Estimating Cognitive Overload in Mobile Applications for Decision Support within the Medical Domain

Derek Flood, Panagiotis Germanakos, Rachel Harrison, Fergal Mc Caffery, George Samaras

2012

Abstract

Mobile applications have the potential to improve the quality of care received by patients from their primary care physicians (PCP). They can allow doctors to access the information they need when and where they need it in order to make informed decisions regarding patients’ health. They can also allow patients to better control conditions such as Diabetes and Gaucher’s disease. However, there are a number of limitations to these devices, such as small screen sizes and limited processing power, which can produce cognitive overload which in turn can negatively impact upon the decision making processes. This paper introduces a new research direction which aims to predict, during the development of mobile health care applications, when cognitive overload is likely to occur. By identifying the user’s previous level of experience, their working memory, the complexity of the interface and the level of distraction imposed by the user’s context, a prediction can be made as to when cognitive overload is likely to occur.

References

  1. Baddeley, A. 1992. Working Memory, Science, Vol. 255, pp. 556-559.
  2. Bekker, H, Thornton, J G., Airey, C M., Connelly, J B., Hewison, J., Robinson M B., Lilleyman, J., MacIntosh, M., Maule, A J., Michie, S., Pearman, A D. 1999. Informed Decision Making: An Annotated Bibliography and Systematic Review, Health Technology Assessment, Vol. 3: No. 1.
  3. García, E., Martin, C., García-Cabot, A., Harrison, R., Flood, D. 2011. Systematic Analysis of Mobile Diabetes Management Applications on Different Platforms. USAB 2011: 379-396.
  4. IEC. 2007. IEC 62366 - Medical devices -- Application of usability engineering to medical devices.
  5. Oviatt, S. 2006. Human-centered Design meets Cognitive Load Theory: Designing Interfaces that help People Think, Proceedings of the 14th annual ACM international conference on Multimedia, October 23- 27, Santa Barbara, CA, USA
  6. Pickering, S., Gathercole, S. 2001. The Working Memory Test Battery for Children, The Psychological Corporation.
  7. PriceWaterhouseCooper Health Research Institute. 2010. Healthcare unwired: new business models delivering care anywhere. Available from: http://www.pwc.com/ us/en/health-industries/publications/healthcare-unwire d.jhtml
  8. Zhang, D., Adipat, B. 2005. Challenges, Methodologies, and Issues in the Usability Testing of Mobile Applications, International Journal of HumanComputer Interaction 18(3): 293 - 308.
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Paper Citation


in Harvard Style

Flood D., Germanakos P., Harrison R., Mc Caffery F. and Samaras G. (2012). Estimating Cognitive Overload in Mobile Applications for Decision Support within the Medical Domain . In Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 3: ICEIS, ISBN 978-989-8565-12-9, pages 103-107. DOI: 10.5220/0003971501030107


in Bibtex Style

@conference{iceis12,
author={Derek Flood and Panagiotis Germanakos and Rachel Harrison and Fergal Mc Caffery and George Samaras},
title={Estimating Cognitive Overload in Mobile Applications for Decision Support within the Medical Domain},
booktitle={Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 3: ICEIS,},
year={2012},
pages={103-107},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0003971501030107},
isbn={978-989-8565-12-9},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 14th International Conference on Enterprise Information Systems - Volume 3: ICEIS,
TI - Estimating Cognitive Overload in Mobile Applications for Decision Support within the Medical Domain
SN - 978-989-8565-12-9
AU - Flood D.
AU - Germanakos P.
AU - Harrison R.
AU - Mc Caffery F.
AU - Samaras G.
PY - 2012
SP - 103
EP - 107
DO - 10.5220/0003971501030107