. Participants were asked about various factors that influenced their choice of specialty. This study focused on those interested in or currently training in psychiatry. To explore differences in factors influencing specialty choice, prevocational doctors interested in psychiatry were compared to those undecided about their specialty. Of the 107 respondents, 56 expressed interest in or were training in psychiatry. The top five factors influencing psychiatry specialty choice were perceived ability, specialty culture, prior experience, work-life balance, and patient interactions. Both prevocational and vocational doctors shared similar views on these factors. Factors such as the cost of training, influence of family and friends, prestige, length of the training program, and salary were reported as less influential. This study identified several factors that were important to junior doctors when selecting psychiatry as a specialty. Active consideration of these factors within service and training frameworks may facilitate improved junior doctor wellbeing and greater workforce retention.

Diagnostic Performance of O-RADS US (Version 2019 and Version 2022) Incorporating Acoustic Shadowing by Junior Radiologists: Analyzing 1061 Adnexal Masses.

Acoustic shadowing is an important benign ultrasound (US) feature for adnexal masses (AMs). To validate the diagnostic performance and interobserver agreement of the 2019 version and 2022 version of Ovarian-Adnexal Reporting and Data System Ultrasound (O-RADS US) and ascertain whether adding acoustic shadowing to O-RADS US v2019 as a benign ultrasound feature can enhance its diagnostic efficacy among junior radiologist. This retrospective study included consecutive women with suspected adnexal masses who underwent ultrasound examinations between September 2022 and January 2024. One junior doctor (Reader 1, 2 years of experience) classified each AM according to the O-RADS US v2019 and the v2022. Lesions were reclassified according to the US features of acoustic shadowing based on the O-RADS US v2019: the O-RADS category was downgraded by one level with acoustic shadowing and remained unchanged without acoustic shadowing for categories 2-5. Receiver operating characteristic (ROC) curve analysis was used to evaluate the diagnostic performance of the two versions of O-RADS and the modified O-RADS model. Two independent junior radiologists (Reader 1 and Reader 2 with 3 years of experience) then classified the 200 AMs randomly selected for a test-retest analysis. Kappa (к) statistics were used to assess the interobserver agreement. Overall, 1015 women (range, 16-86 years) with 1061 AMs were evaluated. Of the lesions, 864 (81.4%) were benign and 197 (18.6%) were malignant. The area under the ROC curve (AUC) for O-RADS v2019 and v2022 were 0.920 (95% confidence interval [CI]: 0.902, 0.936, P < .001) and 0.924 (95% CI: 0.906, 0.939, P < .001), respectively. The modified model based on O-RADS v2019 incorporating acoustic shadowing as a benign US feature showed an improved AUC of 0.934 (95% CI: 0.917, 0.948, P < .001). A significant difference was observed between the AUCs of the modified O-RADS and two versions of O-RADS models (P < .005). The inclusion of acoustic shadowing increased specificity by 5.4% in predicting malignant adnexal masses, compared with the O-RADS US v2019 with a specificity of 76.2%. Using the modified O-RADS category 4 as the optimal cut-off value for predicting malignancy showed a sensitivity, specificity, positive predictive value, and negative predictive value were 94.4% (95% CI: 90.2%, 97.2%), 81.6% (95% CI: 78.8%, 84.1%), 53.9% (95% CI: 50.3%, 57.5%), and 98.5% (95% CI: 97.3%, 99.1%), respectively. The inter-observer agreement in the O-RADS category between these two junior radiologists was good (κ = 0.74, P < .001). We validated the excellent performance of the Ovarian-Adnexal Reporting and Data system Ultrasound for diagnosing adnexal masses, and the inclusion of acoustic shadowing increased specificity by 5.4% in predicting malignant adnexal masses, compared with the O-RADS US v2019 with the specificity of 76.2%.