Citations

Abstract Purpose Professional identities impact professional boundaries and hierarchies, influencing how physicians approach collaboration. Despite the growing emphasis on developing students to become effective collaborators, little is known about how other health professionals (OHPs) shape students' professional identity formation (PIF). This study explored how interacting with OHPs during clinical care contributed to medical students' construction of what it means to be a physician. Methods For this constructivist grounded theory study, researchers conducted 20 semi‐structured interviews with medical students during clinical clerkships. Students drew rich pictures representing their interactions with OHPs and described these pictures during their interviews. Interviews were iteratively conducted and analysed, enabling the research team to theorize how interacting with OHPs contributed to medical students' PIF. Results Participants expressed a strong desire to contribute to patient care and described how interprofessional interactions provided opportunities to do so in ways aligned with their current capabilities. These opportunities were often more accessible than the roles and responsibilities of physicians, and participating alongside OHPs fostered participants' sense of their own developing capabilities and belonging on healthcare teams. Interactions with OHPs helped participants to see the expertise of OHPs and the value of collaborating with them in ways that shifted their focus away from becoming independent. Conceptually, participants' interactions with OHPs became both a mirror reflecting their present readiness to meaningfully contribute and a prism through which they could envision their future identities as physicians in new ways. Conclusions Interprofessional interactions influenced medical students' current and future professional identities, enabling students to see themselves as contributors on health care teams and highlighting collaboration and interdependence as core attributes of the physician profession. These findings highlight opportunities to amplify the impact of interprofessional interactions on the PIF of medical students and the need for research into how OHPs view their roles in these processes.

Abstract Background Precision medicine, sometimes referred to as personalized medicine, is rapidly changing the possibilities for how people will engage health care in the near future. As technology to support precision medicine exponentially develops, there is an urgent need to proactively improve our understanding of precision medicine and pose important research questions (RQs) related to its inclusion in the education and training of future emergency physicians. Methods A seven‐step process was employed to develop a research agenda exploring the intersection of precision and emergency medicine education/training. A literature search of articles about precision medicine was conducted first, which informed the creation of future four scenarios in which trainees and practicing physicians regularly discuss and incorporate precision medicine tools into their discussions and work. Based on these futurist narratives, potential education RQs were generated by an expert panel. A total of 59 initial questions were subsequently categorized and refined to a priority list through a nominal group voting method. The top/priority questions were presented at the 2023 SAEM Consensus Conference on Precision Medicine, Austin, Texas, for further input. Results Eight high‐value education RQs were developed, reflecting a holistic view of the challenges and opportunities for precision medicine education in the knowledge, skills, and attitudes relevant to emergency medicine. These questions contend with topics such as most effective pedagogical methods; intended resulting outcomes and behaviors; the generational differences between practicing emergency physicians, educators, and future trainees; and the desires and expectations of patients. Conclusions Emergency medicine and emergency physicians must be prepared to understand precision medicine and incorporate this information into their “toolbox” of thinking, problem solving, and communication with patients and colleagues. This research agenda on how best to educate future emergency physicians in the use of personalized data to provide optimal health care is the focus of this article.

