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.

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

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.

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Scaling of Theory-of-Mind Tasks

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.

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Validity and reliability of measurement instruments used in research.

The Psychology of Religion and Coping: Theory, Research, Practice

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.

Essentials of Psychological Testing

Basic Principles of the Rasch Model

Scientifically based research used to inform evidence based school reform efforts has been required by the federal government in order to receive grant funding since the reenactment of No Child Left Behind (2002) Educational evaluators are thus faced with the challenge to use rigorous research designs to establish causal relationships However, access to student-level longitudinal or comparison group data is often scarce, which significantly restricts researchers’ choice of research design Although most state departments of education have schooland district-level data available to the public, the individual student-level data that are often needed to perform appropriate statistical analyses are unavailable This exploratory study demonstrates the process of and provides evidence that microanalytical simulation methods, conducted using Microsoft Excel, may be a useful research tool in the field of education if adequate school-level modeling information is available These simulation methods may assist in providing greater opportunities to execute more rigorous methodological designs

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Using Microanalytical Simulation Methods in Educational Evaluation: An Exploratory Study.

This paper revisits a half-century long theoretical controversy associated with the use of magnitude estimation scaling (MES) and category rating scaling (CRS) procedures in measurement. The MES procedure in this study involved instructing participants to write a number that matched their impression of difficulty of a test item. Participants were not restricted in the range of numbers they could choose for their scale. They also had the choice of disclosing their individual scale. After the MES task was completed, participants were given a blank copy of the test to rate the perceived difficulty of each item using a researcher-imposed categorical rating scale from 1 (very easy) to 6 (very difficult). The MES and CRS data were both analyzed using Rasch Rating scale model. Additionally, the MES data were examined with Rasch Partial Credit model. Results indicate that knowing each person's scale is associated with smaller errors of measurement.

Magnitude estimation and categorical rating scaling in social sciences: a theoretical and psychometric controversy.

Limited research has applied a measurement model to compare the rating scale functioning of categorical rating scaling (CRS) and absolute magnitude estimation scaling (MES) when rating subjective stimuli. We used an experimental design and applied the Rasch model to the survey data, with each respondent rating items using MES and one of four commonly used agreement-disagreement rating scales. The results indicated that the CRS and MES data were comparable in person and item separation and reliability when the respondents' scales were known. MES had lower standard error for people and items; however MES had disordered step calibrations. Finally, the respondents reported preference of CRS to MES.

Christine M. Fox

Papers

Basic Principles of the Rasch Model

Using Microanalytical Simulation Methods in Educational Evaluation: An Exploratory Study.

Magnitude estimation and categorical rating scaling in social sciences: a theoretical and psychometric controversy.

An experimental study using Rasch analysis to compare absolute magnitude estimation and categorical rating scaling as applied in survey research.

Mode l Fit and Unidimensionality