Lecturer in Experience Design
Investigating and designing user experiences and interactions with data-driven technologies in the context of health and everyday living.
Postdoc research career (Strathclyde, Manchester, King’s College London)
Visiting Lecturer, King’s College London (2019 - )
19DSB101 Design Research in Practice
19DSP802 Design for Behaviour Change
19DSP851 Design Research Methods
Balatsoukas, P., Porat, T., Sassoon, I., Essers, K., Kokciyan, N., Ashworth, M., Chapman, M., Sklar, E., Drake, A., Parsons, S. and Modgil, S., 2019 (In press). User involvement in the design of a data-driven self-management decision support tool for stroke survivors. In 18th IEEE International Conference on Smart Technologies: EUROCON.
Kökciyan, N., Chapman, M., Balatsoukas, P., Sassoon, I., Essers, K., Ashworth, M., Curcin, V., Modgil, S., Parsons, S. and Sklar, E.I., 2019. A Collaborative Decision Support Tool for Managing Chronic Conditions. Studies in health technology and informatics, 264, pp.644-648.
Chapman, M., Balatsoukas, P., Ashworth, M., Curcin, V., Kökciyan, N., Essers, K., Sassoon, I., Modgil, S., Parsons, S. and Sklar, E.I., 2019, May. Computational Argumentation-based Clinical Decision Support. In Proceedings of the 18th International Conference on Autonomous Agents and MultiAgent Systems (pp. 2345-2347). International Foundation for Autonomous Agents and Multiagent Systems.
Essers, K., Chapman, M., Kokciyan, N., Sassoon, I., Porat, T., Balatsoukas, P., Young, P., Ashworth, M., Curcin, V., Modgil, S. and Parsons, S., 2018, December. The CONSULT System. In Proceedings of the 6th International Conference on Human-Agent Interaction (pp. 385-386). ACM.
Brown, B., Balatsoukas, P., Williams, R., Sperrin, M. and Buchan, I., 2018. Multi-method laboratory user evaluation of an actionable clinical performance information system: Implications for usability and patient safety. Journal of biomedical informatics, 77, pp.62-80.
Fraccaro, P., Vigo, M., Balatsoukas, P., van der Veer, S.N., Hassan, L., Williams, R., Wood, G., Sinha, S., Buchan, I. and Peek, N., 2018. Presentation of laboratory test results in patient portals: influence of interface design on risk interpretation and visual search behaviour. BMC medical informatics and decision making, 18(1), p.11.
Fraccaro, P., Vigo, M., Balatsoukas, P., Buchan, I.E., Peek, N. and van der Veer, S.N., 2018. The influence of patient portals on users’ decision making is insufficiently investigated: a systematic methodological review. International journal of medical informatics, 111, pp.100-111.
Fraccaro, P., Vigo, M., Balatsoukas, P., Buchan, I.E., Peek, N. and van der Veer, S.N., 2018, January. Patient portal adoption rates: A systematic literature review and meta-analysis. Studies in health technology and informatics, 245, p. 79. IOS Press.
Brown, B., Balatsoukas, P., Williams, R., Sperrin, M. and Buchan, I., 2016. Interface design recommendations for computerised clinical audit and feedback: hybrid usability evidence from a research-led system. International journal of medical informatics, 94, pp.191-206.
Balatsoukas, P., Kennedy, C.M., Buchan, I., Powell, J. and Ainsworth, J., 2015. The role of social network technologies in online health promotion: a narrative review of theoretical and empirical factors influencing intervention effectiveness. Journal of medical Internet research, 17(6), p.e141.
Balatsoukas, P., Williams, R., Davies, C., Ainsworth, J. and Buchan, I., 2015. User interface requirements for web-based integrated care pathways: evidence from the evaluation of an online care pathway investigation tool. Journal of medical systems, 39(11), p.183.
For a full list of publication, please check my Google Scholar profile:
Human Computer Interaction, Experience design, Usability engineering, Data & Information Interaction, User-centred design, Digital Health, Connected health.
2021 - UKRI / Arts and Humanities Research Council. Immunity passport service design: informing the UK’s national exit strategy from the lockdown (COVID-19). FEC = £170,361. Principal Investigator.
2020 – National Institute for Health Research (NIHR). Mapping the challenges and requirements for data-driven machine learning-aided stratification and management of long-term conditions in adults with intellectual disabilities. FEC = £120,000. Co-Investigator.