ArticleNeurology. Education2023
Education Research: The Development and Utilization of a Virtual Twitter Onboarding Curriculum for Neurologists, Trainees, and Students: A Prospective Study.
Article in Neurology. Education, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- The Age of Artificial Intelligence in Neurologic Education: Where Are We Going With Educational Technology Today?Neurology. Education · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and Objectives: Social media has increased in popularity among neurologists in the past few years without a parallel increase in training opportunities to learn how to use social media effectively. This study tests the feasibility of an asynchronous, virtual onboarding curriculum using Twitter as a tool for professional development for neurologists and neurology trainees. Methods: Neurologists and neurology trainees were recruited virtually through email, Twitter, and a listserv of the American Academy of Neurology (Synapse). Participants were excluded if they had a professional Twitter account or lived outside the United States. Participants performed all study procedures virtually, including a baseline survey followed by three 30-minute modules: introduction to NeuroTwitter, peer learning, and academic scholarship on Twitter. A postmodule survey was completed to provide postprogram curriculum feedback. Newly created Twitter accounts were followed for 3 months to track Twitter engagement. Results: Sixty-one participants were screened, and 50 were eligible to enroll. Forty-five (90%) participants completed a consent form and baseline survey. Twenty-seven participants completed all 3 modules, and 26 (52%) completed the postmodule survey. Participants indicated that there was a role for social media in neurology but had minimal to no training on how to use it effectively. Twitter knowledge postmodule completion increased by a median of 2 of 15 questions, with a range of -1 to +5. There were no technical barriers with a virtual-based curriculum, and participants were able to access the modules and surveys successfully. Ninety-six percent of participants would recommend the modules to colleagues. Thirty new Twitter accounts were created with an average of 33 followers, 59 following, 16 tweets, and 61 likes at 4 months. Discussion: This study highlights the feasibility of virtual asynchronous content leading to an increase in Twitter knowledge among neurologists who completed our modules, though limited by a high dropout rate. Recruitment for virtual asynchronous modules was an effective approach to deliver informative and interactive content for neurologists. Further studies are needed to determine optimal content and length to promote long-term engagement with Twitter.
Identifiers
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Registered trials
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.