I am currently working on an interdisciplinary PhD project at the University of Manchester which is based in part at the School of Nursing, Midwifery and Social Work and at the School of Computer Science. My aim is to use both psychological and computer science research methods to explore how people with lung cancer use the internet to get informed about their illness. Specifically, I am interested in whether, and if so how, people utilize the internet prior to diagnosis to research their symptoms, and whether this influences their decision to present to health services. My ultimate goal is to make internet search and referrals more effective, thus encouraging earlier presentation in people with lung cancer, thereby increasing likelihood of successful treatment. My project is supervised jointly by Professor Chris Todd from the School of Nursing and Dr. Simon Harper from the School of Computer Science.
The abstract below provides a brief summary of my work, its scientific justification and aims:
Abstract. Lung cancer (LC) has the second-lowest survival rates among all cancer types. People often do not recognize LC symptoms and many wait for several months before presenting to health services. Therefore patients frequently present at a late stage when surgery is no longer possible. To effectively improve symptom awareness among the public and to encourage individuals to seek help promptly, it is important to understand which health information sources this particular patient group typically uses to appraise their symptoms, and how. Considering the rapidly increasing volume of health information on the Web as well as the increasing tendency of individuals to seek health information online, the Web could potentially be a key factor influencing health decisions. Among cancer patients, research to date has mainly examined the use of the Web after diagnosis has taken place. How Web-based content is used before a diagnosis to evaluate symptoms is unclear. There is evidence that people tend to look up unknown symptoms using internet search engines, but whether those with LC do this and how it influences their decision to seek medical help is unknown. The aim of our study is therefore to examine the role the Web currently plays in help-seeking among those with LC, and whether it reduces or prolongs patient delay. Once we have a better understanding of this, we can use strategies such as recommender systems and/or search engine optimization to direct users to appropriate resources tailored to their condition, and experimentally evaluate the impact of these strategies.