Abstract Purpose Assessing expertise using psychometric models usually yields a measure of ability that is difficult to generalize to the complexity of diagnoses in clinical practice. However, using an item response modeling framework, it is possible to create a decision-aligned response model that captures a clinician’s decision-making behavior on a continuous scale that fully represents competing diagnostic possibilities. In this proof-of-concept study, the authors demonstrate the necessary statistical conceptualization of this model using a specific electrocardiogram (ECG) example. Method The authors collected a range of ECGs with elevated ST segments due to either ST-elevation myocardial infarction (STEMI) or pericarditis. Based on pilot data, 20 ECGs were chosen to represent a continuum from “definitely STEMI” to “definitely pericarditis,” including intermediate cases in which the diagnosis was intentionally unclear. Emergency medicine and cardiology physicians rated these ECGs on a 5-point scale (“definitely STEMI” to “definitely pericarditis”). The authors analyzed these ratings using a graded response model showing the degree to which each participant could separate the ECGs along the diagnostic continuum. The authors compared these metrics with the discharge diagnoses noted on chart review. Results Thirty-seven participants rated the ECGs. As desired, the ECGs represented a range of phenotypes, including cases where participants were uncertain in their diagnosis. The response model showed that participants varied both in their propensity to diagnose one condition over another and in where they placed the thresholds between the 5 diagnostic categories. The most capable participants were able to meaningfully use all categories, with precise thresholds between categories. Conclusions The authors present a decision-aligned response model that demonstrates the confusability of a particular ECG and the skill with which a clinician can distinguish 2 diagnoses along a continuum of confusability. These results have broad implications for testing and for learning to manage uncertainty in diagnosis.

Abstract Purpose Using electrocardiogram (ECG) interpretation as an example of a widely taught diagnostic skill, the authors conducted a systematic review and meta-analysis to demonstrate how research evidence on instruction in diagnosis can be synthesized to facilitate improvement of educational activities (instructional modalities, instructional methods, and interpretation approaches), guide the content and specificity of such activities, and provide direction for research. Method The authors searched PubMed/MEDLINE, Embase, Cochrane CENTRAL, PsycInfo, CINAHL, ERIC, and Web of Science databases through February 21, 2020, for empirical investigations of ECG interpretation training enrolling medical students, residents, or practicing physicians. They appraised study quality with the Medical Education Research Study Quality Instrument and pooled standardized mean differences (SMDs) using random effects meta-analysis. Results Of 1,002 articles identified, 59 were included (enrolling 17,251 participants). Among 10 studies comparing instructional modalities, 8 compared computer-assisted and face-to-face instruction, with pooled SMD 0.23 (95% CI, 0.09, 0.36) indicating a small, statistically significant difference favoring computer-assisted instruction. Among 19 studies comparing instructional methods, 5 evaluated individual versus group training (pooled SMD −0.35 favoring group study [95% CI, −0.06, −0.63]), 4 evaluated peer-led versus faculty-led instruction (pooled SMD 0.38 favoring peer instruction [95% CI, 0.01, 0.74]), and 4 evaluated contrasting ECG features (e.g., QRS width) from 2 or more diagnostic categories versus routine examination of features within a single ECG or diagnosis (pooled SMD 0.23 not significantly favoring contrasting features [95% CI, −0.30, 0.76]). Eight studies compared ECG interpretation approaches, with pooled SMD 0.92 (95% CI, 0.48, 1.37) indicating a large, statistically significant effect favoring more systematic interpretation approaches. Conclusions Some instructional interventions appear to improve learning in ECG interpretation; however, many evidence-based instructional strategies are insufficiently investigated. The findings may have implications for future research and design of training to improve skills in ECG interpretation and other types of visual diagnosis.

Purpose To identify features of instruments, test procedures, study design, and validity evidence in published studies of electrocardiogram (ECG) skill assessments. Method The authors conducted a systematic review, searching MEDLINE, Embase, Cochrane CENTRAL, PsycINFO, CINAHL, ERIC, and Web of Science databases in February 2020 for studies that assessed the ECG interpretation skill of physicians or medical students. Two authors independently screened articles for inclusion and extracted information on test features, study design, risk of bias, and validity evidence. Results The authors found 85 eligible studies. Participants included medical students (42 studies), postgraduate physicians (48 studies), and practicing physicians (13 studies). ECG selection criteria were infrequently reported: 25 studies (29%) selected single-diagnosis or straightforward ECGs; 5 (6%) selected complex cases. ECGs were selected by generalists (15 studies [18%]), cardiologists (10 studies [12%]), or unspecified experts (4 studies [5%]). The median number of ECGs per test was 10. The scoring rubric was defined by 2 or more experts in 32 studies (38%), by 1 expert in 5 (6%), and using clinical data in 5 (6%). Scoring was performed by a human rater in 34 studies (40%) and by computer in 7 (8%). Study methods were appraised as low risk of selection bias in 16 studies (19%), participant flow bias in 59 (69%), instrument conduct and scoring bias in 20 (24%), and applicability problems in 56 (66%). Evidence of test score validity was reported infrequently, namely evidence of content (39 studies [46%]), internal structure (11 [13%]), relations with other variables (10 [12%]), response process (2 [2%]), and consequences (3 [4%]). Conclusions ECG interpretation skill assessments consist of idiosyncratic instruments that are too short, composed of items of obscure provenance, with incompletely specified answers, graded by individuals with underreported credentials, yielding scores with limited interpretability. The authors suggest several best practices.

