Period tracker apps that ‘help avoid pregnancy are NOT accurate’
The apps do not accurately track irregular periods and many do not allow the user to change predictions that are incorrect
THOUGHT your period tracker app was a safe way to keep an eye on your cycle and prevent unwanted pregnancies? Think again.
Period tracking apps are inaccurate and do not provide enough support for the user, a new study has found.
More than 680 women were asked about how they tracked their period.
Nearly half said they used a period tracking app to track their period, better understand their body and reactions to different phases of their cycle and to achieve or avoid becoming pregnant.
Researchers from the University of Washington also looked at 2,000 reviews of period tracking apps.
They focused on the nine apps currently available on the Android and Apple market and what the users liked or disliked about them.
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Daniel Epstein, lead author of the study, said: "People didn't feel like the apps were very good at supporting their particular needs or preferences.
"People felt they were better than tracking their periods on paper, but still weren't great in a lot of basic ways."
Many women found the assumptions made by the apps were not accurate or flexible enough to consistently predict their period, especially if they did not have regular periods.
They also found that many apps do not allow users to correct them if the predictions about their cycle are wrong.
This means that the apps are inaccurate for anyone using them to avoid getting pregnant and women using them to track their ovulation ready for a baby.
Co-author Julie Kientz said many teenage girls were relying on the apps as a form of birth control to know when they should avoid having sex.
She said: "That's pretty disconcerting because accuracy can be a problem with these apps."
Nikki Lee, third co-author of the study, said: "In some cases, you don't have a way to go in and say I missed my period because of x reason or because I was in the hospital - both ordinary and exceptional circumstances can screw up the algorithms because they're not really robust.
"The apps are most accurate if your cycles are really, really regular, but the people who most need an app are the people whose cycles aren't regular."
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