“When Am I Fertile?”: A Pilot Study Comparing Ovulation Prediction Accuracy of Apps and LH Kits

Authors

  • Molly Enenbach A.T. Still University, School of Osteopathic Medicine in Arizona
  • Cassandra Haworth A.T. Still University, School of Osteopathic Medicine in Arizona
  • Camille Hawkins A.T. Still University, School of Osteopathic Medicine in Arizona
  • Matthias Kochmann A.T. Still University, School of Osteopathic Medicine in Arizona

DOI:

https://doi.org/10.47611/jsr.v10i1.1216

Keywords:

Fertility, Menstruation, Mobile Applications, Pregnancy, Ovulation Prediction

Abstract

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%  (p<0.05) while sensitivity to predict ovulation ranged from 0% to 31% (p>0.05).  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.

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References or Bibliography

Wilcox AJ, Weinberg CR, Baird DD. Timing of Sexual Intercourse in Relation to Ovulation — Effects on the Probability of Conception, Survival of the Pregnancy, and Sex of the Baby. N Engl J Med. 1995;333(23):1517-1521. doi:10.1056/NEJM199512073332301

Wilcox AJ, Dunson D, Baird DD. The timing of the “fertile window” in the menstrual cycle: Day specific estimates from a prospective study. Br Med J. 2000;321(7271):1259-1262. doi:10.1136/bmj.321.7271.1259

Thijssen A, Meier A, Panis K, Ombelet W. “Fertility Awareness-Based Methods” and subfertility: a systematic review. Facts, views Vis ObGyn. 2014;6(3):113-123. http://www.ncbi.nlm.nih.gov/pubmed/25374654. Accessed April 24, 2020.

Stanford, Joseph B. MD, MSPH; White, George L. Jr PhD, MSPH; Hatasaka HM. Timing Intercourse to Achieve Pregnancy: Current Evidence. Obstet Gynecol. 2002;100(6):1333-1341. doi:10.1016/s0029-7844(02)02382-7

Finer LB, Zolna MR. Declines in unintended pregnancy in the United States, 2008-2011. N Engl J Med. 2016. doi:10.1056/NEJMsa1506575

Hampton K, Mazza D. Should spontaneous or timed intercourse guide couples trying to conceive? Hum Reprod. 2009. doi:10.1093/humrep/dep322

Hampton KD, Mazza D, Newton JM. Fertility-awareness knowledge, attitudes, and practices of women seeking fertility assistance. J Adv Nurs. 2013;69(5):1076-1084. doi:10.1111/j.1365-2648.2012.06095.x

Frank-Herrmann P, Jacobs C, Jenetzky E, et al. Natural conception rates in subfertile couples following fertility awareness training. Arch Gynecol Obstet. 2017;295(4):1015-1024. doi:10.1007/s00404-017-4294-z

Hall J. Female Physiology Before Pregnancy and Female Hormones- ClinicalKey. In: Guyton and Hall Textbook of Medical Physiology. 13th ed. Elsevier Inc; 2016:1037-1054. https://www.clinicalkey.com/#!/content/book/3-s2.0-B9781455770052000822?indexOverride=GLOBAL. Accessed April 15, 2020.

Bull JR, Rowland SP, Scherwitzl EB, Scherwitzl R, Danielsson KG, Harper J. Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles. npj Digit Med. 2019;2(1):83. doi:10.1038/s41746-019-0152-7

Su H-W, Yi Y-C, Wei T-Y, Chang T-C, Cheng C-M. Detection of ovulation, a review of currently available methods. Bioeng Transl Med. 2017;2(3):238-246. doi:10.1002/btm2.10058

Ahrefs - SEO Tools & Resources To Grow Your Search Traffic. https://ahrefs.com/. Accessed February 23, 2020.

Guermandi E, Vegetti W, Bianchi MM, Uglietti A, Ragni G, Crosignani P. Reliability of ovulation tests in infertile women. Obstet Gynecol. 2001. doi:10.1016/S0029-7844(00)01083-8

Natality, 2016-2018 expanded Results Form. https://wonder.cdc.gov/controller/datarequest/D149;jsessionid=6AAFCC43E03CA2868AA38A36EC16C1A5. Accessed April 8, 2020.

No Body’s Business But Mine: How Menstruation Apps Are Sharing Your Data | Privacy International. https://privacyinternational.org/long-read/3196/no-bodys-business-mine-how-menstruations-apps-are-sharing-your-data. Accessed April 8, 2020.

App Store Review Guidelines - Apple Developer. https://developer.apple.com/app-store/review/guidelines/#terms-conditions. Accessed April 15, 2020.

Published

2021-03-31

How to Cite

Enenbach, M., Haworth, C., Hawkins, C. ., & Kochmann, M. (2021). “When Am I Fertile?”: A Pilot Study Comparing Ovulation Prediction Accuracy of Apps and LH Kits. Journal of Student Research, 10(1). https://doi.org/10.47611/jsr.v10i1.1216

Issue

Section

Research Articles