Educational effectiveness of multimedia scenarios in problem-based learning: a three-year comparative study among Japanese medical students

Educational effectiveness of multimedia scenarios in problem-based learning: a three-year comparative study among Japanese medical students | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Educational effectiveness of multimedia scenarios in problem-based learning: a three-year comparative study among Japanese medical students Yuriko Abe, Eric Hajime Jego, Shuichiro Maruoka, Hideto Nakajima, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8516677/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 19 You are reading this latest preprint version Abstract Background Problem-based learning (PBL) traditionally relies on text-based scenarios, but students often find it difficult to fully understand patient conditions on the basis of text alone. In this study, the educational effectiveness levels of multimedia and text-based PBL scenarios were compared in terms of improving students’ understanding of patient conditions and their ability to identify differential diagnoses. Methods From 2021 to 2023, third-year medical students at Nihon University School of Medicine participated in PBL sessions featuring three diseases, namely, Parkinson’s disease, lung cancer, and hypersensitivity pneumonitis, using either text-based or multimedia scenarios. Multimedia elements included medical interview videos, auscultation sounds, and computed tomography (CT) imaging videos. The participants included 121 students in 2021, 112 in 2022, and 114 in 2023. After each PBL session, the students completed a survey and submitted a report, which were analysed and categorized into the following three learning themes: symptoms, physical and diagnostic findings, and differential diagnoses. Results In the Parkinson’s disease scenario, which entailed the presentation of visible symptoms such as tremors and gait abnormalities, 83% of the students reported that they could understand the patient’s condition, significantly more than for lung cancer (58%) or hypersensitivity pneumonitis (53%). Introducing multimedia elements such as auscultation sounds and CT imaging videos significantly increased the proportion of students who explored differential diagnoses in treating lung cancer (p < 0.05) and hypersensitivity pneumonitis (p < 0.01). Moreover, the addition of multimedia medical interviews enhanced this effect, promoting more comprehensive diagnostic reasoning. Tutors also noted that multimedia scenarios helped students visualize patients more effectively. Conclusions Compared with traditional text-based formats, multimedia scenarios enhanced students’ understanding of patients and expanded their consideration of differential diagnoses. For diseases with prominent physical features such as Parkinson’s disease, multimedia medical interviews were particularly effective at helping students recognize clinical presentations. For diseases identified mainly through imaging or auscultation, such as lung cancer and hypersensitivity pneumonitis, multimedia elements enhanced diagnostic reasoning. These findings suggest that incorporating multimedia into PBL facilitates more realistic, engaging, and effective learning experiences in medical education. Trial Registration Not applicable. This study did not involve a clinical trial. Problem-based learning Multimedia scenarios Multimedia medical interview CT imaging videos Differential diagnosis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Background Problem-based learning (PBL) is a vital educational approach that stimulates student learning through the presentation of scenario-based problems; developed at McMaster University in the 1960s, PBL has since expanded to medical schools worldwide [ 1 ]. This approach is widely used in preclinical education in many medical schools as an effective method of acquiring practical knowledge. PBL offers numerous advantages, including encouraging the acquisition of general knowledge, promoting an in-depth approach to learning, and preparing students for the lifelong learning approaches necessary in medical professions [ 2 ]. However, PBL has not been extensively studied, especially among Asian students [ 3 ]. Additionally, to our knowledge, there are no existing studies focusing on examining the educational effectiveness of the use of multimedia videos in PBL in the Japanese language among Japanese medical students. To date, PBL tutorials have primarily involved the use of text-based scenarios. However, text-based scenarios often fail to immerse students, which prevents practical education. Thus, to enhance educational effectiveness, authentic cases are desirable [ 4 ]. In recent years, methods incorporating simulated patients and videos to enhance realism have been explored [ 5 – 8 ]. While producing patient-simulated videos incurs production costs, these videos offer advantages such as the ability to be repeatedly viewed and reused by many students. Videos provide a more realistic format than text does, thereby offering students a better context [ 9 ]. Despite the emphasis in the literature on the importance of appropriate cases and scenarios to yield a meaningful learning process, there has been little focus on how these tools actually function in the learning process [ 10 , 11 ]. Since the early 2000s, medical schools have been enhancing text-based PBL cases for students on the basis of computer- and web-based multimedia scenarios. The use of multimedia has been reported to render cases more engaging and improve self-directed learning [ 12 , 13 ]. There are also reports that using videos as case presentation tools enhances a more vivid depiction of the patient as a complete human rather than a set of written symptoms [ 6 ]. However, it has been reported that text is more effective as a source of information than video is for virtual patients in PBL [ 14 ], and the evaluation of the comparison between multimedia and text is inconsistent. Additionally, many universities still conduct PBL on the basis of text scenarios for students [ 11 ]. In this study, we developed easily repeatable multimedia scenarios closely resembling clinical situations. We conducted PBL sessions with medical students using multimedia scenarios instead of text-based scenarios and measured their educational effectiveness. The purpose of this study was to investigate the effect of using realistic multimedia elements in PBL. Methods Participants A survey targeting third-year students enrolled at the Nihon University School of Medicine (NUSM) in Japan from 2021 to 2023 was conducted with the same questions across all three cohorts. Students at NUSM are suitable representatives of average Japanese medical students for the following reasons. First, the curriculum is structured in accordance with normal standards set by Japanese governing institutions. Second, students at this institution typically rank average among Japanese medical schools in terms of standardized test results. Third, the internal examination results for the three cohorts included in this study were averaged and compared with those for cohorts from previous years. The curriculum at Nihon University School of Medicine includes basic medical education in the first two years, with clinical medicine education commencing in the third year. Clinical clerkships start in the fourth year, meaning that the students in this study had not yet experienced clinical clerkships. PBL in the third year is a compulsory subject, and all students must attend PBL sessions. Therefore, the students included in this study are representative of typical Japanese medical students. Initially, all the students in each of the three years were invited to participate in the study to obtain the most representative data possible. Exclusion criteria included absence on the day of the study, failure to submit a completed survey, and failure to submit the assignment. As the students progressed each year, the third-year cohort differed annually; however, the fixed curriculum ensured equivalent medical knowledge across the cohorts. All study participants provided informed consent, and the study design was approved by the Ethics Committee of Nihon University School of Medicine. Students and tutors were provided the option to opt out of the study. Students were assured that their participation or withdrawal from the study would have no effect whatsoever on their grades. Online PBL (e-PBL) Background and Scenario Development Face-to-face PBL sessions were previously conducted at Nihon University School of Medicine. However, owing to the COVID-19 pandemic, online classes began in 2020, and systematic e-PBL started in 2021. e-PBL is a new method, but its educational effectiveness has been reported [ 7 , 15 , 16 ]. The three PBL scenarios included in this study were Parkinson's disease, lung cancer, and hypersensitivity pneumonitis. All of these were written and used as text-based scenarios prior to this study. The academic calendar in Japan starts in April and ends in March. The years shown in Fig. 1 agree with the Japanese academic calendar. The first section, 2021, reveals that all third-year students studied each of the three scenarios in a text-based format from April 2021 to March 2022. The multimedia material creation initiative began after this academic year. Multimedia scenarios refer to content in which multiple forms of media are integrated, such as videos, audio, and images, to enhance learning and engagement. In 2022, as shown in the second section of Fig. 1 (Multimedia Scenario: Level 1), a variety of multimedia content was developed and used by specialists in each field. These included a multimedia medical interview video for the Parkinson’s disease case and computed tomography (CT) imaging in multimedia format for the lung cancer and hypersensitivity pneumonitis cases. The CT imaging videos were created to simulate actual imaging used in real medical records. Additionally, the hypersensitivity pneumonitis case included audible auscultation for students to listen to. Additional content was produced and implemented in 2023, as shown in the third section of Fig. 1 (Multimedia Scenario: Level 2). This section, 2023, indicates that the multimedia initiative was expanded to include multimedia medical interviews for all three cases. Teaching Materials: Multimedia Scenario Content Originally text-based, the use of these three scenarios required students to read the patient descriptions and imagine how the clinical pathologies would present. CT images depicting abnormalities in specific locations are shown, and sounds such as murmurs, crackles, and wheezes are described in the text. The Parkinson’s disease scenario was created by a neurologist, the lung cancer scenario was created by a thoracic surgeon, and the hypersensitivity pneumonitis scenario was created by a pulmonologist. All of the physicians were experienced senior physicians. In the multimedia scenario for hypersensitivity pneumonitis, the pulmonologist created an audio recording of auscultation sounds featuring fine crackles. Fine crackles are characteristic sounds of hypersensitivity pneumonitis. The multimedia scenarios for lung cancer and hypersensitivity pneumonitis included chest CT imaging videos with abnormal findings provided by a thoracic surgeon and a pulmonologist, respectively. For the multimedia scenarios of Parkinson’s disease, lung cancer, and hypersensitivity pneumonitis, we developed multimedia medical interviews. Medical education specialists designed the scenarios on the basis of physicians’ input, and the medical interviews were filmed in the outpatient consultation rooms of Nihon University Itabashi Hospital. The physicians acted as doctors, while professional actors played the role of patients. The actor portraying a Parkinson’s disease patient was trained by a neurologist in advance