Evaluating the effect of instruction and practice schedule on the acquisition of ECG interpretation skills

The spacing effect in remote information-integration category learning

The present experiments examined whether the temporal distribution of procedural category learning experiences would impact learning outcomes. Participants completed the remote category learning experiments on a smartphone in one of two learning conditions: massed or distributed. Consistent with expectations, distributed learners in both experiments reached higher accuracy levels than massed learners. In Experiment 1 the effect disappeared after accounting for reaction time differences, suggesting that it was driven by attentional mechanisms. In Experiment 2, the spacing advantage was only present for previously studied items during a post-learning test, suggesting a role of consolidation. In both experiments, it seems likely that temporal spacing helped participants discover the optimal information-integration categorization strategy. These results suggest that adult category learning is facilitated by temporal spacing. Future work may further explore the effects of temporal and contextual distinctiveness of learning experiences on category learning outcomes.

Designing an ECG curriculum for residents: Evidence-based approaches to improving resident ECG interpretation skills

Residents enter their training with variable comfort and competency in electrocardiogram (ECG) interpretation. Accurately interpreting an ECG is a fundamental skill in medicine and resident physicians would benefit from a longitudinal, dedicated ECG curriculum as part of their training to enhance interpretation skills and improve patient outcomes. Educators currently employ a wide array of methodologies to teach their trainees proper ECG interpretation skills, with no single modality established as the gold-standard for teaching this crucial skill. We present evidence-based guidance on how educators may develop and implement an effective ECG interpretation curriculum as part of residency training.

Surfing the clinical trials of ECG teaching to medical students: A systematic review

Interpreting an electrocardiogram (ECG) is crucial for every physician. The physician's competency in ECG interpretation needs to be improved at any stage of medical education. The aim of the present study was to review the currently published clinical trials of ECG teaching to medical students and provide suggestions for future works. On May 1, 2022, PubMed, Scopus, Web of Science, Google Scholar, and ERIC were searched to retrieve relevant articles on clinical trials of ECG teaching to medical students. The quality of the included studies was assessed utilizing the Buckley et al. criteria. The screening, data extraction, and quality appraisal processes were duplicated independently. In case of disagreements, consultation with a third author was put forth. In total, 861 citations were found in the databases. After screening abstracts and full texts, 23 studies were deemed eligible. The majority of the studies were of good quality. Peer teaching (7 studies), self-directed learning (6 studies), web-based learning (10 studies), and various assessment modalities (3 studies) comprised the key themes of the studies. Various methods of ECG teaching were encountered in the reviewed studies. Future studies in ECG training should focus on novel and creative teaching methods, the extent to which self-directed learning can be effective, the utility of peer teaching, and the implications of computer-assisted ECG interpretation (e.g., artificial intelligence) for medical students. Long-term knowledge retention assessment studies based on different approaches integrated with clinical outcomes could be beneficial in determining the most efficient modalities.

How to Keep Training-After Residency Training

Lifelong learning in medicine is an important skill and ethical obligation, but many residents do not feel prepared to be effective self-directed learners when training ends. The learning sciences offer evidence to guide self-directed learning, but these insights have not been integrated into a practical and actionable plan for residents to improve their clinical knowledge and reasoning. We encourage residents to establish a self-directed learning plan, just as an athlete employs a training plan in the pursuit of excellence. We highlight four evidence-based learning principles (spaced practice, mixed practice, retrieval practice, and feedback) and four training strategies comprising a weekly training plan: case tracking, simulated cases, quizzing, and new evidence integration. We provide tips for residents to implement and refine their approach and discuss how residency programs can foster these routines and habits. By optimizing their scarce self-directed learning time with a training plan, residents may enhance patient care and their career satisfaction through their pursuit of clinical mastery.

Physician Training for Electrocardiogram Interpretation: A Systematic Review and Meta-Analysis

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.

Assessments of Physicians' Electrocardiogram Interpretation Skill: A Systematic Review

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.

Utility of mobile learning in Electrocardiography

Aims

Mobile learning is attributed to the acquisition of knowledge derived from accessing information on a mobile device. Although increasingly implemented in medical education, research on its utility in Electrocardiography remains sparse. In this study, we explored the effect of mobile learning on the accuracy of electrocardiogram (ECG) analysis and interpretation.

Methods and results

The study comprised 181 participants (77 fourth- and 69 sixth-year medical students, and 35 residents). Participants were randomized to analyse ECGs with a mobile learning strategy [either searching the Internet or using an ECG reference application (app)] or not. For each ECG, they provided their initial diagnosis, key supporting features, and final diagnosis consecutively. Two weeks later, they analysed the same ECGs, without access to any mobile device. ECG interpretation was more accurate when participants used the ECG app (56%), as compared to searching the Internet (50.3%) or neither (43.5%, P = 0.001). Importantly, mobile learning supported participants in revising their initial incorrect ECG diagnosis (ECG app 18.7%, Internet search 13.6%, no mobile device 8.4%, P < 0.001). However, whilst this was true for students, there was no significant difference amongst residents. Internet searches were only useful if participants identified the correct ECG features. The app was beneficial when participants searched by ECG features, but not by diagnosis. Using the ECG reference app required less time than searching the Internet (7:44 ± 4:13 vs. 9:14 ± 4:34, P < 0.001). Mobile learning gains were not sustained after 2 weeks.

