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Assessing readability formula differences with written health information materials: application, results, and
Lih-Wern Wang1, Michael J Miller, Michael R Schmitt
1College of Pharmacy, University of Oklahoma, 4502 East 41st Street, Tulsa, OK 74135, USA.
Background:
Readability formulas are often used to guide the development and evaluation of literacy-sensitive written health information. However, readability formula results may vary considerably as a result of differences in software processing algorithms and how each formula is applied. These variations complicate interpretations of reading grade level estimates, particularly without a uniform guideline for applying and interpreting readability formulas.
Objectives:
This research sought to (1) identify commonly used readability formulas reported in the health care literature, (2) demonstrate the use of the most commonly used readability formulas on written health information, (3) compare and contrast the differences when applying common readability formulas to identical selections of written health information, and (4) provide recommendations for choosing an appropriate readability formula for written health-related materials to optimize their use.
Methods:
A literature search was conducted to identify the most commonly used readability formulas in health care literature. Each of the identified formulas was subsequently applied to word samples from 15 unique examples of written health information about the topic of depression and its treatment. Readability estimates from common readability formulas were compared based on text sample size, selection, formatting, software type, and/or hand calculations. Recommendations for their use were provided.
Results:
The Flesch-Kincaid formula was most commonly used (57.42%). Readability formulas demonstrated variability up to 5 reading grade levels on the same text. The Simple Measure of Gobbledygook (SMOG) readability formula performed most consistently. Depending on the text sample size, selection, formatting, software, and/or hand calculations, the individual readability formula estimated up to 6 reading grade levels of variability.
Conclusions:
The SMOG formula appears best suited for health care applications because of its consistency of results, higher level of expected comprehension, use of more recent validation criteria for determining reading grade level estimates, and simplicity of use. To improve interpretation of readability results, reporting reading grade level estimates from any formula should be accompanied with information about word sample size, location of word sampling in the text, formatting, and method of calculation.
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