Board Examinations Research Articles

Performance of ChatGPT in Board Examinations for Specialists in the Japanese Ophthalmology Society.

We investigated the potential of ChatGPT in the ophthalmological field in the Japanese language using board examinations for specialists in the Japanese Ophthalmology Society. We tested GPT-3.5 and GPT-4-based ChatGPT on five sets of past board examination problems in July 2023. Japanese text was used as the prompt adopting two strategies: zero- and few-shot prompting. We compared the correct answer rate of ChatGPT with that of actual examinees, and the performance characteristics in 10 subspecialties were assessed. ChatGPT-3.5 and ChatGPT-4 correctly answered 112 (22.4%) and 229 (45.8%) out of 500 questions with simple zero-shot prompting, respectively, and ChatGPT-4 correctly answered 231 (46.2%) questions with few-shot prompting. The correct answer rates of ChatGPT-3.5 were approximately two to three times lower than those of the actual examinees for each examination set (p = 0.001). However, the correct answer rates for ChatGPT-4 were close to approximately 70% of those of the examinees. ChatGPT-4 had the highest correct answer rate (71.4% with zero-shot prompting and 61.9% with few-shot prompting) in "blepharoplasty, orbit, and ocular oncology," and the lowest answer rate (30.0% with zero-shot prompting and 23.3% with few-shot prompting) in "pediatric ophthalmology." We concluded that ChatGPT could be one of the advanced technologies for practical tools in Japanese ophthalmology.

Can a Machine Ace the Test? Assessing GPT-4.0's Precision in Plastic Surgery Board Examinations.

As artificial intelligence makes rapid inroads across various fields, its value in medical education is becoming increasingly evident. This study evaluates the performance of the GPT-4.0 large language model in responding to plastic surgery board examination questions and explores its potential as a learning tool. We used a selection of 50 questions from 19 different chapters of a widely-used plastic surgery reference. Responses generated by the GPT-4.0 model were assessed based on four parameters: accuracy, clarity, completeness, and conciseness. Correlation analyses were conducted to ascertain the relationship between these parameters and the overall performance of the model. GPT-4.0 showed a strong performance with high mean scores for accuracy (2.88), clarity (3.00), completeness (2.88), and conciseness (2.92) on a three-point scale. Completeness of the model's responses was significantly correlated with accuracy (P < 0.0001), whereas no significant correlation was found between accuracy and clarity or conciseness. Performance variability across different chapters indicates potential limitations of the model in dealing with certain complex topics in plastic surgery. The GPT-4.0 model exhibits considerable potential as an auxiliary tool for preparation for plastic surgery board examinations. Despite a few identified limitations, the generally high scores on key parameters suggest the model's ability to provide responses that are accurate, clear, complete, and concise. Future research should focus on enhancing the performance of artificial intelligence models in complex medical topics, further improving their applicability in medical education.

Clustering of students admission data using k-means, hierarchical, and DBSCAN algorithms

Admissions in the university undergo procedures and requirements before a student can be officially enrolled. The senior high school grades remain the most significant in college admission decisions. This paper presents the use of data mining to cluster students based on admission datasets. The admission dataset for 2019-2020 was obtained from the office of student affairs and services. This dataset contains 2,114 observations with 11 attributes. Data preparation and data standardization were performed to ensure that the dataset is ready for processing and implemented in R programming language. The optimal number of clusters (k) was identified using the silhouette method. This method gave an optimal number of k=2 which was used in the actual clustering using the k-means and hierarchical clustering algorithms. Both algorithms were able to cluster students into two: cluster 1-social sciences or board courses and cluster 2-management or non-board courses. Further, density-based spatial clustering of applications with noise (DBSCAN) clustering algorithm was also used on the same dataset and it yielded a single cluster. This study can be replicated by using at least a 5-year dataset of students’ admission data employing other algorithms that would suggest students’ retention and turn over to board examinations.

