Decision-Making During Asynchronous Electives: Insights From Emergency Medicine-Bound Medical Students.

Introduction While asynchronous learning is gaining popularity, little is known about learners' decisions regarding compliance with assigned asynchronous material. We sought to explore how medical students make decisions about the use of their time when engaging in asynchronous learning during the residency interview season.  Methods After implementing a four-week blended elective for emergency medicine-bound fourth-year medical students, we conducted a mixed methods study with an explanatory sequential design. We analyzed weekly surveys regarding accountability and barriers to assignment completion and conducted semi-structured focus groups exploring the decisions students made regarding compliance with asynchronous assignments. Using a constructivist approach, we performed a thematic analysis of the transcripts. Results The average assignment completion rate was 36%, with the highest rates for podcasts (58%) and the lowest rates for textbook readings (20%). Compliance with assignments was enhanced by a desire for increased ownership of learning but was hindered by a lack of accountability, learner burnout, and higher prioritization of interviews. Students preferentially selected resources that were shorter in length, entertaining, and more convenient for travel. Conclusion Our study highlights factors impacting student compliance when engaging in asynchronous learning and offers insights into educational and institutional strategies that can be utilized to enhance learner motivation.

Is it worth it? A qualitative analysis of the impact of medical education fellowships on careers.

Objectives: Medical education fellowships provide training in teaching, assessment, educational program administration, and scholarship. The longitudinal impact of this training is unknown. The objective of this study was to explore the impact of medical education fellowships on the careers of graduates. Methods: The authors performed a qualitative study with a constructivist-interpretivist paradigm using semistructured interviews in 2021. The authors used a purposeful randomized stratified sampling strategy of graduates to ensure diversity of representation (gender, region, fellowship duration, and career stage). Two researchers independently analyzed interview transcriptions using a modified grounded theory approach. Results: The authors interviewed 10 graduates and identified three overarching concepts: motivations for pursuing fellowship, benefits of training, and drivers of career development. Graduates sought training because of their desire for growth and career preparation and at the advice of mentors. Fellowships provided knowledge and skills in a structured learning environment, supported by mentors and a collaborative community. Fellowship training shaped the careers of graduates by increasing their self-efficacy, enhancing their outcome expectations, refining their goals, and influencing their professional identity formation. They acquired expertise that prepared them for jobs, developed credibility, felt competitive in the job market, anticipated successful promotion, reached for greater goals, broadened their educational worldview, and evolved their professional identity as a result of fellowship training. Conclusions: Fellowship training in medical education provides knowledge and skills, a structured learning environment, and important relationships that shape the careers of graduates by impacting their self-efficacy, outcome expectations, goal creation, and professional identity formation.

A workforce study of emergency medicine medical education fellowship directors: Describing roles, responsibilities, support, and priorities.

Introduction: Despite emergency medicine (EM) medical education fellowships increasing in number, the position of the medical education fellowship director (FD) remains incompletely defined. The goal of this study was to characterize the roles, responsibilities, support, and priorities for medical education FDs. Methods: We adapted and piloted an anonymous electronic survey consisting of 31 single-answer, multiple-answer, and free-response items. The survey was distributed to FDs via listserv and individual emails from a directory compiled from multiple online resources. We used descriptive statistics to analyze data from items with discrete answer choices. Using a constructivist paradigm, we performed a thematic analysis of free-response data. Results: Thirty-four medical education FDs completed the survey, resulting in a response rate of 77%. Thirty-eight percent of respondents were female. Fifty-three percent earned master's degrees in education and 35% completed a medical education fellowship. Most respondents held other education leadership roles including program director (28%), associate/assistant program director (28%), and vice chair (25%). Sixty-three percent received support in their role, including clinical buy-down (90%), administrative assistants (55%), and salary (5%). There was no difference (χ2 [2, n = 32] = 1.77, p = 0.41) between availability of support and type of hospital (community, university, or public hospital). Medical education FDs dedicated a median of 12 h per month to fellowship responsibilities, include education (median 35% of time), program administration (25%), research mentorship (15%), and recruitment (10%). Medical education FDs describe priorities that can be categorized into three themes related to fellows, fellowship, and institution. Conclusion: This study provides insight into the current position and experience of medical education FDs. The results can clarify the role and responsibilities of FDs as the demand for medical education FDs increases.

