Hello.
My name is Mayara Figueredo.
And I will present a short summary of our paper,
"Using Data to Approach the Unknown:
Patients' and Healthcare Providers' Data Practices
in Fertility Challenges."
Our study investigates how patients and providers
engage with self-tracked data in fertility challenges.
To explore this question, we conducted interviews
with 14 patients and five infertility specialists.
In this talk, I illustrate patients' and providers'
different data practices for a scenario based in different
participant's data.
You can refer to the paper from [INAUDIBLE]..
But here, we will talk about Lucia.
Lucia was 24 when she started trying to conceive.
But she did not get pregnant for many months.
She decided to start tracking her period dates
and temperature using Excel.
Just lightly tracking stuff, not super committed to it.
She conceived but lost her pregnancy,
which was a very difficult experience.
This experience led her to track more
to try to understand why the miscarriage happened
and to avoid it to happen again.
She started using Excel and a fertility software
to track period dates, temperatures, cervical mucous,
intercourse, symptoms, ovulation test, and cervical position.
And as she says in this quote, she had months of data.
And she got really obsessed about it.
After more than a year trying by herself,
she consulted with an infertility specialist,
Dr. Jones.
Dr. Jones asked questions about her periods
but did not analyze her spreadsheets.
She did her own tests then suggested a treatment
with medication to stimulate ovulation.
Lucia did not really understand her reasoning,
but she did the treatment.
She also kept tracking some indicators just in case.
After four unsuccessful cycles, she was very frustrated
with her doctor.
Because she could not even find a cause for her challenges.
But for her surprise, Lucia finally
conceived in the fifth cycle of treatment.
This scenario illustrates how patients' data practices are
entangled with their emotions and how their trajectories
often involve different data, different types of data,
different treatments, healthcare providers, and often difficult
fertility-related events.
It also illustrates how fertility is uncertain.
Or in the words of one of our participants,
how it is unknown.
Fertility is extremely complex and poses a lot of uncertainty
for both healthcare providers and patients.
As shown in the image, there are many factors contributing
to the unknown infertility.
[INAUDIBLE] both patients and providers
use data to approach this unknown.
But they do it in different ways.
Patients use data in an exploratory way.
They see data as a means to learn about their bodies,
to understand why they are not conceiving,
and to increase their chances.
They often track a combination of multiple types of data,
including period dates, ovulation tests,
and lifestyle measures.
Finally, patients' data practices
are often not only involved but driven
by their emotional experiences.
Providers on the other hand, use patients' personal data
in a much more structured way.
They use data to follow a protocol guided
by scientific knowledge and probabilities
to define the best treatment.
They use very specific types of data.
Basically, period dates and the results
of ovulation tests, which they align
with laboratory and radiology tests they conduct.
And their practices are largely driven by medical rationality.
It is easy to see how these different practices can clash.
Like Lucia, patients may feel confused and disappointed
when providers do not explain how they make their decisions
or what data they use to make them.
While providers like Dr. Jones often
have to deal with extensive data that they do not directly
use or need, but despite these conflicts,
all participants also provided information
on how these practices can work well together.
Based on these descriptions, we argued that these practices
are different.
But they also serve different purposes
and have unique benefits.
On one hand, provider's data practices
are useful to divine the best treatment course.
It is not feasible to expect providers
to analyze months of data and impose
such high levels of personalization
may impact or delay cases that would be easily supported
by the current protocol.
On the other hand, patients' data practices
help them to learn about their bodies, which is also
good for providers and also provide them
a sense of control that is important to cope
with the disruptive experience of infertility.
Completely changing patient's practices to mimic providers
could then hinder these benefits and hide the personalized
aspects of their trajectories that
can point to exceptions to the protocol which do happen.
So in the paper, we suggest that in this case,
it may be more indicated to connect these different data
practices without merging them.
And we provide some open suggestions
on how technology can support this bridge by,
for example, making providers' data
practices transparent and visible to patients
as early as possible so they can get used to them,
helping providers consider different types,
different trajectories and help patients
to showcase information that can support that,
supporting providers in addressing
patient's emotional involvement with data,
and finally, exposing how much is known
so patients can have the clearer information
to balance their expectations.
And that's it.
For more information, please refer to our paper.
And you're free to contact me.
Thank you so much for your. attention.