to accurately depict hand tremors, the characteristic gait, distinctive speech patterns, and facial expressions. The actor who played a lung cancer patient was instructed by a thoracic surgeon on how to properly simulate coughing. The actor portraying a patient with hypersensitivity pneumonitis received prior guidance from a pulmonologist on how to express breathlessness and coughing. A video specialist used three video cameras to simultaneously record the doctor, the patient, and the entire outpatient setting. Each multimedia medical interview was then edited into a video of approximately 10 minutes each. e-PBL PBL sessions were conducted targeting third-year medical students. Students and tutors joined e-PBL via a web conferencing tool. The students were divided into 16 groups, with one tutor assigned to each group. The scenario content remained the same each year, with a focus on Parkinson's disease, lung cancer, and hypersensitivity pneumonitis. Students discussed the scenario content and collaboratively documented their discussions using online presentation files. Each PBL session lasted for 60 minutes and was held twice a week for each case. Role of Tutors During the PBL sessions, tutors were responsible for taking attendance and facilitating student discussion by observing and occasionally offering advice and prompts as needed. Tutors were randomly selected among faculty members of the medical school. Tutors received explanations of the scenarios in advance and provided support to students during PBL sessions. Post-PBL Surveys and Assignments After completing the PBL sessions, the students were asked to submit a survey on their opinions of the PBL multimedia program in 2023 (Table S1 ). The deadline for submission was the following day. Their responses to the survey questions were analysed and included as part of the data collected in this research study. The tutors also had the option to respond to surveys about their opinions of the PBL case multimedia. The tutors could choose to respond anonymously or provide their names (Table S2). The surveys were conducted via the use of online forms. The students were also required to submit a PBL assignment the following day. Both the assignments and the surveys were conducted using the same online form system from 2021 to 2023. These assignments included interpretations of the cases, differential diagnoses, and other relevant details. Students were required to freely select two topics that they considered most important about the PBL case. They were asked to investigate each of the two selected topics and include their findings as part of their PBL assignment. To facilitate the analysis for this study, we classified these two selected topics into the following three categories: symptoms, physical and diagnostic findings, and differential diagnoses. Statistical Analysis The R function binom.test (version 4.3.2) was chosen for McNemar’s exact test (Tables S3 and S4, Table 1 , and Fig. 2 ). The PROC FREQ of SAS ver. 9.4 was used for Fisher’s exact test (Tables S5 and S6, Table 2 , and Fig. 3 ). We conducted a statistical analysis of the topics selected by the students, categorizing them into the following three groups: symptoms, physical and diagnostic findings, and differential diagnoses. Each student was required to select two topics, allowing for duplication among these three categories. On the basis of the relationships between the selected topics and each category, the following three selection patterns were identified: "0 topics," "1 topic," and "2 topics", that were treated as ordinal categorical data and used as the dependent variable. Furthermore, the academic year to which each student belonged (2021, 2022, or 2023) was treated as a categorical independent variable, and an ordinal logistic regression analysis was conducted. The right side of Table S7 provides the estimated odds ratios, their 95% confidence intervals, and the corresponding p values obtained from this analysis. The same ordinal logistic regression analysis was applied to the other two categories, i.e., physical and diagnostic findings (Table S8) and differential diagnoses (Table S9). The PROC LOGISTIC option in SAS ver. 9.4 (SAS Institute Inc., Cary, NC, USA) was used for the analyses (Tables S7-S15, Tables 3 – 5 , and Figs. 4 – 6 ). We used the Holm adjustment to control for multiple comparisons. A significant difference was defined as an adjusted p value less than 0.05 according to Holm's method. Results Student Opinions on the Multimedia Medical Interview Among the students in 2023, 109 responded to the survey for all three diseases, as detailed in Table 1 and Fig. 2 . With respect to Parkinson's disease, 83% of the students in 2023 responded as follows: "I can understand the patient’s condition". In contrast, for lung cancer and hypersensitivity pneumonitis, only 58% and 53% of the students, respectively, answered that they could understand the patient’s condition. Table 1 Student responses to the medical interview video in 2023 Variables Parkinson’s disease, n (%) Lung cancer, n (%) Hypersensitivity pneumonitis, n (%) The number of respondents to the questionnaire 109 (100) 109 (100) 109 (100) A) I could understand the patient’s condition. 91 (83) 63 (58) 58 (53) B) There was not enough discussion time. 20 (18) 5 (5) 9 (8) The number of students who responded that they could understand the patient’s condition for Parkinson's disease was greater than the number of students who understood lung cancer (p < 0.001) and hypersensitivity pneumonitis (p < 0.001) (Fig. 2 , Table S4). In all the cases, few students answered that "there was not enough discussion time". Most students felt that the allocated discussion time was adequate. Tutors' Responses to Multimedia Medical Interviews Twelve tutors answered the survey on Parkinson's disease, 15 tutors answered the survey on lung cancer, and 14 tutors answered the survey on hypersensitivity pneumonitis. With respect to Parkinson's disease, more than 90% of the tutors answered the following: " Students can understand the patient’s condition." In contrast, this proportion was only 57% for the hypersensitivity pneumonitis scenario (Table 2 , Fig. 3 and Table S6). No tutors responded that “it was too difficult for the students" (Table 2 ). Table 2 Tutor responses to medical interview videos in 2023 Variables Parkinson’s disease, n (%) Lung cancer, n (%) Hypersensitivity pneumonitis, n (%) The number of respondents to the questionnaire 12 (100) 15 (100) 14 (100) A) Students could understand the patient’s condition. 11 (92) 12 (80) 8 (57) B) Students could understand the skills and attitudes required for medical interviews. 3 (25) 7 (47) 5 (36) C) It was too difficult for the students. 0 (0) 0 (0) 0 (0) D) It was not different from the text-based scenario. 1 (8) 1 (7) 2 (14) E) There was not enough discussion time. 1 (8) 1 (7) 4 (29) Detailed Analysis of Student Reports Revealed What Types of Topics Students Considered Interesting The students chose two topics that they considered important, which they researched and described in their reports. The proportions of students selecting 0, 1, or 2 topics within each category (symptoms, physical and diagnostic findings, and differential diagnosis) are provided in Tables 3 – 5 . The statistical analyses of students’ topic selections are shown in Fig. 4 for Parkinson’s disease, Fig. 5 for lung cancer, and Fig. 6 for hypersensitivity pneumonitis. As revealed in the reports on Parkinson’s disease (Fig. 4 , Table 3 ), students selected topics from the symptoms category more frequently, whereas fewer students selected topics from differential diagnoses category compared with the lung cancer category (Fig. 5 ) and hypersensitivity pneumonitis (Fig. 6 ) cases. The tendencies for more students to select symptoms and fewer to select differential diagnoses remained unchanged, with no significant differences observed after the transition from text-based to multimedia scenarios. In the Parkinson's disease reports (Fig. 4 , Table 3 ), students selected topics within the symptoms category more often compared with the lung cancer (Fig. 5 ) or hypersensitivity pneumonitis reports (Fig. 6 ), with a higher proportion of students selecting 2 topics since 2021, even when the scenario was text-based. This trend did not change despite the introduction of multimedia medical interviews. The numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted p values obtained via Holm's method: * p < 0.05, ** p < 0.01, *** p < 0.001 Table 3 Parkinson’s disease: Student-selected topics Topic Year 2021, n (%) 2022, n (%) 2023, n (%) Total number of students 121 (100) 112 (100) 114 (100) Symptoms Topic choice patterns 2 topics 73 (60) 73 (65) 67 (59) 1 topic 41 (34) 34 (30) 39 (34) 0 topics 7 (6) 5 (4) 8 (7) Physical and diagnostic findings Topic choice patterns 2 topics 5 (4) 2 (2) 1 (1) 1 topic 29 (24) 23 (21) 29 (25) 0 topics 87 (72) 87 (78) 84 (74) Differential diagnosis Topic choice patterns 2 topics 0 (0) 0 (0) 2 (2) 1 topic 16 (13) 17 (15) 20 (18) 0 topics 105 (87) 95 (85) 92 (81) The results for the lung cancer reports are shown in Fig. 5 , Table 4 . Changing the CT-based scenarios from text to multimedia in 2022 increased the number of students who investigated differential diagnoses (p = 0.029 (2022 vs. 2021)) (Table S12). Furthermore, changing the medical interview from text to multimedia in 2023 increased the number of students who investigated differential diagnoses (p < 0.001 (2023 vs. 2021), p = 0.038 (2023 vs. 2022)) (Table S12). Consequently, the number of students who investigated symptoms decreased (p = 0.035 (2023 vs. 2021)) (Table S10), while the number of students who investigated physical and diagnostic findings also decreased (p < 0.001 (2023 vs. 2021), p = 0.005 (2023 vs. 2022)) (Table S11). The numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted p values obtained via Holm's method: * p < 0.05, ** p < 0.01, *** p < 0.001 Table 4 Lung cancer: Student-selected topics Topic Year 2021, n (%) 2022, n (%) 2023, n (%) Total number of students 122 (100) 111 (100) 114 (100) Symptoms Topic choice patterns 2 topics 31 (25) 14 (13) 17 (15) 1 topic 63 (52) 67 (60) 58 (51) 0 topics 28 (23) 30 (27) 39 (34) Physical and diagnostic findings Topic choice patterns 2 topics 1 (1) 0 (0) 0 (0) 1 topic 33 (27) 27 (24) 10 (9) 0 topics 88 (72) 84 (76) 104 (91) Differential diagnosis Topic choice patterns 2 topics 20 (16) 22 (20) 34 (30) 1 topic 44 (36) 56 (50) 58 (51) 0 topics 58 (48) 33 (30) 22 (19) In the hypersensitivity pneumonitis reports (Fig. 6 , Table 5 ), changing the auscultation-based scenario from text to multimedia and the CT-based scenario from text to multimedia in 2022 increased the number of students who investigated differential diagnoses (p = 0.008 (2022 vs. 2021)) (Table S15). Furthermore, changing medical interviews from text to multimedia in 2023 increased the number of students who investigated differential diagnoses (p < 0.001 (2023 vs. 2021)) (Table S15). Consequently, the number of students who investigated symptoms decreased (p < 0.001 (2022 vs. 2021), p < 0.001 (2023 vs. 2021)) (Table S13). The numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted p values obtained via Holm's method: * p < 0.05, ** p < 0.01, *** p < 0.001 Table 5 Hypersensitivity pneumonitis: Study selected topics Topic Year 2021, n (%) 2022, n (%) 2023, n (%) Total number of students 121 (100) 108 (100) 110 (100) Symptoms Topic choice patterns 2 topics 6 (5) 1 (1) 0 (0) 1 topic 36 (30) 7 (6) 6 (5) 0 topics 79 (65) 100 (93) 104 (95) Physical and diagnostic findings Topic choice patterns 2 topics 5 (4) 6 (6) 9 (8) 1 topic 46 (38) 42 (39) 34 (31) 0 topics 70 (58) 60 (56) 67 (61) Differential diagnosis Topic choice patterns 2 topics 42 (35) 56 (52) 63 (57) 1 topic 54 (45) 41 (38) 36 (33) 0 topics 25 (21) 11 (10) 11 (10) Therefore, compared with text-based scenarios, multimedia