Recent applications of computational methods to allosteric drug discovery.

Interest in exploiting allosteric sites for the development of new therapeutics has grown considerably over the last two decades. The chief driving force behind the interest in allostery for drug discovery stems from the fact that in comparison to orthosteric sites, allosteric sites are less conserved across a protein family, thereby offering greater opportunity for selectivity and ultimately tolerability. While there is significant overlap between structure-based drug design for orthosteric and allosteric sites, allosteric sites offer additional challenges mostly involving the need to better understand protein flexibility and its relationship to protein function. Here we examine the extent to which structure-based drug design is impacting allosteric drug design by highlighting several targets across a variety of target classes.

Outcome assessment of medical education fellowships in emergency medicine.

OBJECTIVES: Medical education fellowships in emergency medicine (EM) provide training in teaching, assessment, educational program administration, and scholarship. The longitudinal impact of this training is unknown. Our objective was to characterize the career outcomes of medical education fellowship graduates. METHODS: We solicited curriculum vitae (CV) from graduates of U.S. EM education fellowships by email. We abstracted data from CVs with a standard instrument that included program characteristics, employment history, leadership positions, awards, and scholarly productivity. We calculated and reported descriptive statistics. RESULTS: A total of 71 of 91 (78%) graduates participated. Thirty-three completed a 1-year fellowship and 38 completed a 2-year fellowship. Nineteen (27%) completed an advanced degree during fellowship. Median (range) graduation year was 2016 (1997-2020). The majority, 63 of 71 (89%), work in an academic setting. Graduates held leadership positions in continuing medical education, graduate medical education, and undergraduate medical education. Forty-eight (68%) served on national medical education committees. The mean ± SD number of national medical education awards was 1.27 ± 2.03. The mean ± SD number of national medical education presentations was 7.63 ± 10.83. Graduates authored a mean ± SD of 3.63 ± 5.81 book chapters and a mean ± SD of 4.99 ± 6.17 peer-reviewed medical education research publications. Ten (14%) served on journal editorial boards, 34 (48%) were journal reviewers, and 31 (44%) had received a medical education grant. CONCLUSION: EM medical education fellowship graduates are academically productive and hold education leadership positions.

Does academic practice protect emergency physicians against burnout?

Burnout is a complex syndrome thought to result from long-term exposure to career-related stressors. Physicians are at higher risk for burnout than the general United States (US) working population, and emergency medicine has some of the highest burnout rates of any medical specialty. Burnout impacts physicians' quality of life, but it can also increase medical errors and negatively affect patient safety. Several studies have reported lower burnout rates and higher job satisfaction in academic medicine as compared with private practice. However, researchers have only begun to explore the factors that underlie this protective effect. This paper aims to review existing literature to identify specific aspects of academic practice in emergency medicine that may be associated with lower physician burnout rates and greater career satisfaction. Broadly, it appears that spending time in the area of emergency medicine one finds most meaningful has been associated with reduced physician burnout. Certain non-clinical academic work, including involvement in research, leadership, teaching, and mentorship, have been identified as specific activities that may protect against burnout and contribute to higher job satisfaction. Given the epidemic of physician burnout, hospitals and practice groups have a responsibility to address burnout, both by prevention and by early recognition and support. We discuss methods by which organizations can actively foster physician well-being and provide examples of 2 leading academic institutions that have developed comprehensive programs to promote physician wellness and prevent burnout.

Rigorous Computational and Experimental Investigations on MDM2/MDMX-Targeted Linear and Macrocyclic Peptides.

There is interest in peptide drug design, especially for targeting intracellular protein-protein interactions. Therefore, the experimental validation of a computational platform for enabling peptide drug design is of interest. Here, we describe our peptide drug design platform (CMDInventus) and demonstrate its use in modeling and predicting the structural and binding aspects of diverse peptides that interact with oncology targets MDM2/MDMX in comparison to both retrospective (pre-prediction) and prospective (post-prediction) data. In the retrospective study, CMDInventus modules (CMDpeptide, CMDboltzmann, CMDescore and CMDyscore) were used to accurately reproduce structural and binding data across multiple MDM2/MDMX data sets. In the prospective study, CMDescore, CMDyscore and CMDboltzmann were used to accurately predict binding affinities for an Ala-scan of the stapled α-helical peptide ATSP-7041. Remarkably, CMDboltzmann was used to accurately predict the results of a novel D-amino acid scan of ATSP-7041. Our investigations rigorously validate CMDInventus and support its utility for enabling peptide drug design.

