United States

Background
The spread of pathogens poses a significant threat to public health, but strategies like herd immunity and social distancing can mitigate this risk. Despite the well-documented benefits of these strategies, their effectiveness hinges on widespread public adherence and understanding. Recent events, such as the SARS-CoV-2 pandemic, have underscored the challenges posed by public resistance and misinformation. Studies have highlighted increased skepticism and misinformation regarding vaccination, undermining herd immunity efforts. To address this growing need for resources to counter doubts about public health decisions, we sought to develop software using cellular automaton models that can not only educate individuals on the value of practices like social distancing and vaccinations on disease spread, but also showcase realistic results to improve understanding.
Methods
We developed a simulation tool using a discrete cellular automaton process, modeling disease spread through a population grid where individuals can change states (susceptible, infected, vaccinated). Users can input parameters such as disease transmissibility, vaccination rates, and social distancing protocols to simulate scenarios across time. This model was tested as an educational supplement in an immunology class. Additionally, we developed a probabilistic multi-state cellular automaton model, incorporating stochastic elements to reflect randomness in disease transmission and individual behaviors. We applied the model to real-world data from COVID-19 databases to evaluate the effectiveness of herd immunity and social distancing in different communities.
Results
A survey of students using the discrete simulation found 83% reporting the software was intuitive, while 100% felt it increased understanding of herd immunity. The probabilistic cellular automaton model illustrated the positive impact of vaccination and social distancing on herd immunity, demonstrating vaccine effectiveness can be nearly 650 times more effective when social distancing is enforced. Additionally, the simulations revealed emerging patterns, such as regions without disease spread, possibly informing new metrics for evaluating public health responses.
Conclusion
Overall, this probabilistic simulation can serve as a valuable epidemiological tool to help characterize public health conditions. Furthermore, this simulation can be used as an educational tool for the public to better understand the mechanisms of herd immunity and the impact of their own behavior on disease spread. Future improvements to this model can include consideration of state transition adjustments, external system shocks, and additional considerations to initial conditions. The simulation tool&#39;s user-friendly interface and adaptable parameters make it feasible for widespread educational use, especially in unprecedented times. Its generalizability extends to various public health scenarios, promoting broader understanding of epidemiological strategies.

AMA Research Challenge 2024 

Characterizing Herd Immunity Through Cellular Automaton Models

The purpose of the AAAI conference is to promote research in artificial intelligence (AI) and scientific exchange among AI researchers, practitioners, scientists, and engineers in affiliated disciplines. 

AAAI 2021

Background
The spread of pathogens poses a significant threat to public health, but strategies like herd immunity and social distancing can mitigate this risk. Despite the well-documented benefits of these strategies, their effectiveness hinges on widespread public adherence and understanding. Recent events, such as the SARS-CoV-2 pandemic, have underscored the challenges posed by public resistance and misinformation. Studies have highlighted increased skepticism and misinformation regarding vaccination, undermining herd immunity efforts. To address this growing need for resources to counter doubts about public health decisions, we sought to develop software using cellular automaton models that can not only educate individuals on the value of practices like social distancing and vaccinations on disease spread, but also showcase realistic results to improve understanding.
Methods
We developed a simulation tool using a discrete cellular automaton process, modeling disease spread through a population grid where individuals can change states (susceptible, infected, vaccinated). Users can input parameters such as disease transmissibility, vaccination rates, and social distancing protocols to simulate scenarios across time. This model was tested as an educational supplement in an immunology class. Additionally, we developed a probabilistic multi-state cellular automaton model, incorporating stochastic elements to reflect randomness in disease transmission and individual behaviors. We applied the model to real-world data from COVID-19 databases to evaluate the effectiveness of herd immunity and social distancing in different communities.
Results
A survey of students using the discrete simulation found 83% reporting the software was intuitive, while 100% felt it increased understanding of herd immunity. The probabilistic cellular automaton model illustrated the positive impact of vaccination and social distancing on herd immunity, demonstrating vaccine effectiveness can be nearly 650 times more effective when social distancing is enforced. Additionally, the simulations revealed emerging patterns, such as regions without disease spread, possibly informing new metrics for evaluating public health responses.
Conclusion
Overall, this probabilistic simulation can serve as a valuable epidemiological tool to help characterize public health conditions. Furthermore, this simulation can be used as an educational tool for the public to better understand the mechanisms of herd immunity and the impact of their own behavior on disease spread. Future improvements to this model can include consideration of state transition adjustments, external system shocks, and additional considerations to initial conditions. The simulation tool's user-friendly interface and adaptable parameters make it feasible for widespread educational use, especially in unprecedented times. Its generalizability extends to various public health scenarios, promoting broader understanding of epidemiological strategies.

