Evidence map›Paper›PMID 40206719›Full record

ArticleMayo Clinic proceedings. Digital health2023

Internal Medicine Recruitment in the Age of Social Media: Strategies to Target Residency Applicants.

Thomas M Li, Danielle L Tepper, Alfred P Burger, Matthew A Weissman

Abstract read
In one paragraph

Article in Mayo Clinic proceedings. Digital health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Thomas M LiIcahn School of Medicine at Mount Sinai, New York, New York.
Danielle L TepperDepartment of Internal Medicine, Mount Sinai Beth Israel, New York, New York.
Alfred P BurgerIcahn School of Medicine at Mount Sinai, New York, New York.
Matthew A WeissmanIcahn School of Medicine at Mount Sinai, New York, New York.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Applicants in the 2020-2021 residency interview cycle were unable to attend in-person meetings or visit prospective sites of future training. Instead, they relied on printed or digital media for information. Over the past few years, many graduate medical education programs have increased the use of social media to disseminate information to attract and retain faculty, staff, and trainees. Previous studies have quantified the relative presence of social media in residency programs, but there has been limited work on the assessment of social media platforms that applicants use to evaluate internal medicine programs. To more effectively target residency applicants through social media, we sought to understand the use of social media in general and specifically in the residency application process of an incoming intern class recruited during the 2020-2021 interview season. We administered an anonymous survey after matching to a single institution's 2021 class of 40 internal medicine interns in both categorical and preliminary tracks. The group surveyed came from US medical schools (MD and DO degrees) and international programs. The group surveyed comprised 66% women and 16.7% underrepresented groups as defined by Association of American Medical Colleges guidelines. Our data found that the internal medicine residency applicants mostly used hospital websites and Instagram to evaluate programs. Twitter, which is often assumed to be highly used in academic circles, was rarely used. Our work suggests that a better understanding of the use of digital resources by applicants can allow programs to reach residency applicants in a meaningful way.

Identifiers

PMID40206719
PMCPMC11975680

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.