Qualitative Analysis of Well-being Preparedness at an Emergency Medicine Residency Program.

INTRODUCTION: There is significant variability in the preparedness of incoming interns at the start of residency training with regard to medical knowledge, procedural skills, and attitudes. Specialty-specific preparatory courses aimed at improving clinical skills exist; however, no preparatory courses targeting wellness promotion or burnout prevention have previously been described. Resident well-being has gained increasing attention from the Accreditation Council for Graduate Medical Education, and numerous studies have demonstrated high levels of burnout among resident physicians. The American Medical Association (AMA) divides resident well-being into the following six categories: nutrition, fitness, emotional health, financial health, preventative care, and mindset and behavioral adaptability. Using the AMA's conceptual framework for well-being in residency, we performed a targeted needs assessment to support the development of a "pre-residency" well-being curriculum. Our aim was to discover what current residents and faculty felt were the perceived areas of under-preparedness, in relation to resident well-being, for incoming interns at the start of their residency training. METHODS: Using a grounded theory approach, we conducted a series of semi-structured, focus group interviews. Focus groups consisted of junior residents (postgraduate years [PGY] 1-3), senior residents (PGY-4), and current faculty members. A standardized interview guide was used to prompt discussion and themes were identified from audio recording. We modified theories based on latent and manifest content analysis, and we performed member checking and an external audit to improve validity. RESULTS: Participants noted variable exposure to both formal and informal well-being training prior to residency. Regardless, participants uniformly agreed that their past experiences did not adequately prepare them for the challenges, specific to burnout prevention, faced during residency training. Of the six domains of resident well-being described by the AMA, emotional health, mindset and behavioral adaptability, and financial health were the domains most cited for interns to be underprepared for at the start of residency training. CONCLUSION: Despite variability in prior medical school and life experiences, incoming interns were underprepared in several domains of well-being, including emotional health, mindset and behavioral adaptability, and financial health. Targeted interventions toward these areas of well-being should be piloted and studied further for their potential to mitigate effects of burnout among resident physicians.

Inhibiting IL-2 signaling and the regulatory T-cell pathway using computationally designed peptides.

Background Increased serum levels of soluble interleukin-2 (IL-2) receptor alpha (sIL-2Rα) are an indicator of poor prognosis in patients with B-cell non-Hodgkin lymphoma (NHL). By binding to IL-2, sIL-2Rα upregulates Foxp3 expression and induces the development of regulatory T (Treg) cells. Methods To inhibit the binding of IL-2 to sIL-2Rα with the goal of suppressing the induction of Foxp3 and decreasing Treg cell numbers, we developed peptides by structure-based computational design to disrupt the interaction between IL-2 and sIL-2Rα. Each peptide was screened using an enzyme-linked immunosorbent assay (ELISA), and 10 of 22 peptides showed variable capacity to inhibit IL-2/sIL-2Rα binding. Results We identified a lead candidate peptide, CMD178, which consistently reduced the expression of Foxp3 and STAT5 induced by IL-2/sIL-2Rα signaling. Furthermore, production of cytokines (IL-2/interferon gamma [IFN-γ]) and granules (perforin/granzyme B) was preserved in CD8+ T cells co-cultured with IL-2-stimulated CD4+ T cells that had been pretreated with CMD178 compared to CD8+ cells co-cultured with untreated IL-2-stimulated CD4+ T cells where it was inhibited. Conclusions We conclude that structure-based peptide design can be used to identify novel peptide inhibitors that block IL-2/sIL-2Rα signaling and inhibit Treg cell development. We anticipate that these peptides will have therapeutic potential in B-cell NHL and other malignancies.

Which Emergency Medicine Milestone Sub-competencies are Identified Through Narrative Assessments?

