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Evaluating innovative digital tools to capture electronic patient-reported outcome measurement data for research and clinical care (MRC CASE)

Faculty of Biology, Medicine and Health

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Dr S Van der Veer , Prof W Dixon , Dr J McBeth No more applications being accepted Competition Funded PhD Project (European/UK Students Only)

About the Project

Patient-reported outcome measures (PROMs) reflect the personal impact of illness and treatment as assessed by patients, such as symptom burden or health-related quality of life. Capturing this personal impact is increasingly important in research (e.g. drug trials)1 and clinical settings (e.g. to inform treatment decisions)2. Traditionally, PROMs were paper-based questionnaires. But nowadays, novel data capture methods are available that make optimal use of digital technologies, such as smartphones and smartwatches. This opens up opportunities for research and clinical care to collect PROM data more frequently and in larger populations. However, the measurement properties of these ePROM tools are often unknown, meaning it is unclear if they: measure what they are supposed to measure; are reliable; and are able to detect change over time.

This CASE studentship will uniquely bring academia and industry together to solve this problem. It aims to enhance our understanding of the measurement properties of innovative ePROM tools. For this, you will design and conduct a series of quantitative and qualitative research projects investigating the measurement properties of ePROM tools developed by the supervisory team and by uMotif. uMotif are a London-based digital health company that provides innovative user-centred data capture tools for health research. They are the studentship’s industry partner and see this as an opportunity to increase the robustness of their products. They will host you for a 3-6 month placement to conduct a research study around one of their ePROM tools.

The supervisory team and uMotif have developed several ePROM tools that are available for further investigations in this studentship. Examples include: a digital pain manikin3 (i.e. digital human-shaped drawings where people can shade areas to indicate the location and other aspects of their pain); the ‘motif’ (i.e. uMotif’s patented data capture tool); and a smartwatch version of the EQ-5D, which measures health-related quality of life. There will be room for you to select the tools you would like to focus on for your studies.

Through this studentship you will gain: knowledge on digital health and ePROMs; methodological skills to review, develop and validate ePROM tools; and insights into the digital health industry. You will deliver the evidence base for the measurement properties of ePROM tools, as well as how to further enhance them. Ultimately, the studentship will increase uptake of commercial and non-commercial ePROM tools in research and clinical settings, and contribute to harnessing the data collected through these tools.

Entry Requirements:
Applications are invited from UK/EU nationals only. Applicants must have obtained, or be about to obtain, at least an upper second class honours degree (or equivalent) in a relevant subject.

Funding Notes

This is a CASE studentship in partnership with uMotif Limited and will be funded under the MRC Doctoral Training Programme. If you are interested in this project, please make direct contact with the Supervisor to discuss the project further as soon as possible. You MUST also submit an online application form - full details on how to apply can be found here

As an equal opportunities institution we welcome applicants from all sections of the community regardless of gender, ethnicity, disability, sexual orientation and transgender status. All appointments are made on merit.


1. Rivera SC, Kyte DG, Aiyegbusi OL, Slade AL, McMullan C, Calvert MJ. The impact of patient-reported outcome (PRO) data from clinical trials: A systematic review and critical analysis. Health Qual Life Outcomes. 2019;17(1):1-19. doi:10.1186/s12955-019-1220-z
2. Basch E, Deal AM, Kris MG, et al. Symptom monitoring with patient-reported outcomes during routine cancer treatment: A randomized controlled trial. J Clin Oncol. 2016;34(6):557-565. doi:10.1200/JCO.2015.63.0830
3. Van der Veer SN, Beukenhorst AL, Ali SM, et al. Development of a mobile digital manikin to measure pain location and intensity. Stud Health Technol Inform. 2020;[in press].
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