2014
DOI: 10.3109/0142159x.2014.930112
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Development of competency models for assessors and simulators in high-stakes selection processes

Abstract: This is the accepted version of the paper.This version of the publication may differ from the final published version. Permanent repository link Q1 AbstractBackground: Selection for entry into UK medical specialty training is a high-stakes, high-volume process. For selection into General Practice, a large number of assessors and simulators are involved in the delivery of the selection centre, which represents the final stage of selection. Aim: In order to standardize and quality-assure assessor and simulator … Show more

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Cited by 5 publications
(5 citation statements)
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References 11 publications
(9 reference statements)
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“…In recent years, extended reality technologies have been emerging within the fourth industrial revolution as tools for simulation-based training (SBT) [ 29 ]. The impact identified is relevant, especially in industrial and medical applications [ 30 ].…”
Section: Theorethical Frameworkmentioning
confidence: 99%
“…In recent years, extended reality technologies have been emerging within the fourth industrial revolution as tools for simulation-based training (SBT) [ 29 ]. The impact identified is relevant, especially in industrial and medical applications [ 30 ].…”
Section: Theorethical Frameworkmentioning
confidence: 99%
“…This study was replicated by Patterson, Tavabie et al (2013) to explore competencies for general practice training which resulted in 11 competency domains, of which empathy and perspectivetaking, communication skills, clinical knowledge and expertise and professional integrity were rated as the most important domains. Patterson et al (2014) extended the competency model approach to examine specific knowledge, skills and attributes associated with the roles of assessors and simulations in the GP selection centers in the United Kingdom. In examining applicants' reactions following the shortlisting stage and after the selection center (interview) stage, Patterson et al (2011) reported that, of all the selection methods, the simulated patient consultation (high-fidelity) undertaken at the selection center was rated as most job-relevant and therefore most valid.…”
Section: Selection Framework Based On Well-defined Criteria With Mulmentioning
confidence: 99%
“…Ten papers reported selection in the context of an assessment or selection center. One article (Patterson et al 2014) was a qualitative study exploring competency models to improve uniformity and calibration of the overall process. Two articles described the Australian GP selection center process, two quantitatively (Roberts et al 2014;Patterson, Rowett, et al 2016) and one qualitatively (Burgess et al 2014), two describing a selection center approach into anesthetics training (Gale et al 2010;Roberts et al 2013), three describing the UK GP selection center approach (Mitchison 2009;Patterson, Baron, et al 2009;Patterson, Lievens, et al 2013) and a systematic review (Patterson, Knight, et al 2016).…”
Section: Selection Framework Based On Well-defined Criteria With Mulmentioning
confidence: 99%
“…Manuscripts in this category suggest that there is a combination of measures such as clerkship grades, test scores, and skills simulations that will predict performance on outcome measures such as Accreditation Council for Graduate Medical Education (ACGME) Milestones or a graduate rank order list (re-ranking at the time of graduation). [16][17][18][19][20][21][22] Manuscripts vary in whether they focus on predictions of success in the specialty overall [20][21][22][23][24][25][26][27][28][29][30][31][32][33][34][35] or specifically within training programs. 16,18,19,[36][37][38][39][40][41] Authors of manuscripts in this category describe priority being given to selecting those who will do well during postgraduate training and also focus on avoiding those who will need remediation or be disruptive to program leadership.…”
Section: Using Available Metrics To Predict Performance In Postgradua...mentioning
confidence: 99%