INTRODUCTION: Evaluators use assessment data to make judgments on resident performance within the Accreditation Council for Graduate Medical Education (ACGME) milestones framework. While workplace-based narrative assessments (WBNA) offer advantages to rating scales, validity evidence for their use in assessing the milestone sub-competencies is lacking. This study aimed to determine the frequency of sub-competencies assessed through WBNAs in an emergency medicine (EM) residency program. METHODS: We performed a retrospective analysis of WBNAs of postgraduate year (PGY) 2-4 residents. A shared mental model was established by reading and discussing the milestones framework, and we created a guide for coding WBNAs to the milestone sub-competencies in an iterative process. Once inter-rater reliability was satisfactory, raters coded each WBNA to the 23 EM milestone sub-competencies. RESULTS: We analyzed 2517 WBNAs. An average of 2.04 sub-competencies were assessed per WBNA. The sub-competencies most frequently identified were multitasking, medical knowledge, practice-based performance improvement, patient-centered communication, and team management. The sub-competencies least frequently identified were pharmacotherapy, airway management, anesthesia and acute pain management, goal-directed focused ultrasound, wound management, and vascular access. Overall, the frequency with which WBNAs assessed individual sub-competencies was low, with 14 of the 23 sub-competencies being assessed in less than 5% of WBNAs. CONCLUSION: WBNAs identify few milestone sub-competencies. Faculty assessed similar sub-competencies related to interpersonal and communication skills, practice-based learning and improvement, and medical knowledge, while neglecting sub-competencies related to patient care and procedural skills. These findings can help shape faculty development programs designed to improve assessments of specific workplace behaviors and provide more robust data for the summative assessment of residents.

A Descriptive Analysis of the Use of Twitter by Emergency Medicine Residency Programs.

BACKGROUND: Twitter is increasingly recognized as an instructional tool by the emergency medicine (EM) community. In 2012, the Council of Residency Directors in Emergency Medicine (CORD) recommended that EM residency programs' Twitter accounts be managed solely by faculty. To date, little has been published regarding the patterns of Twitter use by EM residency programs. OBJECTIVE: We analyzed current patterns in Twitter use among EM residency programs with accounts and assessed conformance with CORD recommendations. METHODS: In this mixed methods study, a 6-question, anonymous survey was distributed via e-mail using SurveyMonkey. In addition, a Twitter-based search was conducted, and the public profiles of EM residency programs' Twitter accounts were analyzed. We calculated descriptive statistics and performed a qualitative analysis on the data. RESULTS: Of 168 Accreditation Council for Graduate Medical Education-accredited EM programs, 88 programs (52%) responded. Of those programs, 58% (51 of 88) reported having a program-level Twitter account. Residents served as content managers for those accounts in the majority of survey respondents (61%, 28 of 46). Most programs did not publicly disclose the identity or position of their Twitter content manager. We found a wide variety of applications for Twitter, with EM programs most frequently using Twitter for educational and promotional purposes. There is significant variability in the numbers of followers for EM programs' Twitter accounts. CONCLUSIONS: Applications and usage among EM residency programs are varied, and are frequently not consistent with current CORD recommendations.

Identification and initial optimization of inhibitors of Clostridium difficile (C. difficile) toxin B (TcdB).

The discovery, synthesis and preliminary structure-activity relationship (SAR) of a novel class of inhibitors of Clostridium difficile (C. difficile) toxin B (TcdB) is described. A high throughput screening (HTS) campaign resulted in the identification of moderately active screening hits 1-5 the most potent of which was compound 1 (IC50 = 0.77 µM). In silico docking of an early analog offered suggestions for structural modification which resulted in the design and synthesis of highly potent analogs 13j(IC50 = 1 nM) and 13 l(IC50 = 7 nM) which were chosen as leads for further optimization.

PeptideNavigator: An interactive tool for exploring large and complex data sets generated during peptide-based drug design projects.

