Michelle (Helena) is a honorary research fellow in the Global eHealth Unit.
Michelle has an undergraduate degree in Biomedical Sciences and MSc in Health Technology Assessment, both from Radboud University Nijmegen in the Netherlands. She was awarded her PhD from Imperial College London in 2014. Her doctoral thesis explored the application of mHealth-based collection of information relevant to childhood diarrhoea and pneumonia in rural China. This work made a significant contribution to the evaluation methodology and scarce evidence-base of mHealth-based interventions, which was demonstrated by 20 publications in peer-reviewed journals. Her supervisors were Dr Josip Car, director of the Global eHealth Unit and Prof Igor Rudan, chair in International Health at the University of Edinburgh. During her PhD she collaborated extensively with researchers at the Capital Institute of Pediatrics in Beijing.
Michelle is involved in research projects that make use of mHealth-based tools to improve nutrition and vaccination coverage of young children in rural China. Furthermore, she completed Cochrane Collaboration systematic reviews on telephone consultation for HIV, integrating prevention of mother-to-child transmission of HIV with other health services, and male involvement in prevention of mother-to-child transmission of HIV programmes. In addition, she worked on reviews of the use of mobile phones for improving healthcare in developing countries, the use of apps for diabetes self-care and mobile phone messaging for HIV services.
Michelle teaches in modules on evidence synthesis, eHealth and mHealth and writing scientific research papers, at Imperial College London and at other universities including Kilimanjaro Christian Medical University College in Moshi, Tanzania, and the Karolinska Institutet in Stockholm, Sweden.
et al., 2021, Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study, Jmirx Med, Vol:2, Pages:e25560-e25560
et al., 2021, Authors’ Response to Peer Reviews of “Machine Learning for Risk Group Identification and User Data Collection in a Herpes Simplex Virus Patient Registry: Algorithm Development and Validation Study”, Jmirx Med, Vol:2, Pages:e28917-e28917
Lam C, van Velthoven M, Meinert E, 2020, Developing a blockchain-based supply chain system for advanced therapies: study protocol, Jmir Research Protocols, Vol:9, ISSN:1929-0748, Pages:1-6
et al., 2020, Effectiveness of WeChat for Improving Exclusive Breastfeeding in Huzhu County China: Randomized Controlled Trial, Journal of Medical Internet Research, Vol:22, ISSN:1438-8871
et al., 2020, Mobile fitness and weight management apps: an evaluation protocol, Jmir Research Protocols, Vol:9, ISSN:1929-0748, Pages:1-5