BACKGROUND: Digital textbooks (DTs), in which students read dozens of paragraph clips and systematise their level of knowledge through new questions, can be an alternative for digital natives to consider. Developing DTs is required when teaching digital natives at undergraduate nursing schools. A scoping review is required to understand the current status of DTs in nursing education.
METHODS: The preliminary search has been conducted to check whether the results produced by PubMed (NCBI) were published in English within 10 years and related to DTs. This study includes research targeting undergraduate nursing students. Literature will be further searched using Embase (Elsevier), Cochrane Library and Cumulative Index to Nursing and Allied Health (CINAHL) databases. This scoping review will also consider quantitative, qualitative, and mixed research methods, texts and opinion documents; review studies; and pilot tests. The chosen studies will first be extracted based on the scoping review data extraction section of Joanna Briggs Institute to identify their general characteristics. DTs will be analysed based on the e-textbook framework: information goods, technology and stakeholders.
BACKGROUND: The Institutional Review Board of Nambu University, South Korea, approved this study for review exemption (approval number: 1041478-2022-HR-009). The results of this study will be disseminated through research results to nursing education institutions and hospitals. OPEN SCIENCE FRAMEWORK: https://doi.org/10.17605/OSF.IO/QS6WH.

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By extracting the acupoint names and their main indications from cases in Chinese Acupuncture and Moxibustion Therapy and Practical Acupuncture and Moxibustion, the acupoints and their main indications are represented in a reduced dimension, establishing an \"acupoint-indication\" linkage. Using complex network detection results (node degree values), the specificity of acupoints was assessed. The small-world characteristics of the \"acupoint-indication\" network are utilized to analyze the consistency of acupoint selection in acupuncture prescriptions and strategies to avoid redundant acupoints. The results show that the \"acupoint-indication\" network formed by both texts exhibited an approximate \"long-tail\" distribution, with a large number of node degree values concentrated between 0 and 4 000, while a few nodes have degree values exceeding 10 000. There are significant differences in the number and distribution of nodes with degree values> 10 000 between the two texts. Chinese Acupuncture and Moxibustion Therapy includes 11 acupoints with multiple edges across the body, whereas Practical Acupuncture and Moxibustion contains only 2 such acupoints, located in the lower limbs. Clinically, some acupoints have a broad therapeutic effect and appear in numerous prescriptions. The division of acupoints based on node degree values can coarsely evaluate the body region specificity of acupoints\' regulatory effects. The \"acupoint-indication\" network of Chinese Acupuncture and Moxibustion Therapy has a higher number of edges than that of Practical Acupuncture and Moxibustion, which might be related to the different historical contexts of the two texts. In the future, diagnostic and therapeutic patterns with historical continuity can be utilized to optimize acupuncture prescriptions.
提取《中国针灸治疗学》《实用针灸学》中病案的腧穴名称、主治病症，对穴位与主治病症进行降维表示，建立“穴-症”联系，采用复杂网络检测结果（节点度值）评估穴位的特异性，利用穴-症网络的“小世界”特性分析针灸处方选穴的一致性和避免冗余穴位的策略。结果显示，两本著作形成的“穴-症”网络均存在近似“长尾”的度分布，大量节点度值集中在0~4 000，少量节点的度值高达10 000以上。对于度值>10 000的节点出现了明显的个数与分布差异，《中国针灸治疗学》中包括11个具有多连边数的穴位，遍布全身，《实用针灸学》中仅有2个多连边数的穴位，位于下肢。临床中存在个别穴位具有广泛的治疗效应，出现在大量处方中，通过节点度值的穴位划分能够粗粒度地评估穴位调控作用的躯体区域特异性；《中国针灸治疗学》穴-症网络连边数高于《实用针灸学》穴-症网络，与2本著作不同的时代背景有关，今后可利用具有时代传承特征的诊疗规律优化针灸处方。.

