@article{Enenbach_Haworth_Hawkins_Kochmann_2021, place={Houston, U.S.}, title={“When Am I Fertile?”: A Pilot Study Comparing Ovulation Prediction Accuracy of Apps and LH Kits}, volume={10}, url={https://www.jsr.org/index.php/path/article/view/1216}, DOI={10.47611/jsr.v10i1.1216}, abstractNote={<p>Prediction of peak fertility is critical yet challenging in both planning and preventing pregnancy. Period tracking applications for the smartphone are ubiquitous, free of charge, and user friendly with many providing ovulation estimates. The objective of this study was to analyze the period tracking applications (apps)’ ability to accurately predict fertility windows and ovulation. Three medical students tracked their menstrual cycle over four months in seven commercially available menstrual period tracking applications. Six of the apps were analyzed for fertility window, ovulation prediction, and usability. Two home ovulation kits were utilized to confirm ovulation. The sensitivity to predict the fertility window ranged from 35% to 94%&nbsp; (p&lt;0.05) while sensitivity to predict ovulation ranged from 0% to 31% (p&gt;0.05).&nbsp; Four of the apps allowed for menstrual cycle lengths greater than 35 day and offered an adjustable algorithm. Apps had increased sensitivity due to an expanded fertility window with increased number of predicted fertile days, but a low ovulation sensitivity and an inability to predict the day of ovulation. Additionally, apps allowed for additional personal information to be added with some apps sharing this data with a third party, raising the question of data protection for users. Solely using period tracking apps is not the gold standard for contraception or conception. The use of these apps in conjunction with luteinizing hormone home kits for detection of physiologic ovulation provides an accurate tool that allows a woman to take charge of her reproductive health.</p>}, number={1}, journal={Journal of Student Research}, author={Enenbach, Molly and Haworth, Cassandra and Hawkins, Camille and Kochmann, Matthias}, year={2021}, month={Mar.} }