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Background: The hospital environment is a complex and unpredictable workplace where different providers share the responsibility of patient care. Differences in opinions, values, and experiences between resident physicians and other care team members may trigger conflicts that affect the safety and quality of patient care. Thus, developing conflict competencies may help to negotiate the complexities of different conflict situations and resolve these conflicts. However, the extent of the knowledge and perception of conflict competence among resident physicians remains to be determined.

Methods: A survey and qualitative semi-structured interviews of resident physicians were conducted. Participants were recruited voluntarily. Survey results were analyzed using SPSS 21, and MAXQDA 24 was used to evaluate the interview transcripts with thematic analysis.

Results: Sixty-five resident physicians completed the survey, and fifteen resident physicians were interviewed. 61.5% of the survey respondents identified as female, 76.9% were Caucasian, 35.4% of the respondents were from surgical specialties, and
43.1% of the residents were in their second year of training.
53.8% of the participants reported witnessing or experiencing conflicts weekly, with 44.6% reporting resident physician-nurse conflicts. 63.1% of the conflicts were reported as unresolved, with 16.9% reporting that the conflict affected future working relationships, 25.5% of the conflicts were due to failure of communication, 75.4%residents did not have any form of prior training on conflict management, and 83.1% of them reported interest in conflict competence training. Conflicts mainly affected the quality of care (87.3%) compared to patient safety concerns (12.3%). Participants with prior training in conflict competence were more likely to resolve their reported conflict (p= .047). The interviews highlighted five main themes: sources of conflict, awareness of conflict resolution styles, addressing conflict and outcomes, and the effect on patient care. Sources of conflict included hierarchy and different priorities. 52.2% of the respondents did not know any style of conflict resolution.
Addressing conflict included collaboration, avoidance, competition, and prevention. Avoidance was the most common style used by interviewees, followed by collaboration. While most felt that the conflicts affected the quality of patient care, one interviewee reported severe adverse events on the patient.
Conclusion
Conflicts are rife in the hospital environment and can affect patient care when unresolved. Resident physicians' knowledge of conflict competence is low and does not reflect the complexity of their working environment. Future training in conflict competence and resolution is warranted.

Keywords: conflict, conflict competence, resident physicians, hospitals


Conflict competence among resident physicians: knowledge and perception

Background
Inclusive sexual history training in medical education is crucial for addressing the health needs of LGBTQ+ patients. Literature indicates many physicians feel inadequately trained on LGBTQ+ health needs, exacerbating healthcare disparities. This study evaluates the impact of a structured training program on medical students’ ability to take sexual histories from LGBTQ+ patients effectively.

Methods
A two-hour educational session led by Dr. Shira Heisler, medical director of the Detroit Public Health STD clinic, was presented to 36 Wayne State University School of Medicine students. During this session, students learned how to take a comprehensive sexual history and practiced with peers via role-playing exercises. Participants were recruited via email and received volunteering credit for attendance. Data was collected through pre-session and post-session surveys using a 10-point Likert scale to measure students’ experiences, knowledge, and attitudes. These surveys were intended to highlight gaps in LGBTQ+ sexual history training and evaluate the session’s effectiveness.

Results
Overall, there was a significant increase in students’ comfort interacting with LGBTQ+ patients post-session (p-value = 0.00019). Students’ rating of the importance of taking an LGBTQ+-inclusive sexual history also significantly increased post-session (p-value = 0.00066). First-year medical students demonstrated a statistically significant increase in comfort with taking a sexual history of patients who exclusively have sex with opposite-gender partners (p-value = 0.0015) as well as patients who have sex with partners of the same or multiple genders post-session (p-value = 0.00092), while second-year students did not demonstrate a significant difference post-session for either category.

