TY - JOUR
T1 - Twitter Footprint and the Match in the COVID-19 Era
T2 - Understanding the Relationship between Applicant Online Activity and Residency Match Success
AU - Bukavina, Laura
AU - Dubin, Justin
AU - Isali, Ilaha
AU - Calaway, Adam
AU - Mortach, Sherry
AU - Loeb, Stacy
AU - Kutikov, Alexander
AU - Mishra, Kirtishri
AU - Sindhani, Mohit
AU - Adan, Françoise
AU - Ponsky, Lee
N1 - Publisher Copyright:
© 2022 Lippincott Williams and Wilkins. All rights reserved.
PY - 2022/7/1
Y1 - 2022/7/1
N2 - Introduction:The dramatic reduction of clinical and research activities within medical and surgical departments during COVID-19, coupled with the inability of medical students to engage in research, away rotations and academic meetings, have all posed important implications on residency match.Methods:Using Twitter application programming interface available data, 83,000 program-specific and 28,500 candidate-specific tweets were extracted for the analysis. Applicants to urology residency were identified as matched vs unmatched based on 3-level identification and verification. All elements of microblogging were captured through Anaconda Navigator. The primary endpoint was residency match, assessed as correlation to Twitter analytics (ie retweets, tweets). The final list of matched/unmatched applicants through this process was cross-referenced with internal validation of information obtained from the American Urological Association.Results:A total of 28,500 English language posts from 250 matched and 45 unmatched applicants were included in the analysis. Matched applicants generally showed higher number of followers (median 171 [IQR 88-317.5] vs 83 [42-192], p=0.001), tweet likes (2.57 [1.53-4.52] vs 1.5 [0.35-3.03], p=0.048), and recent and total manuscripts (1 [0-2] vs 0 [0-1], p=0.006); 1 [0-3] vs 0 [0-1], p=0.016) in comparison to the unmatched cohort. On multivariable analysis, after adjusting for location, total number of citations and manuscripts, being a female (OR 4.95), having more followers (OR 1.01), individual tweet likes (OR 1.011) and total number of tweets (OR 1.02) increased overall odds of matching into a urology residency.Conclusions:Our study of the 2021 urology residency application cycle and use of Twitter highlighted distinct differences among matched and unmatched applicants and their respective Twitter analytics, highlighting a potential professional development opportunity offered by social media in underscoring applicants' profiles.
AB - Introduction:The dramatic reduction of clinical and research activities within medical and surgical departments during COVID-19, coupled with the inability of medical students to engage in research, away rotations and academic meetings, have all posed important implications on residency match.Methods:Using Twitter application programming interface available data, 83,000 program-specific and 28,500 candidate-specific tweets were extracted for the analysis. Applicants to urology residency were identified as matched vs unmatched based on 3-level identification and verification. All elements of microblogging were captured through Anaconda Navigator. The primary endpoint was residency match, assessed as correlation to Twitter analytics (ie retweets, tweets). The final list of matched/unmatched applicants through this process was cross-referenced with internal validation of information obtained from the American Urological Association.Results:A total of 28,500 English language posts from 250 matched and 45 unmatched applicants were included in the analysis. Matched applicants generally showed higher number of followers (median 171 [IQR 88-317.5] vs 83 [42-192], p=0.001), tweet likes (2.57 [1.53-4.52] vs 1.5 [0.35-3.03], p=0.048), and recent and total manuscripts (1 [0-2] vs 0 [0-1], p=0.006); 1 [0-3] vs 0 [0-1], p=0.016) in comparison to the unmatched cohort. On multivariable analysis, after adjusting for location, total number of citations and manuscripts, being a female (OR 4.95), having more followers (OR 1.01), individual tweet likes (OR 1.011) and total number of tweets (OR 1.02) increased overall odds of matching into a urology residency.Conclusions:Our study of the 2021 urology residency application cycle and use of Twitter highlighted distinct differences among matched and unmatched applicants and their respective Twitter analytics, highlighting a potential professional development opportunity offered by social media in underscoring applicants' profiles.
KW - internship and residency
KW - social media
KW - urology
UR - https://www.scopus.com/pages/publications/85133286432
U2 - 10.1097/UPJ.0000000000000306
DO - 10.1097/UPJ.0000000000000306
M3 - Article
C2 - 37145779
SN - 2352-0779
VL - 9
SP - 331
EP - 339
JO - Urology Practice
JF - Urology Practice
IS - 4
ER -