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      Is the Patient Activation Measure a valid measure of osteoarthritis self-management attitudes and capabilities? Results of a Rasch analysis

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          Abstract

          Background

          The Patient Activation Measure (PAM-13) was developed using Rasch analysis to assess knowledge, skills and confidence in the management of one’s health. Previous studies report positive relationships between PAM-13 scores, self-management behaviours and longitudinal health outcomes in adults with chronic disease. There is little extant measurement property evidence for the use of PAM-13 in specific osteoarthritis (OA) populations. This study tested measurement properties of the PAM-13 in people living with hip and knee OA.

          Methods

          Item response frequency analysis was conducted. Rasch analysis evaluated the fit of the PAM-13 data to the Rasch model. Model-data fit was evaluated using infit and outfit statistics; person/item reliability and person separation indices were computed. Unidimensionality was evaluated using Principal Components Analysis of Rasch residuals and the data were assessed for item redundancy. Differential Item Functioning (DIF) examined bias in respondent subgroups and correlations tested relationships between PAM-13 and other patient-reported outcomes.

          Results

          Two-hundred-and-seventeen PAM-13 surveys were completed; there were no missing responses, floor or ceiling effects. Person and item reliability were acceptable (0.98 and 0.87 respectively) with good separation (person separation index 2.58). Unidimensionality was evaluated, with 49.4% of the variance explained by the first eigenvector. There was evidence of potential local response-dependence. The Rasch fit statistics were acceptable (except for item-2). There were some issues identified with targeting of the PAM-13 items to people with higher ability and the item difficulty order was different to that proposed in original cohorts. Significant DIF was identified for sex and educational level for a small number of items. PAM-13 scores were moderately correlated with depressive symptoms on the Depression Anxiety Stress Scale and Assessment of Quality of Life-6D. There were small correlations between PAM-13 and Knee injury and Osteoarthritis Outcome Score pain and activities of daily living scores.

          Conclusions

          This study provides some evidence of adequate person and item reliability, unidimensionality, and construct validity to support the use of PAM-13 to measure patient activation in people living with hip and knee OA. Possible limitations regarding targeting, different item difficulty order, DIF and local response dependence should be investigated in future research.

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          Most cited references29

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          Development and testing of a short form of the patient activation measure.

          The Patient Activation Measure (PAM) is a 22-item measure that assesses patient knowledge, skill, and confidence for self-management. The measure was developed using Rasch analyses and is an interval level, unidimensional, Guttman-like measure. The current analysis is aimed at reducing the number of items in the measure while maintaining adequate precision. We relied on an iterative use of Rasch analysis to identify items that could be eliminated without loss of significant precision and reliability. With each item deletion, the item scale locations were recalibrated and the person reliability evaluated to check if and how much of a decline in precision of measurement resulted from the deletion of the item. The data used in the analysis were the same data used in the development of the original 22-item measure. These data were collected in 2003 via a telephone survey of 1,515 randomly selected adults. Principal Findings. The analysis yielded a 13-item measure that has psychometric properties similar to the original 22-item version. The scores for the 13-item measure range in value from 38.6 to 53.0 (on a theoretical 0-100 point scale). The range of values is essentially unchanged from the original 22-item version. Subgroup analysis suggests that there is a slight loss of precision with some subgroups. The results of the analysis indicate that the shortened 13-item version is both reliable and valid.
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            Do increases in patient activation result in improved self-management behaviors?

            The purpose of this study is to determine whether patient activation is a changing or changeable characteristic and to assess whether changes in activation also are accompanied by changes in health behavior. To obtain variability in activation and self-management behavior, a controlled trial with chronic disease patients randomized into either intervention or control conditions was employed. In addition, changes in activation that occurred in the total sample were also examined for the study period. Using Mplus growth models, activation latent growth classes were identified and used in the analysis to predict changes in health behaviors and health outcomes. Survey data from the 479 participants were collected at baseline, 6 weeks, and 6 months. Positive change in activation is related to positive change in a variety of self-management behaviors. This is true even when the behavior in question is not being performed at baseline. When the behavior is already being performed at baseline, an increase in activation is related to maintaining a relatively high level of the behavior over time. The impact of the intervention, however, was less clear, as the increase in activation in the intervention group was matched by nearly equal increases in the control group. Results suggest that if activation is increased, a variety of improved behaviors will follow. The question still remains, however, as to what interventions will improve activation.
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              Sample size and item calibration stability

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                Author and article information

                Contributors
                jillian.eyles@sydney.edu.au
                manuela.ferreira@sydney.edu.au
                kathryn.mills@mq.edu.au
                barbara.Lucas@sydney.edu.au
                sarah.robbins@sydney.edu.au
                Matthew.Williams1@health.nsw.gov.au
                LeeHans@ramsayhealth.com.au
                AppletonS@ramsayhealth.com.au
                david.hunter@sydney.edu.au
                Journal
                Health Qual Life Outcomes
                Health Qual Life Outcomes
                Health and Quality of Life Outcomes
                BioMed Central (London )
                1477-7525
                5 May 2020
                5 May 2020
                2020
                : 18
                : 121
                Affiliations
                [1 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, Kolling Institute of Medical Research, Institute of Bone and Joint Research, Faculty of Medicine and Health, University of Sydney, ; Sydney, Australia
                [2 ]GRID grid.412703.3, ISNI 0000 0004 0587 9093, Department of Rheumatology, , Royal North Shore Hospital , ; Sydney, Australia
                [3 ]GRID grid.412703.3, ISNI 0000 0004 0587 9093, Physiotherapy Department, Royal North Shore Hospital, ; Sydney, Australia
                [4 ]GRID grid.1004.5, ISNI 0000 0001 2158 5405, Faculty of Medicine and Health Sciences, , Macquarie University, ; Sydney, Australia
                [5 ]Rehabilitation Department, Hunters Hill Private Hospital, Sydney, Australia
                [6 ]Physiotherapy Department, Mount Wilga Private Hospital, Sydney, Australia
                Author information
                https://orcid.org/0000-0002-1625-8490
                https://orcid.org/0000-0002-0360-733X
                https://orcid.org/0000-0003-2587-1649
                https://orcid.org/0000-0003-3197-752X
                Article
                1364
                10.1186/s12955-020-01364-6
                7201682
                32370751
                5e224e3d-451d-4178-9165-e62e85d77338
                © The Author(s) 2020

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 6 July 2018
                : 14 April 2020
                Categories
                Research
                Custom metadata
                © The Author(s) 2020

                Health & Social care
                measurement properties,rasch,osteoarthritis,psychometrics,patient activation
                Health & Social care
                measurement properties, rasch, osteoarthritis, psychometrics, patient activation

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