Developing a Smartphone Application That Promotes Responsible Short-Acting Beta2-Agonist Use in People with Asthma: A Participatory Design.
Liselot Nicoline van den BergCynthia HallenslebenNiels Henrik ChavannesAnke VersluisPublished in: International journal of environmental research and public health (2022)
Around 339 million people worldwide have asthma, and 50% have uncontrolled asthma. One trait of uncontrolled asthma, often seen in primary care, is short-acting β2-agonist (SABA) overuse, defined as using SABA more than twice a week. SABA overuse can cause adverse health effects. An application could help patients gain more insight into their SABA use. Engaging stakeholders during the development is important to maximize the usability of and adherence to an application. This study describes the development process of an application that promotes responsible SABA use in people with asthma, using a participatory design. Different stakeholder groups were involved in two iterative development cycles. In the first cycle, four end-users evaluated the app's prototype. During the second cycle, five end-users were interviewed about the usability of the new version. Resulting in an app that allows patients to register SABA use, asthma symptoms, and symptom triggers. A graph shows how these factors are related, and end-users can show the graph to their physician to facilitate communication. Medication use is compared to the medical guidelines or, when applicable, to the advice given by the users' healthcare professionals. End-users found the app helpful. Research into the usability and effectiveness of the app in a bigger sample will follow.
Keyphrases
- chronic obstructive pulmonary disease
- lung function
- primary care
- end stage renal disease
- allergic rhinitis
- ejection fraction
- chronic kidney disease
- newly diagnosed
- healthcare
- randomized controlled trial
- peritoneal dialysis
- electronic health record
- health information
- systematic review
- cystic fibrosis
- type diabetes
- gene expression
- emergency department
- air pollution
- clinical trial
- machine learning
- magnetic resonance imaging
- patient reported
- patient reported outcomes
- clinical practice
- study protocol
- metabolic syndrome
- insulin resistance
- convolutional neural network
- genome wide
- weight loss
- general practice
- dual energy