Exploring the impact of the environment on physical activity in patients with chronic obstructive pulmonary disease (EPCOT)-A comparative analysis between suggested and free walking: Protocol study.
Larissa Guimarães PaivaTúlio Medina Dutra de OliveiraNara Batista de SouzaKlaus Chaves AlbertoDaniela Pereira AlmeidaCristino Carneiro OliveiraAnderson JoséCarla MalagutiPublished in: PloS one (2024)
The environment on physical activity for chronic obstructive disease (EPCOT) is a randomized controlled clinical trial protocol approved by our institution's Ethics Committee and registered with The Brazilian Registry of Clinical Trials (ReBEC) (https://ensaiosclinicos.gov.br, number RBR-4tfwdhp). This protocol will involve 38 volunteers diagnosed with COPD recruited from the pulmonary physiotherapy and rehabilitation service. The volunteers were randomly divided into two walking groups: an experimental group (ERG) with guidance for walking in a suggested environment and an active control group (ACG) instructed to choose their own routes. The intervention consisted of eight consecutive weeks, with progressive walks carried out 3 to 5 times weekly. The primary outcome will be assessing participants' physical activity levels. Secondary outcomes will include exercise capacity, quality of life, dyspnea levels, motivation, anxiety, depression, and perceptions of the environment. All assessments will occur before and after the intervention period, aiming to fill a literature gap by investigating the impact of urban environments on COPD-related physical activity. The results may shed light on the importance of environmental factors in promoting physical activity among individuals with COPD, helping to develop more effective interventions.
Keyphrases
- physical activity
- randomized controlled trial
- chronic obstructive pulmonary disease
- sleep quality
- clinical trial
- body mass index
- healthcare
- lung function
- primary care
- multiple sclerosis
- depressive symptoms
- systematic review
- type diabetes
- mental health
- machine learning
- pulmonary hypertension
- insulin resistance
- palliative care
- deep learning
- study protocol
- air pollution
- high intensity
- weight loss
- global health
- resistance training