scenarios could help students better understand patients’ conditions in diseases such as Parkinson’s disease, who present with visible symptoms such as tremors and the characteristic gait. In contrast, for diseases such as lung cancer and hypersensitivity pneumonitis, where physical findings are less apparent but abnormalities are detected through auscultation or imaging, the multimedia scenarios encouraged students to consider a broader range of differential diagnoses. Discussion In PBL, students identify their learning needs, engage in self-directed learning, and reflect on their acquired knowledge and learning strategies [ 17 ]. Building on this framework, our study demonstrated that compared with the scenarios for the other two diseases, the Parkinson’s disease multimedia scenario was more helpful in enabling students to better understand the patient’s condition. This likely occurs because Parkinson’s disease presents more physical characteristics, such as distinctive walking patterns, speech, and tremors, making the video material more effective at conveying the patient’s condition. In the multimedia scenario related to Parkinson's disease in the 2023 academic year, 83% of the students responded as follows "I can understand the patient’s condition". This proportion was greater than those in the multimedia scenarios for lung cancer and hypersensitivity pneumonitis. The proportion of tutors who responded that "students could understand the patient’s condition" exhibited a similar trend to that of the students across all three diseases, and the differences were not statistically significant. The lack of statistical significance is likely due to the small number of tutors. In contrast, converting the CT imaging video in the lung cancer scenario and both auscultation and the CT imaging video in the hypersensitivity pneumonitis scenario from text-based descriptions to a multimedia format increased the proportion of students investigating differential diagnoses. In the hypersensitivity pneumonitis scenario, fine crackles were included in the auscultation recordings, and in both the lung cancer and hypersensitivity pneumonitis scenarios, CT image videos were converted into multimedia elements, making the scenarios more realistic. Additionally, in the lung cancer scenario, changing the medical interview to a multimedia format increased the number of students investigating differential diagnoses. By incorporating multimedia elements, students could engage more deeply with the cases and investigate differential diagnoses more strategically. Strategically investigating differential diagnoses suggests that students were thinking more critically about the scenarios and engaging in more in-depth learning to reach a diagnosis instead of simply examining symptoms or physical and diagnostic findings. Considering differential diagnoses is a key objective of PBL and contributes to the evolution of clinical reasoning [ 18 ]. However, in the case of Parkinson's disease, there was no significant difference in the number of students in the differential diagnosis category when the scenario was changed from a text-based format to a multimedia medical interview. The text-based scenario provided detailed descriptions of characteristic features such as gait, speech patterns, and tremors, whereas the multimedia medical interview emphasized these features through visual representation. Therefore, in both scenarios, it is likely that students were likely to investigate the distinctive symptoms and physical and diagnostic findings. Furthermore, since the scenario made it easier for students to recognize the characteristics of Parkinson's disease, the diagnosis may have been more straightforward, resulting in fewer students investigating differential diagnoses. It is acknowledged that realistic scenarios enhance student motivation, ultimately increasing the effectiveness of PBL. The video cases were generally perceived as a valuable stimulus for group discussions in PBL [ 19 ]. In addition, it is important to provide education that enables students to examine patients with diseases that are commonly seen in their local communities [ 20 ]. In other words, to maximize the effectiveness of the PBL approach, cases must be tailored to the specific sociocultural, economic, and educational contexts of the given region. In particular, since medical interviews vary by country because of language differences, videos should be prepared in the students' native languages. In the multimedia medical interviews created for this study, patients were portrayed by trained actors resembling real patients, and physicians were portrayed by specialists, with filming taking place in hospitals. In other words, we created multimedia-simulated patients who were very realistic. To our knowledge, this is the first report of e-PBL based on realistic multimedia-simulated patients in Japan. Therefore, we believe that this study is novel and valuable, as it provides evidence to support the idea that multimedia can play a role in enhancing the ability of students to consider various differential diagnoses. It is still debated whether text-based or multimedia scenarios are more effective for PBL. Previous studies have revealed that compared with video cases, many students find triggers in paper cases more appropriate for deriving learning objectives and helpful for improving their thinking process. In contrast, facilitators found no significant difference between the effectiveness of the two approaches [ 21 ]. Another study indicated that the use of video reduced the pace of PBL and impeded students' ability to review and critically appraise the presented information [ 15 ]. In this study, an approximately equal proportion of students and tutors reported that multimedia scenarios were helpful in understanding the patient’s condition. Only a small number of both students and tutors indicated that there was not enough discussion time. Therefore, the potential drawback of multimedia scenarios reducing the pace of the PBL was not a significant issue. In contrast, incorporating multimedia, such as videos, into medical education materials can support and enhance learning [ 22 ]. PBL with video triggers more interest and is preferred over paper cases [ 23 ]. Video medical interviews help students visualize patients but require significant time and cost to produce [ 24 ]. Therefore, it is preferable to present video medical interviews only when they are highly effective. The advantage of multimedia for auscultation and imaging findings is that they can be produced more easily than full multimedia medical interviews can. Therefore, in terms of cost effectiveness, the use of multimedia such as audio clips and video imaging can be feasible for a wide range of educational institutions. In this study, the effect of multimedia varied depending on the content of the scenario. For diseases with few prominent physical features, such as lung cancer and hypersensitivity pneumonitis, ensuring realistic auscultation findings and CT imaging resulted in better differential diagnoses. Furthermore, visualizing the medical interview further enhanced the students’ ability to independently consider differential diagnoses. For diseases with significant physical features, such as Parkinson's disease, making medical interviews more realistic made it easier for students to understand patients and led to greater learning effectiveness. In other words, this study revealed that the educational effect of making scenarios realistic in terms of physical features varied depending on the characteristics of the disease. Scenarios that effectively presented physical features increased the ability of students to visualize the patient’s conditions, a crucial element in case comprehension. Additionally, for diseases with few physical features, scenarios involving multimedia auscultation and imaging findings are cost-effective and highly impactful. One limitation of this study is the small number of PBL sessions in which multimedia scenarios were incorporated. Furthermore, the multimedia scenarios were limited to three diseases. In the future, it would be beneficial to conduct additional studies with multimedia scenarios for various diseases. Conclusions In this study, the educational effectiveness of multimedia scenarios in PBL was evaluated by comparing them with traditional text-based scenarios. Our findings suggest that multimedia scenarios enhanced students' understanding of patient conditions and encouraged broader and more in-depth consideration of differential diagnoses. For diseases with distinctive physical manifestations, such as Parkinson’s disease, multimedia medical interviews were particularly effective at helping students understand key clinical characteristics. The majority of both students and tutors reported that multimedia scenarios made it easier for students to understand the patient’s condition. In diseases with abnormal findings on auscultation or imaging, such as lung cancer and hypersensitivity pneumonitis, integrating multimedia elements such as auscultation sounds and CT imaging video led to a greater emphasis on diagnostic reasoning. This tendency was amplified when the medical interview was also presented in a multimedia format. Despite their clear advantages, the implementation of multimedia scenarios remains limited. Expanding their application to a broader range of medical conditions and assessing their long-term impact on clinical reasoning will be important for refining PBL methodologies in medical education. Abbreviations PBL, Problem-based learning; CT, computed tomography Declarations Ethics Approval and Consent to Participate This study was conducted in accordance with the principles of the Declaration of Helsinki and established ethical principles for research involving human participants. The study protocol was approved by the Nihon University School of Medicine Ethics Committee (Approval No. 2024-21; Approval No. Irinsho 2024-21). Informed consent was obtained using an opt-out approach. Students were assured that their participation or withdrawal from the study would have no effect whatsoever on their grades. All collected data were anonymized and stored securely. Consent for Publication Not applicable. No individual participant data or identifying images are included in this article. Availability of Data and Materials The datasets generated and analyzed in this study are not publicly available to protect participant confidentiality but can be obtained from the corresponding author upon reasonable request. Competing Interests The authors declare that they have no competing interests. Funding This study was supported by grants from JSPS KAKENHI Grant Number 22K10425 (Y.A.). Author Contributors Y.A. wrote the manuscript, and E.H.J., S.M., H.N., S.S., S.M., and C.H. edited and critically reviewed the manuscript. Y.A., S.M., H.N. and N.O. created the multimedia scenarios. Y.A., S.M., H.N., S.S., Y.U., T.T., and C.H. managed the PBL. Y.A., S.M., H.N., S.M., and C.H. conceived the study. Y.A. and T.T. performed the statistical analyses. Y.A. raised funds. All the authors have read and agreed to the published version of the manuscript. 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Effects of an online problem-based learning program on sexual health care competencies among oncology nurses: a pilot study. J Contin Educ Nurs. 2014;45:393-401. Hmelo-Silver CE. Problem-based learning: what and how do students learn? Educational Psychology Review. 2004;16:235-66. Groves M, Scott I, Alexander H. Assessing clinical reasoning: a method to monitor its development in a PBL curriculum. Med Teach. 2002;24:507-15. de Leng B, Dolmans D, van de Wiel M, Muijtjens A, van der Vleuten C. How video cases should be used as authentic stimuli in problem-based medical education. Med Educ. 2007;41:181-8. Bestetti RB, Couto LB, Romão GS, Araújo GT, Restini CB. Contextual considerations in implementing problem-based learning approaches in a Brazilian medical curriculum: the UNAERP experience. Med Educ Online. 