The influence of candidates' physical attributes on assessors' ratings in clinical practice

Autor: Michael D Reid, P. Yeates, Rachel Westacott, Amir H Sam, Celia A. Brown, Malcolm W.R. Reed, Mark Gurnell, Viral Thakerar
Rok vydání: 2021
Předmět:
Zdroj: Medical teacher. 43(5)
ISSN: 1466-187X
0142-159X
Popis: Background \ud Assessments of physician competence in the work-place are common and often contribute to high-stakes assessments. Previous research suggests that assessors’ judgements can be influenced by candidates’ physical attributes. We investigated whether simulated candidates’ scores were influenced by assessor bias based on tattoos, hair colour, and a regional accent.\ud \ud Methods \ud We used an experimental, video-based, single-blinded, randomised, internet-based design. We created videos of simulated medical intern performances of a clinical examination at four different standards of competence. Four videos were also created of simulated candidates performing at a ‘clear pass’ standard, with either no stereotypical attribute (CPX), purple hair (CPH), tattoos (CPT) or a Liverpool English accent (CPA). Assessors were randomly assigned to watch five videos including the “clear pass” candidate without an attribute and one of the “clear pass” candidates with an attribute and asked to give an overall global grade for each candidate. We compared the global grades for the clear pass candidates with and without attributes.\ud \ud Results \ud Ninety-eight assessors were included in the analysis. The total scores for the candidates with stereotyped attributes were not significantly lower than the candidate with no attribute. Assessors showed moderate levels of agreement between the global grades awarded for all the candidates. The global grades awarded to candidate with a stereotypical attribute were not significantly lower than for those without.\ud \ud Conclusions \ud The presence of tattoos, purple hair, or a regional accent did not systematically negatively influence the grade or score awarded by assessors to candidates in observed clinical examination scenarios.
Databáze: OpenAIRE
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