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Digital manikins as a novel tool to measure self-reported pain in large-scale research studies

Project Description

Moderate to severe pain affects 1 in 5 adults. It is among the most prominent symptoms of musculoskeletal disease, and substantially affects the quality of life of people suffering from it. Accurately measuring pain over time is therefore central to understanding the natural history and mechanisms of musculoskeletal disease, as well as to evaluating treatment response in trials and clinical care.

Pain is commonly measured through patient-reported questionnaires, but language and literacy barriers hamper their use in certain patient groups and settings. Also, questionnaires may be suboptimal for engaging people in data collection over longer periods of time. Manikins are drawings that represent the human body. They provide an easy way for people to report the extent and location of their pain by shading areas on the manikin, and overcome the potential barriers associated with questionnaires. Traditional paper-based manikins require experts to manually score manikin reports in order to obtain quantitative data. Some available digital pain manikins have automated this manual scoring process, but can only be used on a dedicated device. Others are more widely accessible as a smartphone app, but have not been validated.

This project aims to expedite the use of digital manikins as the new standard for pain assessment in large scale research studies. It will provide insight in the current state of affairs, validate existing tools, and provide recommendations to guide future work by researchers and app developers. You will have a multidisciplinary supervisory team with expertise in health informatics, digital epidemiology, clinical medicine and statistics. They will support you with obtaining knowledge and skills to validate novel digital health measurement tools through prospectively collecting and analysing quantitative and qualitative data in people with chronic pain. There will be ample opportunity to engage with industry partners through the supervisors’ network.

Training/ techniques to be provided:
This PhD aims to support the student with developing quantitative skills through analysing novel longitudinal data, as well as qualitative research skills through interviewing patients.
The supervisors have experience of: systematic reviewing, measurement properties, qualitative research, health informatics (Van der Veer); and digital epidemiology, musculoskeletal disease, pain (Dixon). The student will be based within the Centre for Health Informatics with strong links with the Centre for Epidemiology, that together are leading in the development and application of novel tools for collection of patient-generated health data. The student will complete in-house courses in health informatics methodology (led by the Centre for Health Informatics) and digital and clinical epidemiology (led by the Centre for Epidemiology) as required. They will attend and contribute to seminars and journal clubs in both centres. They will also have access to additional training in musculoskeletal epidemiology through the UK Research Musculoskeletal Epidemiology partnership.

Entry Requirements:
This project would suit a student with a strong health informatics or epidemiology background who has a particular interest in health measurement and digital technology. Candidates are expected to hold (or be due to obtain) a minimum upper-second (or equivalent) class undergraduate degree in health informatics, psychology, a clinical discipline, or other relevant subject. A Masters degree in a relevant subject and/or relevant research experience is desirable.

For international students we also offer a unique 4 year PhD programme that gives you the opportunity to undertake an accredited Teaching Certificate whilst carrying out an independent research project across a range of biological, medical and health sciences. For more information please visit

Funding Notes

Applications are invited from self-funded students. This project has a Band 1 fee. Details of our different fee bands can be found on our website (View Website). For information on how to apply for this project, please visit the Faculty of Biology, Medicine and Health Doctoral Academy website (View Website).

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.


Aresi G, Hassan L, Rayner H, Mitra S, Burton JO, Sanders C, Van der Veer SN. Reasons for underreporting of uremic pruritus in people with chronic kidney disease: a qualitative study. Journal of Pain and Symptom Management 2019; Epub ahead of print

Austin L, Sharp CA, Van der Veer SN, Machin M, Humphreys J, Mellor P, McCarthy J, Ainsworth J, Sanders C, Dixon WG. Providing ‘the bigger picture’: benefits and feasibility of integrating remote monitoring from smartphones into the electronic health record. Rheumatology 2019; Epub ahead of print

Consumer Smartwatches for Collecting Self-Report and Sensor Data: App Design and Engagement.
Beukenhorst AL, Sergeant JC, Little MA, McBeth J, Dixon WG. Stud Health Technol Inform. 2018;247:291-295

Fraccaro P, Vigo M, Balatsoukas P, Buchan IE, Peek N, Van der Veer SN. The influence of patient portals on users’ decision making is under-investigated: a systematic methodological review. International Journal of Medical Informatics 2018; 111:100-111

Druce KL, McBeth J, van der Veer SN, Selby DA, Vidgen B, Georgatzis K, Hellman B, Lakshminarayana R, Chowdhury A, Schultz DM, Sanders C, Sergeant JC, Dixon WG. Recruitment and Ongoing Engagement in a UK Smartphone Study Examining the Association between Weather and Pain: Cohort Study. JMIR Mhealth Uhealth. 2017 Nov 1;5(11):e168.

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