The Effect of User Factors on Consumer Familiarity with Health Terms: Using Gender as a Proxy for Background Knowledge About Gender-Specific Illnesses.
ABSTRACT An algorithm estimating vocabulary complexity of a consumer health text can help improve readability of consumer health materials. We had previously developed and validated an algorithm predicting lay familiarity with health terms on the basis of the terms' frequency in consumer health texts and experimental data. Present study is part of the program studying the influence of reader factors on familiarity with health terms and concepts. Using gender as a proxy for background knowledge, the study evaluates male and female participants' familiarity with terms and concepts pertaining to three types of health topics: male-specific, female-specific and gender-neutral. Of the terms / concepts of equal predicted difficulty, males were more familiar with those pertaining to neutral and male-specific topics (the effect was especially pronounced for "difficult" terms); no topic effect was observed for females. The implications for tailoring health readability formulas to various target populations are discussed.
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ABSTRACT: The quality of consumer health information on the World Wide Web is an important issue for medicine, but to date no systematic and comprehensive synthesis of the methods and evidence has been performed. To establish a methodological framework on how quality on the Web is evaluated in practice, to determine the heterogeneity of the results and conclusions, and to compare the methodological rigor of these studies, to determine to what extent the conclusions depend on the methodology used, and to suggest future directions for research. We searched MEDLINE and PREMEDLINE (1966 through September 2001), Science Citation Index (1997 through September 2001), Social Sciences Citation Index (1997 through September 2001), Arts and Humanities Citation Index (1997 through September 2001), LISA (1969 through July 2001), CINAHL (1982 through July 2001), PsychINFO (1988 through September 2001), EMBASE (1988 through June 2001), and SIGLE (1980 through June 2001). We also conducted hand searches, general Internet searches, and a personal bibliographic database search. We included published and unpublished empirical studies in any language in which investigators searched the Web systematically for specific health information, evaluated the quality of Web sites or pages, and reported quantitative results. We screened 7830 citations and retrieved 170 potentially eligible full articles. A total of 79 distinct studies met the inclusion criteria, evaluating 5941 health Web sites and 1329 Web pages, and reporting 408 evaluation results for 86 different quality criteria. Two reviewers independently extracted study characteristics, medical domains, search strategies used, methods and criteria of quality assessment, results (percentage of sites or pages rated as inadequate pertaining to a quality criterion), and quality and rigor of study methods and reporting. Most frequently used quality criteria used include accuracy, completeness, readability, design, disclosures, and references provided. Fifty-five studies (70%) concluded that quality is a problem on the Web, 17 (22%) remained neutral, and 7 studies (9%) came to a positive conclusion. Positive studies scored significantly lower in search (P =.02) and evaluation (P =.04) methods. Due to differences in study methods and rigor, quality criteria, study population, and topic chosen, study results and conclusions on health-related Web sites vary widely. Operational definitions of quality criteria are needed.JAMA The Journal of the American Medical Association 287(20):2691-700. · 29.98 Impact Factor
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ABSTRACT: We have developed a systematic methodology using corpus-based text analysis followed by human review to assign "consumer-friendly display (CFD) names" to medical concepts from the National Library of Medicine (NLM) Unified Medical Language System (UMLS) Metathesaurus. Using NLM MedlinePlus queries as a corpus of consumer expressions and a collaborative Web-based tool to facilitate review, we analyzed 425 frequently occurring concepts. As a preliminary test of our method, we evaluated 34 ana-lyzed concepts and their CFD names, using a questionnaire modeled on standard reading assessments. The initial results that consumers (n=10) are more likely to understand and recognize CFD names than alternate labels suggest that the approach is useful in the development of consumer health vocabularies for displaying understandable health information.AMIA ... Annual Symposium proceedings / AMIA Symposium. AMIA Symposium 02/2005;
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ABSTRACT: Accurate assessment of the difficulty of consumer health texts is a prerequisite for improving readability. General purpose readability formulas based primarily on word length are not well suited for the health domain, where short technical terms may be unfamiliar to consumers. To address this need, we previously developed a regression model for predicting "average familiarity" with consumer health vocabulary (CHV) terms. The primary goal was to evaluate the ability of the CHV term familiarity model to predict (1) surface-level familiarity of health-related terms and (2) understanding of the underlying meaning (concept familiarity) among actual consumers. Secondary goals involved exploring the effect of demographic factors (eg, health literacy) on surface-level and concept-level familiarity and describing the relationship between the two levels of familiarity. Survey instruments for assessing surface-level familiarity (45 items) and concept-level familiarity (15 items) were developed. All participants also completed a demographic survey and a standardized health literacy assessment, S-TOFHLA. Based on surveys completed by 52 consumers, linear regression suggests that predicted CHV term familiarity is a statistically significantly predictor (P < .001) of participants' surface-level and concept-level familiarity performance. Health literacy was a statistically significant predictor of surface-level familiarity scores (P < .001); its effect on concept-level familiarity scores warrants further investigation (P = 0.06). Educational level was not a significant predictor of either type of familiarity. Participant scores indicated that conceptualization lagged behind recognition, especially for terms predicted as "likely to be familiar" (P = .006). This exploratory study suggests that the CHV term familiarity model is predictive of consumer recognition and understanding of terms in the health domain. Potential uses of such a model include readability formulas tailored to the consumer health domain and tools to "translate" professional medical documents into text that is more accessible to consumers. The study also highlights the usefulness of distinguishing between surface-level term familiarity and deeper concept understanding and presents one method for assessing familiarity at each level.Journal of Medical Internet Research 02/2007; 9(1):e5. · 3.77 Impact Factor