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RareWorld:
DesigningforDispersedPopulationswithRareDiseases
HaleyMacLeod
hemacleo@indiana.edu
KayConnelly
connelly@indiana.edu
KatieSiek
ksiek@indiana.edu
Co-authors:Kim Oakes, Ben Jelen, Annu Prabhakar,
Shuo Yang, Dr. Lora Oehlberg, Dr. Sriraam Natarajan
Study1:Exploratoryinterviewswithpeoplewithrarediseases
We conducted interviews with 19 people about their experiences living with their condition, relationships and support, use
of technology and information management, and sense making practices. We discuss how having a disease that is
invisible or unfamiliar influences many roles.
MacLeod,H.,Oakes,K.,Geisler,D.,Connelly,K.,andSiek,K.(2015).RareWorld:TowardsTechnologyforPeoplewithRareDiseases.
InCHI2015.-HonourableMentionAward
Study2:Surveywithpeoplewithcommonchronicillnesses
andrarediseases
We distributed a survey with questions about demographics, use of technology for health
information and support, and perception of healthcare providers to people with common chronic
illnesses and people with rare diseases. We adapt and apply a machine learning algorithm to
distinguish between these two groups.
MacLeod, H., Yang, S., Oakes, K. Connelly, K. and Natarajan, S.(2016). Identifying Rare Diseases from Behavioural Data: A
MachineLearningApproach.InCHASE2016.
Study3:Asynchronous,Remote,CommunityResearch
withpeoplewithrarediseases
We conducted a study in a private Facebook group over several months where
participants responded to discussion prompts and completed a variety of
research activities. We analyzed this data to better understand the role of the
disease in their relationships with friends and family.
MacLeod,H.,Jelen,B.,Prabhakar,A.,Oehlberg,L.,Siek,K.andConnelly,K.(2016).Asynchronous
RemoteCommunities(ARC)forResearchingDistributedPopulations.InPervasiveHealth2016.
10% of People have
a Rare Disease
7,000
There are more than
different rare diseases.
Approach: KeyFindings:
People with rare diseases face a unique set of challenges, different from what
we know about people with common chronic illnesses:
•  They have a hard time expressing what they are going through to friends,
who haven't heard of the disease or don't see visible symptoms.
Common chronic illnesses tend to be more recognizable or familiar to
these friends.
•  They tend to strongly identify with their disease, and it moderates most
other aspects of their life. In common chronic illnesses, there is an
emphasis on “the whole person” outside of just the diease that is not the
same in the case of rare diseases.
•  They often lie about how they're feeling, downplay their symptoms, or
even tell people they have a different disease than they actually do
(typically a common disease the friend would have heard of).
•  Friends & family often don't believe that they are actually sick or think
they are exaggerating their symptoms.
NextSteps:
•  Speculative design, design futuring: how might digital technologies
address these needs now and in the future?
•  Deploying & evaluating: how can we evaluate technologies when
populations are geographically distributed?
If everyone with a rare disease
lived in the same country, it would
be the world's 3rd most populous nation.

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Rare World: Designing for Dispersed Populations with Rare Diseases

  • 1. RareWorld: DesigningforDispersedPopulationswithRareDiseases HaleyMacLeod hemacleo@indiana.edu KayConnelly connelly@indiana.edu KatieSiek ksiek@indiana.edu Co-authors:Kim Oakes, Ben Jelen, Annu Prabhakar, Shuo Yang, Dr. Lora Oehlberg, Dr. Sriraam Natarajan Study1:Exploratoryinterviewswithpeoplewithrarediseases We conducted interviews with 19 people about their experiences living with their condition, relationships and support, use of technology and information management, and sense making practices. We discuss how having a disease that is invisible or unfamiliar influences many roles. MacLeod,H.,Oakes,K.,Geisler,D.,Connelly,K.,andSiek,K.(2015).RareWorld:TowardsTechnologyforPeoplewithRareDiseases. InCHI2015.-HonourableMentionAward Study2:Surveywithpeoplewithcommonchronicillnesses andrarediseases We distributed a survey with questions about demographics, use of technology for health information and support, and perception of healthcare providers to people with common chronic illnesses and people with rare diseases. We adapt and apply a machine learning algorithm to distinguish between these two groups. MacLeod, H., Yang, S., Oakes, K. Connelly, K. and Natarajan, S.(2016). Identifying Rare Diseases from Behavioural Data: A MachineLearningApproach.InCHASE2016. Study3:Asynchronous,Remote,CommunityResearch withpeoplewithrarediseases We conducted a study in a private Facebook group over several months where participants responded to discussion prompts and completed a variety of research activities. We analyzed this data to better understand the role of the disease in their relationships with friends and family. MacLeod,H.,Jelen,B.,Prabhakar,A.,Oehlberg,L.,Siek,K.andConnelly,K.(2016).Asynchronous RemoteCommunities(ARC)forResearchingDistributedPopulations.InPervasiveHealth2016. 10% of People have a Rare Disease 7,000 There are more than different rare diseases. Approach: KeyFindings: People with rare diseases face a unique set of challenges, different from what we know about people with common chronic illnesses: •  They have a hard time expressing what they are going through to friends, who haven't heard of the disease or don't see visible symptoms. Common chronic illnesses tend to be more recognizable or familiar to these friends. •  They tend to strongly identify with their disease, and it moderates most other aspects of their life. In common chronic illnesses, there is an emphasis on “the whole person” outside of just the diease that is not the same in the case of rare diseases. •  They often lie about how they're feeling, downplay their symptoms, or even tell people they have a different disease than they actually do (typically a common disease the friend would have heard of). •  Friends & family often don't believe that they are actually sick or think they are exaggerating their symptoms. NextSteps: •  Speculative design, design futuring: how might digital technologies address these needs now and in the future? •  Deploying & evaluating: how can we evaluate technologies when populations are geographically distributed? If everyone with a rare disease lived in the same country, it would be the world's 3rd most populous nation.