Digi-Predict Asthma: Digital predictors of asthma attacks

This study is a prospective observational study to identify risk factors of asthma exacerbations. There is no active intervention. Unlike a traditional observational study, we are not assessing an exposure of interest and assessing outcome, rather we are measuring a diverse range of physiological, behavioural and environmental factors to evaluate their relationship(s) with asthma exacerbations. These variables include medication data from dispensing records and smart inhalers; peak flow data from a bluetooth smart peak flow meter; nocturnal cough from a cough monitoring app on the participant's phone; and physiological variables (e.g. heart rate) collected by a smart watch. All smart devices will be provided to the study participants. Diet, asthma control and general wellbeing will also be assessed using participant questionnaires. There will be two study visits in person – one at baseline (enrolment) and one at 6 months. The visits can take place either at The University of Auckland Grafton campus or at the participant's place of residence or other nominated location, whichever suits the participant best. These will be conducted by a member of the research team. At the initial visit at start of the study, participants will be provided with the required smart devices and instructions and a demonstration of how to use these devices. It is expected that these study visits would take up to 2 hours. In between these visits, participants will have some short questionnaires to complete either self-completed online remotely or researcher-assisted over the phone every 2 weeks for 6 months post-enrolment. These will take up to 5-10 minutes to complete. For the smart devices - participants will be given: a smart inhaler, smart peak flow meter, and smart watch. Some participants - those who already use a spacer on a regular basis and are familiar with the small volume spacer device - will be offered a smart (digital) spacer to use also instead of a traditional spacer. This measures inspiratory flow and inhalation. These devices will need to be paired to the participant's smart phone and their relevant app downloaded for it to work. Most of the data from the smart devices will be gathered passively i.e., participants won’t need to do anything extra other than use the devices as normal with their inhaler(s) and using the peak flow meter daily instead of your usual peak flow meter. Participants will need to use the cough monitoring app each night. Participants may need to open the apps a few times a week to ensure the data syncs successfully between the devices and the phone. Participants will need to wear the smartwatch during sleep and during awake hours everyday. Exceptions are made for wearing the smart watch for example when charging the watch and when having a shower or when there is any discomfort. Participants will also receive a quick text or phone call each month (whichever they prefer) to see how they are doing with the technology and devices. Researchers can access the collected data from the devices from the devices which will sync data with the related apps. To allow transfer of data from the smart devices, Bluetooth will need to be switched on. To send the data (upload), participants need to connect to the internet a few times a week to allow the data to be uploaded. This study involves collection of a large amount of information using different technologies to help us build a model using artificial intelligence (AI) to predict when an asthma attack might occur. We will use a type of AI called machine learning to analyse the data collected to identify patterns related to asthma attacks. The collected data will be entered into a machine learning component external to participants. No AI data will be fed back to participants at this stage of the study.