Easy-to-Read Health Materials (NLM Boost Box)
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Slides were given as part of a presentation hosted by the National Library of Medicine's Boost Box program. The description of the session: Miraida Morales will discuss the challenges of using easy-to-read health materials, such as their high reading level, lack of control or standardization of readability, and problems with readability formulas. In this session she will offer practical solutions for what librarians and other professionals can do to minimize these issues for our communities. Miraida will also share her research findings on how adult beginning and developing readers evaluate health information materials.
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Easy-to-Read Health Materials (NLM Boost Box)
- 1. EASY-TO-READ HEALTH MATERIALS: Are they really? Slides created by Miraida Morales for the National Library of Medicine Copyright 2016 Use only with permission
- 2. Introduction Miraida Morales Ph.D. Candidate, Rutgers University Health Literacy | Adult New Readers | Community Health Practices
- 3. Agenda Readability formulas What are they? How do they work? Limitations Should we be using these formulas on health materials? Case Studies How do different people evaluate health information?
- 4. Readability a quality that determines how easy are texts to read for a particular individual, but... identifying just what makes texts easy to read remains a problem... especially for health materials
- 5. WHY? Readability is usually determined through the application of formulas to text
- 6. Flesch Kincaid Grade Level = (0.39 x ASL) + (11.8 x ASW) - 15.59 Dale Chall = (Raw Score = 0.1579 * (PDW) + 0.0496 * ASL) SMOG Formula = SO MANY FORMULAS ! The formulas do not take into account meaning.
- 7. How do these formulas work? They count the average length of words (syllables) They count the average number of words in a sentence They match these counts to grade levels
- 8. Assumptions longer words are more rare than shorter words in English & longer sentences have more complex structure
- 9. Limitation #1 Health materials include lots of “rare” or long words.
- 10. Limitation #2 Shorter texts are not always better.
- 11. Limitation #3 Readability formulas were developed using educational texts, often for educational purposes.
- 12. Limitation #4 Readability formulas precede advances in computation.
- 13. Limitation #5 Readability formulas can only assess complete sentences.
- 14. The big picture.
- 15. Let’s look at an example Although gestational diabetes is a serious condition, you can learn how to take care of it and prevent problems for you and your baby. Because the placenta leaves your body when the baby is delivered, gestational diabetes usually goes away when the baby is born. (American Diabetes Association)
- 16. Flesch-Kincaid Grade Level: 12.7 Average syllable length: 1.88 Average words per sentence: 16
- 18. Problem #1 Who is responsible for determining the readability of health materials?
- 19. Problem #2 Is everyone using the same method to determine readability of health materials?
- 20. Problem #3 Health information tends to be rather difficult to read. How do we simplify it?
- 22. Going beyond Easy-to- Read materials Don’t need to only rely on docs in the Easy-to-Read collection Readability of these documents doesn’t vary that much from documents not included in this collection. This means we have a bigger selection of topics available. Readability formulas are not necessarily applicable to health materials. Vocabulary and sentence length assumptions built into readability formulas don’t hold for health materials. Health materials tend to over-index on long words. Health materials don’t always include full sentences (e.g. bulleted lists, phases, etc.).
- 23. “Besides word and sentence length, what features of text and reader might better determine the readability of health materials for adult new readers?
- 24. We don’t know enough about how different people read.
- 25. [ Topic Knowledge ] [ Reading Expertise ] = X What’s the relationship between these factors?
- 26. CASE STUDIES WITH ADULT READERS 2. Adult women, some high school ed 3. Evaluate Diabetes Brochures 1. Diaspora Community Services
- 27. DESIGN FEATURES Document Length Preferred shorter document to longer one. One woman had trouble recalling information in the longer document. This is consistent with perceived ease or difficulty. Charts and Lists Though preferred, these proved difficult for participants to interpret accurately. Information presented in these formats was not necessarily easier to recall. Images Provide visual markers to anchor the text. Allow for scanning. Serve similar purpose to section headings.
- 28. “That’s true.” AND “I know…” Prior Knowledge All participants viewed favorably portions of brochures that resonated with their prior knowledge. Future Use Usefulness of information in the brochures was an important evaluation criteria for participants.
- 29. Sources of difficulty when reading Statistics Percentages and other numerical figures were difficulty for participants to interpret. Word Use Lack of definitions for complicated health terms, such as gestational diabetes or prediabetes created uncertainty or confusion. Bulleted Lists Because they often lack function words or phrases, information presented in lists can be difficult to interpret. Participants often expected list to follow a narrative structure, with each item linking to the previous one.
- 30. MANY READERS, MANY TEXTS A. Types of Readers B. Types of Knowledge C. Types of Texts D. Types of Uses
- 31. FUTURE DIRECTIONS Research into cohesion, narrativity, simplification User & usability studies What do members of our communities want?
