Hi everyone.
I am currently doing a doctorate research project which aims to show
how information graphics can be used to support health technology
assessment which is a key area of policy making in healthcare.
In health technology assessment (HTA), the scientific research
community provides evidence based syntheses to support high level
decisions about priorities in health spending. In the UK, for
instance, HTA is fundamental to the decision making processes at the
National Instititute of Health and Clinical Excellence and its
importance is growing both in the UK and internationally. In this
context, there is commonly a need to present complex multi-dimensional
data to decision makers of differing professional backgrounds. The
opportunities and role of the designer in producing information
graphics to support the presentation of such information in HTA is
only just beginning to be understood.
One challenge in my research is to show an empirical effect in terms
of understanding or information absorption between a purely numerical
(tabulated) and a graphical presentation of research data.
My first question is therefore:
Is anyone aware of a bibliography or reference source for empirical
studies that demonstrate/evaluate the benefits of information graphics
in decision support?
Some of the literature I’ve found so far suggests that the more
complex the information, the greater the advantage of using
information graphics (given the fact that there is a learning curve
for unfamiliar presentations of information). I can design an
experiment that gradually increases the complexity of a decision,
based on more and more information, but I need to know how to assess
how well people are absorbing information, so that I can compare
different presentation methods.
I’ve so far found three common ways of measuring effectiveness, used
in such comparative evaluative studies in management science:
1) Present some data in two or more forms, and ask a series of
questions which require the participant to obtain information from
the data, counting the number (and/or speed) of correct responses.
2) Ask participants to predict the next value in a (real) sequential
data set, and measure their responses against the actual values.
3) Ask participants which presentation method they preferred using a
qualitative technique, such as a questionnaire or interview delivered
after the event.
My second question is:
Does anyone know any other obvious (or even less than obvious...) ways
of measuring the effectiveness of information graphics that I may have
missed?
...............................................
Will Stahl-Timmins B.A., M.A.
PhD Researcher: Information Graphics in Health Technology Assessment.
T: +44 (0) 1392 406 967
M: +44 (0) 7941 865 196
E: [log in to unmask]
www.pms.ac.uk/infographics/
www.pms.ac.uk/pentag/
www.willstahl.com
|