2014;19:24366. Ghanchi NK, Khan S, Afridi A, Sajid S, Afzal S, Ahmed I, et al. Video or paper for delivery of problem-based learning cases? Med Educ. 2013;47:1131. Ruiz JG, Mintzer MJ, Issenberg SB. Learning objects in medical education. Med Teach. 2006;28:599-605. Chan LK, Patil NG, Chen JY, Lam JC, Lau CS, Ip MS. Advantages of video trigger in problem-based learning. Med Teach. 2010;32:760-5. Amoako-Sakyi D, Amonoo-Kuofi H. Problem-based learning in resource-poor settings: lessons from a medical school in Ghana. BMC Med Educ. 2015;15:221. Additional Declarations No competing interests reported. Supplementary Files SupplementaryTablessubmitver.2.docx Additional Files Table S1. Student opinions on multimedia medical interviews Table S2. Tutor opinions on the multimedia medical interview Table S3.Distribution of student responses to the medical interview video in 2023 (N = 109) Table S4.Statistical analysis of student responses to the medical interview video in 2023 Table S5. Distribution of tutor responses to medical interview videos in 2023 Table S6. Statistical analysis of tutor responses to medical interview videos in 2023 Table S7. Statistical analysis of Parkinson’s disease (symptoms) Table S8. Statistical analysis of Parkinson’s disease (physical and diagnostic findings) Table S9. Statistical analysis of Parkinson’s disease (differential diagnosis) Table S10.Statistical analysis of lung cancer (symptoms) Table S11.Statistical analysis of lung cancer (physical and diagnostic findings) Table S12. Statistical analysis of lung cancer differential diagnosis Table S13. Statistical analysis of hypersensitivity pneumonitis (symptoms) Table S14. Statistical analysis of hypersensitivity pneumonitis (physical and diagnosticfindings) Table S15. Statistical analysis of hypersensitivity pneumonitis (differential diagnosis) Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 14 May, 2026 Reviews received at journal 13 May, 2026 Reviews received at journal 12 May, 2026 Reviews received at journal 11 May, 2026 Reviewers agreed at journal 11 May, 2026 Reviewers agreed at journal 11 May, 2026 Reviews received at journal 10 May, 2026 Reviewers agreed at journal 10 May, 2026 Reviewers agreed at journal 09 May, 2026 Reviewers agreed at journal 07 May, 2026 Reviews received at journal 06 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 06 May, 2026 Reviewers invited by journal 06 May, 2026 Editor invited by journal 04 May, 2026 Editor assigned by journal 13 Jan, 2026 Submission checks completed at journal 13 Jan, 2026 First submitted to journal 13 Jan, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8516677","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":639740481,"identity":"149208ae-81ae-4ec4-979b-0e41fe44757e","order_by":0,"name":"Yuriko 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03:54:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8516677/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8516677/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":109279132,"identity":"cc80a856-ada0-49d7-9e2a-ce10d21b1ebb","added_by":"auto","created_at":"2026-05-14 16:17:20","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":326556,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of problem-based learning scenarios for 2021 to 2023: Transition from text-basedto multimedia approaches.\u003c/p\u003e","description":"","filename":"floatimage1.png","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/9a700942e1ee2cecef1c22e5.png"},{"id":109279134,"identity":"aac88e43-8f6f-40ad-9256-ea5a2fe65144","added_by":"auto","created_at":"2026-05-14 16:17:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":31389,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of students who responded \"I can understand the patient’s condition\" in 2023. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt;0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt;0.001\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/7eec358ed7b8b909153ce97a.png"},{"id":109296353,"identity":"b61231bd-b2ee-4c81-89b8-8be7ec7d4227","added_by":"auto","created_at":"2026-05-15 08:46:36","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":29588,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of tutors who responded that \"students can understand the patient’s condition\" in 2023. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt;0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt;0.001\u003c/p\u003e","description":"","filename":"floatimage3.png","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/2fc6cf4ccc6c3d98029c3243.png"},{"id":109279136,"identity":"bf931953-f015-4781-98c3-b5ba64ddffda","added_by":"auto","created_at":"2026-05-14 16:17:20","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":107243,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of students selecting 0, 1 or 2 topics for the Parkinson's disease scenario.\u003c/p\u003e\n\u003cp\u003eThe numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt;0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt;0.001\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/242593cb1b43b13956b321e9.png"},{"id":109279137,"identity":"29c1297c-5a39-4ba2-8098-9fb6597acda0","added_by":"auto","created_at":"2026-05-14 16:17:20","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":109813,"visible":true,"origin":"","legend":"\u003cp\u003ePercentage of students selecting 0, 1 or 2 topics for the lung cancer scenario.\u003c/p\u003e\n\u003cp\u003eThe numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e \u0026lt;0.05, **\u003cem\u003e p\u003c/em\u003e \u0026lt;0.01, ***\u003cem\u003e p\u003c/em\u003e \u0026lt;0.001\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/6145e259addcedb1387700e9.png"},{"id":109296375,"identity":"b2c3ebb7-ee1f-4e03-8400-32b3acc9e12a","added_by":"auto","created_at":"2026-05-15 08:46:43","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":715212,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/5efdd0ff-f021-4c99-8caa-a2f8461c02e0.pdf"},{"id":109296576,"identity":"30bee1f0-23a9-4602-a202-4b73843d710c","added_by":"auto","created_at":"2026-05-15 08:48:17","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":28766,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eAdditional Files\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S1. \u003c/strong\u003eStudent opinions on multimedia medical interviews\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S2. \u003c/strong\u003eTutor opinions on the multimedia medical interview\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S3.\u003c/strong\u003eDistribution of student responses to the medical interview video in 2023 (N = 109)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S4.\u003c/strong\u003eStatistical analysis of student responses to the medical interview video in 2023\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S5.\u003c/strong\u003e Distribution of tutor responses to medical interview videos in 2023\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S6.\u003c/strong\u003e Statistical analysis of tutor responses to medical interview videos in 2023\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S7.\u003c/strong\u003e Statistical analysis of Parkinson’s disease (symptoms)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S8.\u003c/strong\u003e Statistical analysis of Parkinson’s disease (physical and diagnostic findings)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S9.\u003c/strong\u003e Statistical analysis of Parkinson’s disease (differential diagnosis)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S10.\u003c/strong\u003eStatistical analysis of lung cancer (symptoms)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S11.\u003c/strong\u003eStatistical analysis of lung cancer (physical and diagnostic findings)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S12.\u003c/strong\u003e Statistical analysis of lung cancer differential diagnosis\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S13.\u003c/strong\u003e Statistical analysis of hypersensitivity pneumonitis (symptoms)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S14.\u003c/strong\u003e Statistical analysis of hypersensitivity pneumonitis (physical and diagnosticfindings)\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable S15.\u003c/strong\u003e Statistical analysis of hypersensitivity pneumonitis (differential diagnosis)\u003c/p\u003e","description":"","filename":"SupplementaryTablessubmitver.2.docx","url":"https://assets-eu.researchsquare.com/files/rs-8516677/v1/a8d09af90f2d877ccb841684.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Educational effectiveness of multimedia scenarios in problem-based learning: a three-year comparative study among Japanese medical students","fulltext":[{"header":"Background","content":"\u003cp\u003eProblem-based learning (PBL) is a vital educational approach that stimulates student learning through the presentation of scenario-based problems; developed at McMaster University in the 1960s, PBL has since expanded to medical schools worldwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. This approach is widely used in preclinical education in many medical schools as an effective method of acquiring practical knowledge. PBL offers numerous advantages, including encouraging the acquisition of general knowledge, promoting an in-depth approach to learning, and preparing students for the lifelong learning approaches necessary in medical professions [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. However, PBL has not been extensively studied, especially among Asian students [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Additionally, to our knowledge, there are no existing studies focusing on examining the educational effectiveness of the use of multimedia videos in PBL in the Japanese language among Japanese medical students.\u003c/p\u003e \u003cp\u003eTo date, PBL tutorials have primarily involved the use of text-based scenarios. However, text-based scenarios often fail to immerse students, which prevents practical education. Thus, to enhance educational effectiveness, authentic cases are desirable [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In recent years, methods incorporating simulated patients and videos to enhance realism have been explored [\u003cspan additionalcitationids=\"CR6 CR7\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. While producing patient-simulated videos incurs production costs, these videos offer advantages such as the ability to be repeatedly viewed and reused by many students. Videos provide a more realistic format than text does, thereby offering students a better context [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Despite the emphasis in the literature on the importance of appropriate cases and scenarios to yield a meaningful learning process, there has been little focus on how these tools actually function in the learning process [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Since the early 2000s, medical schools have been enhancing text-based PBL cases for students on the basis of computer- and web-based multimedia scenarios. The use of multimedia has been reported to render cases more engaging and improve self-directed learning [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. There are also reports that using videos as case presentation tools enhances a more vivid depiction of the patient as a complete human rather than a set of written symptoms [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. However, it has been reported that text is more effective as a source of information than video is for virtual patients in PBL [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], and the evaluation of the comparison between multimedia and text is inconsistent. Additionally, many universities still conduct PBL on the basis of text scenarios for students [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn this study, we developed easily repeatable multimedia scenarios closely resembling clinical situations. We conducted PBL sessions with medical students using multimedia scenarios instead of text-based scenarios and measured their educational effectiveness. The purpose of this study was to investigate the effect of using realistic multimedia elements in PBL.