Laura Symul, une chercheuse de l’Ecole Polytechnique de Lausanne, vient de publier un article qui comparait les données de sympto avec celles de kindara. Le but n’est pas encore de confirmer l’efficacité de sympto que nous connaissons depuis 2009, cela sera notre prochaine étape, mais d’analyser les données de ces deux applis en vue d’une meilleure connaissance scientifique:
Un résumé français se trouve sur le site de l’EPFL:
https://actu.epfl.ch/news/les-applications-de-fertilite-sont-elles-utiles/
Visualizing the data from the modelling part of the study. Each line is a
user, each dot is a day. The dot colors are inferred biological states; Red
dots are the menses; black dots are the most likely day of ovulation; blue dots
are the follicular phase days; yellow dots are the luteal phase days. Credit:
L. Symul (EPFL/Stanford)
For many women of reproductive age,
the most common way of assessing their menstrual health and fertility means
regular visits to a gynecologist or another clinician. When it comes to evaluating
changes in fertility, menstrual health, and quality of life, these visits
typically rely on remembering, which can lead to significant inaccuracies in
evaluation.
On the other hand, many women today
are turning to so-called “fertility awareness” (FAM) apps to support them in tracking
their menstrual cycles. There is a multitude of such apps available, which only
demonstrates how popular they’ve become in recent years.
But how accurate are FAM apps? What
do users track? Can they help them and their gynecologists? These are hard to
answer for a simple reason: Neither visits nor app use have been systematically
studied on a population level to determine and compare their accuracy in
evaluating menstrual health and fertility in a meaningful way.
This is what Laura Symul at EPFL’s Digital Epidemiology Lab has done. Working with Stanford University (which she has now joined), Symul led a large-scale study on 200,000 users of two FAM apps, Sympto
and Kindara. Both apps support the “Sympto-Thermal Method” and facilitate the identification
of the fertile and infertile times of a woman’s menstrual cycle by taking into
account recordings of cervical fluid, body temperature at wake-up, and other
biological signs.
The scientists tracked more than 30
million days of observations from over 2.7 million menstrual cycles. The
overall study had two aims: First, to see how and what users voluntarily
track on FAM apps. Second, to find out if these records allow an accurate detection
and estimation of ovulation timing.
In terms of user demographics and
behavior, the study found that the typical FAM app user is around 30 years old,
lives in a western country (in Europe or Northern America) and has a healthy
BMI. App users log their observations more frequently when they also log sexual
intercourse, and when you look at them on a population level, reported
fertility awareness body signs exhibit temporal patterns that follow very
closely those that have been found in small-scale clinical studies.
Analyzing the data, the scientists
found that women who were seeking pregnancy recorded Sympto-Thermal
measurements every single day for up to 40% of their menstrual cycles. Then, by
modeling the data, they found that the average duration and range of the
follicular phase, which begins the menstrual cycle and ends at ovulation, were
larger than previously reported. In fact, the modeling showed that only 24% of
ovulations occur at days 14 to 15 of the cycle. On the other hand, the data
showed that the duration and range of the luteal phase – the latter part of the
menstrual cycle – matched previous studies.
The findings offer an affordable
means for studying the interactions between the menstrual cycle and other
physiological systems on a large scale. “Our study provides a common ground for
users and their doctors to incorporate digital records in their visits,
evaluate their own menstrual patterns and compare them with the statistics we
report,” says Laura Symul.
She continues: “New technologies, and
in particular self-tracking, are changing the way we perceive our bodies and
health. Both users and doctors wonder about the opportunities and the
usefulness of digital self-tracking. Our study shows that users voluntarily
track their menstrual cycle and fertility-related body signs very frequently,
and what they track is aligned with what is expected in the vast majority of
cases. While these measurements and observations are noisy and not perfectly
regular, they provide valuable information for inferring the underlying
hormonal changes and timing of ovulation in a way that is scalable both in time
and in number of participants.”
Marcel Salathé, director of the
Digital Epidemiology Lab adds: “The digital epidemiology approach presented
here can help to lead to a better understanding of menstrual health and its connection
to women’s health overall, which has historically been severely under-studied.”
Other contributors
University of Geneva
Funding
Swiss National Science Foundation (Postdoc
Mobility grant)
Reference
Laura Symul, Katarzyna Wac, Paula
Hillard, Marcel Salathé. Assessment of Menstrual Health Status and Evolution
through Mobile Apps for Fertility Awareness. Nature Digital Medicine xx
xxxx 2019. DOI: xxxxxxxx
Contact
Professor Marcel
Salathé
+41 21 69 30991,
+41 21 69 55206
marcel.salathe@epfl.ch
Dr Laura
Symul
+1 650 313
8116
lsymul@stanford.edu
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