Medically Reviewed by: Monica Rincon, MSc., NFP Health Professional
In these days on a smartphone, women of all reproductive ages track their period by a period tracker app, being the fourth most popular health app among women. In some of these apps, you can log as well your reproductive health and fertility signs (cervical mucus and/or temperature). In 2016, Researchers at Columbia University Medical Center concluded that about 95% of smartphone menstrual cycle tracking (n=108) are inaccurate.
Health care providers recommend women monitor their menstrual cycle to identify potential reproductive problems, but their concern is that accuracy is needed the most. Furthermore, a period tracking app alone is not enough to determine the fertile window of a woman, when the timing of conception should be accurately framing your day of ovulation.
An ovulation tracker app is just as important as a period tracker app. Tracking these two important signs of ovulation together will help you greatly improve both your accuracy and efficiency. Why? The key reason is because a normal woman’s luteal phase (the phase after ovulation day till the next period day) will naturally be the same number of days (between 11 to 16 days), not fluctuating even one day.
Here is how they are interrelated and can be used to predict the next ovulation day (X) and the next period day:
Next Ovulation Day (X) = Next Period Day(Y) - Luteal Phase Length (Z)
Next Period Day( Y) = Current Ovulation Day (X)+ Luteal Phase Length (Z)
So, with any of the two numbers confirmed, you or the Premom app will calculate the third number and predict the next ovulation day or next period day.
Accuracy helps the efficiency. How? Let’s give an ideal example. If you have seen 100% accuracy of both the period prediction day and the ovulation prediction day with Premom, you could just do an ovulation test before and on the predicted ovulation day to verify it - the number of ovulation testing days will be cut from 20 to 2.
Reality has never been this ideal. However, it is possible for you to get your highest accuracy.
A common root cause of inaccurate predictions is inaccurate data input. Some women will forget to log their period start day; more will forget to log their period end day. And some just forget to log their new period at all.
Keep in mind: accurate prediction is not possible if the app doesn't have an accurate and updated record unless the user has a very regular cycle that doesn’t change at all.
Premom will keep analyzing your pattern with all of the data input. Your new input will help the app adjust its previous analysis and optimize the calculation for you. The more Premom collects efficient data from your input, the higher the accuracy of your ovulation day prediction will be.
With the accuracy of prediction getting higher, Premom understands you better. For example, when you see the difference between the predicted period start day and the actual period start day dropping from 8 days to 1 day as you continue to use the app, it signals that the AI of Premom is working for you and is on the right track.
You are going to be ultimately empowered to take charge of your fertility cycle and health with the least data logging: just the ovulation day, period start day and period end day.
You’ll also have both accuracy and efficiency, and you know how important it is to have both.
1. Broad A, Biswakarma R, Harper JC. A survey of women's experiences of using period tracker applications: Attitudes, ovulation prediction and how the accuracy of the app in predicting period start dates affects their feelings and behaviours. Womens Health (Lond). 2022 Jan-Dec;18:17455057221095246. doi: 10.1177/17455057221095246. PMID: 35465788; PMCID: PMC9047811.
2. Berglund Scherwitzl E, Lundberg O, Kopp Kallner H, Gemzell Danielsson K, Trussell J, Scherwitzl R. Perfect-use and typical-use Pearl Index of a contraceptive mobile app. Contraception. 2017;96(6):420-5.
2. Moglia ML, Nguyen HV, Chyjek K, Chen KT, Castaño PM. Evaluation of smartphone menstrual cycle tracking applications using an adapted APPLICATIONS scoring system. Obstetrics & Gynecology. 2016;127(6):1153-60.
3. Frank-Herrmann P, Gnoth C, Baur S, Strowitzki T, Freundl G. Determination of the fertile window: Reproductive competence of women – European cycle databases. Gynecological Endocrinology. 2005;20(6):305-12.
4. Lewis TL. A systematic self-certification model for mobile medical apps. J Med Internet Res. 2013;15(4):e89.
Updated August 24, 2020