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Can apps and calendar methods predict ovulation with accuracy?

Sarah Johnson1, Lorrae Marriott2, Michael Zinaman3

  • 1a SPD Development Company Ltd , Clinical and Regulatory Affairs , Bedford , UK.

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|May 12, 2018
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Summary
This summary is machine-generated.

Cycle tracking apps and calendar methods show low accuracy in predicting ovulation. Ovulation day varies significantly, making length-based predictions unreliable for fertility awareness.

Keywords:
Ovulation predictionappsfertilitymenstrual cycle

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Area of Science:

  • Reproductive endocrinology
  • Gynecology
  • Biostatistics

Background:

  • Fertility awareness-based methods (FABMs) are used for family planning and conception.
  • Cycle tracking apps and calendar methods are popular tools for predicting ovulation.
  • The accuracy of these methods relies on consistent menstrual cycle lengths, which is often not the case.

Purpose of the Study:

  • To determine the accuracy of ovulation prediction by cycle tracking apps and published calendar methods.
  • To compare the predictions of these methods against the true probability of ovulation based on luteinizing hormone (LH) surges.

Main Methods:

  • 949 volunteers collected urine samples throughout one menstrual cycle.
  • Luteinizing hormone (LH) surges were measured to determine the actual ovulation day.
  • Data from volunteers was used to assess the accuracy of four published calendar methods and various cycle-tracking apps.

Main Results:

  • Mean cycle length was 28 days, but only 15% of women had a consistent 28-day cycle.
  • Ovulation prediction accuracy for apps was no better than 21%.
  • Calendar methods like 'standard days' and 'rhythm' had high prediction rates (70-89%) but low accuracy.

Conclusions:

  • Ovulation timing varies significantly even within the same cycle length.
  • Calendar and app-based ovulation prediction methods relying solely on cycle length are inaccurate.
  • Accurate ovulation prediction requires methods beyond simple cycle length calculations.