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Rating scale analysis
01 Jan 1982-
About: The article was published on 1982-01-01 and is currently open access. It has received 1897 citations till now. The article focuses on the topics: Rating scale & Polytomous Rasch model.
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TL;DR: In this paper, an unidimensional latent trait model for responses scored in two or more ordered categories is developed, which can be viewed as an extension of Andrich's Rating Scale model to situations in which ordered response alternatives are free to vary in number and structure from item to item.
Abstract: A unidimensional latent trait model for responses scored in two or more ordered categories is developed. This “Partial Credit” model is a member of the family of latent trait models which share the property of parameter separability and so permit “specifically objective” comparisons of persons and items. The model can be viewed as an extension of Andrich's Rating Scale model to situations in which ordered response alternatives are free to vary in number and structure from item to item. The difference between the parameters in this model and the “category boundaries” in Samejima's Graded Response model is demonstrated. An unconditional maximum likelihood procedure for estimating the model parameters is developed.
3,368 citations
TL;DR: The authors show how IRT techniques can be used to develop new attachment scales with desirable psychometric properties, and indicate that commonly used attachment scales can be improved in a number of important ways.
Abstract: Self-report measures of adult attachment are typically scored in ways (e.g., averaging or summing items) that can lead to erroneous inferences about important theoretical issues, such as the degree of continuity in attachment security and the differential stability of insecure attachment patterns. To determine whether existing attachment scales suffer from scaling problems, the authors conducted an item response theory (IRT) analysis of 4 commonly used self-report inventories: Experiences in Close Relationships scales (K. A. Brennan, C. L. Clark, & P. R. Shaver, 1998), Adult Attachment Scales (N. L. Collins & S. J. Read, 1990), Relationship Styles Questionnaire (D. W. Griffin & K. Bartholomew, 1994) and J. Simpson's (1990) attachment scales. Data from 1,085 individuals were analyzed using F. Samejima's (1969) graded response model. The authors' findings indicate that commonly used attachment scales can be improved in a number of important ways. Accordingly, the authors show how IRT techniques can be used to develop new attachment scales with desirable psychometric properties.
2,883 citations
Cites background from "Rating scale analysis"
...5) and standardized weighted mean squares of the item residuals (Wright & Masters, 1982, chap....
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TL;DR: The Patient Activation Measure is a valid, highly reliable, unidimensional, probabilistic Guttman-like scale that reflects a developmental model of activation that has good psychometric properties indicating that it can be used at the individual patient level to tailor intervention and assess changes.
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.
2,085 citations
TL;DR: Giacino et al. as discussed by the authors evaluated the diagnostic utility of the JFK Coma Recovery Scale-Revised (CRS-R) with 80 patients admitted to an inpatient Coma Intervention Program with a diagnosis of either vegetative state (VS) or minimally conscious state (MCS).
1,433 citations