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      Activating primary care COPD patients with multi-morbidity through tailored self-management support

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          Abstract

          Given the dearth of COPD self-management interventions that specifically acknowledge multi-morbidity in primary care, we aimed to activate COPD patients through personalised self-management support that recognised the implications of co-morbidities. This single-group experimental study included patients aged 40−84 with a spirometry diagnosis of COPD and at least one co-morbidity. A self-management education programme for COPD in the context of multi-morbidity, based on the Health Belief Model, was tailored and delivered to participants by general practice nurses in face-to-face sessions. At 6 months’ follow-up, there was significant improvement in patient activation ( p < 0.001), COPD-related quality of life ( p = 0.012), COPD knowledge ( p < 0.001) and inhaler device technique ( p = 0.001), with no significant change in perception of multi-morbidity ( p = 0.822) or COPD-related multi-morbidity (0.084). The programme improved patients’ self-efficacy for their COPD as well as overall health behaviour. The findings form an empirical basis for further testing the programme in a large-scale randomised controlled trial.

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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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            The statistical interpretation of pilot trials: should significance thresholds be reconsidered?

            Background In an evaluation of a new health technology, a pilot trial may be undertaken prior to a trial that makes a definitive assessment of benefit. The objective of pilot studies is to provide sufficient evidence that a larger definitive trial can be undertaken and, at times, to provide a preliminary assessment of benefit. Methods We describe significance thresholds, confidence intervals and surrogate markers in the context of pilot studies and how Bayesian methods can be used in pilot trials. We use a worked example to illustrate the issues raised. Results We show how significance levels other than the traditional 5% should be considered to provide preliminary evidence for efficacy and how estimation and confidence intervals should be the focus to provide an estimated range of possible treatment effects. We also illustrate how Bayesian methods could also assist in the early assessment of a health technology. Conclusions We recommend that in pilot trials the focus should be on descriptive statistics and estimation, using confidence intervals, rather than formal hypothesis testing and that confidence intervals other than 95% confidence intervals, such as 85% or 75%, be used for the estimation. The confidence interval should then be interpreted with regards to the minimum clinically important difference. We also recommend that Bayesian methods be used to assist in the interpretation of pilot trials. Surrogate endpoints can also be used in pilot trials but they must reliably predict the overall effect on the clinical outcome.
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              Chronic obstructive pulmonary disease exacerbation and inhaler device handling: real-life assessment of 2935 patients.

              Acute exacerbations of chronic obstructive pulmonary disease (COPD) can be prevented by inhaled treatment. Errors in inhaler handling, not taken into account in clinical trials, could impact drug delivery and minimise treatment benefit. We aimed to assess real-life inhaler device handling in COPD patients and its association with COPD exacerbations.To this end, 212 general practitioners and 50 pulmonologists assessed the handling of 3393 devices used for continuous treatment of COPD in 2935 patients. Handling errors were observed in over 50% of handlings, regardless of the device used. Critical errors compromising drug delivery were respectively made in 15.4%, 21.2%, 29.3%, 43.8%, 46.9% and 32.1% of inhalation assessment tests with Breezhaler® (n=876), Diskus® (n=452), Handihaler® (n=598), pressurised metered-dose inhaler (pMDI) (n=422), Respimat® (n=625) and Turbuhaler® (n=420).The proportion of patients requiring hospitalisation or emergency room visits in the past 3 months for severe COPD exacerbation was 3.3% (95% CI 2.0-4.5) in the absence of error and 6.9% (95% CI 5.3-8.5) in the presence of critical error (OR 1.86, 95% CI 1.14-3.04, p<0.05).Handling errors of inhaler devices are underestimated in real life and are associated with an increased rate of severe COPD exacerbation. Training in inhaler use is an integral part of COPD management.
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                Author and article information

                Contributors
                sameera.ansari@unsw.edu.au
                Journal
                NPJ Prim Care Respir Med
                NPJ Prim Care Respir Med
                NPJ Primary Care Respiratory Medicine
                Nature Publishing Group UK (London )
                2055-1010
                3 April 2020
                3 April 2020
                2020
                : 30
                : 12
                Affiliations
                [1 ]ISNI 0000 0004 4902 0432, GRID grid.1005.4, School of Public Health and Community Medicine, , UNSW Sydney, ; Sydney, NSW Australia
                [2 ]ISNI 0000 0004 0486 528X, GRID grid.1007.6, School of Health and Society, , University of Wollongong Australia, ; Wollongong, NSW Australia
                [3 ]ISNI 0000 0004 1936 834X, GRID grid.1013.3, Sydney School of Health Sciences, Faculty of Medicine and Health, , The University of Sydney, ; Sydney, NSW Australia
                [4 ]GRID grid.429098.e, Ingham Institute for Applied Medical Research, ; Sydney, NSW Australia
                [5 ]ISNI 0000 0001 2105 7653, GRID grid.410692.8, South Western Sydney Local Health District, ; Sydney, NSW Australia
                [6 ]ISNI 0000 0004 4902 0432, GRID grid.1005.4, Centre for Primary Health Care and Equity, , UNSW Sydney, ; Sydney, NSW Australia
                [7 ]ISNI 0000 0004 0405 3820, GRID grid.1033.1, Faculty of Health Sciences and Medicine, , Bond University, ; Gold Coast, QLD Australia
                Author information
                http://orcid.org/0000-0003-3192-7936
                http://orcid.org/0000-0002-8638-5372
                Article
                171
                10.1038/s41533-020-0171-5
                7125179
                32245961
                9aeaa0ec-d71a-4ddb-b25e-626f8c6c73ff
                © The Author(s) 2020

                Open Access This 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 28 April 2019
                : 5 March 2020
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100001203, GlaxoSmithKline Australia (GSKA);
                Award ID: 204950
                Award ID: 204950
                Award ID: 204950
                Award ID: 204950
                Award Recipient :
                Funded by: FundRef https://doi.org/10.13039/501100000925, Department of Health | National Health and Medical Research Council (NHMRC);
                Award ID: GNT1093032
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2020

                chronic obstructive pulmonary disease,patient education,health services,translational research,public health

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