The abstract is a crucial element almost always included in papers. It summarizes the article’s content and functions as a bibliographic guide for readers looking for a specific study. In other words, abstracts should answer the question, “What is this paper about?”
In addition to summarizing the article, the abstract often provides insights into the methods, results, and conclusions of the research conducted.
Many scientific papers are behind paywalls and accessing them is often costly. However, abstracts are typically available for free.
Academic articles and abstracts undergo several editorial and scientific reviews, which leads many to expect that abstracts faithfully represent the content of the articles. Unfortunately, this isn’t always the case.
In the late 1990s, a group of researchers examined the prevalence of inconsistencies between article abstracts and their actual content. The team analyzed more than 260 articles (44 pieces from six leading scientific journals) published in 1996 and 1997. Researchers identified two main types of errors in the abstracts: inconsistencies with the article’s body and omissions of relevant information.
Although the study’s results varied across different journals, they showed that between 18% and 68% of articles had issues with their abstracts. Researchers concluded that inconsistent or missing information was “common, even in large-circulation general medical journals.” Their findings were published in 1999 in JAMA, one of the journals they had analyzed.
25 years have passed since the publication of the JAMA study, and almost 30 years since some of the articles were released. Science has evolved significantly since then. However, subsequent studies suggest that the problem of abstract inconsistencies remains prevalent.
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In 2016, a different group of researchers compiled and analyzed studies in this field and published their findings in BMC Medical Research Methodology. Their literature review revealed that the level of inconsistency across these studies had a median of 39%, ranging from 4% to 78%.
Recognizing that not all errors carry the same weight, the review also distinguished between severe inconsistencies and milder ones. In this case, the level of inconsistency was somewhat lower but still significant, at a median of 19%.
Subsequent studies, including one recently published in The American Journal of Surgery, continue to highlight this trend in the scientific literature.
So, what’s happening? Are scientists misrepresenting their data, or is this just a substantial accumulation of errors? Article abstracts play a crucial role in receiving citations from other scholarly articles, making this metric vital for evaluating scientific work. However, the publication of an article can sometimes hinge on the novelty of its results.
This creates an incentive to emphasize certain findings and put them into context later. A non-significant result might lead journal editors or future readers to lose interest in the article, regardless of the study’s overall quality. This phenomenon contributes to publication bias, where studies with positive results are overrepresented in scientific literature due to the interest in novelty.
Academic clickbait. Experts have also scrutinized article titles in recent years. An eye-catching headline can significantly influence a reader’s interest in a study, whether consciously or unconsciously.
A 2016 study published in Frontiers in Psychology examined this phenomenon and investigated how headline phrasing impacts a study’s reach.
Author Gwilym Lockwood analyzed more than 2,000 academic articles and found that titles phrased positively tended to achieve better metrics than average. In contrast, papers using puns performed worse. Meanwhile, titles framed as questions didn’t significantly deviate from the average.
Abstracts are just one issue among many that scientific publishers contend with. Publishers face several pressures from controversies like the “research article mill” and challenges related to publishing fees or access to content.
AI presents both a problem and a potential solution. Authors can instruct programs like ChatGPT to write a paper for them. However, scientific publishers have also started incorporating AI tools in the publishing process. This technology can generate more “objective” abstracts and detect and correct possible errors and inconsistencies between texts and abstracts.
Image | Glenn Carstens-Peters
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