PhD studentships in health technology @UCLIC (UCL Interaction Centre)

Please note: these are not our PhD studentships though a couple of the projects will be supervised by researchers who are also working on the CHI+MED project.

From UCLIC’s Opportunities page:

“We are recruiting to a iHealth PhD studentshipat the moment. Please see the advert and information on how to apply at PRISM – see further details. The closing date is 6 June 2014.”

In the ‘further details‘ document there are several potential / proposed projects for the iHealth studentship, two of them would be supervised by CHI+MED researchers including Prof Ann Blandford and Dr Anna Cox., highlighted in bold green below.

Digital engagement with health-related personal informatics systems
Personal informatics (PI) technologies like Fitbit, Runkeeper, Strava and MyFitnessPal are designed to enable people to collect data about different aspects of their lives and to help them to reflect upon their health and change their behaviour. There has been a huge increase in recent years in the number of PI systems available). There has also been significant interest within academia in developing systems to better support people in collecting and understanding personal data (e.g., Li et al., (2010), in encouraging behaviour change (e.g., Consolvo et al., 2008) and in understanding and supporting the development of habits (Judah et al, 2013, Stawarz et al 2014).

However, we know little about how best to design personal informatics systems to ensure engagement with the system that lasts long enough to enable people to develop healthy habits. What encourages people to reflect on their data? How effective are leaderboards in this context? Does reflection lead to new goals being set? Are those goals effective and realistic? How can the system encourage strong enough engagement to result in habit formation? The aim of this PhD project will be to develop prototype personal informatics systems aimed at supporting healthy behavior change and evaluate the effectiveness of design decisions using in-the-wild experimental techniques. Applicants should have a strong background in quantitative and qualitative research methods and will probably have an MSc or work experience in HCI or interaction design.

Proposed supervisors:
Anna Cox: UCL Interaction Centre, Div of Psychology & Language Sciences
Ben Gardner Sood: Health Behaviour Research Centre, Dept of Epidemiology & Public Health

Making sense of personal health data and medical knowledge: New approaches to online health interventions
Online systems – from Personal Health Records to peer support – are commonplace in modern medicine. In the UK, individual online access to GP records is forthcoming to help deliver the policy of ‘no decision about me, without me’. Many online interventions have proven successful at improving patient outcomes, yet many others still fail. A traditional evidence-based medicine approach struggles to explain why: a recent systematic review concluded “insufficient reporting of implementation and context of use makes it impossible to determine why some health IT implementations are successful and others are not.” We need different methodological approaches: ones that can explore the detailed factors that influence outcomes. Such techniques have been developed within human-computer interaction research, and are increasingly applied in healthcare; they deliver insights that complement those from established health research approaches.

The current project will take a cross-faculty, interdisciplinary approach centred on two case studies: Patients Know Best at Great Ormond Street Hospital, and Shift.ms. PKB is a patient-managed online health record, currently available in over 25 UK hospitals (including GOSH) and internationally. Shift.ms is a social networking and information provision site for people suffering from multiple sclerosis, used in UCLH.

We will investigate how users (patients and carers) use these online systems to make sense of their own health conditions, what information they share or keep private, and how design features and contextual factors influence people’s use and experiences of such systems. Data gathering will be qualitative and longitudinal (involving interviews, observations, think-aloud protocols and patient diaries), supplemented by quantitative measures of degree of engagement. Data will be analysed through established qualitative and quantitative techniques, drawing (as appropriate) on theories of information interaction, sense making and health cognition. Findings will inform the design of future online health interventions as well as contributing to our theoretical understanding of this area.

Proposed supervisors:
Henry Potts: CHIME, Faculty of Population Health Sciences
Ann Blandford: UCL Interaction Centre (Human-Computer Interaction)

 

 

 

 

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