- 32. ONGOING RESEARCH Recruiting participants Focusing on adult new & developing readers Conducting usability tests Collaborating with libraries
- 33. THANKS! Any questions? You can find me at: @Miraidam miraidam@gmail.com
- 34. References & More Reading ○ DuBay, W. H. (2004). The Principles of Readability. Costa Mesa: Impact Information, 76. Retrieved from http://files.eric.ed.gov/fulltext/ED490073.pdf ○ Feng, L., Elhadad, N., & Huenerfauth, M. (2009, March). Cognitively motivated features for readability assessment. In Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics (pp. 229-237). Association for Computational Linguistics. ○ McNamara, D. S., Graesser, A. C., McCarthy, P. M., & Cai, Z. (2014). Automated evaluation of text and discourse with Coh-Metrix. Cambridge University Press. ○ Schriver, K. (2000). Readability Formulas in the New Millennium: What’s the Use? ACM Journal of Computer Documentation, 24(3), 138–140. ○ http://www.readabilityformulas.com/
Notas do Editor
- This is what we’re doing today. We’re going to take a deep dive into readability formulas. Then we’re going to consider what these formulas can and can’t do. Next, we’ll look at some general problems that arise when we apply these formulas to health information. Finally, I’ll present some initial findings of a series of case studies with adults as they evaluate health materials.
- It’s important to be clear about what readability means, and why it’s problematic for health information. Simply put, is something easy to read? If yes, then we say it’s readable. However, language is multi-dimensional. When we talk about language, we are talking about vocabulary, meaning, and structure. It isn’t clear where the ease or difficulty lies: is it the words, the structure, or the meaning that makes something hard to read? This is really problematic for health information and we’re now going to take a look at why this might be so.
- Let’s consider how we currently determine the readability of documents. Readability has been operationalized into mathematical formulas that make strong assumptions about the relationship of words and sentences to educational attainment.
- Here are some well known and frequently used formulas. Formulas are very widely available. NOTE: The formulas do not take into account meaning.
- Health terms, names of conditions, treatments, body parts, etc. Rarity in relation to general language is not necessarily problematic. Think about a person who is dealing with a health condition--they already have some awareness or knowledge of an otherwise rare word.
- Some readers need explanations, definitions, and context clues that will make text longer.
- Not necessarily applicable to adults or to non-school texts such as newspapers, magazines, health information.
- We now have the ability to use natural language processing techniques, the use of computers, we have lots and lots of machine readable texts to analyze. All of this can be done in a much grander scale, using more texts, faster, and cheaper.
- Consider that health materials often include charts, graphs, lists, phrases, diagrams
- Let’s take a step back and consider some of these assumptions and what all this looks like in our professional practice.
- Consider this example. I’ve highlighted possible sources of difficulty in this segment. 1. Notice that both sentences start with a dependent clause. This might be stylistically pleasing to read, but it might be hard to read for a new/beginning reader. 2. Notice that placenta and its relationship to diabetes, is not explained.
- Guidelines recommend the use readability formulas when creating health content. NLM provides us with a collection of Easy-to-Read health information resources from various health agencies. From the pov of authority and reliability, this service is indispensable.
- Content creators
- 1. There is no verification system, so standardization is difficult to achieve. 2. Resources have not been evaluated by actual readers.
- Terminology, jargon, structure. Think back to the gestational diabetes example presented earlier. Also, shorter doesn’t always mean easier to read. Formulas don’t tell us what in our document might cause difficulty in reading: is it word usage? Is it jargon? Is it long sentences? Is it complex grammar? Without knowing this, it’s difficult for us to amend or simplify text.
- What do we do now?! Don’t despair.
- Don’t limit ourselves to materials in the ETR collection--so in this way, our resources have grown. In fact, the readability (as determined by formulas) of docs in and out of the ETR collection is pretty similar/consistent across the board. Furthermore, readability formulas simply might not be well suited for health information. So what now?
- What do I mean? Different people know different things about different health topics. Also, people have different levels of reading expertise. There are people who read a lot at work, for instance. There are people who read a lot in another language. There are people who read mostly novels. There are people who mostly read the news. All of these different reading practices contribute to different levels of expertise. Expertise includes the development of certain strategies: skimming, browsing, headline reading, speed reading, highlighting, note-taking, bookmarking, sharing, etc.
- To learn more about how different adult readers evaluate health information, I carried out an exploratory case study. This early study has been expanded into a much bigger project, which I can discuss at the end if we have time and if you’re still interested. In any case, the earlier study was a collaboration with Diaspora (talk about Diaspora)