|Masse, Louise - UNIV OF BRITISH COLUMBIA|
|Wilson, Mark - U OF CALIFORNIA BERKELEY|
|Nebeling, Linda - NATIONAL CANCER INSTITUTE|
Submitted to: Health Education Research
Publication Type: Review Article
Publication Acceptance Date: December 1, 2006
Publication Date: December 1, 2006
Citation: Masse, L.C., Wilson, M., Baranowski, T., Nebeling, L. 2006. Improving psychometric methods in health education and health behavior research. Health Education Research. (21)1:i1-i3. Interpretive Summary: This manuscript is an introduction to this special issue of Health Education Research concerning Item Response Modeling (IRM), a new psychometric method. It provides a brief history on use of IRM in other areas of research; overviews the professional meeting at which the IRM methods were showcased; and overviews the other manuscripts appearing in this special issue.
Technical Abstract: Item response modeling (IRM), also referred to as item response theory, is well established and widely implemented in educational measurement, but its application is lagging in our area. A number of issues seem to stunt the application of IRM methods: (i) few IRM applications have been presented in the context of health education and health behavior research; (ii) lack of awareness as to what IRM can do beyond assessing the psychometric properties of a scale; (iii) lack of psychometricians trained in our field; (iv) current software is not user friendly and (v) few training opportunities are available to researchers in our area. A workshop and symposium was sponsored aimed at improving health outcomes methods and devoted a significant amount of time to explaining IRM and the usefulness of IRM-computerized adaptive testing methods for assessing health outcomes. The National Cancer Institute is a major partner of the National Institutes of Health (NIH) cooperative initiative Patient-Reported Outcomes Measurement Information System aimed at developing an item bank repository that is publicly available and which can serve as a template for computerized adaptive testing for health outcomes assessment. It is hoped that this supplement as well as the other ongoing initiatives will lead to improved methods in health education and health behavior research. Many important IRM applications have not been presented (such as the development of an item bank, computerized adaptive testing and measurement of change). However, this supplement provides numerous applications that can have widespread use in the field of health education and health behavior research. We hope that these applications will advance the field by enhancing the quality of the measures available and the appropriateness of the methods involved.