There is growing interest in peptide-based drug design and discovery. Due to their relatively large size, polymeric nature, and chemical complexity, the design of peptide-based drugs presents an interesting "big data" challenge. Here, we describe an interactive computational environment, PeptideNavigator, for naturally exploring the tremendous amount of information generated during a peptide drug design project. The purpose of PeptideNavigator is the presentation of large and complex experimental and computational data sets, particularly 3D data, so as to enable multidisciplinary scientists to make optimal decisions during a peptide drug discovery project. PeptideNavigator provides users with numerous viewing options, such as scatter plots, sequence views, and sequence frequency diagrams. These views allow for the collective visualization and exploration of many peptides and their properties, ultimately enabling the user to focus on a small number of peptides of interest. To drill down into the details of individual peptides, PeptideNavigator provides users with a Ramachandran plot viewer and a fully featured 3D visualization tool. Each view is linked, allowing the user to seamlessly navigate from collective views of large peptide data sets to the details of individual peptides with promising property profiles. Two case studies, based on MHC-1A activating peptides and MDM2 scaffold design, are presented to demonstrate the utility of PeptideNavigator in the context of disparate peptide-design projects.

Development and application of a multi-modal task analysis to support intelligent tutoring of complex skills.

BACKGROUND: Contemporary work in the design and development of intelligent training systems employs task analysis (TA) methods for gathering knowledge that is subsequently encoded into task models. These task models form the basis of intelligent interpretation of student performance within education and training systems. Also referred to as expert models, they represent the optimal way(s) of performing a training task. Within Intelligent Tutoring Systems (ITSs), real-time comparison of trainee task performance against the task model drives automated assessment and interactive support (such as immediate feedback) functionality. However, previous task analysis (TA) methods, including various forms of cognitive task analysis (CTA), may not be sufficient to support identification of the detailed design specifications required for the development of an ITS for a complex training task incorporating multiple underlying skill components, as well as multi-modal information presentation, assessment, and feedback modalities. Our current work seeks to develop an ITS for training Robotic Assisted Laparoscopic Surgery (RALS), a complex task domain that requires a coordinated utilization of integrated cognitive, psychomotor, and perceptual skills. RESULTS: In this paper, we describe a methodological extension to CTA, referred to as multi-modal task analysis (MMTA) that elicits and captures the nuances of integrated and isolated cognitive, psychomotor, and perceptual skill modalities as they apply to training and performing complex operational tasks. In the current case, we illustrate the application of the MMTA method described here to RALS training tasks. The products of the analysis are quantitatively summarized, and observations from a preliminary qualitative validation are reported. CONCLUSIONS: We find that iterative use of the described MMTA method leads to sufficiently complete and robust task models to support encoding of cognitive, psychomotor, and perceptual skills requisite to training and performance of complex skills within ITS task models.

The Council of Emergency Medicine Residency Directors Speaker Evaluation Form for Medical Conference Planners.

OBJECTIVES: No summative speaker evaluation form with validity and reliability evidence currently exists in the English medical education literature specifically to help conference planners make future decisions on speakers. We seek to perform a proof-of-concept evaluation of a concise, effective evaluation form to be filled out by audience members to aid conference planners. METHODS: We created the Council of Emergency Medicine Residency Directors (CORD-EM) form, a novel, three-question speaker evaluation form for the CORD-EM national conference and evaluated it for proof of concept. The CORD-EM form was analyzed with three evaluators and randomized to select only two evaluators' ratings to make results more generalizable to a generic audience evaluating the speaker. RESULTS: Forty-six total evaluations ranged from 6 to 9 (mean ± standard deviation = 8.1 ± 1.2). The form demonstrated excellent internal consistency (Cronbach's alpha = 0.923) with good inter-rater reliability (intraclass correlation = 0.617) in the conference context. CONCLUSIONS: The CORD-EM speaker evaluation form is, to our knowledge, the first evaluation form with early reliability and validity evidence specifically designed to help conference planners. Our results suggest that a short speaker evaluation form can be an effective instrument in the toolbox for conference planners.

Development of a Simple Electron Transfer and Polarization Model and Its Application to Biological Systems.

