The Use of a Smartphone App and an Activity Tracker to Promote Physical Activity in the Management of Chronic Obstructive Pulmonary Disease: Randomized Controlled Feasibility Study

• Published in: JMIR mHealth and uHealth Vol. 8; no. 6; p. e16203
• Main Authors: Bentley, Claire L, Powell, Lauren, Potter, Stephen, Parker, Jack, Mountain, Gail A, Bartlett, Yvonne Kiera, Farwer, Jochen, O'Connor, Cath, Burns, Jennifer, Cresswell, Rachel L, Dunn, Heather D, Hawley, Mark S
• Format: Journal Article
• Language: English
• Published: Canada JMIR Publications 03.06.2020
• Subjects: Behavior; Chronic illnesses; Chronic obstructive pulmonary disease; Digital technology; Exercise; Feasibility Studies; Feedback; Fitness Trackers; Health care; Health services; Humans; Intervention; Interviews; Mobile Applications; Motivation; Original Paper; Personal health; Physical fitness; Pulmonary Disease, Chronic Obstructive - therapy; Quality of life; Smartphone; Smartphones; Technology Acceptance Model; Usability testing; United Kingdom > UK; feasibility; mobile health; activity tracker; health behavior change; mHealth; pulmonary rehabilitation; Fitbit; self-management; chronic obstructive pulmonary disease; physical activity
• ISSN: 2291-5222; 2291-5222
• DOI: 10.2196/16203

Chronic obstructive pulmonary disease (COPD) is highly prevalent and significantly affects the daily functioning of patients. Self-management strategies, including increasing physical activity, can help people with COPD have better health and a better quality of life. Digital mobile health (mHealth) techniques have the potential to aid the delivery of self-management interventions for COPD. We developed an mHealth intervention (Self-Management supported by Assistive, Rehabilitative, and Telehealth technologies-COPD [SMART-COPD]), delivered via a smartphone app and an activity tracker, to help people with COPD maintain (or increase) physical activity after undertaking pulmonary rehabilitation (PR). This study aimed to determine the feasibility and acceptability of using the SMART-COPD intervention for the self-management of physical activity and to explore the feasibility of conducting a future randomized controlled trial (RCT) to investigate its effectiveness. We conducted a randomized feasibility study. A total of 30 participants with COPD were randomly allocated to receive the SMART-COPD intervention (n=19) or control (n=11). Participants used SMART-COPD throughout PR and for 8 weeks afterward (ie, maintenance) to set physical activity goals and monitor their progress. Questionnaire-based and physical activity-based outcome measures were taken at baseline, the end of PR, and the end of maintenance. Participants, and health care professionals involved in PR delivery, were interviewed about their experiences with the technology. Overall, 47% (14/30) of participants withdrew from the study. Difficulty in using the technology was a common reason for withdrawal. Participants who completed the study had better baseline health and more prior experience with digital technology, compared with participants who withdrew. Participants who completed the study were generally positive about the technology and found it easy to use. Some participants felt their health had benefitted from using the technology and that it assisted them in achieving physical activity goals. Activity tracking and self-reporting were both found to be problematic as outcome measures of physical activity for this study. There was dissatisfaction among some control group members regarding their allocation. mHealth shows promise in helping people with COPD self-manage their physical activity levels. mHealth interventions for COPD self-management may be more acceptable to people with prior experience of using digital technology and may be more beneficial if used at an earlier stage of COPD. Simplicity and usability were more important for engagement with the SMART-COPD intervention than personalization; therefore, the intervention should be simplified for future use. Future evaluation will require consideration of individual factors and their effect on mHealth efficacy and use; within-subject comparison of step count values; and an opportunity for control group participants to use the intervention if an RCT were to be carried out. Sample size calculations for a future evaluation would need to consider the high dropout rates.