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eParticipants\u003c/h2\u003e \u003cp\u003eA survey targeting third-year students enrolled at the Nihon University School of Medicine (NUSM) in Japan from 2021 to 2023 was conducted with the same questions across all three cohorts. Students at NUSM are suitable representatives of average Japanese medical students for the following reasons. First, the curriculum is structured in accordance with normal standards set by Japanese governing institutions. Second, students at this institution typically rank average among Japanese medical schools in terms of standardized test results. Third, the internal examination results for the three cohorts included in this study were averaged and compared with those for cohorts from previous years.\u003c/p\u003e \u003cp\u003eThe curriculum at Nihon University School of Medicine includes basic medical education in the first two years, with clinical medicine education commencing in the third year. Clinical clerkships start in the fourth year, meaning that the students in this study had not yet experienced clinical clerkships. PBL in the third year is a compulsory subject, and all students must attend PBL sessions. Therefore, the students included in this study are representative of typical Japanese medical students.\u003c/p\u003e \u003cp\u003eInitially, all the students in each of the three years were invited to participate in the study to obtain the most representative data possible. Exclusion criteria included absence on the day of the study, failure to submit a completed survey, and failure to submit the assignment. As the students progressed each year, the third-year cohort differed annually; however, the fixed curriculum ensured equivalent medical knowledge across the cohorts. All study participants provided informed consent, and the study design was approved by the Ethics Committee of Nihon University School of Medicine. Students and tutors were provided the option to opt out of the study. Students were assured that their participation or withdrawal from the study would have no effect whatsoever on their grades.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eOnline PBL (e-PBL) Background and Scenario Development\u003c/h3\u003e\n\u003cp\u003eFace-to-face PBL sessions were previously conducted at Nihon University School of Medicine. However, owing to the COVID-19 pandemic, online classes began in 2020, and systematic e-PBL started in 2021. e-PBL is a new method, but its educational effectiveness has been reported [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe three PBL scenarios included in this study were Parkinson's disease, lung cancer, and hypersensitivity pneumonitis. All of these were written and used as text-based scenarios prior to this study.\u003c/p\u003e \u003cp\u003eThe academic calendar in Japan starts in April and ends in March. The years shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e agree with the Japanese academic calendar. The first section, 2021, reveals that all third-year students studied each of the three scenarios in a text-based format from April 2021 to March 2022. The multimedia material creation initiative began after this academic year.\u003c/p\u003e \u003cp\u003eMultimedia scenarios refer to content in which multiple forms of media are integrated, such as videos, audio, and images, to enhance learning and engagement. In 2022, as shown in the second section of Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (Multimedia Scenario: Level 1), a variety of multimedia content was developed and used by specialists in each field. These included a multimedia medical interview video for the Parkinson\u0026rsquo;s disease case and computed tomography (CT) imaging in multimedia format for the lung cancer and hypersensitivity pneumonitis cases. The CT imaging videos were created to simulate actual imaging used in real medical records. Additionally, the hypersensitivity pneumonitis case included audible auscultation for students to listen to.\u003c/p\u003e \u003cp\u003eAdditional content was produced and implemented in 2023, as shown in the third section of Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e (Multimedia Scenario: Level 2). This section, 2023, indicates that the multimedia initiative was expanded to include multimedia medical interviews for all three cases.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eTeaching Materials: Multimedia Scenario Content\u003c/h3\u003e\n\u003cp\u003eOriginally text-based, the use of these three scenarios required students to read the patient descriptions and imagine how the clinical pathologies would present. CT images depicting abnormalities in specific locations are shown, and sounds such as murmurs, crackles, and wheezes are described in the text. The Parkinson\u0026rsquo;s disease scenario was created by a neurologist, the lung cancer scenario was created by a thoracic surgeon, and the hypersensitivity pneumonitis scenario was created by a pulmonologist. All of the physicians were experienced senior physicians.\u003c/p\u003e \u003cp\u003eIn the multimedia scenario for hypersensitivity pneumonitis, the pulmonologist created an audio recording of auscultation sounds featuring fine crackles. Fine crackles are characteristic sounds of hypersensitivity pneumonitis. The multimedia scenarios for lung cancer and hypersensitivity pneumonitis included chest CT imaging videos with abnormal findings provided by a thoracic surgeon and a pulmonologist, respectively. For the multimedia scenarios of Parkinson\u0026rsquo;s disease, lung cancer, and hypersensitivity pneumonitis, we developed multimedia medical interviews. Medical education specialists designed the scenarios on the basis of physicians\u0026rsquo; input, and the medical interviews were filmed in the outpatient consultation rooms of Nihon University Itabashi Hospital. The physicians acted as doctors, while professional actors played the role of patients. The actor portraying a Parkinson\u0026rsquo;s disease patient was trained by a neurologist in advance to accurately depict hand tremors, the characteristic gait, distinctive speech patterns, and facial expressions. The actor who played a lung cancer patient was instructed by a thoracic surgeon on how to properly simulate coughing. The actor portraying a patient with hypersensitivity pneumonitis received prior guidance from a pulmonologist on how to express breathlessness and coughing. A video specialist used three video cameras to simultaneously record the doctor, the patient, and the entire outpatient setting. Each multimedia medical interview was then edited into a video of approximately 10 minutes each.\u003c/p\u003e\n\u003ch3\u003ee-PBL\u003c/h3\u003e\n\u003cp\u003ePBL sessions were conducted targeting third-year medical students. Students and tutors joined e-PBL via a web conferencing tool. The students were divided into 16 groups, with one tutor assigned to each group. The scenario content remained the same each year, with a focus on Parkinson's disease, lung cancer, and hypersensitivity pneumonitis. Students discussed the scenario content and collaboratively documented their discussions using online presentation files. Each PBL session lasted for 60 minutes and was held twice a week for each case.\u003c/p\u003e\n\u003ch3\u003eRole of Tutors\u003c/h3\u003e\n\u003cp\u003eDuring the PBL sessions, tutors were responsible for taking attendance and facilitating student discussion by observing and occasionally offering advice and prompts as needed. Tutors were randomly selected among faculty members of the medical school. Tutors received explanations of the scenarios in advance and provided support to students during PBL sessions.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003ePost-PBL Surveys and Assignments\u003c/h2\u003e \u003cp\u003eAfter completing the PBL sessions, the students were asked to submit a survey on their opinions of the PBL multimedia program in 2023 (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The deadline for submission was the following day. Their responses to the survey questions were analysed and included as part of the data collected in this research study. The tutors also had the option to respond to surveys about their opinions of the PBL case multimedia. The tutors could choose to respond anonymously or provide their names (Table S2). The surveys were conducted via the use of online forms.\u003c/p\u003e \u003cp\u003eThe students were also required to submit a PBL assignment the following day. Both the assignments and the surveys were conducted using the same online form system from 2021 to 2023. These assignments included interpretations of the cases, differential diagnoses, and other relevant details. Students were required to freely select two topics that they considered most important about the PBL case. They were asked to investigate each of the two selected topics and include their findings as part of their PBL assignment. To facilitate the analysis for this study, we classified these two selected topics into the following three categories: symptoms, physical and diagnostic findings, and differential diagnoses.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eThe R function binom.test (version 4.3.2) was chosen for McNemar\u0026rsquo;s exact test (Tables S3 and S4, Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). The PROC FREQ of SAS ver. 9.4 was used for Fisher\u0026rsquo;s exact test (Tables S5 and S6, Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, and Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWe conducted a statistical analysis of the topics selected by the students, categorizing them into the following three groups: symptoms, physical and diagnostic findings, and differential diagnoses. Each student was required to select two topics, allowing for duplication among these three categories. On the basis of the relationships between the selected topics and each category, the following three selection patterns were identified: \"0 topics,\" \"1 topic,\" and \"2 topics\", that were treated as ordinal categorical data and used as the dependent variable. Furthermore, the academic year to which each student belonged (2021, 2022, or 2023) was treated as a categorical independent variable, and an ordinal logistic regression analysis was conducted. The right side of Table S7 provides the estimated odds ratios, their 95% confidence intervals, and the corresponding \u003cem\u003ep\u003c/em\u003e values obtained from this analysis. The same ordinal logistic regression analysis was applied to the other two categories, i.e., physical and diagnostic findings (Table S8) and differential diagnoses (Table S9).\u003c/p\u003e \u003cp\u003eThe PROC LOGISTIC option in SAS ver. 9.4 (SAS Institute Inc., Cary, NC, USA) was used for the analyses (Tables S7-S15, Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, and Figs.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e). We used the Holm adjustment to control for multiple comparisons. A significant difference was defined as an adjusted p value less than 0.05 according to Holm's method.