National ABSITE Preparation Practices: A Survey of General Surgery Residency Program Directors

The American Board of Surgery In-Training Examination (ABSITE) was designed as a low-stakes, medical knowledge examination for US general surgery residency programs. However, in practice, this exam has been utilized for higher stakes purposes, such as resident promotion or remediation, and fellowship selection. Several studies have demonstrated the efficacy of ABSITE preparation resources, but best practices for ABSITE preparation and national preparatory habits are currently unknown. The aim of this work was to determine current residency programs' strategies for ABSITE preparation. We distributed an electronic survey to program directors or program coordinators of US general surgery programs asking them to anonymously report program ABSITE educational practices and ABSITE scores. We analyzed the proportion of responses using descriptive statistics and compared the effect of various strategies using the Mann-Whitney testing for nonparametric data. An average ABSITE percentile score was calculated for each residency based on program self-reported scores. Association of Program Directors (APDS) Listserv PARTICIPANTS: General surgery residency programs participating at the time of distribution (278). Response rate was 24% (66/278); 41 programs (62.1%) identified as university-affiliated, and 25 (37.9%) were community-based. Median intern class size was 8 (range: 3-14), including preliminary interns. Average ABSITE percentile score was 52.8% (range 36.9%-67.6%). There were no significant differences in ABSITE scores based on affiliation or program size. Educational resources utilized for ABSITE preparation included SCORE (89.3%), Q-banks (50%), and surgical textbooks (25.8%). The majority (56.1%) of programs reported using a year-long curriculum for ABSITE preparation, and 66.6% used a time-limited curriculum completed in the months immediately prior to ABSITE. Most programs reported that ABSITE scores were a low priority (63.6%) or not a priority (13.6%). The existence of a year-long curriculum for ABSITE was positively correlated with score as compared to programs without a year-long curricula (53.9% vs 48.5%, p <0.01). Programs using a time-limited curriculum demonstrated lower scores as compared to programs without time-limited curricula (51.3% v 56.1%, p < 0.01). General surgery programs use a variety of strategies to prepare residents for the ABSITE. Despite reporting that they utilize ABSITE scores for a variety of high stakes purposes including evaluation for promotion and as a predictor of the preparedness for the ABS QE, many programs reported that they consider ABSITE scores as a low priority. A year-long focused curriculum was the only strategy correlated with increased scores, which may reflect the value of encouraging consistent studying and spaced repetition. Additional work is needed to guide programs in optimal utilization of ABSITE scores for remediation and resident evaluation, as well as understanding how ABSITE preparatory strategies correlate with clinical performance.

My Experiences in the Lives of Students

This paper examines my role as a teacher in educating students who have no idea what Sociology is and preparing them for their higher studies. Understanding my purpose as a teacher and what motivated me to become a teacher/educator in order to assist students in developing their strategic approach to the upcoming board examination, as well as what the subjective is all about. This article demonstrates how my experience has shaped my students and me into my better selves, as well as what is possible if we all strive to do the shame

Performance of ChatGPT on the Brazilian Radiology and Diagnostic Imaging and Mammography Board Examinations.

This prospective exploratory study conducted from January 2023 through May 2023 evaluated the ability of ChatGPT to answer questions from Brazilian radiology board examinations, exploring how different prompt strategies can influence performance using GPT-3.5 and GPT-4. Three multiple-choice board examinations that did not include image-based questions were evaluated: (a) radiology and diagnostic imaging, (b) mammography, and (c) neuroradiology. Five different styles of zero-shot prompting were tested: (a) raw question, (b) brief instruction, (c) long instruction, (d) chain-of-thought, and (e) question-specific automatic prompt generation (QAPG). The QAPG and brief instruction prompt strategies performed best for all examinations (P < .05), obtaining passing scores (≥60%) on the radiology and diagnostic imaging examination when testing both versions of ChatGPT. The QAPG style achieved a score of 60% for the mammography examination using GPT-3.5 and 76% using GPT-4. GPT-4 achieved a score up to 65% in the neuroradiology examination. The long instruction style consistently underperformed, implying that excessive detail might harm performance. GPT-4's scores were less sensitive to prompt style changes. The QAPG prompt style showed a high volume of the "A" option but no statistical difference, suggesting bias was found. GPT-4 passed all three radiology board examinations, and GPT-3.5 passed two of three examinations when using an optimal prompt style. Keywords: ChatGPT, Artificial Intelligence, Board Examinations, Radiology and Diagnostic Imaging, Mammography, Neuroradiology © RSNA, 2023 See also the commentary by Trivedi and Gichoya in this issue.