Conclusion
By addressing medical education gaps in LGBTQ+ health, this session aimed to improve LGBTQ+ community healthcare outcomes. The data collected suggests that attending inclusive sexual history-taking education sessions effectively improves students’ comfort with taking a sexual history for both LGBTQ+ and non-LGBTQ+ patients. Ultimately, fostering an inclusive approach to sexual history-taking can contribute to more equitable healthcare.

Cultivating confidence: improving LGBTQ+-focused sexual history training for medical students​

Background
Effective communication in challenging patient interactions is crucial in medicine. While simulation labs are ideal for training, they lack universal accessibility. AI-based patient encounters provide an innovative tool for medical education that allow students to test new communication methods in a risk-free environment. We present an integrated educational module with best practice videos and an AI-based simulation app for honing skills in delivering difficult news to patients.

Methods 
The educational component includes videos on best practices for delivering bad news, followed by interactive training using an AI-powered app based on a Large-Language Model, programmed in Python. To build the AI simulation modules, a pilot case prompt was first created by specifying the clinical scenario and patient personality in ChatGPT-4o. This prompt was further refined to an appropriate length and personality specifications using an iterative prompting process within ChatGPT-4o. After testing this case in the app environment, multiple cases were designed using standardized prompts based on the pilot case specifying diagnoses, communication styles, and personality traits based on the Big Five model. The AI app incorporates diverse clinical scenarios presenting challenging situations and difficult conversations and provides personalized feedback based on the SPIKES protocol.

App Development 
The AI-powered app was developed to simulate realistic patient interactions. The OpenAI API was employed to generate patient responses and emotional cues using ChatGPT-4o from predefined cases. Each case includes a multidimensional prompt architecture, enabling the AI to portray various clinical scenarios and patient personalities accurately. A separate AI agent evaluates student performance using the SPIKES model criteria and provides real-time formative feedback on communication techniques.

Results 
The AI patient actors demonstrated accurate personality embodiments and significant emotional responses. In addition to giving appropriate responses, the app also provided body language and contextualizing statements in line with the encoded personality before beginning dialogue such as “fidgets nervously” or “takes a deep breath, trying to calm down.” The app assessed student performance against the SPIKES protocol and generated constructive feedback. The AI Patient Actor app for difficult conversations is openly available at https://patient-actor-dc.streamlit.app/.

Conclusion 
This fully integrated educational module, combining best practice videos and an AI simulation app, is an innovative tool for communication skills training that can provide formative skills training at scale. The module will be incorporated into Dartmouth's Geisel School of Medicine curriculum. Validation through cohort testing will follow.

Difficult conversations skills training using an AI-based patient actor app

Artificial intelligence (AI) has significant potential in medicine, especially in diagnostics and education. ChatGPT has achieved levels comparable to medical students on text-based USMLE questions, yet there's a gap in its evaluation on image-based questions. This study evaluated ChatGPT-4's performance on image-based questions from USMLE Step 1, Step 2, and Step 3. The overall performance of ChatGPT-4 on USMLE Steps 1, 2, and 3 was evaluated using 376 questions, including 54 with images. The accuracy was 85.7% for Step 1, 92.5% for Step 2, and 86.9% for Step 3. For image-based questions, the accuracy was 70.8% for Step 1, 92.9% for Step 2, and 62.5% for Step 3. In contrast, text-based questions showed higher accuracy: 89.5% for Step 1, 92.5% for Step 2, and 90.1% for Step 3. Performance dropped significantly for difficult image-based questions in Steps 1 and 3 (p=0.0196 and p=0.0020 respectively), but not in Step 2 (p=0.9574). Despite these challenges, the AI's accuracy on image-based questions exceeded the passing rate for all three exams. ChatGPT-4 can handle image-based USMLE questions above the passing rate, showing promise for its use in medical education and diagnostics. Further development is needed to improve its direct image processing capabilities and overall performance.

