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      Blended Self-Management Interventions to Reduce Disease Burden in Patients With Chronic Obstructive Pulmonary Disease and Asthma: Systematic Review and Meta-analysis

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          Abstract

          Background

          Chronic obstructive pulmonary disease (COPD) and asthma have a high prevalence and disease burden. Blended self-management interventions, which combine eHealth with face-to-face interventions, can help reduce the disease burden.

          Objective

          This systematic review and meta-analysis aims to examine the effectiveness of blended self-management interventions on health-related effectiveness and process outcomes for people with COPD or asthma.

          Methods

          PubMed, Web of Science, COCHRANE Library, Emcare, and Embase were searched in December 2018 and updated in November 2020. Study quality was assessed using the Cochrane risk of bias (ROB) 2 tool and the Grading of Recommendations, Assessment, Development, and Evaluation.

          Results

          A total of 15 COPD and 7 asthma randomized controlled trials were included in this study. The meta-analysis of COPD studies found that the blended intervention showed a small improvement in exercise capacity (standardized mean difference [SMD] 0.48; 95% CI 0.10-0.85) and a significant improvement in the quality of life (QoL; SMD 0.81; 95% CI 0.11-1.51). Blended intervention also reduced the admission rate (relative ratio [RR] 0.61; 95% CI 0.38-0.97). In the COPD systematic review, regarding the exacerbation frequency, both studies found that the intervention reduced exacerbation frequency (RR 0.38; 95% CI 0.26-0.56). A large effect was found on BMI ( d=0.81; 95% CI 0.25-1.34); however, the effect was inconclusive because only 1 study was included. Regarding medication adherence, 2 of 3 studies found a moderate effect ( d=0.73; 95% CI 0.50-0.96), and 1 study reported a mixed effect. Regarding self-management ability, 1 study reported a large effect ( d=1.15; 95% CI 0.66-1.62), and no effect was reported in that study. No effect was found on other process outcomes. The meta-analysis of asthma studies found that blended intervention had a small improvement in lung function (SMD 0.40; 95% CI 0.18-0.62) and QoL (SMD 0.36; 95% CI 0.21-0.50) and a moderate improvement in asthma control (SMD 0.67; 95% CI 0.40-0.93). A large effect was found on BMI ( d=1.42; 95% CI 0.28-2.42) and exercise capacity ( d=1.50; 95% CI 0.35-2.50); however, 1 study was included per outcome. There was no effect on other outcomes. Furthermore, the majority of the 22 studies showed some concerns about the ROB, and the quality of evidence varied.

          Conclusions

          In patients with COPD, the blended self-management interventions had mixed effects on health-related outcomes, with the strongest evidence found for exercise capacity, QoL, and admission rate. Furthermore, the review suggested that the interventions resulted in small effects on lung function and QoL and a moderate effect on asthma control in patients with asthma. There is some evidence for the effectiveness of blended self-management interventions for patients with COPD and asthma; however, more research is needed.

          Trial Registration

          PROSPERO International Prospective Register of Systematic Reviews CRD42019119894; https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=119894

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          Most cited references77

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          RoB 2: a revised tool for assessing risk of bias in randomised trials

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            A power primer.

            One possible reason for the continued neglect of statistical power analysis in research in the behavioral sciences is the inaccessibility of or difficulty with the standard material. A convenient, although not comprehensive, presentation of required sample sizes is provided here. Effect-size indexes and conventional values for these are given for operationally defined small, medium, and large effects. The sample sizes necessary for .80 power to detect effects at these levels are tabled for eight standard statistical tests: (a) the difference between independent means, (b) the significance of a product-moment correlation, (c) the difference between independent rs, (d) the sign test, (e) the difference between independent proportions, (f) chi-square tests for goodness of fit and contingency tables, (g) one-way analysis of variance, and (h) the significance of a multiple or multiple partial correlation.
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              Interrater reliability: the kappa statistic

              The kappa statistic is frequently used to test interrater reliability. The importance of rater reliability lies in the fact that it represents the extent to which the data collected in the study are correct representations of the variables measured. Measurement of the extent to which data collectors (raters) assign the same score to the same variable is called interrater reliability. While there have been a variety of methods to measure interrater reliability, traditionally it was measured as percent agreement, calculated as the number of agreement scores divided by the total number of scores. In 1960, Jacob Cohen critiqued use of percent agreement due to its inability to account for chance agreement. He introduced the Cohen’s kappa, developed to account for the possibility that raters actually guess on at least some variables due to uncertainty. Like most correlation statistics, the kappa can range from −1 to +1. While the kappa is one of the most commonly used statistics to test interrater reliability, it has limitations. Judgments about what level of kappa should be acceptable for health research are questioned. Cohen’s suggested interpretation may be too lenient for health related studies because it implies that a score as low as 0.41 might be acceptable. Kappa and percent agreement are compared, and levels for both kappa and percent agreement that should be demanded in healthcare studies are suggested.
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                Author and article information

                Contributors
                Journal
                J Med Internet Res
                J Med Internet Res
                JMIR
                Journal of Medical Internet Research
                JMIR Publications (Toronto, Canada )
                1439-4456
                1438-8871
                March 2021
                31 March 2021
                : 23
                : 3
                : e24602
                Affiliations
                [1 ] Department of Public Health and Primary Care Leiden University Medical Center Leiden Netherlands
                [2 ] Faculty of Nursing and Health Zhengzhou University Zhengzhou China
                [3 ] Faculty of Health, Sports and Social Work Inholland University of Applied Sciences Amsterdam Netherlands
                [4 ] Zonnehuisgroep Amstelland Amstelveen Netherlands
                [5 ] Department Family Medicine and Population Health Faculty of Medicine and Health Sciences University of Antwerp Antwerp Belgium
                Author notes
                Corresponding Author: Xiaoyue Song x.song@ 123456lumc.nl
                Author information
                https://orcid.org/0000-0001-6533-6136
                https://orcid.org/0000-0003-3881-5419
                https://orcid.org/0000-0003-3765-756X
                https://orcid.org/0000-0003-2048-4906
                https://orcid.org/0000-0002-0601-4708
                https://orcid.org/0000-0001-6225-5189
                https://orcid.org/0000-0002-8638-4978
                https://orcid.org/0000-0002-8607-9199
                https://orcid.org/0000-0002-9489-7925
                Article
                v23i3e24602
                10.2196/24602
                8047793
                33788700
                a1b5513f-d91e-44eb-a3b5-31af8885c6a2
                ©Xiaoyue Song, Cynthia Hallensleben, Weihong Zhang, Zongliang Jiang, Hongxia Shen, Robbert J J Gobbens, Rianne M J J Van Der Kleij, Niels H Chavannes, Anke Versluis. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 31.03.2021.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License ( https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in the Journal of Medical Internet Research, is properly cited. The complete bibliographic information, a link to the original publication on http://www.jmir.org/, as well as this copyright and license information must be included.

                History
                : 26 September 2020
                : 26 November 2020
                : 17 January 2021
                : 18 January 2021
                Categories
                Review
                Review

                Medicine
                blended intervention,copd,asthma,meta-analysis,systematic review
                Medicine
                blended intervention, copd, asthma, meta-analysis, systematic review

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