Doctor-patient interaction (natural dialogue) study
differs significantly from the wizard-of-oz studies,
that have been used extensively by others in the design
of spoken dialogue systems. Researchers who use the
wizard-of-oz techniques begin the process with a pre-
experimental phase that involves studying natural hu-
man dialogues. Whereas the natural dialogue takes
place prior to any system design or functional specifi-
cations (Yankelovich, 2008). The main purpose is to
launch the design process.
Before designing the medical dialogue system, we
wanted to discover how doctors and patients inter-
act in the diagnosis process. From the analysis of
the doctor-patient interaction, we found that the in-
teraction is doctor-centered as well as we found that
patients question asking behavior is hampered by the
cultural influences such as: distance power, high un-
certainty avoidance and the like (see section 3.5).
It is impossible to produce a medical dialogue sys-
tem design based entirely on doctor-patient face-to-
face interaction. Rather it can play an important role
in the early stages of the development life cycle, and
serve as an effective starting point for spoken medical
dialogue system design.
5 CONCLUSIONS
We have analyzed the interaction in 29 audio-taped
doctor-patient diagnosis dialogues in the Gamby
Teaching hospital. The study is mainly conducted
to investigate the information seeking and informa-
tion provisioning behavior of doctors and patients.
The finding shows that there is no statistical signif-
icant difference between doctor information seeking
and patient information seeking behavior. Similarly,
we didn’t find any significant difference between pa-
tients information provisioning and doctors informa-
tion provisioning behavior. From this analysis we
conclude that studying face-to-face interaction be-
tween doctor and patients is an effective starting point
for spoken medical dialogue system design. We also
found an influence of culture on doctor-patient in-
teraction; so cultural values should be incorporated
while designing and developing a medical dialogue
system. Finally, based on our results, we propose a
model to assist user requirements elicitation in order
to develop a medical spoken dialogue system. In the
future we will implement our model to develop a med-
ical dialogue system.
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