Social media refers to websites and applications designed to allow the sharing of user‐generated content, such as text, photos, or video. Twitter is one such application, allowing users to upload “tweets” of up to 280 characters that are seen by their “followers” and published within the application for anyone else who is interested. Approximately 5800 tweets are sent every second, and around 326 million people use Twitter every month. Within the medical community, Twitter has been rapidly adopted and is used for education, networking, and sharing research. Many medical journals have a social media presence. The Journal of Inherited Metabolic Disease (JIMD) joined Twitter in March 2016 (@JIMD_editors). In September 2019, the role of Social Media Editor was created with an increased emphasis on trying to use social media, especially Twitter, to promote the journal and the speciality.

In the last 3 months of 2019, the @JIMD_editors account shared 566 tweets, approximately 6.2 tweets a day, with each tweet seen by an average of 670 people (a total of 380 200 “impressions”). Links shared within those tweets were clicked on over 2000 times, bringing people to journal content that they might otherwise never have seen. With new methods of sharing research come different ways to measure the impact of what is published. Altmetrics, or article‐level metrics, have been proposed as an alternative or adjunct to more traditional citation impact metrics. Altmetrics do not include citations but calculate scholar impact based on social media sharing, news reports, and the appearance of articles in online reference managers. Wiley, the publisher that is now home to JIMD and JIMD Reports, is affiliated with Altmetric, one of the most established altmetric platforms.

At the end of 2019, Altmetric shared its top 100 papers of the year, drawing on 2.7 million research outputs with 62.5 million combined mentions. This helps to demonstrate how these new metrics can be used to highlight important papers, such as a comprehensive study of autism rates looking at 650 000 children and considering the impact of the measles, mumps, and rubella (MMR) vaccine.1 However, the metric is also heavily skewed towards “popular” work, with the satirical paper “Parachute use to prevent death and major trauma when jumping from aircraft: a randomised controlled trial” from the Christmas edition of the British Medical Journal featured in the top 10.2

Within the immediate sphere of Inherited Metabolic Disease teams, Twitter use appears to be low. At the 2018 annual meeting, for example, only around 200 related tweets were sent by just 36 users. However, social media can be used to bring work from the journal to a wider audience, and this is something that we saw with the paper “Proposal for a simplified classification of IMD based on a pathophysiological approach: a practical guide for clinicians by Saudubray et al.3” The link to this paper has been shared in 162 tweets from 91 different accounts with a combined reach (the sum of the follower counts) of over 140 000 users. It has an Altmetric attention score of 61, placing it in the top 5% of over 14 000 000 tracked articles to date. A total of 170 users have clicked on links shared directly from the JIMD Twitter account to visit the journal site.

The interest in this paper likely reflects the confusion that metabolic medicine engenders in clinicians. Saudubray et al's3 proposal came a year after Ferreira et al published a nosology of inborn errors, identifying 1015 well‐characterised errors in addition to a further 111 conditions that may be inborn errors.4 In 2014 the Society for the Study of Inborn Errors of Metabolism published a disease classification, featuring 487 Inborn Errors in 86 disease groups. Even allowing for variation based on classification strategy, it is clear that the number of diagnoses is growing, as is the number of disease groups. For those working within the field, the progress is breath‐taking, but for those clinical staff not directly involved in inborn errors, this growing complexity can be incomprehensible.

The pathways and significance of inborn errors can seem especially obtuse at times. Clinicians may only see patients with these conditions infrequently, but their encounters are often at key times, such as before diagnosis or during an acute deterioration. Therefore, for many, the important areas of knowledge around inborn errors are when to suspect them and what to expect from a given disease if one knows what he or she is dealing with. This is the attraction of Saudubray et al's proposal—those 1000 or so conditions are divided into just three groups with some further subdivision based on what a given molecule is doing within the body.3 The simplified classification has captured interest because it provides a framework for healthcare professionals to understand a diverse group of conditions that they may encounter infrequently, giving rapid insight into clinical presentations and treatment possibilities. The high Altmetric score and the number of “URL clicks” show the efficacy of using social media as a tool to disseminate new ideas and the enthusiasm for educational work with a wider appeal.

The authors do acknowledge that this work is not definitive and that conditions may straddle different groups. As always, classification of complex disorders is not an easy task, and with the rapid expansion of new disorders, our metabolic community will keep on working on consensus and harmonising nosology approaches. The authors expect follow up on this exciting topic, so please stay tuned!