In the original version of the book, the following belated corrections have been incorporated: The author name "Marcelo Brites" has been changed to "Marcelo Brites-Pereira" in the Frontmatter, Backmatter and in Chapter 49. The book has been updated with the changes.
There is growing evidence for the use of mobile health technology to support change in physical activity (PA) behaviour. However, studies in COPD have yielded mixed results, possibly because the contextual factors that characterise the use of mobile technology in COPD are not well understood. This study compared intrapersonal characteristics of patients with COPD who use mobile applications (apps) with those who do not.Patients with COPD were eligible if they used smartphones. They were surveyed about their use of mobile apps (any app beyond calls/texts apps), and specifically, apps for PA promotion and for COPD management, performed a 4.5m gait speed test and used an accelerometer (ActiGraph GT3X+) for 7 days. Chi-square, Mann-Whitney U and T-tests were used to compare sociodemographic (age, sex, marital status, education, occupation), health-related (FEV1pp, gait speed, CAT, mMRC, 6MWT) and PA (step count; time in sedentary, light, moderate and vigorous PA) characteristics between patients using and not using mobile apps.A total of 54 participants were enrolled (72% male; 67±8yrs; FEV1 48±18pp). 31/54 (57%) used mobile apps; from these, 15 (48%) used apps for PA promotion, 4 (13%) used apps for COPD management and 4 (13%) used both. Participants using mobile apps walked at a higher speed (Median [M] 1. 49 [1.33-1.72] vs. M 1.31 [0.98-1.54]m/s; p=0.021) and spent more time in vigorous PA (M 0.49 [0.14-1.45] vs. M 0.12 [0.07-0.84]min/day; p=0.025) than those not using apps. No other differences were found.Patients with COPD using apps presented higher functionality and PA behaviours than those not using them.Future studies should investigate possible explanations for these findings to inform future mHealth apps.
Effectiveness of technology-based interventions to improve physical activity (PA) in people with COPD is controversial. Mixed results may be due to participants' characteristics influencing their use of and engagement with mobile health apps. This study compared demographic, clinical, physical and PA characteristics of patients with COPD using and not using mobile apps in daily life. Patients with COPD who used smartphones were asked about their sociodemographic and clinic characteristics, PA habits and use of mobile apps (general and PA-related). Participants performed a six-minute walk test (6MWT), gait speed test and wore an accelerometer for 7 days. Data were compared between participants using (App Users) and not using (Non-App Users) mobile apps. A sub-analysis was conducted comparing characteristics of PA–App Users and Non-Users. 59 participants were enrolled (73% Male; 66.3 ± 8.3 yrs; FEV1 48.7 ± 18.4% predicted): 59% were App Users and 25% were PA-App Users. Significant differences between App Users and Non-App Users were found for age (64.2 ± 8.9 vs. 69.2 ± 6.3yrs), 6MWT (462.9 ± 91.7 vs. 414.9 ± 82.3 m), Gait Speed (Median 1.5 [Q1–Q3: 1.4–1.8] vs. 2.0 [1.0–1.5]m/s), Time in Vigorous PA (0.6 [0.2–2.8] vs. 0.14 [0.1–0.7]min) and Self-Reported PA (4.0 [1.0–4.0] vs. 1.0 [0.0–4.0] Points). Differences between PA–App Users and Non-Users were found in time in sedentary behavior (764.1 [641.8–819.8] vs. 672.2 [581.2–749.4] min) and self-reported PA (4.0 [2.0–6.0] vs. 2.0 [0.0–4.0] points). People with COPD using mobile apps were younger and had higher physical capacity than their peers not using mobile apps. PA-App Users spent more time in sedentary behaviors than Non-Users although self-reporting more time in PA.
Relationship between fatigue, physical activity and health-related factors in COPDFatigue is highly prevalent in COPD and may be associated with reduced physical activity (PA) and poor outcomes. This study explored the relationship between fatigue, objectively measured PA and health-related factors in people with COPD.Fatigue was assessed with the Checklist of Individual Strength (CIS20) and CIS20-Subjective Fatigue (CIS20-SF) and PA with Actigraph GT3X monitors (moderate-to-vigorous PA, MVPA; total PA; steps/day). Dyspnoea (modified Medical Research Council, mMRC), exercise tolerance (6min walk distance, 6MWD), lung function (spirometry) and GOLD classification A-D were collected. Spearman (ρ) and Pearson (r) correlations and multiple regressions were performed. Variables entered the model if correlation≥0.2. 54 patients participated (68±7yrs; 82% men) and 69% reported fatigue (CIS20-SF≥27). Fatigue was significantly correlated with MVPA, steps/day, mMRC, 6MWD, GOLD A-D and FEV1pp (Table 1). In regression models for CIS20 (p=.001; r 2 =.37) and CIS20-SF (p=.003; r 2 =.31), dyspnoea was the only significant variable.People with higher scores of fatigue present lower PA levels, although the relationship is weak. Dyspnoea appears to have the largest influence on fatigue.
Motivation and physical activity in COPD: an exploratory studyPatients with COPD value Health, Fitness and Psychological motives to be physically active, although these are not related to their PA behaviour. Findings highlight the complex nature of PA and the need to further explore factors influencing PA and motivation in this population.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.