Here we present a new method for point charge calculation which we call QET (charges by electron transfer). The intent of this work is to develop a method that can be useful for studying charge transfer in large biological systems. It is based on the intuitive framework of the QEQ method with the key difference being that the QET method tracks all pairwise electron transfers by augmenting the QEQ pseudoenergy function with a distance dependent cost function for each electron transfer. This approach solves the key limitation of the QEQ method which is its handling of formally charged groups. First, we parametrize the QET method by fitting to electrostatic potentials calculated using ab initio quantum mechanics on over 11,000 small molecules. On an external test set of over 2500 small molecules the QET method achieves a mean absolute error of 1.37 kcal/mol/electron when compared to the ab initio electrostatic potentials. Second, we examine the conformational dependence of the charges on over 2700 tripeptides. With the tripeptide data set, we show that the conformational effects account for approximately 0.4 kcal/mol/electron on the electrostatic potentials. Third, we test the QET method for its ability to reproduce the effects of polarization and electron transfer on 1000 water clusters. For the water clusters, we show that the QET method captures about 50% of the polarization and electron transfer effects. Finally, we examine the effects of electron transfer and polarizability on the electrostatic interaction between p38 and 94 small molecule ligands. When used in conjunction with the Generalized-Born continuum solvent model, polarization and electron transfer with the QET model lead to an average change of 17 kcal/mol on the calculated electrostatic component of ΔG.

Rational, computer-enabled peptide drug design: principles, methods, applications and future directions.

Peptides provide promising templates for developing drugs to occupy a middle space between small molecules and antibodies and for targeting 'undruggable' intracellular protein-protein interactions. Importantly, rational or in cerebro design, especially when coupled with validated in silico tools, can be used to efficiently explore chemical space and identify islands of 'drug-like' peptides to satisfy diverse drug discovery program objectives. Here, we consider the underlying principles of and recent advances in rational, computer-enabled peptide drug design. In particular, we consider the impact of basic physicochemical properties, potency and ADME/Tox opportunities and challenges, and recently developed computational tools for enabling rational peptide drug design. Key principles and practices are spotlighted by recent case studies. We close with a hypothetical future case study.

Avalanche for shape and feature-based virtual screening with 3D alignment.

This report introduces a new ligand-based virtual screening tool called Avalanche that incorporates both shape- and feature-based comparison with three-dimensional (3D) alignment between the query molecule and test compounds residing in a chemical database. Avalanche proceeds in two steps. The first step is an extremely rapid shape/feature based comparison which is used to narrow the focus from potentially millions or billions of candidate molecules and conformations to a more manageable number that are then passed to the second step. The second step is a detailed yet still rapid 3D alignment of the remaining candidate conformations to the query conformation. Using the 3D alignment, these remaining candidate conformations are scored, re-ranked and presented to the user as the top hits for further visualization and evaluation. To provide further insight into the method, the results from two prospective virtual screens are presented which show the ability of Avalanche to identify hits from chemical databases that would likely be missed by common substructure-based or fingerprint-based search methods. The Avalanche method is extended to enable patent landscaping, i.e., structural refinements to improve the patentability of hits for deployment in drug discovery campaigns.

A combined cheminformatic and bioinformatic approach to address the proteolytic stability challenge in peptide-based drug discovery.

We have created models to predict cleavage sites for several human proteases including caspase-1, caspase-3, caspase-6, caspase-7, cathepsin B, cathepsin D, cathepsin G, cathepsin K, cathepsin L, elastase-2, granzyme A, granzyme B, matrix metallopeptidase-2 (MMP2), MMP7, MMP9, thrombin, and trypsin-1. Rather than representing the sequence pattern around the potential cleavage site through a series of flags with each flag representing one of the 20 standard amino acids, we first represent each amino acid by its calculated properties. For these calculated properties, we use validated cheminformatic descriptors, such as molecular weight, logP, and polar surface area, of the individual amino acids. Finally, the cleavage site-specific descriptors are calculated through various combinations of the individual amino acid descriptors for the residues surrounding the cleavage site. Some of these combinations do not take into account the location of the residue, as long as it is in a prescribed neighborhood of the potential cleavage site, whereas others are sensitive to the precise order of the residues in the sequence. The key advantage of this approach is that it allows one to perform meaningful calculations with nonstandard amino acids for which little or no data exists. Finally, using both docking and molecular dynamics simulations, we examine the potential for and limitations of protease crystal structures to impact the design of proteolytically stable peptides.