Purpose To determine whether “chronometric pressure” (i.e., a verbal prompt to increase speed) could predictably alter medical learners’ speed–accuracy trade-off during a simulated surgical task, thus modifying the challenge. Method The authors performed a single-task, interrupted time-series study, enrolling surgery residents and medical students from two institutions in September and October 2015. Participants completed 10 repetitions of a simulated blood vessel ligation (placement of two ligatures 1 cm apart). Between repetitions 5 and 6, participants were verbally encouraged to complete the next repetition 20% faster than the previous one. Outcomes included time and accuracy (ligature tightness, placement distance). Data were analyzed using random-coefficients spline models. Results The authors analyzed data from 78 participants (25 medical students, 16 first-year residents, 37 senior [second-year or higher] residents). Overall, time decreased from the 1st (mean [standard deviation] 39.8 seconds [18.4]) to the 10th (29.6 [12.5]) repetition. The spline model showed a decrease in time between repetitions 5 and 6 of 8.6 seconds (95% confidence interval: −11.1, −6.1). The faster time corresponded with declines in ligature tightness (unadjusted difference −19%; decrease in odds 0.86 [0.76, 0.98]) and placement accuracy (unadjusted difference −5%; decrease in odds 0.86 [0.75, 0.99]). Significant differences in the speed–accuracy trade-off were seen by training level, with senior residents demonstrating the greatest decline in accuracy as speed increased. Conclusions Chronometric pressure influenced the speed–accuracy trade-off and modified the challenge level in a simulated surgical task. It may help unmask correctable deficiencies or false plateaus in learners’ skill development.

BACKGROUND AND OBJECTIVE: Pediatrics has embraced technology-enhanced simulation (TES) as an educational modality, but its effectiveness for pediatric education remains unclear. The objective of this study was to describe the characteristics and evaluate the effectiveness of TES for pediatric education. METHODS: This review adhered to PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) standards. A systematic search of Medline, Embase, CINAHL, ERIC, Web of Science, Scopus, key journals, and previous review bibliographies through May 2011 and an updated Medline search through October 2013 were conducted. Original research articles in any language evaluating the use of TES for educating health care providers at any stage, where the content solely focuses on patients 18 years or younger, were selected. Reviewers working in duplicate abstracted information on learners, clinical topic, instructional design, study quality, and outcomes. We coded skills (simulated setting) separately for time and nontime measures and similarly classified patient care behaviors and patient effects. RESULTS: We identified 57 studies (3666 learners) using TES to teach pediatrics. Effect sizes (ESs) were pooled by using a random-effects model. Among studies comparing TES with no intervention, pooled ESs were large for outcomes of knowledge, nontime skills (eg, performance in simulated setting), behaviors with patients, and time to task completion (ES = 0.80–1.91). Studies comparing the use of high versus low physical realism simulators showed small to moderate effects favoring high physical realism (ES = 0.31–0.70). CONCLUSIONS: TES for pediatric education is associated with large ESs in comparison with no intervention. Future research should include comparative studies that identify optimal instructional methods and incorporate pediatric-specific issues into educational interventions.