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStudent Opinions on the Multimedia Medical Interview\u003c/h2\u003e \u003cp\u003eAmong the students in 2023, 109 responded to the survey for all three diseases, as detailed in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. With respect to Parkinson's disease, 83% of the students in 2023 responded as follows: \"I can understand the patient\u0026rsquo;s condition\". In contrast, for lung cancer and hypersensitivity pneumonitis, only 58% and 53% of the students, respectively, answered that they could understand the patient\u0026rsquo;s condition.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eStudent responses to the medical interview video in 2023\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParkinson\u0026rsquo;s disease, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLung cancer, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHypersensitivity pneumonitis, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe number of respondents to the questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e109 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e109 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e109 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA) I could understand the patient\u0026rsquo;s condition.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e91 (83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e63 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (53)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB) There was not enough discussion time.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe number of students who responded that they could understand the patient\u0026rsquo;s condition for Parkinson's disease was greater than the number of students who understood lung cancer (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and hypersensitivity pneumonitis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Table S4). In all the cases, few students answered that \"there was not enough discussion time\". Most students felt that the allocated discussion time was adequate.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec12\" class=\"Section2\"\u003e \u003ch2\u003eTutors' Responses to Multimedia Medical Interviews\u003c/h2\u003e \u003cp\u003eTwelve tutors answered the survey on Parkinson's disease, 15 tutors answered the survey on lung cancer, and 14 tutors answered the survey on hypersensitivity pneumonitis. With respect to Parkinson's disease, more than 90% of the tutors answered the following: \" Students can understand the patient\u0026rsquo;s condition.\" In contrast, this proportion was only 57% for the hypersensitivity pneumonitis scenario (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Table S6). No tutors responded that \u0026ldquo;it was too difficult for the students\" (Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTutor responses to medical interview videos in 2023\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVariables\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eParkinson\u0026rsquo;s disease, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eLung cancer, n (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eHypersensitivity pneumonitis, n (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eThe number of respondents to the questionnaire\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e12 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e15 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eA) Students could understand the patient\u0026rsquo;s condition.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e11 (92)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e12 (80)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eB) Students could understand the skills and attitudes required for medical interviews.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5 (36)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eC) It was too difficult for the students.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eD) It was not different from the text-based scenario.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eE) There was not enough discussion time.\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4 (29)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003eDetailed Analysis of Student Reports Revealed What Types of Topics Students Considered Interesting\u003c/h2\u003e \u003cp\u003eThe students chose two topics that they considered important, which they researched and described in their reports. The proportions of students selecting 0, 1, or 2 topics within each category (symptoms, physical and diagnostic findings, and differential diagnosis) are provided in Tables\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e. The statistical analyses of students\u0026rsquo; topic selections are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e for Parkinson\u0026rsquo;s disease, Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e for lung cancer, and Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e for hypersensitivity pneumonitis.\u003c/p\u003e \u003cp\u003eAs revealed in the reports on Parkinson\u0026rsquo;s disease (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), students selected topics from the symptoms category more frequently, whereas fewer students selected topics from differential diagnoses category compared with the lung cancer category (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) and hypersensitivity pneumonitis (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e) cases. The tendencies for more students to select symptoms and fewer to select differential diagnoses remained unchanged, with no significant differences observed after the transition from text-based to multimedia scenarios.\u003c/p\u003e \u003cp\u003eIn the Parkinson's disease reports (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), students selected topics within the symptoms category more often compared with the lung cancer (Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e) or hypersensitivity pneumonitis reports (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e), with a higher proportion of students selecting 2 topics since 2021, even when the scenario was text-based. This trend did not change despite the introduction of multimedia medical interviews.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eParkinson\u0026rsquo;s disease: Student-selected topics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2023, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e112 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e73 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73 (65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (59)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41 (34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e34 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e7 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e8 (7)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical and diagnostic findings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e29 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e23 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e29 (25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e87 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e87 (78)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84 (74)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifferential diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2 (2)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e17 (15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20 (18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e105 (87)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e95 (85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92 (81)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe results for the lung cancer reports are shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e. Changing the CT-based scenarios from text to multimedia in 2022 increased the number of students who investigated differential diagnoses (p\u0026thinsp;=\u0026thinsp;0.029 (2022 vs. 2021)) (Table S12). Furthermore, changing the medical interview from text to multimedia in 2023 increased the number of students who investigated differential diagnoses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (2023 vs. 2021), p\u0026thinsp;=\u0026thinsp;0.038 (2023 vs. 2022)) (Table S12). Consequently, the number of students who investigated symptoms decreased (p\u0026thinsp;=\u0026thinsp;0.035 (2023 vs. 2021)) (Table S10), while the number of students who investigated physical and diagnostic findings also decreased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (2023 vs. 2021), p\u0026thinsp;=\u0026thinsp;0.005 (2023 vs. 2022)) (Table S11).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eLung cancer: Student-selected topics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2023, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e122 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e111 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e114 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31 (25)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14 (13)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e17 (15)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e63 (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e67 (60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e28 (23)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e30 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e39 (34)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical and diagnostic findings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e33 (27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e27 (24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10 (9)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e88 (72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e84 (76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (91)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifferential diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e20 (16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e22 (20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (30)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e44 (36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (50)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e58 (51)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58 (48)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e33 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22 (19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eIn the hypersensitivity pneumonitis reports (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e5\u003c/span\u003e), changing the auscultation-based scenario from text to multimedia and the CT-based scenario from text to multimedia in 2022 increased the number of students who investigated differential diagnoses (p\u0026thinsp;=\u0026thinsp;0.008 (2022 vs. 2021)) (Table S15). Furthermore, changing medical interviews from text to multimedia in 2023 increased the number of students who investigated differential diagnoses (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (2023 vs. 2021)) (Table S15). Consequently, the number of students who investigated symptoms decreased (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (2022 vs. 2021), p\u0026thinsp;\u0026lt;\u0026thinsp;0.001 (2023 vs. 2021)) (Table S13).