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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Abstract Aim: This study protocol aims to examine the effectiveness and preconditions of a self-management program—named REducing Delay through edUcation on eXacerbations (REDUX)—in China. Background: The high disease burden in people with chronic lung disease is mainly due to exacerbations. There is a need for effective exacerbation-management interventions. A nurse-led program, REDUX, helped patients self-manage exacerbations. Design: A single-arm pre-post study. Methods: Fifty-four patients and 24 healthcare professionals (HCPs) in Chinese primary care will be included. The core element of the program is a personalized action plan. HCPs will receive training in using the action plan to help patients manage exacerbations. The intervention will start when a patient is referred to the nurse for a post-exacerbation consultation and ends when the patient presents for the second post-exacerbation consultation. During the first post-exacerbation consultation, the patient and nurse will create the action plan. The primary outcomes in patients will include the delays between the onset of exacerbation and recognition, between exacerbation recognition and action, between exacerbation recognition and consultation with a doctor, and when the patients feel better after receiving medical help from HCPs. The secondary outcomes will include preconditions of the program. The ethics approval was obtained in September 2021. Discussion: This study will discuss a culturally adapted nurse-led self-management intervention for people with chronic lung disease in China. The intervention could help Chinese HCPs provide efficient care and reduce their workload. Furthermore, it will inform future research on tailoring nurse-led self-management interventions in different contexts. Impact: The study will contribute to the evidence on the effectiveness and preconditions of REDUX in China. If effective, the result will assist the nursing of people with chronic lung disease. Trial registration: Registered in the Chinese clinical trial registry (ID: 2100051782).
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A substantial proportion of chronic disease patients do not respond to self-management interventions, which suggests that one size interventions do not fit all, demanding more tailored interventions. To compose more individualized strategies, we aim to increase our understanding of characteristics associated with patient activation for self-management and to evaluate whether these are disease-transcending. A cross-sectional survey study was conducted in primary and secondary care in patients with type-2 Diabetes Mellitus (DM-II), Chronic Obstructive Pulmonary Disease (COPD), Chronic Heart Failure (CHF) and Chronic Renal Disease (CRD). Using multiple linear regression analysis, we analyzed associations between self-management activation (13-item Patient Activation Measure; PAM-13) and a wide range of socio-demographic, clinical, and psychosocial determinants. Furthermore, we assessed whether the associations between the determinants and the PAM were disease-transcending by testing whether disease was an effect modifier. In addition, we identified determinants associated with low activation for self-management using logistic regression analysis. We included 1154 patients (53% response rate); 422 DM-II patients, 290 COPD patients, 223 HF patients and 219 CRD patients. Mean age was 69.6±10.9. Multiple linear regression analysis revealed 9 explanatory determinants of activation for selfmanagement: age, BMI, educational level, financial distress, physical health status, depression, illness perception, social support and underlying disease, explaining a variance of 16.3%. All associations, except for social support, were disease transcending. This study explored factors associated with varying levels of activation for self-management. These results are a first step in supporting clinicians and researchers to identify subpopulations of chronic disease patients less likely to be engaged in self-management. Increased scientific efforts are needed to explain the greater part of the factors that contribute to the complex nature of patient activation for self-management.
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Chronic diseases represent a significant burden for the society and health systems; addressing this burden is a key goal of the European Union policy. Health and other professionals are expected to deliver behaviour change support to persons with chronic disease. A skill gap in behaviour change support has been identified, and there is room for improvement. Train4Health is a strategic partnership involving seven European Institutions in five countries, which seeks to improve behaviour change support competencies for the self-management of chronic disease. The project envisages a continuum in behaviour change support education, in which an interprofessional competency framework, relevant for those currently practising, guides the development of a learning outcomes-based curriculum and an educational package for future professionals (today’s undergraduate students).