Abstract 16722: Performance Evaluation of ChatGPT 4.0 on Cardiovascular Clinical Cases From the USMLE Step 2CK and Step 3 of the National Board of Medical Examiners

Introduction: As the prominence of online chat-based artificial intelligence (AI) platforms increases, medical students and residents in training may be inclined to utilize these tools as supplementary resources while preparing for their United States Medical Licensing Board (USMLE) examinations. Hypothesis: The aim of this study was to assess the performance of ChatGPT 4.0 in responding to cardiovascular (CV) clinical vignettes from USMLE sample questions provided by the National Board of Medical Examiners (NBME). Methods: We extracted the 31 CV clinical vignettes from the official NBME USMLE Step 2 Clinical Knowledge and Step 3 self-assessments, and submitted them to ChatGPT 4.0. The clinical cases encompassed a range of topics such as preventive medicine, congenital heart disease, valvular heart disease, electrophysiology, heart failure, and pericardial disease. Each of the 31 cases had a MCQ: 29/31 had at least 5 answer choices, while the remaining 2 had 4 answer choices each. The performance of the AI model was assessed using the NBME-provided answers. Subsequently, two experienced cardiologists independently reviewed the explanations provided by the model for each case and classified them as “accurate” - if they aligned with appropriate guidelines, and as “inaccurate” if they conveyed incorrect or inappropriate information. Results: The AI model attained a grade of 90.3% (28/31). The initial agreement between the 2 reviewers was near perfect with a Cohen’s Kappa of 0.85. Any identified discrepancies were subsequently addressed and resolved. Of the correctly answered questions, accurate explanations were provided by the AI model in 89.2% of cases (25/28). Conclusions: The high performance of ChatGPT 4.0, suggests it could be an effective additional CV study resource for residents and medical students preparing for the USMLE Step 2 CK and Step 3 exams.

Analysis of the Doctor of Public Health (DrPH) training and identity needs in the United States: a qualitative study

BackgroundThe Doctor of Public Health (DrPH) is the highest attainable degree in the field of public health, specifically designed to prepare professionals to address complex public health challenges in practical settings. This study was designed to explore the importance of achieving a shared and uniform understanding of DrPH education, assess the optimal direction for DrPH training, and investigate the specific curriculum requirements by gathering insights from current DrPH students and alumni in the United States.MethodsA total of 13 focus group discussions and two in-depth interviews (total participants: 50) were conducted through Zoom to see how DrPH students and alumni assessed their DrPH educational programs.ResultsThree overarching findings emerged from the analysis of focus group discussions and in-depth interviews. First, participants expressed a preference against a national DrPH board examination, but advocated for a standardized common core curriculum that extends across the entire nation. Second, the ideal direction for DrPH training was perceived to involve a practice-based approach, emphasizing the importance of multi-, inter-, and trans-disciplinary instruction delivered by faculty with practical experience. Last, there was a demand for a DrPH-specific unique curriculum encompassing areas such as mixed method analysis, leadership and management, applied communication, crisis and change management, proficiency in addressing contemporary topics, and tailored applied and integrative learning requirements specific to the DrPH program.ConclusionsWe explored a range of DrPH training and identity needs among 50 participants, comprised of students and alumni who directly benefit from DrPH education. By considering these inputs, individuals from institutions that offer the DrPH degree can further enhance the quality of public health practice training and make significant contributions to the overall advancement of the field of public health.

Can generative artificial intelligence pass the orthopaedic board examination?