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eThe numbers of topics selected by the students are shown in light grey for 0, medium grey for 1 and dark grey for 2. Adjusted \u003cem\u003ep\u003c/em\u003e values obtained via Holm's method: * \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05, ** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01, *** \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab5\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 5\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eHypersensitivity pneumonitis: Study selected topics\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eYear\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2022, n (%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2023, n (%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTotal number of students\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e121 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e108 (100)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e110 (100)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSymptoms\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e6 (5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0 (0)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e36 (30)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e7 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e6 (5)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e79 (65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100 (93)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e104 (95)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePhysical and diagnostic findings\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e5 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6 (6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9 (8)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e46 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e42 (39)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34 (31)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70 (58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e60 (56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e67 (61)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDifferential diagnosis\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTopic choice patterns\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e42 (35)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e56 (52)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e63 (57)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1 topic\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e54 (45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e41 (38)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e36 (33)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e0 topics\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25 (21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e11 (10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11 (10)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTherefore, compared with text-based scenarios, multimedia scenarios could help students better understand patients\u0026rsquo; conditions in diseases such as Parkinson\u0026rsquo;s disease, who present with visible symptoms such as tremors and the characteristic gait. In contrast, for diseases such as lung cancer and hypersensitivity pneumonitis, where physical findings are less apparent but abnormalities are detected through auscultation or imaging, the multimedia scenarios encouraged students to consider a broader range of differential diagnoses.\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn PBL, students identify their learning needs, engage in self-directed learning, and reflect on their acquired knowledge and learning strategies [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Building on this framework, our study demonstrated that compared with the scenarios for the other two diseases, the Parkinson\u0026rsquo;s disease multimedia scenario was more helpful in enabling students to better understand the patient\u0026rsquo;s condition. This likely occurs because Parkinson\u0026rsquo;s disease presents more physical characteristics, such as distinctive walking patterns, speech, and tremors, making the video material more effective at conveying the patient\u0026rsquo;s condition. In the multimedia scenario related to Parkinson's disease in the 2023 academic year, 83% of the students responded as follows \"I can understand the patient\u0026rsquo;s condition\". This proportion was greater than those in the multimedia scenarios for lung cancer and hypersensitivity pneumonitis. The proportion of tutors who responded that \"students could understand the patient\u0026rsquo;s condition\" exhibited a similar trend to that of the students across all three diseases, and the differences were not statistically significant. The lack of statistical significance is likely due to the small number of tutors.\u003c/p\u003e \u003cp\u003eIn contrast, converting the CT imaging video in the lung cancer scenario and both auscultation and the CT imaging video in the hypersensitivity pneumonitis scenario from text-based descriptions to a multimedia format increased the proportion of students investigating differential diagnoses. In the hypersensitivity pneumonitis scenario, fine crackles were included in the auscultation recordings, and in both the lung cancer and hypersensitivity pneumonitis scenarios, CT image videos were converted into multimedia elements, making the scenarios more realistic. Additionally, in the lung cancer scenario, changing the medical interview to a multimedia format increased the number of students investigating differential diagnoses. By incorporating multimedia elements, students could engage more deeply with the cases and investigate differential diagnoses more strategically. Strategically investigating differential diagnoses suggests that students were thinking more critically about the scenarios and engaging in more in-depth learning to reach a diagnosis instead of simply examining symptoms or physical and diagnostic findings. Considering differential diagnoses is a key objective of PBL and contributes to the evolution of clinical reasoning [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. However, in the case of Parkinson's disease, there was no significant difference in the number of students in the differential diagnosis category when the scenario was changed from a text-based format to a multimedia medical interview. The text-based scenario provided detailed descriptions of characteristic features such as gait, speech patterns, and tremors, whereas the multimedia medical interview emphasized these features through visual representation. Therefore, in both scenarios, it is likely that students were likely to investigate the distinctive symptoms and physical and diagnostic findings. Furthermore, since the scenario made it easier for students to recognize the characteristics of Parkinson's disease, the diagnosis may have been more straightforward, resulting in fewer students investigating differential diagnoses.\u003c/p\u003e \u003cp\u003eIt is acknowledged that realistic scenarios enhance student motivation, ultimately increasing the effectiveness of PBL. The video cases were generally perceived as a valuable stimulus for group discussions in PBL [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. In addition, it is important to provide education that enables students to examine patients with diseases that are commonly seen in their local communities [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. In other words, to maximize the effectiveness of the PBL approach, cases must be tailored to the specific sociocultural, economic, and educational contexts of the given region. In particular, since medical interviews vary by country because of language differences, videos should be prepared in the students' native languages. In the multimedia medical interviews created for this study, patients were portrayed by trained actors resembling real patients, and physicians were portrayed by specialists, with filming taking place in hospitals. In other words, we created multimedia-simulated patients who were very realistic. To our knowledge, this is the first report of e-PBL based on realistic multimedia-simulated patients in Japan. Therefore, we believe that this study is novel and valuable, as it provides evidence to support the idea that multimedia can play a role in enhancing the ability of students to consider various differential diagnoses.\u003c/p\u003e \u003cp\u003eIt is still debated whether text-based or multimedia scenarios are more effective for PBL. Previous studies have revealed that compared with video cases, many students find triggers in paper cases more appropriate for deriving learning objectives and helpful for improving their thinking process. In contrast, facilitators found no significant difference between the effectiveness of the two approaches [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. Another study indicated that the use of video reduced the pace of PBL and impeded students' ability to review and critically appraise the presented information [\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]. In this study, an approximately equal proportion of students and tutors reported that multimedia scenarios were helpful in understanding the patient\u0026rsquo;s condition. Only a small number of both students and tutors indicated that there was not enough discussion time. Therefore, the potential drawback of multimedia scenarios reducing the pace of the PBL was not a significant issue.\u003c/p\u003e \u003cp\u003eIn contrast, incorporating multimedia, such as videos, into medical education materials can support and enhance learning [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]. PBL with video triggers more interest and is preferred over paper cases [\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Video medical interviews help students visualize patients but require significant time and cost to produce [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]. Therefore, it is preferable to present video medical interviews only when they are highly effective. The advantage of multimedia for auscultation and imaging findings is that they can be produced more easily than full multimedia medical interviews can. Therefore, in terms of cost effectiveness, the use of multimedia such as audio clips and video imaging can be feasible for a wide range of educational institutions. In this study, the effect of multimedia varied depending on the content of the scenario. For diseases with few prominent physical features, such as lung cancer and hypersensitivity pneumonitis, ensuring realistic auscultation findings and CT imaging resulted in better differential diagnoses. Furthermore, visualizing the medical interview further enhanced the students\u0026rsquo; ability to independently consider differential diagnoses. For diseases with significant physical features, such as Parkinson's disease, making medical interviews more realistic made it easier for students to understand patients and led to greater learning effectiveness. In other words, this study revealed that the educational effect of making scenarios realistic in terms of physical features varied depending on the characteristics of the disease.\u003c/p\u003e \u003cp\u003eScenarios that effectively presented physical features increased the ability of students to visualize the patient\u0026rsquo;s conditions, a crucial element in case comprehension. Additionally, for diseases with few physical features, scenarios involving multimedia auscultation and imaging findings are cost-effective and highly impactful.\u003c/p\u003e \u003cp\u003eOne limitation of this study is the small number of PBL sessions in which multimedia scenarios were incorporated. Furthermore, the multimedia scenarios were limited to three diseases. In the future, it would be beneficial to conduct additional studies with multimedia scenarios for various diseases.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, the educational effectiveness of multimedia scenarios in PBL was evaluated by comparing them with traditional text-based scenarios. Our findings suggest that multimedia scenarios enhanced students' understanding of patient conditions and encouraged broader and more in-depth consideration of differential diagnoses.