Dr. Liseth Tjin-Kam-Jet – Siemons is epidemiologist and post-doc researcher at the Persuasive Health Technology Lab; Center for eHealth & Wellbeing Research; department of Psychology, Health & Technology; University of Twente, Enschede, the Netherlands. She studied organizational as well as health psychology and graduated with honors from the research master “Social Systems Evaluation and Survey Research”, within the track “Evaluation and Assessment in Health and Safety Psychology’”. She obtained her PhD in the measurement, modelling and monitoring of disease activity in patients with rheumatoid arthritis.
During her PhD Liseth followed a 3-month internship at the group of Prof. Dr. E. Krishnan from the School of Medicine at Stanford University (CA, USA), with whom she published several articles. She has been and is involved in several research projects as well as the supervision of PhD, master, and bachelor students. Also, Liseth hosted and organized several international conferences.
Her overall research interests and expertise lay in epidemiology, methodology and statistics, behavioral science, Big Data, disease outcomes, health technology (eHealth), and public health.
Liseth her overall research interests and expertise lay in epidemiology, methodology and statistics, behavioral science, Big Data, disease outcomes, health technology (eHealth), and public health.
- Statistics and methodology
- Research assignment Bachelor 2
- Monitoring and Persuasive Coaching
- Supervisor of bachelor, master, and PhD students
Currently, research focuses on:
- The use of Big Data for Personalized, Persuasive, and Safe Healthcare
What factors that are crucial for using and managing big data to support the growing needs for personalized and cost-effective healthcare? We want to better understand how to use data from large and complex datasets in an effective, efficient, secure and safe way to design real-time, accurate, persuasive and personalized feedback systems.
- ePublic Health: Developing an interactive platform for tailored risk communication to prevent non-alimentary zoonotic diseases
Developing a web-based communication dashboard (i.e. the eZoon dashboard) to reduce uncertainties and to foster individual and collective protective actions against zoonotic hazards and disasters. An adaptive Question and Answer system and e-learning game for professionals and the general public will be part of the eZoon dashboard to increase awareness, self-management via self-learning, and user-adaptive communication.
- Predicting infection outbreaks: a data-driven approach
Drug-resistant infections are one of the most serious and growing treats to public health. Rather than merely monitoring infection spread, this project aims to predict upcoming infection outbreaks based on clinical data, mobility data, and geo-data, that would enable precautions to be taken in time.