BackgroundResident training programs in the US use the Orthopaedic In-Training Examination (OITE) developed by the American Academy of Orthopaedic Surgeons (AAOS) to assess the current knowledge of their residents and to identify the residents at risk of failing the Amerian Board of Orthopaedic Surgery (ABOS) examination. Optimal strategies for OITE preparation are constantly being explored. There may be a role for Large Language Models (LLMs) in orthopaedic resident education. ChatGPT, an LLM launched in late 2022 has demonstrated the ability to produce accurate, detailed answers, potentially enabling it to aid in medical education and clinical decision-making. The purpose of this study is to evaluate the performance of ChatGPT on Orthopaedic In-Training Examinations using Self-Assessment Exams from the AAOS database and approved literature as a proxy for the Orthopaedic Board Examination. Methods301 SAE questions from the AAOS database and associated AAOS literature were input into ChatGPT's interface in a question and multiple-choice format and the answers were then analyzed to determine which answer choice was selected. A new chat was used for every question. All answers were recorded, categorized, and compared to the answer given by the OITE and SAE exams, noting whether the answer was right or wrong. ResultsOf the 301 questions asked, ChatGPT was able to correctly answer 183 (60.8%) of them. The subjects with the highest percentage of correct questions were basic science (81%), oncology (72.7%, shoulder and elbow (71.9%), and sports (71.4%). The questions were further subdivided into 3 groups: those about management, diagnosis, or knowledge recall. There were 86 management questions and 47 were correct (54.7%), 45 diagnosis questions with 32 correct (71.7%), and 168 knowledge recall questions with 102 correct (60.7%). ConclusionsChatGPT has the potential to provide orthopedic educators and trainees with accurate clinical conclusions for the majority of board-style questions, although its reasoning should be carefully analyzed for accuracy and clinical validity. As such, its usefulness in a clinical educational context is currently limited but rapidly evolving. Clinical relevanceChatGPT can access a multitude of medical data and may help provide accurate answers to clinical questions.

Association Between Educational Resources and Pediatric Fellows' Mental Health Attitudes and Self-Reported Competence.

Children with chronic medical conditions (CCMC) have high rates of mental health (MH) conditions. This study examines associations between MH educational resources during fellowship and 3 dependent variables: fellows' interest, perceived responsibility, and self-reported competence in assessing MH concerns of CCMC. Subspecialty fellows taking the American Board of Pediatrics in-training examinations in February 2020 were invited to participate in a survey inquiring about MH educational resources. Logistic regression examined associations between MH educational resources and the 3 dependent variables, adjusting for demographics and program-level characteristics. Of the 97.7% (4216) fellows who responded, 3870 were included in analyses. About 37.5% reported formal MH teaching sessions; 36.7% reported on-site MH professionals engaged in teaching; 41.6% reported co-assessing patients with MH specialists; and 28.3% reported performance evaluation of their MH skills. All 4 resources were significantly and positively associated with self-reported competence in adjusted analyses, with odds ratios (OR) ranging from 1.28 (95% confidence interval (95% CI): 1.03-1.58) for formal teaching sessions to 2.14 (95% CI: 1.73-2.65) for performance evaluation. Resources were positively associated with the dependent variables in a "dose-response" pattern. Respondents who reported having all 4 educational resources compared to zero resources had an OR of 2.20 (95% CI: 1.74-2.78)for high MH interest, 3.18 (95% CI: 2.45-4.12)for high perceived responsibility, and 4.38 (95% CI: 3.43-5.60)for high self-reported competence CONCLUSIONS: Access to mental health educational resources was associated with higher interest, perceived responsibility, and self-reported competence; investing in these resources may improve fellows' skills in addressing the emotional needs of CCMC.

Assessment of ChatGPT’s performance on neurology written board examination questions

Background and objectivesChatGPT has shown promise in healthcare. To assess the utility of this novel tool in healthcare education, we evaluated ChatGPT’s performance in answering neurology board exam questions.MethodsNeurology board-style...

Evaluation of Preparation and Outcome of the Joint Admissions and Matriculation Board Examinations Among First Year Medical Students in Rivers State

Background: In most countries of the world, entrance into tertiary institution is regulated by statutory examining councils / bodies, after passing recommended examinations. The aim of this study was to evaluate the determinants of success at the Nigerian University Tertiary Matriculation Examination (UTME) among first year undergraduate medical students in Rivers State in the year 2022. Materials and Methods: A retrospective cross-sectional analytical study was carried out among first year undergraduate medical students in four universities. Data was collated and analysed using the Statistical Package for the Social Sciences (SPSS) version 20.0. Results: There were 219 (45.1%) males and 267 (54.9%) females, and their mean age was 19.45±2.80 years. Majority (n=372, 76.6%) of students prepared daily for at least 3-4 hours over at least 3 to 4 months (n=179, 36.8%) before passing their examinations. There were computer-related (134, 27.6%) and other issues. Only 257 (52.9%) students passed their UTME at first attempt. The number of UTME attempts reduces as average daily preparation hours increases; the higher the average daily examination preparation hours, the higher the chances of scoring above 200 in first attempt; the higher the number of months of active preparation, the lower the number of attempts at UTME; and these relationships were statistically significant (being p=0.000, p=0.009, and p=0.036 respectively). Conclusion: The determinants of success at the UTME of the JAMB among others are associated with students’ quality of input in preparing for the examinations. There are roles to be played at multiple levels to achieve needed improvement.

