Behavioural change is a complex issue and there are many factors that impact willingness to start or stop a particular behaviour. In particular, perceptions, attitudes and other psychological factors play a vital role in administring a behavior. One of the examples of such problematic behaviour is non-adherence to asthma medication. Patients should be able to control their asthma by regular use of inhalers, hence preventing asthma exacerbations and even death. However, asthma adherence is poor, resulting in: severe symptoms and asthma attacks; considerable negative impact on patients’ lives and a significant care spending. A proactive, rather reactive health care is possible through the improvement of patient asthma-management, as long as we can understand what leads to a better adherence and how can this habitualness be created. This means understanding the perceptions, asthmatics, their psychological traits and the context of adherence-related behaviour (Dow et al, 2001; Wright et al, 2004).
Therefore, this research will focus on exploring behavioural change in terms of patients’ behaviour and the particular role that perceptions, attitudes and psychological traits have. In other words, the main research question will be:
What influences patients' behavioural change and leads to a higher level of adherence? This question will be investigated using mixed methods by conducting interviews and data mining novel data sources such as Twitter.
The first part of this PhD will investigate perceptions and attitudes patients and non-patients have about asthma. This will be done using predominantly open-source data from social media and interviews. In particular, the focus will be on defining and exploring perceptions extracted from context data (such as Twitter) as well extracting perceptions from qualitative research.
The second stage commences with an in-depth exploration of psychological traits that influence patients’ behaviour, through surveys and using novel data collection methodologies, such as data crowdsourcing. The questions that will be responded are: which are other factors that could be relevant for habit creation/prediction in terms of inhaler use (what are their individual and group-based variable importance) and how can they be collected, connected and understood.
Answering these complex questions can inform the development of the future delivery devices and inhalers, in other words – what kind of context data should be collected to positively influence patients’ behaviour. Following these finding, we will also be able to understand the asthmatics’ lifestyle and identity, reveal natural groups of asthmatics, based on patterns in their behaviour and psychological traits. Lastly, this research can open the door to the assessment of types of interventions that are the most likely to influence behaviour in each of these groups.
The drive toward a digital-based economy is bringing every asthmatic sufferer, their digital and environmental footprints and activities into one digital realm. Having insights from multiple fields could be the key to reduction of preventable deaths. The multidisciplinary nature of this research will combine predictive algorithms that can be used as risk stratification tools with medical purposes, along with psychological aspects. Taking into account ethical considerations, an ethical process will be subject to approval by the University of Nottingham and GSK, whereas data collected during this PhD will be stored and managed following the Data Protection principles.
This author is supported by the Horizon Centre for Doctoral Training at the University of Nottingham (RCUK Grant No. EP/L015463/1) and Glaxo Smith Kline.