Readability: Drawing a Map in Your Reader’s Mind

This article was originally published in the Journal of Medical Writing, Volume 33, Issue 2, 2024 as one of the winning essays of the Geoff Hall Scholarship Essay Competition by the European Medical Writers Association.

Reading a scientific document can feel like a treasure hunt: Precious knowledge is hidden within the article, waiting to be unraveled. However, its map (the text itself) may sometimes be quite confusing.

Our brain won’t invest excessive effort in deciphering it, at least not without some nudging. Even though it enjoys a good challenge, it is an efficient energy-saving machine.

Let us first agree with our brains that reading is no simple feat. It is a relatively recent skill, so much so that it lacks a dedicated brain region, and evolution built it upon areas for visual processing [1]. Yes, our visual system has been literally recycled for reading.

It takes us years of practice to automatize the decoding of written material – although you might have forgotten those challenging childhood days. Still, one out of five adults in Europe has poor literacy, meaning that they struggle with basic text comprehension [2].

Unfortunately, these numbers get worse for scientific manuscripts, the pinnacle of complex written information. Given that they are crucial for condensing and sharing our knowledge, shouldn’t they be easy to read?

Researchers have -obviously- come up with a term for how easy content is to read: readability. In a nutshell, high readability means that a text is clear, concise, and easy to understand, whereas low readability indicates the opposite.

Quantifying and researching this property, much as reading itself, can be challenging. While there are more than 200 traditional formulas, none of them is specifically designed for scientific documents [3]. Most commonly used metrics (like the Flesch Reading-Ease score) are primarily based on simple features like sentence and word length [4], not even considering linguistic factors such as semantic relevance or text coherence [5].

Besides, they do not account for the neurocognitive aspects of reading – our brains are still out of the loop.

Easy-to-read scientific articles tend to have a higher success rate, and, surprisingly, a higher chance of going viral [6]. Yet readability goes beyond improving citation rates. It is a key weapon against two major enemies of science: Misinformation and reproducibility issues.

The first comes in many flavors, particularly when laypeople turn to secondary sources because the original is too difficult to comprehend, potentially resulting in distortions or sensationalism. Most of us can relate to this to some degree.

But wait, how is readability related to the infamous reproducibility crisis?  

Overall scientific literature is becoming more complex over time [7]; if researchers struggle to understand a paper, it might hinder its reproducibility.  This concern is not exclusive to humans: in programming-related areas[8], computers need machine-readable content to ensure replicable results.

Clear documents are deeply intertwined with the integrity and utility of research. Plus, they are good for our brains: they require minimal cognitive effort to be decoded.

Most writing guidelines oversimplify how the brain reads, focusing mostly on grammar, even though linguistic complexity alone has a minor effect on scientific impact [9].

So, can scientific documents be more brain-friendly? They can, if we turn them into brain maps.

While reading, our visual system connects the shape of letters with speech sounds [1]. However, it is significantly more efficient at building spatial blueprints – it is its primary job. We can exploit this feature by incorporating descriptive diagrams. They shouldn’t be limited to the results section alone! The more we use to support an idea, the easier it becomes to grasp.

Visuals are a powerful tool, especially when combined with text anchors: phrases, headlines, and symbols that act as reference points, creating a layout to spatially organize the flow of information. Yet, with great power comes great responsibility. For instance, it’s easy to misuse color scales, leading to misinterpretation [10]. The solution is to always use reliable scientific color maps, such as those created by the researcher and designer Fabio Crameri [11].

Moreover, we can leverage another type of brain map, one we have employed since long before the invention of writing: stories. They glue every piece of information together, forming schemes that make it easier to recall and pass down. Today, we call this “Storytelling”, the art of communicating events or ideas through engaging narratives.

Storytelling is great for readability because it harnesses the brain’s natural affinity for stories. Just as we can effortlessly remember the particulars of a seven-book series such as Harry Potter, storytelling can convey complex data in a memorable manner. By converting scientific articles into compelling narratives, we transform the scientific journey into an enjoyable experience.