Do Local Socio-Economic Structures Determine the Spatial Distribution of Human Capital? Analysis of Connections for Rural Areas in Poland

The article has an empirical nature. The subject of detailed analysis is the variations in spatial distribution of human capital in rural areas of Poland and the analysis of the correlation of this phenomenon with local structures of the socio-economic development process. The diagnosis and assessment of variations in the spatial distribution of human capital were performed based on an author’s indicator—a synthetic measure of human capital level (HCI—human capital index). The characterisation of local socio-economic structures was based on the typology of rural areas according to Rural Development Monitoring (RDM 2014 and 2023). The study was conducted for rural areas in Poland defined by the Main Statistical Office based on the administrative criteria of rural and rural-urban municipalities. A total of 2172 municipalities were covered by the study. The data analysis was conducted spatially at the NUTS 5 level and comparatively at the NUTS 2 level for the years 2013–2018. The assumption was verified that the processes of human capital concentration in rural areas in Poland are related to local socio-economic structures of development processes, and the local structure factor that influences the existing differences is the degree of use of agricultural functions. The results of statistical tests positively verify this relationship as statistically significant. Moreover, the article provides strong arguments for shaping regional and rural policy and its implementation. The assumption about the need to change the approach to the study of rural space was positively verified; it is suggested to move away from analyses conducted at the level of the NUTS 2 region to the level of the NUTS 5 municipality. Research on rural areas makes sense only from a local perspective; it allows for a more accurate illustration of the specificity of local communities, revealing their development potentials and barriers, and, as a result, more effective programming of instruments supporting local development, dedicating specific support programs individually for each municipality, while the regional approach presents the state of differences too generally and may often lead to incorrect interpretation. In the empirical part of the article, taxonomic methods of hierarchy (patternless) and classification of multi-featured objects were used. As a result, each object (municipality) was assigned a synthetic measure—the relative human capital level index (HCI). Based on the HCI index, an ex-post hierarchical classification of municipalities was carried out. The main sources of data (diagnostic variables) for the construction of the HCI index were the Local Data Bank of the Central Statistical Office (BDL GUS), the national census of NSP 2011, the Ministry of Finance, the Ministry of Family and Social Policy, and District Examination Boards. The source of data on local socio-economic structures expressed based on the typology of rural areas according to the Rural Development Monitoring (RDM) methodology was the European Fund for the Development of Polish Villages (EFRWP).

AI did not pass Finnish plastic surgery written board examination

AI did not pass Finnish plastic surgery written board examination

Perceived Psychological Preparedness of the New Tertiary Curriculum Graduates in Taking the Professional Board Examination

This study was conducted to explore the perceived psychological preparedness of the selected graduates from the psychology department of the University of Cebu-Main Campus. It described the participants` preparedness in taking the psychometrician board examination. The way the participants adapt to the challenges experienced while reviewing, the experiences encountered by the participants through the factors, and the different coping strategies used to enhance and prepare for the upcoming board examination. The study utilized the qualitative method. There were sixteen (16) participants in this study, and they were selected through non-probability sampling, specifically purposive sampling. In data collection, an interview with a semi-structured interview guide has been used. In analyzing the qualitative data, thematic analysis by Boyatzis is being used. Codes, categories, and finding common themes were identified from the transcript of in-depth interviews. Eleven (11) emergent themes were created based on the participant's responses, which were classified under three (3) primary themes that provided answers to the sub-problems in this research. The emergent themes were extracted from the significant critical statements of the key participants. The description provided by the participants on their preparedness for taking the professional board examination, Factors that Influenced the Participants` Preparedness, has four (4) emergent themes categorized as: On Motivation; On Academic Factors; On Individual Factors; On Environmental Factors. For the challenges faced by the graduate participants about preparedness, the overarching theme is Challenges experienced by the Participants. The preparation has five (5) emergent themes: Lack of Academic Preparation, the Impact on Overall Health, High Expectations, Poor Study Habits, And Self-Confidence. The ways or strategies the participants used to cope with the difficulties faced in the examination preparation, the overarching theme is Participants’ Cope with the Challenges Met has two (2) emergent themes identified: By Ways of Addressing Challenges; By Seeking Social Support. The findings and recommendations derived from the study were used to improve the preparedness of the new tertiary curriculum graduates in taking the professional board examination.