Evaluating the Performance of ChatGPT-4o Vision Capabilities on Image-Based USMLE Step 1, Step 2, and Step 3 Examination Questions

Despite more female physicians in training than ever before, existing literature demonstrates the distressing reality that medical students continue to experience sexism in clinical settings. Research indicates that female medical students are more likely than male students to experience gender discrimination within evaluations, educational opportunities, and workplace relationships. Even though many medical students recognize sexism from patients as an issue, limited research exists on this topic. This study aims to quantify the extent to which medical students experience sexism from patients. 

The survey, yielding 58 responses (41 female and 17 male), revealed that 91% of respondents recognized sexism as a problem medical students face in clinical rotations. Specifically, 93% of females and 24% of males responded that they have faced sexism from patients in clinical settings. 85% of female students report being frequently mistaken for a nurse or nursing student, despite clear role introductions. Only 18% of male students reported being mistaken for other healthcare roles and, specifically, 0% reported being mistaken for nursing staff. Moreover, 66% of female students and 35% of male students received comments on their appearance or family planning from patients. 63% of females and 18% of males were subjected to inappropriate or sexually suggestive patient comments. Frequency analysis revealed that 7% of female students encounter sexism from patients weekly, 41% monthly, 46% yearly, and 5% never. In contrast, 71% of male students report never experiencing sexism from patients and 29% experience sexism from patients yearly. No male students reported monthly, weekly, or daily occurrences. Respondents shared examples of sexism they experienced in the free response section of the survey. Female students described countless instances of being mistaken for nurses and enduring sexually suggestive remarks from patients. Notably, one male student described observing the gender disparity, stating he is often mistaken for a doctor, while his female colleagues are consistently assumed to be nurses.

In conclusion, although both male and female medical students experience sexism from patients, female students are disproportionately affected by gender discrimination. These findings highlight the need for systemic change and policies to safeguard students and foster inclusive learning environments. Recommendations for improvement include implementing badge tags that state “medical student,” in addition to educating faculty to recognize and support students facing gender discrimination from patients.

Exploring how medical students experience sexism from patients in clinical settings

Medical education is an evolving process that continues to incorporate various modes of delivery to enrich medical students’ learning. Film is a unique medium that has been shown to be an effective teaching method in educating students about patient socioeconomic factors and clinical interactions. Although film is established as an effective teaching tool, there is little to no data regarding film’s effectiveness in improving medical students’ awareness and understanding of governmental healthcare policies. The aim of this study was to determine if medical students’ understanding of disability healthcare policy was significantly influenced after viewing the film Crip Camp. Medical students watched the film Crip Camp and engaged in peer-facilitated discussion of the film. Prior to the screening, participants completed a Likert scale and yes/no survey questionnaire to assess their baseline awareness of disability policy. Following the screening, students completed the survey again. The pre- and post-survey groups were compared for statistical significance using the Mann-Whitney U test. Furthermore, a One-Way Chi-Square analysis test was conducted. In total, 18 participants responded to the surveys given at the film screening. There was a statistically significant difference between pre- and post-survey answers regarding Question 1: “Do you think that the government is doing enough in 2024 to provide services for individuals with disabilities?”(U = 420, z = 8.81, p < 0.01). Furthermore, most students who answered “Mostly not” to the previous question, also indicated “Yes” regarding Question 2: “Do you think that the state of Michigan should establish opt-in in-patient facilities for those with severe disabilities?” (ꭓ² = 5.0294, df = 2, a = 0.05). The data suggests that there was a significant difference in participants’ understanding of disability healthcare policy after viewing Crip Camp. The number of students that answered “I don’t know” to Question 1 decreased from 8 to 3. Thus, it can be inferred that the film influenced the students’ understanding because they took a stance on Question 1 post-screening. Following the screening, significantly more students selected “Mostly not” for Question 1 and “Yes” for Question 2. Hence, it can be inferred that the students became more inclined to support the government establishing opt-in services for individuals with disabilities. The scope of future studies could aim to assess students’ knowledge on health policy, and whether our screenings impact their future approach to care.