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A loss of physical functioning (i.e., a low physical capacity and/or a low physical activity) is a common feature in patients with chronic obstructive pulmonary disease (COPD). To date, the primary care physiotherapy and specialized pulmonary rehabilitation are clearly underused, and limited to patients with a moderate to very severe degree of airflow limitation (GOLD stage 2 or higher). However, improved referral rates are a necessity to lower the burden for patients with COPD and for society. Therefore, a multidisciplinary group of healthcare professionals and scientists proposes a new model for referral of patients with COPD to the right type of exercise-based care, irrespective of the degree of airflow limitation. Indeed, disease instability (recent hospitalization, yes/no), the burden of disease (no/low, mild/moderate or high), physical capacity (low or preserved) and physical activity (low or preserved) need to be used to allocate patients to one of the six distinct patient profiles. Patients with profile 1 or 2 will not be referred for physiotherapy; patients with profiles 3–5 will be referred for primary care physiotherapy; and patients with profile 6 will be referred for screening for specialized pulmonary rehabilitation. The proposed Dutch model has the intention to get the right patient with COPD allocated to the right type of exercise-based care and at the right moment.
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If eHealth interventions are not used (properly), their potential benefits cannot be fulfilled. User perceptions of eHealth are an important determinant of its successful implementation. This study examined how patients with chronic obstructive pulmonary disease (COPD) and their physiotherapists (PHTs) value an eHealth self-management intervention following a period of use. The study aimed to evaluate the perceptions of COPD patients and their PHTs as eHealth users. In this study, an eHealth self-management intervention (website and mobile phone app) aimed at stimulating physical activity (PA) in COPD patients was evaluated by its users (patients and PHTs). As participants in a randomized controlled trial (RCT), they were asked how they valued the eHealth intervention after 6 months’ use. Interview requests were made to 33 PHTs from 26 participating practices, and a questionnaire was sent to 76 patients. The questionnaire was analyzed in Excel (Microsoft). The interviews with the PHTs and text messages (short message service, SMS) sent between patients and PHTs were transcribed and independently coded in MAXQDA 10 for Windows (VERBI GmbH).
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This open access book is a valuable resource for students in health and other professions and practicing professionals interested in supporting effective change in self-management behaviors in chronic disease, such as medication taking, physical activity and healthy eating. Developed under the auspices of the Train4Health project, funded by the Erasmus+ program of the European Union, the book contains six chapters written by international contributors from different disciplines. This chapter sets the stage for the remaining book, by introducing the Train4Health project and by explaining how the learning outcomes presented in subsequent chapters have been derived and linked with content of the book. Firstly, the Train4Health interprofessional competency framework to support behaviour change in persons self-managing chronic disease is briefly presented. This European competency framework was the starting point for developing the learning outcomes-based curriculum, which is succinctly addressed in the subsequent section. Finally, practical considerations about the Train4Health curriculum are discussed, including opportunities and challenges for interprofessional education.
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Background: COPD self-management is a complex behavior influenced by many factors. Despite scientific evidence that better disease outcomes can be achieved by enhancing self-management, many COPD patients do not respond to self-management interventions. To move toward more effective self-management interventions, knowledge of characteristics associated with activation for self-management is needed. The purpose of this study was to identify key patient and disease characteristics of activation for self-management. Methods: An explorative cross-sectional study was conducted in primary and secondary care in patients with COPD. Data were collected through questionnaires and chart reviews. The main outcome was activation for self-management, measured with the 13-item Patient Activation Measure (PAM). Independent variables were sociodemographic variables, self-reported health status, depression, anxiety, illness perception, social support, disease severity, and comorbidities. Results: A total of 290 participants (age: 67.2±10.3; forced expiratory volume in 1 second predicted: 63.6±19.2) were eligible for analysis. While poor activation for self-management (PAM-1) was observed in 23% of the participants, only 15% was activated for self-management (PAM-4). Multiple linear regression analysis revealed six explanatory determinants of activation for self-management (P,0.2): anxiety (β: -0.35; -0.6 to -0.1), illness perception (β: -0.2; -0.3 to -0.1), body mass index (BMI) (β: -0.4; -0.7 to -0.2), age (β: -0.1; -0.3 to -0.01), Global Initiative for Chronic Obstructive Lung Disease stage (2 vs 1 β: -3.2; -5.8 to -0.5; 3 vs 1 β: -3.4; -7.1 to 0.3), and comorbidities (β: 0.8; -0.2 to 1.8), explaining 17% of the variance. Conclusion: This study showed that only a minority of COPD patients is activated for self-management. Although only a limited part of the variance could be explained, anxiety, illness perception, BMI, age, disease severity, and comorbidities were identified as key determinants of activation for self-management. This knowledge enables health care professionals to identify patients at risk of inadequate self-management, which is essential to move toward targeting and tailoring of self-management interventions. Future studies are needed to understand the complex causal mechanisms toward change in self-management
