Video abstracts and plain language summaries are more effective than graphical abstracts and published abstracts.

<h4>Background</h4>Journals are trying to make their papers more accessible by creating a variety of research summaries including graphical abstracts, video abstracts, and plain language summaries. It is unknown if individuals with science, science-related, or non-science careers prefer different summaries, which approach is most effective, or even what criteria should be used for judging which approach is most effective. A survey was created to address this gap in our knowledge. Two papers from Nature on similar research topics were chosen, and different kinds of research summaries were created for each one. Questions to measure comprehension of the research, as well as self-evaluation of enjoyment of the summary, perceived understanding after viewing the summary, and the desire for more updates of that summary type were asked to determine the relative merits of each of the summaries.<h4>Results</h4>Participants (n = 538) were randomly assigned to one of the summary types. The response of adults with science, science-related, and non-science careers were slightly different, but they show similar trends. All groups performed well on a post-summary test, but participants reported higher perceived understanding when presented with a video or plain language summary (p<0.0025). All groups enjoyed video abstracts the most followed by plain language summaries, and then graphical abstracts and published abstracts. The reported preference for different summary types was generally not correlated to the comprehension of the summaries. Here we show that original abstracts and graphical abstracts are not as successful as video abstracts and plain language summaries at producing comprehension, a feeling of understanding, and enjoyment. Our results indicate the value of relaxing the word counts in the abstract to allow for more plain language or including a plain language summary section along with the abstract.

Abstract licence: CC BY

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.