ArticleBMC medical education2023
Prompt identification of struggling candidates in near peer-led basic life support training: piloting an online performance scoring system.
Article in BMC medical education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 1 citations in OpenAlex.
- The Use of Peer-Assisted Learning in Teaching Clinical Skills in Undergraduate Medical Education: A Scoping Review.Journal of medical education and curricular developmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundBristol Medical School has adopted a near peer-led teaching approach to deliver Basic Life Support training to first year undergraduate medical students. Challenges arose when trying to identify early in the course which candidates were struggling with their learning, in sessions delivered to large cohorts. We developed and piloted a novel, online performance scoring system to better track and highlight candidate progress.
methodsDuring this pilot, a 10-point scale was used to evaluate candidate performance at six time-points during their training. The scores were collated and entered on an anonymised secure spreadsheet, which was conditionally formatted to provide a visual representation of the score. A One-Way ANOVA was performed on the scores and trends analysed during each course to review candidate trajectory. Descriptive statistics were assessed. Values are presented as mean scores with standard deviation (x̄±SD).
resultsA significant linear trend was demonstrated (P < 0.001) for the progression of candidates over the course. The average session score increased from 4.61 ± 1.78 at the start to 7.92 ± 1.22 at the end of the final session. A threshold of less than 1SD below the mean was used to identify struggling candidates at any of the six given timepoints. This threshold enabled efficient highlighting of struggling candidates in real time.
conclusionsAlthough the system will be subject to further validation, our pilot has shown the use of a simple 10-point scoring system in combination with a visual representation of performance helps to identify struggling candidates earlier across large cohorts of students undertaking skills training such as Basic Life Support. This early identification enables effective and efficient remedial support.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.