A Brief Overview of Spin: The Twists and Turns of Scientific Writing

This blogpost was written by Tijn van Hoesel. Tijn is a PhD student of our meta-research group and started his PhD in September 2024. During his PhD, he will be working on investigating the impact of spin and other reporting practices in scientific research with his supervisors Marjan Bakker and Bennett Kleinberg.

We have all been there, you are reading an abstract describing an interesting study that seems very convincing and has found some promising and (of course, most importantly!) significant results. However, after having read the rest of the paper, it all seem a lot less convincing, promising, and significant. Maybe the abstract only states the significant results, while in the full text five more outcomes are described for which no significant effect was found. Or maybe, after reading the sample details, you realize that the recommendations for practice stated in the abstract are not as ‘widely applicable’ as they are made out to be. Either way, it seems like you have just fallen victim to spin. 

The word ‘spin’ in a social and behavioural context is commonly associated with the world of politics and its interaction with the media (Gaber, 1999; Grattan, 1998). Spin, in the political context, can generally be defined as “a favourable bias” (Andrews, 2006, p. 32). Moreover, spin can be seen as a part of propaganda and as a conscious, deliberate strategy of communication applied to achieve a certain goal (Macnamara, 2022). Often, in politics and public communication, the goal is to influence public opinion about a given situation/event, topic, person, or organization. Usually, the person who puts a favourable bias on the information (i.e., ‘spins’ the information) is referred to as a spin doctor. They may use various spin strategies like cherry picking, misrepresenting facts/numbers/quotes, presenting speculations as facts, burying bad news with other news, or reporting only to like-minded journalists. 

Spin in Scientific Writing 
Although more well-known in politics, the use of spin is a communication strategy that may be applied, whether deliberately or not, by people in all kinds of contexts. One such context in which proper communication of information is crucial, is scientific research. Allegedly, the first mention of spin in scientific writing was in a paper by Horton (1995), who described the use of hyperbole and “the conscious and unconscious tricks of authorial rhetoric” (p. 985) in scientific papers. More specifically, Horton mentions “the manipulation of language to convince the reader of the likely truth of a result” (p. 985). In his paper, Horton breaks down the discussion section of a paper and focusses on its linguistic features and the structure of the argumentation. His idea of spin seems to mostly revolve around the specific use of language. 

About 15 years later, Boutron and colleagues (2010) conducted what is now the most cited investigation into spin in medical literature and defined it as: “specific reporting that could distort the interpretation of results and misleading readers” (p. 2058). Examples of such spin practices are (1) selective/strategic reporting of results throughout the report, (2) focussing on secondary analyses or sub-/within-group analyses, (3) claiming equivalence for statistically nonsignificant results, (4) use of (hype) words like “important”, “novel”, or “crucial” (i.e., linguistic spin), and (5) unsupported extrapolation of findings to other situations and/or populations. Compared to Horton (1995), Boutron and colleagues (2010) widen the concept of spin to include non-linguistic elements. Here, it is important to note that there are different ideas about what constitutes spin in scientific writing and how it should be defined. 

The spin practices in scientific writing have some similarities with the spin strategies used in politics and public communications. Both involve the selective presentation and/or misrepresentation of information and making unsupported claims. However, an important difference between the two is that the use of spin in politics is generally considered a conscious and planned effort, while the use of spin in scientific writing is believed to not necessarily be a conscious decision. To indicate this important difference, I prefer the term spin ‘practices’ when talking about scientific writing as opposed to spin ‘strategies’, which is often used in politics and public communication contexts. 

Context of Spin Research 
The use of spin practices in scientific writing has mostly been of interest to (meta-) scientists in the field of (bio)medicine. Most of their research focusses on the presence of spin practices in two types of studies: (1) randomized controlled trials (e.g., Arunachalam et al., 2017; Gewandter et al., 2015; Guo et al., 2023) or (2) systematic reviews and/or meta-analyses (e.g., Balcerak et al., 2021; Corcoran et al., 2022; Flores et al., 2021). I believe this focus can partially be explained by the existence of well-known and widely-applied reporting guidelines for these types of studies, which are the CONSORT (Moher et al., 2010) and the PRISMA (Page et al., 2021) guidelines, respectively. These guidelines provide a structured way to evaluate the quality of reporting for a particular type of study, allowing deviations from those guidelines to be labelled as ‘spin practices’. Additionally, a clear and extensive classification of spin in systematic reviews (SR) and meta-analyses (MA) was developed by Yavchitz and colleagues (2016), making it easy for other researchers to evaluate spin in SRs and MAs in their own sub-field of interest. 