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Background: There is an emergence of mobile health (mHealth) interventions to support self-management in patients with chronic obstructive pulmonary disease (COPD). Recently, an evidence-driven mHealth intervention has been developed to support patients with COPD in exacerbation-related self-management: the Copilot app. Health care providers (HCPs) are important stakeholders as they are the ones who have to provide the app to patients, personalize the app, and review the app. It is, therefore, important to investigate at an early stage whether the app is feasible in the daily practice of the HCPs. Objective: The aim of this study is to evaluate the perceived feasibility of the Copilot app in the daily practice of HCPs. Methods: A multimethods design was used to investigate how HCPs experience working with the app and how they perceive the feasibility of the app in their daily practice. The feasibility areas described by Bowen et al were used for guidance. HCPs were observed while performing tasks in the app and asked to think aloud. The System Usability Scale was used to investigate the usability of the app, and semistructured interviews were conducted to explore the feasibility of the app. The study was conducted in primary, secondary, and tertiary care settings in the Netherlands from February 2019 to September 2019. Results: In total, 14 HCPs participated in this study—8 nurses, 5 physicians, and 1 physician assistant. The HCPs found the app acceptable to use. The expected key benefits of the app were an increased insight into patient symptoms, more structured patient conversations, and more tailored self-management support. The app especially fits within the available time and workflow of nurses. The use of the app will be influenced by the autonomy of the professional, the focus of the organization on eHealth, costs associated with the app, and compatibility with the current systems used. Most HCPs expressed that there are conditions that must be met to be able to use the app. The app can be integrated into the existing care paths of primary, secondary, and tertiary health care settings. Individual organizational factors must be taken into account when integrating the app into daily practice. Conclusions: This early-stage feasibility study shows that the Copilot app is feasible to use in the daily practice of HCPs and can be integrated into primary, secondary, and tertiary health care settings in the Netherlands. The app was considered to best fit the role of the nurses. The app will be less feasible for those organizations in which many conditions need to be met to use the app. This study provides a new approach to evaluate the perceived feasibility of mHealth interventions at an early stage and provides valuable insights for further feasibility testing.
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Background: Adequate self-management skills are of great importance for patients with chronic obstructive pulmonary disease (COPD) to reduce the impact of COPD exacerbations. Using mobile health (mHealth) to support exacerbation-related self-management could be promising in engaging patients in their own health and changing health behaviors. However, there is limited knowledge on how to design mHealth interventions that are effective, meet the needs of end users, and are perceived as useful. By following an iterative user-centered design (UCD) process, an evidence-driven and usable mHealth intervention was developed to enhance exacerbation-related self-management in patients with COPD. Objective: This study aimed to describe in detail the full UCD and development process of an evidence-driven and usable mHealth intervention to enhance exacerbation-related self-management in patients with COPD. Methods: The UCD process consisted of four iterative phases: (1) background analysis and design conceptualization, (2) alpha usability testing, (3) iterative software development, and (4) field usability testing. Patients with COPD, health care providers, COPD experts, designers, software developers, and a behavioral scientist were involved throughout the design and development process. The intervention was developed using the behavior change wheel (BCW), a theoretically based approach for designing behavior change interventions, and logic modeling was used to map out the potential working mechanism of the intervention. Furthermore, the principles of design thinking were used for the creative design of the intervention. Qualitative and quantitative research methods were used throughout the design and development process. Results: The background analysis and design conceptualization phase resulted in final guiding principles for the intervention, a logic model to underpin the working mechanism of the intervention, and design requirements. Usability requirements were obtained from the usability testing phases. The iterative software development resulted in an evidence-driven and usable mHealth intervention—Copilot, a mobile app consisting of a symptom-monitoring module, and a personalized COPD action plan. Conclusions: By following a UCD process, an mHealth intervention was developed that meets the needs and preferences of patients with COPD, is likely to be used by patients with COPD, and has a high potential to be effective in reducing exacerbation impact. This extensive report of the intervention development process contributes to more transparency in the development of complex interventions in health care and can be used by researchers and designers as guidance for the development of future mHealth interventions.
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