Film as a Teaching Tool: Enhancing Medical Students' Understanding of Disability Healthcare Policy

Background: Lesbian, Gay, Bisexual, Transgender, Queer, Intersex, and Asexual (LGBTQIA+) individuals are less likely to afford medical care, have higher rates of depression, and are more likely to feel discriminated against by medical providers based on their sexual orientation or gender identity. These health disparities introduce a need for medical providers to be practiced in both LGBTQIA+ cultural competence and unique healthcare concerns; however, currently in the United States, there is no required pre-clinical medical education regarding LGBTQIA+ healthcare. Previous studies have shown that discussion-based learning and virtual patient interactions are effective in improving the knowledge and skills of medical students. Our purpose is to determine if a medical skills-based workshop utilizing simulated patient scenarios will improve medical students’ self-perceived knowledge and competence when providing care to members of the LGBTQIA+ community. 

Methods: A workshop was presented to 100 first-year medical students at one medical institution introducing LGBTQIA+ concepts, terminology, and unique healthcare concerns. An anonymous survey was administered after the workshop to determine participants’ self-perceived knowledge of LGBTQIA+ concepts and self-perceived competence in caring for members of this population. Knowledge was scored on a scale from 0 (low knowledge) to 10 (high knowledge); competence was determined by participants' level of agreement to several Likert-styled statements. A paired t-test was conducted to determine the significance (p < 0.05) of the difference in self-perceived knowledge before and after the workshop.

Results: Results indicated a significant increase (p < 0.001) of mean self-perceived knowledge in both LGBTQIA+ unique healthcare concerns and terminology in first-year medical students who completed the workshop. In addition, 84% of participants agreed or strongly agreed they felt more competent in their ability to use inclusive language when speaking with LGBTQIA+ patients. Particularly, participants who do not identify as LGBTQIA+ members demonstrated a benefit in their self-perceived competence of LGBTQIA+ terminology and knowledge of healthcare concerns. 

Conclusions: The results of this study demonstrate how an informational workshop utilizing interactive practice scenarios regarding LGBTQIA+ terminology and healthcare concerns strongly correlates with the improvement of self-perceived knowledge and competence of first-year medical students. Considering there is no standardized curriculum for LGBTQIA+ medical education, the pedagogy demonstrated can be extended to other medical institutions with the goal of molding future physicians who can provide quality care to members of the LGBTQIA+ community.

Improving Self-perceived Competence in LGBTQIA+ Healthcare in Medical School Preclinical Education

Abstract Title: Investigating Potential Bias in Medical School Assessments

Background: Assessments are critical in medical education, shaping career paths from entry to progression. Despite efforts for equity, disparities persist. Underrepresented minority groups and women score lower on the MCAT and USMLE, with differences by gender and ethnicity persisting. Biases extend to narrative assessments like letters of recommendation and MSPEs, where non-white students receive fewer strong descriptors, and gendered terms characterize 
female students. This study investigates how gender, race, language proficiency, and 
immigration status influence test outcomes, aiming to inform fair assessment practices.

Methods: 54 first-year medical students completed a practice test and demographic survey at the University of Central Florida College of Medicine. Test questions underwent Angoff scoring and 12-item writing flaw rubric evaluation. Students received immediate feedback and qualitative analysis of incorrect responses. Quantitative analysis included Mantel-Haenszel chisquare tests and two-sample tests for differential item functioning. Multivariate logistic regression assessed demographic predictors of test outcomes, combining quantitative and qualitative approaches.

Results: Logistic regression showed gender alone did not predict question outcomes, but its interaction with overall performance did. Non-uniform differential item functioning was observed, confirmed by significant Chi-square results. Limited study participation precluded separate race analysis, affecting statistical power. The Nagelkerke measure quantified variation explained by DIF. Ongoing analysis will examine group performance trends to identify broader disparities.

Conclusion: This study identifies nuanced biases in medical school assessments, particularly regarding gender. While logistic regression didn't directly predict gender's impact on question outcomes, its interaction with performance suggested predictive value. Significant Chi-square results confirmed differential item functioning, with ongoing analysis aiming to reveal broader performance trends among demographic groups. This insight informs efforts to foster fairness in 
medical education assessments.

