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Leveraging artificial intelligence for resident recruitment

The researchers of this study aimed to evaluate candidates for competitive medical residencies beyond their academic performance scores. They analyzed the personal statements of medical students applying to a general surgery residency and compared them to personal statements of current general surgery residents using text analytic methods.

By assessing candidates' personality and drives through their language, researchers sought to better inform who they are as an individual and to help gauge their fit in a particular residency. Results revealed that residency applicants demonstrated more self-assurance and trust but less stress-proneness and impulsiveness in their language than the general population, while current residents exhibited more emotional awareness and organization but less self-assurance and power-drive.

These findings offer empirical insights and implications for facilitating candidate evaluation, highlighting the importance of assessing candidates' language beyond their academic performance scores. By evaluating candidates' language, we can better understand their traits and motivations, providing a more comprehensive evaluation of their fit for a particular residency


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