Influencing factors of examiner: Examples from certificated orthodontists board examination

The rating result reflects not only the performance of the candidate but some extent of the examiner's preference. Examiner bias could be objective, which means it can't be changed by the examiner like gender, age, race, educational level, or professional experience. No study about examiner bias was performed in the dental education realm, especially in the orthodontic field. Therefore, this study aimed to figure out possible influencing factors in examiners from examples of the Taiwan Board of Orthodontist examination. The examiner groups comprised 29 males and 21 females selected from the certificated Taiwan Board of Orthodontists. Every examiner would receive a series of lectures about rating standards before the exam. The score data were collected from 2009 to 2019. As for the univariate regression model of the Taiwan Board of Orthodontist examination, the experienced examiner with a certification of more than 15 years tends to rate more leniently, but female examiners tend to rate harsher. The scores would increase with the examiner's age in both the univariate regression model of self-prepared and assigned cases. As for the multivariate model of self-prepared exams, the elder and the examiner who work in private practice clinics tend to rate more leniently. As for the multivariate model of the assigned case exam, the score would be only affected by age. However, further studies are necessary to determine the direct relation among these factors.

Performance evaluation of ChatGPT, GPT-4, and Bard on the official board examination of the Japan Radiology Society.

Herein, we assessed the accuracy of large language models (LLMs) in generating responses to questions in clinical radiology practice. We compared the performance of ChatGPT, GPT-4, and Google Bard using questions from the Japan Radiology Board Examination (JRBE). In total, 103 questions from the JRBE 2022 were used with permission from the Japan Radiological Society. These questions were categorized by pattern, required level of thinking, and topic. McNemar's test was used to compare the proportion of correct responses between the LLMs. Fisher's exact test was used to assess the performance of GPT-4 for each topic category. ChatGPT, GPT-4, and Google Bard correctly answered 40.8% (42 of 103), 65.0% (67 of 103), and 38.8% (40 of 103) of the questions, respectively. GPT-4 significantly outperformed ChatGPT by 24.2% (p < 0.001) and Google Bard by 26.2% (p < 0.001). In the categorical analysis by level of thinking, GPT-4 correctly answered 79.7% of the lower-order questions, which was significantly higher than ChatGPT or Google Bard (p < 0.001). The categorical analysis by question pattern revealed GPT-4's superiority over ChatGPT (67.4% vs. 46.5%, p = 0.004) and Google Bard (39.5%, p < 0.001) in the single-answer questions. The categorical analysis by topic revealed that GPT-4 outperformed ChatGPT (40%, p = 0.013) and Google Bard (26.7%, p = 0.004). No significant differences were observed between the LLMs in the categories not mentioned above. The performance of GPT-4 was significantly better in nuclear medicine (93.3%) than in diagnostic radiology (55.8%; p < 0.001). GPT-4 also performed better on lower-order questions than on higher-order questions (79.7% vs. 45.5%, p < 0.001). ChatGPTplus based on GPT-4 scored 65% when answering Japanese questions from the JRBE, outperforming ChatGPT and Google Bard. This highlights the potential of using LLMs to address advanced clinical questions in the field of radiology in Japan.

Are We Teaching Evidence-Based and Inclusive Practices in Gender-Affirming Care? Perspectives From Plastic Surgery In-Service Examinations.