Conclusion

Whilst mobile learning contributes to increased ECG diagnostic accuracy, the benefits were not sustained over time.

Visual category learning: Navigating the intersection of rules and similarity

Visual categorization is fundamental to expertise in a wide variety of disparate domains, such as radiology, art history, and quality control. The pervasive need to master visual categories has served as the impetus for a vast body of research dedicated to exploring how to enhance the learning process. The literature is clear on one point: no category learning technique is always superior to another. In the present review, we discuss how two factors moderate the efficacy of learning techniques. The first, category similarity, refers to the degree of featural overlap of exemplars. The second moderator, category type, concerns whether the features that define category membership can be mastered through learning processes that are implicit/non-verbal (information-integration categories) or explicit/verbal (rule-based categories). The literature on each moderator has been conducted almost entirely in isolation, such that their potential interaction remains underexplored. We address this gap in the literature by reviewing empirical and theoretical evidence that these two moderators jointly influence the efficacy of learning techniques.

Accuracy of Physicians' Electrocardiogram Interpretations: A Systematic Review and Meta-analysis

IMPORTANCE

The electrocardiogram (ECG) is the most common cardiovascular diagnostic test. Physicians' skill in ECG interpretation is incompletely understood.

OBJECTIVES

To identify and summarize published research on the accuracy of physicians' ECG interpretations.

DATA SOURCES

A search of PubMed/MEDLINE, Embase, Cochrane CENTRAL (Central Register of Controlled Trials), PsycINFO, CINAHL (Cumulative Index to Nursing and Allied Health), ERIC (Education Resources Information Center), and Web of Science was conducted for articles published from database inception to February 21, 2020.

STUDY SELECTION

Of 1138 articles initially identified, 78 studies that assessed the accuracy of physicians' or medical students' ECG interpretations in a test setting were selected.

DATA EXTRACTION AND SYNTHESIS

Data on study purpose, participants, assessment features, and outcomes were abstracted, and methodological quality was appraised with the Medical Education Research Study Quality Instrument. Results were pooled using random-effects meta-analysis.

MAIN OUTCOMES AND MEASURES

Accuracy of ECG interpretation.

RESULTS

Of 1138 studies initially identified, 78 assessed the accuracy of ECG interpretation. Across all training levels, the median accuracy was 54% (interquartile range [IQR], 40%-66%; n = 62 studies) on pretraining assessments and 67% (IQR, 55%-77%; n = 47 studies) on posttraining assessments. Accuracy varied widely across studies. The pooled accuracy for pretraining assessments was 42.0% (95% CI, 34.3%-49.6%; n = 24 studies; I2 = 99%) for medical students, 55.8% (95% CI, 48.1%-63.6%; n = 37 studies; I2 = 96%) for residents, 68.5% (95% CI, 57.6%-79.5%; n = 10 studies; I2 = 86%) for practicing physicians, and 74.9% (95% CI, 63.2%-86.7%; n = 8 studies; I2 = 22%) for cardiologists.

CONCLUSIONS AND RELEVANCE

Physicians at all training levels had deficiencies in ECG interpretation, even after educational interventions. Improved education across the practice continuum appears warranted. Wide variation in outcomes could reflect real differences in training or skill or differences in assessment design.

Is computer-assisted instruction more effective than other educational methods in achieving ECG competence amongst medical students and residents? A systematic review and meta-analysis

OBJECTIVES

It remains unclear whether computer-assisted instruction (CAI) is more effective than other teaching methods in acquiring and retaining ECG competence among medical students and residents.

DESIGN

This systematic review and meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines.

DATA SOURCES

Electronic literature searches of PubMed, databases via EBSCOhost, Scopus, Web of Science, Google Scholar and grey literature were conducted on 28 November 2017. We subsequently reviewed the citation indexes for articles identified by the search.

ELIGIBILITY CRITERIA

Studies were included if a comparative research design was used to evaluate the efficacy of CAI versus other methods of ECG instruction, as determined by the acquisition and/or retention of ECG competence of medical students and/or residents.

DATA EXTRACTION AND SYNTHESIS

Two reviewers independently extracted data from all eligible studies and assessed the risk of bias. After duplicates were removed, 559 papers were screened. Thirteen studies met the eligibility criteria. Eight studies reported sufficient data to be included in the meta-analysis.

RESULTS

In all studies, CAI was compared with face-to-face ECG instruction. There was a wide range of computer-assisted and face-to-face teaching methods. Overall, the meta-analysis found no significant difference in acquired ECG competence between those who received computer-assisted or face-to-face instruction. However, subanalyses showed that CAI in a blended learning context was better than face-to-face teaching alone, especially if trainees had unlimited access to teaching materials and/or deliberate practice with feedback. There was no conclusive evidence that CAI was better than face-to-face teaching for longer-term retention of ECG competence.

CONCLUSION

CAI was not better than face-to-face ECG teaching. However, this meta-analysis was constrained by significant heterogeneity amongst studies. Nevertheless, the finding that blended learning is more effective than face-to-face ECG teaching is important in the era of increased implementation of e-learning.

PROSPERO REGISTRATION NUMBER

CRD42017067054.