Investigating Potential Bias in Medical School Assessments

Background 
Ophthalmology is a highly competitive specialty to match into, yet many medical students have limited exposure to the field. Early exposure and mentorship are essential to introduce students to ophthalmology, better preparing them for residency applications. 
Research on mentorship in ophthalmology for preclinical and clerkship students remains scarce, with no systematic review. Our objective is to conduct a comprehensive review of the critical role of mentorship in medical students' path in ophthalmology. We seek to offer actionable recommendations for medical schools to bridge the divide between preclinical education and clinical exposure to ophthalmology. 
Methods 
Using PRISMA methodology, a literature review was conducted via databases PubMed and Embase. The objective was to identify all published literature on ophthalmology mentorship programs for first through third-year medical students in the United States. 
Inclusion Criteria: 
Intervention: providing mentorship (clinical opportunity, personal mentorship, research exposure, etc.)
Setting: specific to ophthalmology 
Population: First, second, and third-year U.S. medical students 
English language 
Information from chosen articles was summarized into an evidence table. Areas of interest included number of students in the study, year in medical school, intervention type and length, and pre-and post-intervention measurement methods. 
Results 
93 articles were retrieved with 19 duplicates. 74 articles were screened by two independent reviewers. Titles and abstracts were screened, excluding 17 articles. The remaining 57 underwent full-text screening. Seven articles meeting all inclusion criteria were included in this review. Three additional articles were discovered in the references of reviewed articles and were added. 304 subjects were studied, comprising of first, second, and third-year medical students. One study also included four undergraduate students. Seven of ten articles reported significantly increased ophthalmology knowledge. Six of ten articles evaluated the change in student interest in ophthalmology. Five articles reported an interest increase post-intervention, with four articles indicating a statistically significant increase post-intervention. 
Conclusion 
The studies in this review highlight how early exposure to ophthalmology is crucial for enhancing students' skills and knowledge in preparation for elective rotations and residency applications in their fourth year. 
While only four studies showed a significant increase in interest in ophthalmology, this outcome may be influenced by students already interested in ophthalmology being more likely to participate in the offered mentorship and exposure programs. 
Structured programs aimed at providing exposure and mentorship to ophthalmology are invaluable resources for aspiring ophthalmologists. Medical schools can consider adopting similar initiatives to bridge the gap in pre-clinical ophthalmology exposure and knowledge.

Medical Student Ophthalmology Mentorship Initiatives in the United States: A Systematic Review​

Background
Wearable technology has become a rapidly growing consumer market which is expected to double between 2021 and 2026. One popular use for wearables is to track health outcomes. Amid escalating mistrust towards the medical community, this study investigates how varying levels of trust in the healthcare system affect an individual’s decision to track their health with wearables, the frequency of using wearables to track their health, and sharing the data with their providers.

Methods
Data from the 2022 Health Information National Trends Survey (HINTS) 6 was analyzed for trust in the healthcare system, use and sharing of health information from wearable devices, and socio-demographic characteristics (age, gender, income, and race). Level of trust in the healthcare system, the main study predictor, was categorized into four levels: not a lot, a little, somewhat, and a lot. Dependent variables were 1) use of a wearable device to track healthcare information; 2) willingness to share wearable health information with a provider; and 3) frequency of tracking metrics on a wearable over the past month.

Results
Among the 6,118 respondents, 84.8% reported moderate to high levels of trust in the U.S. healthcare system, and 33.2% used wearables in the past year to track their healthcare data. 70.8% of wearable users stated that they had used a wearable to track their health daily or nearly daily during the past month, and 78.1% of respondents were willing to share wearable data with a healthcare provider. Participants with a lot of trust were significantly more willing to share their wearable data with a healthcare provider (AOR:1.49;[95% CI 1.27-1.73]), after controlling for covariates. Increasing income levels resulted in a higher likelihood of using a wearable to track health data (AOR:1.33;[95% CI 1.29-1.37]) and increased frequency of tracking health metrics on wearables (AOR:1.10;[95% CI 1.06-1.13]). Men are also less likely to use wearables (AOR:0.62;[95% CI 0.54-0.70]) and track their health with them continuously (AOR:0.85;[95% CI 0.74-0.97]) than women.

Conclusion:
This study suggests that increasing levels of trust in the healthcare system, increasing income, and being female are associated with greater adoption of wearable technology for health information tracking and sharing.

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Conflict competence among resident physicians: knowledge and perception

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