Since millions seek health information online, it is vital for this information to be comprehensible. Most studies use readability formulas, which ignore vocabulary, and conclude that online health information is too difficult. We developed a vocabularly-based, naïve Bayes classifier to distinguish between three difficulty levels in text. It proved 98% accurate in a 250-document evaluation. We compared our classifier with readability formulas for 90 new documents with different origins and asked representative human evaluators, an expert and a consumer, to judge each document. Average readability grade levels for educational and commercial pages was 10th grade or higher, too difficult according to current literature. In contrast, the classifier showed that 70-90% of these pages were written at an intermediate, appropriate level indicating that vocabulary usage is frequently appropriate in text considered too difficult by readability formula evaluations. The expert considered the pages more difficult for a consumer than the consumer did.

Abstract

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This pilot study explores the impact of a health topics overview (HTO) on reading comprehension. The HTO is generated automatically based on the presence of Unified Medical Language System terms. In a controlled setting, we presented health texts and posed 15 questions for each. We compared performance with and without the HTO. The answers were available in the text, but not always in the HTO. Our study (n¼48) showed that consumers with low health literacy or high stress performed poorly when the HTO was available without linking directly to the answer. They performed better with direct links in the HTO or when the HTO was not available at all. Consumers with high health literacy or low stress performed better regardless of the availability of the HTO. Our data suggests that vulnerable consumers relied solely on the HTO when it was available and were misled when it did not provide the answer.

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