This interdisciplinary project highlighted several
themes which we expect to be recurring when design-
ing social machines for health professionals, given the
general characteristics of the domain. Firstly, design-
ing for time constraints is crucial, given that clini-
cians are very busy. Hence, an easily learnable inter-
face is recommended, where all features are directly
accessible on display. Security is another important
theme, and access control aspects should be carefully
thought out. Furthermore, social machines that sup-
port knowledge sharing should allow users to identify
misinformation, which is critical in healthcare.
The choice of participatory design allowed us to
identify these themes and concerns, which might not
have been addressed without input from the users.
Our overall experience of using participatory design
in healthcare was greatly positive. Participants were
very motivated and gave thorough and careful feed-
back. On the other hand, recruiting participants was
the biggest issue, as healthcare professionals are gen-
erally very busy and communication channels tend to
be controlled. We worked around this issue by ensur-
ing that different types of stakeholders were involved
in the study, from experienced to new facilitators and
from isolated workplaces to busy hospitals.
The range of participatory design methods used
provided us with a wealth of both quantitative and
qualitative data and allowed for a good level of user
engagement and interaction. The two-hour brain-
storming session, which resulted in 26 pages of tran-
script, allowed participants to exchange and visualise
ideas, and thus served as a good basis for establish-
ing requirements. The phone interviews did not pro-
vide the same level of idea generation, but carrying
them out separately with each facilitator provided a
safe space for them to express their personal views on
a HM machine. Furthermore, the paper-based proto-
typing session was found to be very useful, as it al-
lowed us to concretise ideas at an early stage.
The questions presented in Figure 1 were partic-
ularly useful for designing the HM social machine.
They guided the requirement elicitation process, from
structuring the brainstorming session to analysing the
qualitative data obtained. We would, hence, recom-
mend their use to other social machine designers.
In the future, we wish to continue using the partic-
ipatory design methodology and implement the feed-
back received as part of the current study. In order
to create a truly usable social machine for the Heart
Manual service, we plan to include more participants
and to investigate new topics, such as the moderat-
ing role of the HM team. Applying the methodology
presented in this paper to the design of other social
machines is another exciting avenue for future work.
ACKNOWLEDGEMENTS
This research was supported by the EPSRC SociaM
project under grant EP/J017728/1.
REFERENCES
Bangor, A., Kortum, P., and Miller, J. (2009). Determining
what individual SUS scores mean: Adding an adjec-
tive rating scale. J. Usability Studies, 4(3):114–123.
Brooke, J. (2013). SUS: a retrospective. Journal of usability
studies, 8(2):29–40.
Brooks, F., Pospopa, C., and Schott, P. (2004). Midwifery
on the net: new communication technology. British
Journal of Midwifery, 12(2):107–110.
Clark, M., Kelly, T., and Deighan, C. (2011). A system-
atic review of the heart manual literature. European
Journal of Cardiovascular Nursing, 10(1):3–13.
Deighan, C., Pagliari, C., Michalova, L., Elliott, J., Brook-
mann, F., and Taylor, L. (2015). Digital heart manual:
making technology accessible with a user-friendly re-
source. In Health Informatics Scotland Conference.
British Computer Society.
Donath, J. (2014). The social machine: designs for living
online. MIT Press.
Hendler, J. and Berners-Lee, T. (2010). From the seman-
tic web to social machines: A research challenge for
AI on the world wide web. Artificial Intelligence,
174(2):156–161.
Murray-Rust, D. and Robertson, D. (2015). Bootstrapping
the next generation of social machines. In Crowd-
sourcing, pages 53–71. Springer.
Rolls, K., Hansen, M., Jackson, D., and Elliott, D. (2016).
How health care professionals use social media to cre-
ate virtual communities: An integrative review. Jour-
nal of Medical Internet Research, 18(6):e166.
Schuler, D. and Namioka, A., editors (1993). Participatory
Design: Principles and Practices. L. Erlbaum Asso-
ciates Inc., Hillsdale, NJ, USA.
Shadbolt, N. R., Smith, D. A., Simperl, E., Van Kleek, M.,
Yang, Y., and Hall, W. (2013). Towards a classification
framework for social machines. In Proceedings of the
22nd International Conference on World Wide Web,
pages 905–912. ACM.
Simonsen, J. and Robertson, T. (2012). Routledge Interna-
tional Handbook of Participatory Design. Routledge.
Smart, P., Simperl, E., and Shadbolt, N. (2014). A taxo-
nomic framework for social machines. In Social Col-
lective Intelligence, pages 51–85. Springer.
The Heart Manual Department (2016). The Heart Manual.
http://www.theheartmanual.com.
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