Gondy Leroy1, Stephen Helmreich, James R Cowie. 1. School of Information Systems and Technology, Claremont Graduate University, Claremont, CA 91711, USA. gondy.leroy@cgu.edu
Abstract
PURPOSE: Willingness and ability to learn from health information in text are crucial for people to be informed and make better medical decisions. These two user characteristics are influenced by the perceived and actual difficulty of text. Our goal is to find text features that are indicative of perceived and actual difficulty so that barriers to reading can be lowered and understanding of information increased. METHODS: We systematically manipulated three text characteristics, - overall sentence structure (active, passive, extraposed-subject, or sentential-subject), noun phrases complexity (simple or complex), and function word density (high or low), - which are more fine-grained metrics to evaluate text than the commonly used readability formulas. We measured perceived difficulty with individual sentences by asking consumers to choose the easiest and most difficult version of a sentence. We measured actual difficulty with entire paragraphs by posing multiple-choice questions to measure understanding and retention of information in easy and difficult versions of the paragraphs. RESULTS: Based on a study with 86 participants, we found that low noun phrase complexity and high function words density lead to sentences being perceived as simpler. In the sentences with passive, sentential-subject, or extraposed-subject sentences, both main and interaction effects were significant (all p<.05). In active sentences, only noun phrase complexity mattered (p<.001). For the same group of participants, simplification of entire paragraphs based on these three linguistic features had only a small effect on understanding (p=.99) and no effect on retention of information. CONCLUSIONS: Using grammatical text features, we could measure and improve the perceived difficulty of text. In contrast to expectations based on readability formulas, these grammatical manipulations had limited effects on actual difficulty and so were insufficient to simplify the text and improve understanding. Future work will include semantic measures and overall text composition and their effects on perceived and actual difficulty. LIMITATIONS: These results are limited to grammatical features of text. The studies also used only one task, a question-answering task, to measure understanding of information. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
PURPOSE: Willingness and ability to learn from health information in text are crucial for people to be informed and make better medical decisions. These two user characteristics are influenced by the perceived and actual difficulty of text. Our goal is to find text features that are indicative of perceived and actual difficulty so that barriers to reading can be lowered and understanding of information increased. METHODS: We systematically manipulated three text characteristics, - overall sentence structure (active, passive, extraposed-subject, or sentential-subject), noun phrases complexity (simple or complex), and function word density (high or low), - which are more fine-grained metrics to evaluate text than the commonly used readability formulas. We measured perceived difficulty with individual sentences by asking consumers to choose the easiest and most difficult version of a sentence. We measured actual difficulty with entire paragraphs by posing multiple-choice questions to measure understanding and retention of information in easy and difficult versions of the paragraphs. RESULTS: Based on a study with 86 participants, we found that low noun phrase complexity and high function words density lead to sentences being perceived as simpler. In the sentences with passive, sentential-subject, or extraposed-subject sentences, both main and interaction effects were significant (all p<.05). In active sentences, only noun phrase complexity mattered (p<.001). For the same group of participants, simplification of entire paragraphs based on these three linguistic features had only a small effect on understanding (p=.99) and no effect on retention of information. CONCLUSIONS: Using grammatical text features, we could measure and improve the perceived difficulty of text. In contrast to expectations based on readability formulas, these grammatical manipulations had limited effects on actual difficulty and so were insufficient to simplify the text and improve understanding. Future work will include semantic measures and overall text composition and their effects on perceived and actual difficulty. LIMITATIONS: These results are limited to grammatical features of text. The studies also used only one task, a question-answering task, to measure understanding of information. Copyright 2010 Elsevier Ireland Ltd. All rights reserved.
Authors: Frederick Muench; Katherine van Stolk-Cooke; Jon Morgenstern; Alexis N Kuerbis; Kendra Markle Journal: J Med Internet Res Date: 2014-02-05 Impact factor: 5.428