Purpose: Evaluating medical school selection tools is vital for evidence-based student selection. With previous reviews revealing knowledge gaps, this meta-analysis offers insights into the effectiveness of these selection tools. Methods: A systematic review and meta-analysis were conducted applying the following criteria: peer-reviewed articles available in English, published from 2010 and which include empirical data linking performance in selection tools with assessment and dropout outcomes of undergraduate entry medical programs. Systematic reviews, meta-analyses, general opinion pieces, or commentaries were excluded. Effect sizes (ESs) of the predictability of academic and clinical performance within and by the end of the medicine program were extracted, and the pooled ESs were presented. Results: Sixty-seven out of 2,212 articles were included, which yielded 236 ESs. Previous academic achievement predicted medical program academic performance (Cohen’s d=0.697 in early program; 0.619 in end of program) and clinical exams (0.545 in end of program). Within aptitude tests, verbal reasoning and quantitative reasoning predicted academic achievement in the early program and in the last years (0.704 & 0.643, respectively). Overall aptitude tests predicted academic achievement in both the early and last years (0.550 & 0.371, respectively). Neither panel interviews, multiple mini-interviews, nor situational judgement tests (SJT) yielded statistically significant pooled ES. Conclusion Current evidence suggests that learning outcomes are predicted by previous academic achievement and aptitude tests. The predictive value of SJT and topics such as selection algorithms, features of interview (e.g., content of the questions) and the way the interviewers’ reports are used, warrant further research.

Purpose: Evaluating medical school selection tools is vital for evidence-based student selection. With previous reviews revealing knowledge gaps, this meta-analysis offers insights into the effectiveness of these selection tools. Methods: A systematic review and meta-analysis were conducted applying the following criteria: peer-reviewed articles available in English, published from 2010 and which include empirical data linking performance in selection tools with assessment and dropout outcomes of undergraduate entry medical programs. Systematic reviews, meta-analyses, general opinion pieces, or commentaries were excluded. Effect sizes (ESs) of the predictability of academic and clinical performance within and by the end of the medicine program were extracted, and the pooled ESs were presented. Results: Sixty-seven out of 2,212 articles were included, which yielded 236 ESs. Previous academic achievement predicted medical program academic performance (Cohen’s d=0.697 in early program; 0.619 in end of program) and clinical exams (0.545 in end of program). Within aptitude tests, verbal reasoning and quantitative reasoning predicted academic achievement in the early program and in the last years (0.704 & 0.643, respectively). Overall aptitude tests predicted academic achievement in both the early and last years (0.550 & 0.371, respectively). Neither panel interviews, multiple mini-interviews, nor situational judgement tests (SJT) yielded statistically significant pooled ES. Conclusion Current evidence suggests that learning outcomes are predicted by previous academic achievement and aptitude tests. The predictive value of SJT and topics such as selection algorithms, features of interview (e.g., content of the questions) and the way the interviewers’ reports are used, warrant further research.

Purpose: Evaluating medical school selection tools is vital for evidence-based student selection. With previous reviews revealing knowledge gaps, this meta-analysis offers insights into the effectiveness of these selection tools. Methods: A systematic review and meta-analysis were conducted applying the following criteria: peer-reviewed articles available in English, published from 2010 and which include empirical data linking performance in selection tools with assessment and dropout outcomes of undergraduate entry medical programs. Systematic reviews, meta-analyses, general opinion pieces, or commentaries were excluded. Effect sizes (ESs) of the predictability of academic and clinical performance within and by the end of the medicine program were extracted, and the pooled ESs were presented. Results: Sixty-seven out of 2,212 articles were included, which yielded 236 ESs. Previous academic achievement predicted medical program academic performance (Cohen’s d=0.697 in early program; 0.619 in end of program) and clinical exams (0.545 in end of program). Within aptitude tests, verbal reasoning and quantitative reasoning predicted academic achievement in the early program and in the last years (0.704 & 0.643, respectively). Overall aptitude tests predicted academic achievement in both the early and last years (0.550 & 0.371, respectively). Neither panel interviews, multiple mini-interviews, nor situational judgement tests (SJT) yielded statistically significant pooled ES. Conclusion Current evidence suggests that learning outcomes are predicted by previous academic achievement and aptitude tests. The predictive value of SJT and topics such as selection algorithms, features of interview (e.g., content of the questions) and the way the interviewers’ reports are used, warrant further research.

Purpose: It aimed to compare the use of the tele-objective structured clinical examination (teleOSCE) with in-person assessment in high-stakes clinical examination so as to determine the impact of the teleOSCE on the assessment undertaken. Discussion follows regarding what skills and domains can effectively be assessed in a teleOSCE. Methods: This study is a retrospective observational analysis. It compares the results achieved by final year medical students in their clinical examination, assessed using the teleOSCE in 2020 (n=285), with those who were examined using the traditional in-person format in 2019 (n=280). The study was undertaken at the University of New South Wales, Australia. Results: In the domain of physical examination, students in 2020 scored 0.277 points higher than those in 2019 (mean difference=–0.277, P<0.001, effect size=0.332). Across all other domains, there was no significant difference in mean scores between 2019 and 2020. Conclusion The teleOSCE does not negatively impact assessment in clinical examination in all domains except physical examination. If the teleOSCE is the future of clinical skills examination, assessment of physical examination will require concomitant workplace-based assessment.

The coronavirus disease 2019 (COVID-19) pandemic has required educators to adapt the in-person objective structured clinical examination (OSCE) to online settings in order for it to remain a critical component of the multifaceted assessment of a student’s competency. This systematic scoping review aimed to summarize the assessment methods and validity and reliability of the measurement tools used in current online OSCE (hereafter, referred to as teleOSCE) approaches. A comprehensive literature review was undertaken following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines. Articles were eligible if they reported any form of performance assessment, in any field of healthcare, delivered in an online format. Two reviewers independently screened the results and analyzed relevant studies. Eleven articles were included in the analysis. Pre-recorded videos were used in 3 studies, while observations by remote examiners through an online platform were used in 7 studies. Acceptability as perceived by students was reported in 2 studies. This systematic scoping review identified several insights garnered from implementing teleOSCEs, the components transferable from telemedicine, and the need for systemic research to establish the ideal teleOSCE framework. TeleOSCEs may be able to improve the accessibility and reproducibility of clinical assessments and equip students with the requisite skills to effectively practice telemedicine in the future.

Purpose: It aimed to compare the use of the tele-objective structured clinical examination (teleOSCE) with in-person assessment in high-stakes clinical examination so as to determine the impact of the teleOSCE on the assessment undertaken. Discussion follows regarding what skills and domains can effectively be assessed in a teleOSCE. Methods: This study is a retrospective observational analysis. It compares the results achieved by final year medical students in their clinical examination, assessed using the teleOSCE in 2020 (n=285), with those who were examined using the traditional in-person format in 2019 (n=280). The study was undertaken at the University of New South Wales, Australia. Results: In the domain of physical examination, students in 2020 scored 0.277 points higher than those in 2019 (mean difference=–0.277, P<0.001, effect size=0.332). Across all other domains, there was no significant difference in mean scores between 2019 and 2020. Conclusion The teleOSCE does not negatively impact assessment in clinical examination in all domains except physical examination. If the teleOSCE is the future of clinical skills examination, assessment of physical examination will require concomitant workplace-based assessment.