Point-of-Care-ultrasound in undergraduate medical education: a scoping review of assessment methods
Bibliographic record
Abstract
Abstract Background Point-of-Care-Ultrasound (POCUS) curricula have rapidly expanded in undergraduate medical education (UME). However, the assessments used in UME remain variable without national standards. This scoping review characterizes and categorizes current assessment methods using Miller’s pyramid for skills, performance, and competence of POCUS in UME. A structured protocol was developed using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR). A literature search of MEDLINE was performed from January 1, 2010, to June 15, 2021. Two independent reviewers screened all titles and abstracts for articles that met inclusion criteria. The authors included all POCUS UME publications in which POCUS-related knowledge, skills, or competence were taught and objectively assessed. Articles were excluded if there were no assessment methods used, if they exclusively used self-assessment of learned skills, were duplicate articles, or were summaries of other literature. Full text analysis and data extraction of included articles were performed by two independent reviewers. A consensus-based approach was used to categorize data and a thematic analysis was performed. Results A total of 643 articles were retrieved and 157 articles met inclusion criteria for full review. Most articles (n = 132; 84%) used technical skill assessments including objective structured clinical examinations (n = 27; 17%), and/or other technical skill-based formats including image acquisition (n = 107; 68%). Retention was assessed in n = 98 (62%) studies. One or more levels of Miller’s pyramid were included in 72 (46%) articles. A total of four articles (2.5%) assessed for students’ integration of the skill into medical decision making and daily practice. Conclusions Our findings demonstrate a lack of clinical assessment in UME POCUS that focus on integration of skills in daily clinical practice of medical students corresponding to the highest level of Miller’s Pyramid. There exists opportunities to develop and integrate assessment that evaluate higher level competencies of POCUS skills of medical students. A mixture of assessment methods that correspond to multiple levels of Miller’s pyramid should be used to best assess POCUS competence in UME.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.114 | 0.315 |
| Meta-epidemiology (narrow) | 0.003 | 0.003 |
| Meta-epidemiology (broad) | 0.009 | 0.009 |
| Bibliometrics | 0.042 | 0.034 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.008 | 0.009 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".