Prompt identification of struggling candidates in near peer-led basic life support training: piloting an online performance scoring system.
Basic Life Support
Competency Assessment Instrument
Immediate Feedback
Peer teaching and assessment
Scoring system
Journal
BMC medical education
ISSN: 1472-6920
Titre abrégé: BMC Med Educ
Pays: England
ID NLM: 101088679
Informations de publication
Date de publication:
02 May 2023
02 May 2023
Historique:
received:
14
07
2022
accepted:
03
04
2023
medline:
4
5
2023
pubmed:
3
5
2023
entrez:
2
5
2023
Statut:
epublish
Résumé
Bristol 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. During 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). A 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. Although 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.
Sections du résumé
BACKGROUND
BACKGROUND
Bristol 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.
METHODS
METHODS
During 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).
RESULTS
RESULTS
A 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.
CONCLUSIONS
CONCLUSIONS
Although 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.
Identifiants
pubmed: 37131183
doi: 10.1186/s12909-023-04225-0
pii: 10.1186/s12909-023-04225-0
pmc: PMC10152634
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
303Informations de copyright
© 2023. The Author(s).
Références
Resuscitation. 2021 Apr;161:270-290
pubmed: 33773828
BMC Med Educ. 2022 Feb 16;22(1):100
pubmed: 35172820
Med Educ Online. 2014 Nov 06;19:24841
pubmed: 25382803
Sultan Qaboos Univ Med J. 2010 Aug;10(2):203-9
pubmed: 21509230
J Grad Med Educ. 2013 Dec;5(4):541-2
pubmed: 24454995
Resusc Plus. 2021 Mar 27;6:100108
pubmed: 34223369
Resuscitation. 2021 Apr;161:98-114
pubmed: 33773835
Resuscitation. 2015 Oct;95:288-301
pubmed: 26477418
Perspect Med Educ. 2019 Oct;8(5):298-304
pubmed: 31562635
BMC Med Educ. 2019 Mar 1;19(1):67
pubmed: 30823878
Resuscitation. 2021 Apr;161:80-97
pubmed: 33773834
Adv Health Sci Educ Theory Pract. 2010 Dec;15(5):625-32
pubmed: 20146096
Intensive Care Med. 2002 Jun;28(6):698-700
pubmed: 12107673
Acad Med. 2018 Mar;93(3):391-398
pubmed: 28767496
Trends Cogn Sci. 2011 Jan;15(1):20-7
pubmed: 20951630
Adv Simul (Lond). 2016 Dec 07;1:31
pubmed: 29450000
BMJ Open. 2019 Jun 11;9(6):e026140
pubmed: 31189674
J R Coll Physicians Lond. 1993 Oct;27(4):412-7
pubmed: 8289165
BMC Med Educ. 2017 Mar 28;17(1):65
pubmed: 28351359
Resuscitation. 2012 Jul;83(7):894-9
pubmed: 22285723
Resuscitation. 2015 Nov;96:199-207
pubmed: 26316279
J Med Life. 2010 Oct-Dec;3(4):465-7
pubmed: 21254750
BMC Med Educ. 2019 Nov 9;19(1):415
pubmed: 31706306
Resuscitation. 1999 Jun;41(1):19-23
pubmed: 10459588
Afr Health Sci. 2019 Jun;19(2):2252-2262
pubmed: 31656511
Resuscitation. 2015 Aug;93:58-62
pubmed: 26054546
Adv Physiol Educ. 2014 Mar;38(1):42-5
pubmed: 24585468
Yale J Biol Med. 2014 Jun 06;87(2):207-12
pubmed: 24910566
World J Emerg Med. 2019;10(2):75-80
pubmed: 30687442