Background Resident physicians take annual in-service examinations (ISEs) as part of continuing medical education, which set educational priorities, allow for formative feedback, and guide preparation for final board examinations. Gender-affirming care is provided in many specialties but has been an underrepresented area in medical education. Plastic surgeons provide a large portion of gender-affirming surgical care. Educational gaps in standardized ISEs may contribute to ongoing health care disparities for transgender and gender diverse people. Objective To evaluate the quality of content pertaining to gender-affirming surgery (GAS) on plastic surgery ISEs. Methods Plastic surgery ISEs from years 2012 to 2020 were accessed online through the American Council of Academic Plastic Surgeons website in June 2022. All 5 gender diverse authors analyzed examinations for the presence of GAS questions; identified questions were analyzed for quantity, organization based on content category, affirming language, and accuracy against current guidelines. Results Of 1959 ISE questions available for review, 11 GAS questions were identified for a total frequency of 0.56%. Most GAS questions (6 of 11, 55%) were miscategorized. Inappropriate language, including misgendering of patients, occurred in 7 of 11 (64%) questions. No questions discussed GAS beyond chest or genital surgery, or common variations of these procedures. Transgender identities were represented as only binary, with no mention of nonbinary or gender-fluid individuals. Conclusions Our study illustrates that there are significant gaps in educational content pertaining to gender-affirming care on plastic surgery ISEs.

A Cultural Transformation: Pakistani Girls Outperforming Boys in Education

In this paper, we highlight and present a nuanced picture of girls’ outperformance and boys’ underperformance in education in the urban centres of Pakistan. This is a very interesting and remarkable gender reverse trend in education performance in the dominated socio-cultural context of Pakistan. The paper takes into account the annual results of two examination boards: a) Board of Intermediate and Secondary Education (BISE) Peshawar and b) Board of Intermediate and Secondary Education (BISE) Faisalabad, Pakistan. Employing content analysis techniques, we have examined young boys’ and girls’ educational performance in secondary school certificate (SSC) and higher secondary schools certificate (HSSC) examinations from 2002 to 2016. The paper takes into account the first three positions as an indicator of outperformance. The paper simply highlights the trend of structure transformation and does not inquire about reasons for boys’ underperformance and girls’ outperformance. The study findings suggest that girls are outperforming boys in the urban centres of Pakistan.

An On-the-Go Platform for Continuing Medical Education in Radiation Oncology in Brazil

Brazil faces a shortage of radiation oncologists, especially in underserved regions. In 2022, there were 751 active Radiation Oncologists. Moreover, there is a constant need for continuing education, as Radiation Oncology is a complex specialty with continuous updates and technological advancements. Training requires specialized centers that can provide highly skilled mentors and expose trainees to modern radiotherapy techniques, which is expensive and depends upon significant investments. However, other strategies can also contribute to improving training in the country. Active methodologies are highly effective learning tools; therefore, we created a free gamified mobile app based on evidence-based comments from the National Board Exam to provide exam preparation and theory review. We retrieved National Board Exams from 2018 to 2021. Radiation Oncologists created detailed answers to questions, including the evidence supporting the rationale and linked references for further reading. The answers were all in Portuguese. Gamification was implemented to increase adherence, motivation, and engagement with the material. We evaluated the app's metrics and usage rates across the 2022 Board Exam Cohort. Launched in June 2022, the app registered until December 2022 278 active users. The mean age was 34.5 years (range 21 - 61). Most users were physicians (70.2%), but there were also medical students (2.6%), radiotherapists (14.6%), and physicists (12.7%). Users were distributed across all Brazilian regions and 81.5% (22/27) of the Brazilian States (including the Federal District). Four out of the five States without users were in the North, and one in the Northeast. Two unrepresented states were those without radiotherapy centers (Roraima and Amapá). The Southeast region and São Paulo State concentrated the majority of users (57% and 37.7%, respectively). In 2022, 87 physicians applied to the Radiation Oncology Board Certification Exams, and 31 (35.6%) were certified. Most successful applicants were app users (25/31; 80.6%). Time spent in the app varied across users, ranging from 0 to 92.4 hours in one month (mean of 4.16 hours). Radioteraquiz demonstrated high engagement with its on-the-go platform, ensuring practical, accurate, evidence-based information. Overall, the gamified active method shows the potential to improve learning effectiveness and promote continuing education, helping professionals stay current with the latest advancements in the field. In addition, it reached radiation oncologists across the country, increasing access to high-quality information for those away from reference centers and who are not proficient in English. Ultimately, this can improve patient care and outcomes.