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      The Manchester Respiratory-related Sleep Symptoms scale for patients with COPD: development and validation

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          Abstract

          Background

          In COPD disturbed sleep is related to exacerbation frequency, poor quality of life, and early mortality. We developed the Manchester Respiratory-related Sleep Symptoms scale (MaRSS) to assess sleep-time symptoms in COPD.

          Methods

          Focus groups including COPD and age-matched controls were used to develop an item-list, which was then administered to COPD patients and age-matched controls in a cross-sectional study. Hierarchical and Rasch analysis informed item selection and scale unidimensionality. Construct validity was examined using Pearson’s correlation with the Sleep Problems Index, St George’s Respiratory Questionnaire (SGRQ), and FACIT-Fatigue scale. MaRSS change scores from baseline (stable) to exacerbation were assessed in a separate sub-study of COPD patients.

          Results

          Thirty-six COPD patients and nine age-matched controls produced an initial 26-item list. The cross-sectional study involved 203 COPD patients (male: 63%, mean age 64.7 years) and 50 age-matched controls (male: 56%, mean age 65.8 years). Eighteen items were removed to develop an eight-item unidimensional scale covering breathlessness, chest tightness, cough, sputum production, lack of sleep, and medication use. MaRSS scores significantly correlated with sleep problems, SGRQ Total, and FACIT-Fatigue ( r=0.58–0.62) and demonstrated a good fit to the Rasch model (chi-squared=29.2; P=0.04). In the substudy, MaRSS scores demonstrated a moderate effect size from baseline to exacerbation visit in 27 patients with 32 exacerbation episodes (Cohen’s d=0.6).

          Conclusion

          The MaRSS is a reliable, valid, and clinically responsive measure of respiratory-related symptoms that disturb sleep. It is simple to use and score, making it suitable for research and clinical practice.

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          Most cited references 11

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          Statistical methods for assessing agreement between two methods of clinical measurement.

          In clinical measurement comparison of a new measurement technique with an established one is often needed to see whether they agree sufficiently for the new to replace the old. Such investigations are often analysed inappropriately, notably by using correlation coefficients. The use of correlation is misleading. An alternative approach, based on graphical techniques and simple calculations, is described, together with the relation between this analysis and the assessment of repeatability.
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            Psychometric properties of the Medical Outcomes Study Sleep measure.

            Sleep is an active and highly organized biological process that is an important component of life. Self-report measures of sleep provide information that can be useful for characterizing the quality of sleep in subgroups of the population. A 12-item self-report sleep measure, the Medical Outcomes Study Sleep measure, was developed and evaluated previously in a sample of 3445 individuals with chronic illness. In this study, we evaluate the psychometric properties of the MOS Sleep measure in a nationally representative sample of 1011 US adults aged 18 and older and in a sample of 173 adults with neuropathic pain participating in a clinical drug trial. The average age of the general population sample was 46; 51% were female and 81% were white. The average age of the sample of adults with neuropathic pain was 72; 53% were female and 95% were white. Internal consistency reliability estimates for the MOS Sleep scales were 0.73 or higher, with the exception of the daytime somnolence scale in the US general population, which was 0.63. At baseline of the clinical trial, the neuropathic pain patients reported significantly more sleep disturbance and daytime somnolence, as well as less quantity and adequacy of sleep than patients in the general US population. The MOS Sleep scales were found to be responsive to change in the clinical trial with statistically significant improvements observed after administration of pregabalin for sleep disturbance (standardized response mean, SRM=-0.76, P=0.0007), shortness of breath (SRM=-0.20, P=0.0302), sleep adequacy (SRM=0.57, P=0.0014), sleep quantity (SRM=0.55, P=0.0086), and sleep problems (SRM=-0.62, P=0.0036). This study provides further support for the reliability and validity of the MOS Sleep measure. The instrument can be used to assess important aspects of sleep perceived by adults in the general population or participating in clinical studies.
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              Application of Rasch analysis in the development and application of quality of life instruments.

              This paper discusses recent advances that have been made in the field of psychometrics, specifically, the application of Rasch analysis to the instrument development process. It emphasizes the importance of assessing the fundamental scaling properties of an instrument prior to consideration of traditional psychometric indicators. The paper introduces Rasch analysis and shows how it has been applied in the development of needs-based measures in order to ensure that they provide unidimensional measurement. By ensuring that scales are based on the same measurement model and that they fit the Rasch model it is possible for QoL scores to be compared across diseases by means of cocalibration and item banking.
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                Author and article information

                Journal
                Int J Chron Obstruct Pulmon Dis
                Int J Chron Obstruct Pulmon Dis
                International Journal of COPD
                International Journal of Chronic Obstructive Pulmonary Disease
                Dove Medical Press
                1176-9106
                1178-2005
                2018
                29 November 2018
                : 13
                : 3885-3894
                Affiliations
                [1 ]The Medicines Evaluation Unit, Wythenshawe Hospital, Manchester, UK
                [2 ]University of Manchester, Manchester University NHS Foundation Trust, Manchester, UK
                [3 ]Division of Population Health, University of Manchester, Manchester, UK
                [4 ]Medicines Evaluation Unit, Manchester, UK
                [5 ]University of Manchester, Manchester, UK
                [6 ]University of Manchester, School of Health Sciences, Manchester Academic Health Sciences Centre, Manchester, UK
                [7 ]University of Manchester, The Medicines Evaluation Unit, Manchester, UK
                [8 ]University of Manchester, School of Health Sciences, Manchester, UK, janelle.yorke@ 123456manchester.ac.uk
                Author notes
                Correspondence: Janelle Yorke, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Room 5.320, Jean McFarlane University, Oxford Road, Manchester M13 9PL, UK, Tel +44 0 161 306 7780, Email janelle.yorke@ 123456manchester.ac.uk
                Article
                copd-13-3885
                10.2147/COPD.S171140
                6276610
                © 2018 Khan et al. This work is published and licensed by Dove Medical Press Limited

                The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License ( http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.

                Categories
                Original Research

                Respiratory medicine

                copd, sleep, dyspnea, cough, sputum, outcome measure

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