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BACKGROUND: The American Society for Metabolic and Bariatric Surgery (ASMBS) textbook serves as a comprehensive resource for bariatric surgery, covering recent advancements and clinical questions. Testing artificial intelligence (AI) engines using this authoritative source ensures accurate and up-to-date information and provides insight in its potential implications for surgical education and training.
OBJECTIVE: To determine the quality and to compare different large language models\' (LLMs) ability to respond to textbook questions relating to bariatric surgery.
METHODS: Remote.
METHODS: Prompts to be entered into the LLMs were multiple-choice questions found in \"The ASMBS Textbook of Bariatric Surgery, second Edition. The prompts were queried into 3 LLMs: OpenAI\'s ChatGPT-4, Microsoft\'s Bing, and Google\'s Bard. The generated responses were assessed based on overall accuracy, the number of correct answers according to subject matter, and the number of correct answers based on question type. Statistical analysis was performed to determine the number of responses per LLMs per category that were correct.
RESULTS: Two hundred questions were used to query the AI models. There was an overall significant difference in the accuracy of answers, with an accuracy of 83.0% for ChatGPT-4, followed by Bard (76.0%) and Bing (65.0%). Subgroup analysis revealed a significant difference between the models\' performance in question categories, with ChatGPT-4\'s demonstrating the highest proportion of correct answers in questions related to treatment and surgical procedures (83.1%) and complications (91.7%). There was also a significant difference between the performance in different question types, with ChatGPT-4 showing superior performance in inclusionary questions. Bard and Bing were unable to answer certain questions whereas ChatGPT-4 left no questions unanswered.
CONCLUSIONS: LLMs, particularly ChatGPT-4, demonstrated promising accuracy when answering clinical questions related to bariatric surgery. Continued AI advancements and research is required to elucidate the potential applications of LLMs in training and education.

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BACKGROUND: The United States Medical Licensing Examination (USMLE) step 1 is one of the two examinations written after completion of the first two years (basic science stage) of medical school to be eligible to apply for residency training in the USA. A huge number and types of study materials are available to prepare for the exam which might confuse students choosing a resource. We investigated learning resources being used by the third and fifth-semester medical students and their association with academic performance. We also compared learning resources and exam scores of high-performing and low-performing students.
METHODS: Data collection was done using structured (quantitative study) and semi-structured (qualitative study) questionnaires during a face-to-face interview. This article is about the quantitative part which was designed as a correlational study. Single factor one-way analysis of variance (ANOVA), Pearson correlation coefficient test, T-test, and Fisher\'s exact test were used to analyze the data.
RESULTS: About half of all students used three or more commercial resources dealing with the same content. A weak negative correlation was observed between the number of commercial resources and the exam scores, especially when the number of these resources was three or more (r = -0.26). The mean exam score of textbook users was statistically significantly higher than the mean score of textbook non-users (p = 0.01). The usage of textbooks was statistically significantly higher in the cohort of top performers in comparison to the rest of the students (p = 0.006). In addition to less usage of textbooks, the mean number of review books was higher in the group of weakest students (2.84 versus 3.7; p = 0.75).
CONCLUSIONS: Most students did not use professional textbooks and about half used too many commercial review resources. While the former fact was significantly associated with poor academic performance, the later fact had weak negative correlation with exam score. Pedagogical interventions are urgently needed to make the right type of learning resources available by making professional textbooks more USMLE-oriented and helping the students choose the best and right number of resources for optimum academic performance. By fulfilling the observed needs of the students in this way, they might feel empowered because of self-determination which will motivate studies.

Previous research suggests that underrepresentation in medical curricula perpetuates inequities in healthcare. This study aimed to quantify the prevalence of human phenotypic diversity (e.g., skin tone, sex, body size, and age) across 11 commonly used anatomy atlases and textbooks in pre-clerkship medical education, published from 2015 to 2020. A systematic visual content analysis was conducted on 5001 images in which at least one phenotypic attribute was quantifiable. Anatomy images most prevalently portrayed light skin tones, males, persons with intermediate body sizes, and young to middle-aged adults. Of the 3883 images in which there was a codable skin tone, 81.2% (n = 3154) depicted light, 14.3% (n = 554) depicted intermediate, and 4.5% (n = 175) depicted dark skin tones. Of the 2384 images that could be categorized into a sex binary, 38.4% (n = 915) depicted females and 61.6% (n = 1469) depicted males. A male bias persisted across all whole-body and regional-body images, including those showing sex organs or those showing characteristics commonly associated with a specific sex (e.g. for males, facial hair and/or muscle hypertrophy). Within sex-specific contexts, darker skin was underrepresented, but male depictions displayed greater overall skin tone variation. Although most images could not be assigned to a body size or age category, when codable, these images overwhelmingly depicted adults (85.0%; 482 of 567) with smaller (34.7%; 93 of 268) or intermediate (64.6%; 173 of 268) body sizes. Ultimately, these outcomes provide reference metrics for monitoring ongoing and future efforts to address representation inequalities portrayed in anatomical imagery.