Despite this focus, it is good to note that other types of studies are not entirely neglected. A number of studies investigated spin in nonrandomized trials (e.g., Lazarus et al., 2015), diagnostic accuracy studies (e.g., Ochodo et al., 2013), and clinical prediction model studies (e.g., Andaur Navarro et al., 2023). A very recent development with regards to clinical prediction model studies, is a framework for identifying and evaluating spin that has been developed by Andaur Navarro and colleagues (2024). In their framework, the authors identified several spin practices and facilitators. Some of which are specific for prediction model research (e.g., “Ignoring the risk of optimism in model performance” p. 5), while others are also applicable to a wider range of study types (e.g., “Unsubstantiated claims of clinical usefulness are reported” p. 8). 

Although spin can occur in all parts of a paper, it is the abstract that has gotten a lot, if not most, of the attention in spin research. One of the main interest lies in the discrepancies between what has been reported in the results section of the full-text and what is reported and concluded in the abstract. It is argued that abstracts play an important role in science communication, which justifies the focus on abstracts found in spin research. This justification is supported by a recent study which found that 98.6% of health academics and researchers read the abstract first and over 80% of researchers rated the abstract as important or very important (Shiely et al., 2024). Furthermore, it has been found that clinicians also heavily rely on abstracts for information due to a lack of time to read the full article or the fact that the full article is behind a paywall (Khaliq et al., 2012; Saint et al., 2000). It goes without saying that the possible consequences of misinterpreted results and unsubstantiated claims of effectiveness can be severe, especially considering RCT’s and applications in clinical practice. 

Spin Research Findings 
Most studies investigating spin practices are mainly interested in measuring the prevalence of these practices. In a systematic review across 31 studies, it was found that the prevalence of spin in abstracts ranged from 9.6% to 83.6% and that the prevalence of spin in the main text ranged from 18.9% to 100% (Chiu et al., 2017). These wide ranges of prevalence are most likely due to the varying definitions and operationalisations of spin used and the varying sub-fields investigated across the different studies. More recent studies, not captured by this systematic review, have found comparable prevalence rates: 70% of papers evaluating ovarian cancer biomarkers (Ghannad et al., 2019), 46% of abstracts and 38% of full-text reports of systematic reviews of diagnostic accuracy studies in high-impact journals (McGrath et al., 2020), 67% of abstracts of systematic reviews and meta-analyses on cannabis use disorder (Corcoran et al., 2022), and 78% of abstracts of papers describing RCTs in sleep medicine (Guo et al., 2023). 

Besides studies investigating the prevalence of spin, there have also been a couple of studies investigating other phenomena in relation to spin practices. For example, it was found that spin practices were not significantly related to either non-financial conflict of interest or industry funding (Jellison et al., 2019; Lieb et al., 2016). There also has been some interest in the interplay between spin practices and citation bias, where it is suggested that citation bias is less severe for negative studies that are positively spun (De Vries et al., 2016, 2017; Duyx et al., 2017). Other studies have explored the effects that spin practices might have on readers and their interpretation of the presented findings. For example, there is mixed evidence on the effect of spin on the perception of findings of RCTs. Where some studies find that spin in abstracts significantly increases the reader’s perceived effectiveness of a treatment (Boutron et al., 2014; Jankowski et al., 2022), other studies find no such effect (Shinohara et al., 2017; Van Hoesel & Bakker, 2024). These same studies found similarly mixed results regarding the effect of spin on readers’ interest in reading the full-text article, and their interest in extending the line of research for the investigated treatment. 

What’s next? 
You may have noticed that few firm conclusions can be reached from the current state of spin research and that those which can be reached are usually applicable only to specific situations (e.g., RCT’s with non-significant primary outcomes). Needless to say, more research is needed in order to establish the effects of spin and its relation to other (meta-scientific) concepts. I think that, within (bio)medicine, research on spin practice should more often consider other types of studies and that an effort should be made to come to a clear definition of spin. Furthermore, I personally believe a lot can also be gained from previous meta-scientific research in other disciplines, such as the social sciences. These disciplines investigate other meta-scientific concepts that have obvious overlap with the concept of spin, like questionable research practices (John et al., 2012; Nagy et al., 2024). This way, hopefully, we can get more insight into spin and its consequences on science and practice. Until then, we are probably best off not taking abstracts at face value and remaining critical. 

References 

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