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Facebook, Social Media and Your Medical School Application

Medical School Application FacebookA study by Carl Schuman of the University of Miami confirmed what you should already know: Facebook can ruin your chances of getting into medical school! Be sure to make your Facebook, Twitter, etc accounts private before applying. Don’t post public pictures and be sure your accounts can’t be seen by the public. Admissions committee members will Google you, Facebook you, etc to find out your dirty secrets. Be careful!

The abstract of the study published in BMJ is as follows:
Background Social networking (SN) has become ubiquitous in modern culture. The potential consequences of revealing personal information through SN websites are not fully understood.

Objective To assess familiarity with, usage of, and attitudes towards, SN websites by admissions offices at US medical schools and residency programmes.

Methods A 26-question survey was distributed in autumn 2009 to 130 US medical school admissions officers and 4926 residency programme directors accredited by the Accreditation Council for Graduate Medical Education.

Results A total of 600 surveys were completed, with 46 (8%) respondents who self-identified as reviewing only medical school applications, 511 (85%) who reported reviewing residency programme applications and 43 (7%) who reported reviewing both. 90/600 (15%) medical schools or programmes maintain profiles on SN websites and 381/600 (64%) respondents reported being somewhat or very familiar with searching individual profiles on SN websites. While a minority of medical schools and residency programmes routinely use SN websites in the selection process (53/600; 9%), more than half of respondents felt that unprofessional information on applicants’ SN websites could compromise their admission into medical school or residency (315/600; 53%).

Conclusions SN websites will affect selection of medical students and residents. Formal guidelines for professional behaviour on SN websites might help applicants avoid unforeseen bias in the selection process.