A short note on the multilingual brain: While science is predominantly written in English, this is not the first language of many authors and readers. This is highly relevant because our brains are unconsciously drawn by the beauty of our native languages to express ideas, which sometimes results in content that is complicated to read.

For instance, as a non-native English speaker, I often find myself crafting catchy sentences, only to realize that they fall flat or sound awkward – even if they are grammatically correct. 

On the other hand, we should bear in mind that slang or ‘excessively English’ nuances can be difficult to grasp. For example, phrasal verbs might be harder to understand because their concept (changing a verb’s meaning by adding a particle) is not conceivable in many languages. In this case, we can enhance the text flow by simply using whole verbs when possible.

This ‘readability awareness’ bridges language barriers, encouraging more accessible and inclusive manuscripts.

In a world where knowledge is our ultimate treasure, we cannot afford unreadable maps.

Scientific documents can be easy to read if they speak plainly and effectively, acknowledging the diverse linguistic backgrounds of the audience. Let’s move beyond grammar and readability formulas: by integrating graphic techniques and storytelling into our skill set, we can help readers navigate toward a better understanding.

It’s all about drawing the right map in our readers’ minds.

References:

1. S. Dehaene, Reading in the brain: The new science of how we read. Penguin, 2010.
2. PIAAC – Programme for International Assessment of Adult Competencies, “Technical Report of the Survey of Adult Skills t (3rd Edition),” 2019. [Online]. Available: https://www.oecd.org/skills/piaac/publications/PIAAC_Technical_Report_2019.pdf
3. T. Vergoulis, I. Kanellos, A. Tzerefos, S. Chatzopoulos, T. Dalamagas, and S. Skiadopoulos, “A Study on the Readability of Scientific Publications,” in Digital Libraries for Open Knowledge, A. Doucet, A. Isaac, K. Golub, T. Aalberg, and A. Jatowt, Eds., in Lecture Notes in Computer Science. Cham: Springer International Publishing, 2019, pp. 136–144. doi: 10.1007/978-3-030-30760-8_12.
4. R. G. Benjamin, “Reconstructing Readability: Recent Developments and Recommendations in the Analysis of Text Difficulty,” Educ. Psychol. Rev., vol. 24, no. 1, pp. 63–88, Mar. 2012, doi: 10.1007/s10648-011-9181-8.
5. “Moving beyond classic readability formulas: new methods and new models – Crossley – 2019 – Journal of Research in Reading – Wiley Online Library.” https://onlinelibrary.wiley.com/doi/full/10.1111/1467-9817.12283 (accessed Sep. 20, 2023).
6. M. Guerini, A. Pepe, and B. Lepri, “Do Linguistic Style and Readability of Scientific Abstracts Affect their Virality?,” Proc. Int. AAAI Conf. Web Soc. Media, vol. 6, no. 1, Art. no. 1, 2012, doi: 10.1609/icwsm.v6i1.14305.
7. P. Plavén-Sigray, G. J. Matheson, B. C. Schiffler, and W. H. Thompson, “The readability of scientific texts is decreasing over time,” eLife, vol. 6, p. e27725, Sep. 2017, doi: 10.7554/eLife.27725.
8. A. P. Akella, D. Koop, and H. Alhoori, “Laying foundations to quantify the ‘Effort of Reproducibility.’” arXiv, Aug. 24, 2023. Accessed: Sep. 21, 2023. [Online]. Available: http://arxiv.org/abs/2308.12580
9. C. Lu et al., “Analyzing linguistic complexity and scientific impact,” J. Informetr., vol. 13, no. 3, pp. 817–829, Aug. 2019, doi: 10.1016/j.joi.2019.07.004.
10. F. Crameri, G. E. Shephard, and P. J. Heron, “The misuse of colour in science communication,” Nat. Commun., vol. 11, no. 1, p. 5444, Oct. 2020, doi: 10.1038/s41467-020-19160-7.
11. F. Crameri, “Scientific colour maps.” Zenodo, Jun. 14, 2023. doi: 10.5281/ZENODO.1243862.