Don’t Rely on Fertility Apps

Don’t Rely on Fertility Apps

Millions of women use fertility apps to predict timing of ovulation, but unfortunately, most apps do not reliably predict the fertile window.

A review of 73 fertility apps, published in Current Medical Research and Opinion, in May 2018 found that even the best app only had 21 percent accuracy in predicting a woman’s day of ovulation.  Another study presented at the 2016 annual meeting of the American College of Obstetricians and Gynecologists found that of the 53 fertility apps tested, only 4 accurately predicted the best days for conception.

There are only a few apps that have published research validating their products.  “The lack of published evidence is really quite striking in this area,” said Victoria Jennings, the director of Georgetown’s Institute for Reproductive Health”

In addition, fertility apps are not regulated by the U.S. Food and Drug Administration (FDA).  According to the FDA, apps that are used for conception and contraception are considered medical devices, but since fertility apps are considered low-risk devices, they do not require FDA approval.  On the other hand, if an app is marketed for contraception purposes, it would require FDA approval.

For women who are trying to conceive, a better predictor of ovulation than fertility apps would be using a home urine ovulation prediction kit.  The best thing to use these apps for is tracking the menstrual cycle.  The apps provide an easy tool for tracking the length and duration of the cycles.  For women who are having difficulty conceiving, this is important data for them to have to discuss with their physicians.

To sum it up, if you are trying to conceive, I would recommend using a fertility app to track your cycles and a urine ovulation prediction kit to monitor for ovulation.  If you are 35 years old or older, you should speak with your physician if you haven’t conceived within 6 months of trying or earlier if you have specific medical issues that would necessitate a sooner fertility evaluation.

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