\u003c/p\u003e \u003cp\u003eFor diseases with distinctive physical manifestations, such as Parkinson\u0026rsquo;s disease, multimedia medical interviews were particularly effective at helping students understand key clinical characteristics. The majority of both students and tutors reported that multimedia scenarios made it easier for students to understand the patient\u0026rsquo;s condition.\u003c/p\u003e \u003cp\u003eIn diseases with abnormal findings on auscultation or imaging, such as lung cancer and hypersensitivity pneumonitis, integrating multimedia elements such as auscultation sounds and CT imaging video led to a greater emphasis on diagnostic reasoning. This tendency was amplified when the medical interview was also presented in a multimedia format.\u003c/p\u003e \u003cp\u003eDespite their clear advantages, the implementation of multimedia scenarios remains limited. Expanding their application to a broader range of medical conditions and assessing their long-term impact on clinical reasoning will be important for refining PBL methodologies in medical education.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003ePBL, Problem-based learning; CT, computed tomography\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cem\u003eEthics Approval and Consent to Participate\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with the principles of the Declaration of Helsinki and established ethical principles for research involving human participants. The study protocol was approved by the Nihon University School of Medicine Ethics Committee (Approval No. 2024-21; Approval No. Irinsho 2024-21). Informed consent was obtained using an opt-out approach. Students were assured that their participation or withdrawal from the study would have no effect whatsoever on their grades. All collected data were anonymized and stored securely.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eConsent for Publication\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable. No individual participant data or identifying images are included in this article.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAvailability of Data and Materials\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe datasets generated and analyzed in this study are not publicly available to protect participant confidentiality but can be obtained from the corresponding author upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eCompeting Interests\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eFunding\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was supported by grants from JSPS KAKENHI Grant Number 22K10425 (Y.A.).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAuthor Contributors\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eY.A. wrote the manuscript, and E.H.J., S.M., H.N., S.S., S.M., and C.H. edited and critically reviewed the manuscript. Y.A., S.M., H.N. and N.O. created the multimedia scenarios. Y.A., S.M., H.N., S.S., Y.U., T.T., and C.H. managed the PBL. Y.A., S.M., H.N., S.M., and C.H. conceived the study. Y.A. and T.T. performed the statistical analyses. Y.A. raised funds. All the authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eAcknowledgements\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe thank Koichi Inoue and Hiroshi Takatsu (Research Institute of Medical Science, Medical Research Support Center, Multimedia Studio, Nihon University School of Medicine) for their support in this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eNorman GR, Schmidt HG. The psychological basis of problem-based learning: a review of the evidence. Acad Med. 1992;67:557-65.\u003c/li\u003e\n\u003cli\u003eDavis MH. AMEE medical education guide no. 15: problem-based learning: a practical guide. Med Teach. 1999;21:130-40.\u003c/li\u003e\n\u003cli\u003eWun YT, Tse EY, Lam TP, Lam CL. PBL curriculum improves medical students\u0026apos; participation in small-group tutorials. Med Teach. 2007;29:e198-203.\u003c/li\u003e\n\u003cli\u003eAzer SA. Twelve tips for creating trigger images for problem-based learning cases. Med Teach. 2007;29:93-7.\u003c/li\u003e\n\u003cli\u003eIkegami A, Ohira Y, Uehara T, Noda K, Suzuki S, Shikino K, et al. Problem-based learning using patient-simulated videos showing daily life for a comprehensive clinical approach. Int J Med Educ. 2017;8:70-6.\u003c/li\u003e\n\u003cli\u003eBizzocchi J, Schell R. Rich-narrative case study for online PBL in medical education. Acad Med. 2009;84:1412-8.\u003c/li\u003e\n\u003cli\u003eBudakoğlu I, Coşkun \u0026Ouml;, \u0026Ouml;zeke V. e-PBL with multimedia animations: a design-based research. BMC Med Educ. 2023;23:338.\u003c/li\u003e\n\u003cli\u003eJivram T, Kavia S, Poulton E, Hernandez AS, Woodham LA, Poulton T. The development of a virtual world problem-based learning tutorial and comparison with interactive text-based tutorials. Front Digit Health. 2021;3:611813.\u003c/li\u003e\n\u003cli\u003eKamin C, O\u0026apos;Sullivan P, Deterding R, Younger M. A comparison of critical thinking in groups of third-year medical students in text, video, and virtual PBL case modalities. Acad Med. 2003;78:204-11.\u003c/li\u003e\n\u003cli\u003eDahlgren MA, \u0026Ouml;berg G. Questioning to learn and learning to question: structure and function of problem-based learning scenarios in environmental science education. Higher Education. 2001;41:263-82.\u003c/li\u003e\n\u003cli\u003eOmori JS, Wong VS, Nishimura S. Medical school hotline: enhancing problem-based learning with technology: the introduction of iPads into the John A. burns school of medicine curriculum. Hawaii J Med Public Health. 2013;72:362-4.\u003c/li\u003e\n\u003cli\u003ePersson AC, Fyrenius A, Bergdahl B. Perspectives on using multimedia scenarios in a PBL medical curriculum. Med Teach. 2010;32:766-72.\u003c/li\u003e\n\u003cli\u003eMaldonado R. The use of multimedia clinical case scenario software in a problem-based learning course: impact on faculty workload and student learning outcomes. J Physician Assist Educ. 2011;22:51-5.\u003c/li\u003e\n\u003cli\u003eWoodham LA, Ellaway RH, Round J, Vaughan S, Poulton T, Zary N. Medical student and tutor perceptions of video versus text in an interactive online virtual patient for problem-based learning: a pilot study. J Med Internet Res. 2015;17:e151.\u003c/li\u003e\n\u003cli\u003eKim KJ, Kee C. Evaluation of an e-PBL model to promote individual reasoning. Med Teach. 2013;35:e978-83.\u003c/li\u003e\n\u003cli\u003eKim JH, Shin JS. Effects of an online problem-based learning program on sexual health care competencies among oncology nurses: a pilot study. J Contin Educ Nurs. 2014;45:393-401.\u003c/li\u003e\n\u003cli\u003eHmelo-Silver CE. Problem-based learning: what and how do students learn? Educational Psychology Review. 2004;16:235-66.\u003c/li\u003e\n\u003cli\u003eGroves M, Scott I, Alexander H. Assessing clinical reasoning: a method to monitor its development in a PBL curriculum. Med Teach. 2002;24:507-15.\u003c/li\u003e\n\u003cli\u003ede Leng B, Dolmans D, van de Wiel M, Muijtjens A, van der Vleuten C. How video cases should be used as authentic stimuli in problem-based medical education. Med Educ. 2007;41:181-8.\u003c/li\u003e\n\u003cli\u003eBestetti RB, Couto LB, Rom\u0026atilde;o GS, Ara\u0026uacute;jo GT, Restini CB. Contextual considerations in implementing problem-based learning approaches in a Brazilian medical curriculum: the UNAERP experience. Med Educ Online. 2014;19:24366.\u003c/li\u003e\n\u003cli\u003eGhanchi NK, Khan S, Afridi A, Sajid S, Afzal S, Ahmed I, et al. Video or paper for delivery of problem-based learning cases? Med Educ. 2013;47:1131.\u003c/li\u003e\n\u003cli\u003eRuiz JG, Mintzer MJ, Issenberg SB. Learning objects in medical education. Med Teach. 2006;28:599-605.\u003c/li\u003e\n\u003cli\u003eChan LK, Patil NG, Chen JY, Lam JC, Lau CS, Ip MS. Advantages of video trigger in problem-based learning. Med Teach. 2010;32:760-5.\u003c/li\u003e\n\u003cli\u003eAmoako-Sakyi D, Amonoo-Kuofi H. Problem-based learning in resource-poor settings: lessons from a medical school in Ghana. BMC Med Educ. 2015;15:221.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-education","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"meed","sideBox":"Learn more about [BMC Medical Education](http://bmcmededuc.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/meed/default.aspx","title":"BMC Medical Education","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Problem-based learning, Multimedia scenarios, Multimedia medical interview, CT imaging videos, Differential diagnosis","lastPublishedDoi":"10.21203/rs.3.rs-8516677/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8516677/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eProblem-based learning (PBL) traditionally relies on text-based scenarios, but students often find it difficult to fully understand patient conditions on the basis of text alone. In this study, the educational effectiveness levels of multimedia and text-based PBL scenarios were compared in terms of improving students\u0026rsquo; understanding of patient conditions and their ability to identify differential diagnoses.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003e From 2021 to 2023, third-year medical students at Nihon University School of Medicine participated in PBL sessions featuring three diseases, namely, Parkinson\u0026rsquo;s disease, lung cancer, and hypersensitivity pneumonitis, using either text-based or multimedia scenarios. Multimedia elements included medical interview videos, auscultation sounds, and computed tomography (CT) imaging videos. The participants included 121 students in 2021, 112 in 2022, and 114 in 2023. After each PBL session, the students completed a survey and submitted a report, which were analysed and categorized into the following three learning themes: symptoms, physical and diagnostic findings, and differential diagnoses.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn the Parkinson\u0026rsquo;s disease scenario, which entailed the presentation of visible symptoms such as tremors and gait abnormalities, 83% of the students reported that they could understand the patient\u0026rsquo;s condition, significantly more than for lung cancer (58%) or hypersensitivity pneumonitis (53%). Introducing multimedia elements such as auscultation sounds and CT imaging videos significantly increased the proportion of students who explored differential diagnoses in treating lung cancer (p\u0026thinsp;\u0026lt;\u0026thinsp;0.05) and hypersensitivity pneumonitis (p\u0026thinsp;\u0026lt;\u0026thinsp;0.01). Moreover, the addition of multimedia medical interviews enhanced this effect, promoting more comprehensive diagnostic reasoning. Tutors also noted that multimedia scenarios helped students visualize patients more effectively.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eCompared with traditional text-based formats, multimedia scenarios enhanced students\u0026rsquo; understanding of patients and expanded their consideration of differential diagnoses. For diseases with prominent physical features such as Parkinson\u0026rsquo;s disease, multimedia medical interviews were particularly effective at helping students recognize clinical presentations. For diseases identified mainly through imaging or auscultation, such as lung cancer and hypersensitivity pneumonitis, multimedia elements enhanced diagnostic reasoning. These findings suggest that incorporating multimedia into PBL facilitates more realistic, engaging, and effective learning experiences in medical education.\u003c/p\u003e\u003ch2\u003eTrial Registration\u003c/h2\u003e \u003cp\u003eNot applicable. This study did not involve a clinical trial.\u003c/p\u003e","manuscriptTitle":"Educational effectiveness of multimedia scenarios in problem-based learning: a three-year comparative study among Japanese medical students","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-05-14 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