Christine M. Fox

Bio: Christine M. Fox is an academic researcher from University of Toledo. The author has contributed to research in topics: Rasch model & Item response theory. The author has an hindex of 12, co-authored 34 publications receiving 6921 citations.

Applying the Rasch Model: Fundamental Measurement in the Human Sciences

Abstract: For many researchers, the Rasch model provides a very practical solution to data analysis in the social sciences. This volume contends that Rasch measurement is the model of choice because it is the closest to realizing the sort of objective fundamental measurement so long revered in the physical sciences. Trevor Bond has worked with leading Rasch theoreticians for more than 15 years, advising developmentalists and teachers on how to conduct and interpret Rasch analyses of their own data. After each of his many research presentations, Dr. Bond was asked to recommend a suitable text for those who wish to learn more about Rasch analysis. Unfortunately, the books published to date require a significant knowledge of statistics and not easily accessible to many practicing researchers. This lack of a suitable introductory text is the driving force behind this book. The goals of this authored volume are: * to present an accessible overview of the basic properties and principles of Rasch analysis, that does not require a sophisticated statistical background, * to demonstrate how Rasch analysis can be applied to a number of generic problems encountered by psychologists and educators, and * to prepare readers for performing their own analyses and interpreting the results. This book is ideal for all researchers in the human sciences interested in learning how to actually implement the Rasch model with their own data.

Uses of Rasch Modeling in Counseling Psychology Research.

Abstract: Inferences made from summary indices of psychometric scales must be reliable and valid to advance scientific knowledge in counseling psychology. This article illustrates traditional and innovative uses of the Rasch model in the development and validation of small- and large-scale psychological instruments. Discussion of traditional uses of the Rasch model included reliability and validity of scale scores, whereas discussion of innovative uses included (a) determining the optimal number of response categories for Likert-type items and (b) obtaining a measure of response style for each person. Both mathematical and conceptual explanations are provided, and counseling psychology data are used to illustrate examples.

Development of the Patient Activation Measure (PAM): Conceptualizing and Measuring Activation in Patients and Consumers

Abstract: Two significant emerging policy directions put patients and consumers in a key role for influencing health care quality and costs. First, consumer-directed health plans rely on informed consumer choices to contain costs and improve the quality of care. This approach assumes that consumers will make more prudent health and health care choices when they are given financial incentives along with access to comparative cost and quality information. This approach also assumes that the combination of financial incentives and relevant information will increase their “activation” (Gabel, Lo Sasso, and Rice 2002). Second, the Chronic Illness Care Model (Bodenheimer et al. 2002) emphasizes patient-oriented care, with patients and their families integrated as members of the care team. A critical element in the model is activated patients, with the skills, knowledge, and motivation to participate as effective members of the care team (Von Korff et al. 1997). A key health policy question is, what would it take for consumers to become effective and informed managers of their health and health care? What skills, knowledge, beliefs, and motivations do they need to become “activated” or more effectual health care actors? These are essential questions if we hope to improve the health care process, the outcomes of care, and control costs. This is true especially with regard to the 99 million Americans with a chronic disease. Because those with chronic illness need ongoing care, account for a large portion of health care costs, and must play an important role in maintaining their own functioning, encouraging their activation should be a priority. Even though patient activation is a central concept in both the consumer driven health care approach and the chronic illness care models, it remains conceptually and empirically underdeveloped. There has been a lack of conceptual clarity regarding “activation,” and thus a lack of adequate measurement. There are a number of existing methods for assessing different aspects of activation, such as health locus of control (Wallston, Stein, and Smith), self-efficacy in self-managing behaviors (Lorig et al. 1996), and readiness to change health-related behaviors (DiClemente et al. 1991; Prochaska, Redding, and Evers 1997), but these measures tend to focus on the prediction of a single behavior. Moreover, there is no existing measure that includes the broad range of elements involved in activation, including the knowledge, skills, beliefs, and behaviors that a patient needs to manage a chronic illness. In this paper we describe the development of the Patient Activation Measure (PAM), a measure of activation that is grounded in rigorous conceptualization and appropriate psychometric methods. The PAM was developed in four stages: Stage 1.Conceptually defining activation involved a literature review, systematic consultation with experts using a “consensus method,” and consultation with individuals with chronic disease using focus groups. Stage 2.Preliminary scale development began by building on the domains identified in stage one and operationalizing them with survey items within each domain. Steps included generating, refining, and testing a large item pool. We used Rasch psychometric methods to develop the scale and test the preliminary measure's psychometric properties. Stage 3.Stage three involved exploring the possibility of extending the range of the measure, refining the response categories, and testing whether the measure could be used with respondents who had no chronic illnesses. Stage 4.In the fourth and final stage a national probability sample was used to assess the performance of the measure across different subsamples in the population and to assess the construct validity of the measure.

Scaling of Theory-of-Mind Tasks

Abstract: Two studies address the sequence of understandings evident in preschoolers' developing theory of mind. The first, preliminary study provides a meta-analysis of research comparing different types of mental state understandings (e.g., desires vs. beliefs, ignorance vs. false belief). The second, primary study tests a theory-of-mind scale for preschoolers. In this study 75 children (aged 2 years, 11 months to 6 years, 6 months) were tested on 7 tasks tapping different aspects of understanding persons' mental states. Responses formed a consistent developmental progression, where for most children if they passed a later item they passed all earlier items as well, as confirmed by Guttman and Rasch measurement model analyses.

Validity and reliability of measurement instruments used in research.

Abstract: Purpose. Issues related to the validity and reliability of measurement instruments used in research are reviewed. Summary. Key indicators of the quality of a measuring instrument are the reliability and validity of the measures. The process of developing and validating an instrument is in large part focused on reducing error in the measurement process. Reliability estimates evaluate the stability of measures, internal consistency of measurement instruments, and interrater reliability of instrument scores. Validity is the extent to which the interpretations of the results of a test are warranted, which depends on the particular use the test is intended to serve. The responsiveness of the measure to change is of interest in many of the applications in health care where improvement in outcomes as a result of treatment is a primary goal of research. Several issues may affect the accuracy of data collected, such as those related to self-report and secondary data sources. Self-report of patients or subjects is required for many of the measurements conducted in health care, but self-reports of behavior are particularly subject to problems with social desirability biases. Data that were originally gathered for a different purpose are often used to answer a research question, which can affect the applicability to the study at hand. Conclusion. In health care and social science research, many of the variables of interest and outcomes that are important are abstract concepts known as theoretical constructs. Using tests or instruments that are valid and reliable to measure such constructs is a crucial component of research quality.

Essentials of Psychological Testing

Abstract: Series Preface. One: Introduction to Psychological Tests and Their Uses. Two: Essential Statistics for Testing. Three: Essentials of Test Score Interpretation. Four: Essentials of Reliability. Five: Essentials of Validity. Six: Essential Test Item Considerations. Seven: Essentials of Test Use. Appendix A: Commercially Available Tests. Appendix B: Addresses of Test Publishers and Distributors. Appendix C: Table of Areas and Ordinates of the Normal Curve. References. Index. Acknowledgments. About the Author.