The accuracy of web sites and cellular phone applications in predicting the fertile window

Setton, Robert; Tierney, Christina; Tsai, Tony

doi:10.1097/aog.0000000000001341

Cited by 50Mobile Health and mHealth ApplicationsReproductive Health and TechnologiesReproductive Health and Contraception

The accuracy of web sites and cellular phone applications in predicting the fertile window

Setton, Robert, Tierney, Christina, Tsai, Tony·2016·Obstetrics & Gynecology

DOI 10.1097/aog.0000000000001341

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Abstract

OBJECTIVE: To evaluate the validity of fertility web sites and applications (apps) by comparing the predicted fertile window of these modalities to the actual fertile window of a standard 28-day cycle. METHODS: This was a descriptive study. The top resulting free web sites and electronic apps downloadable to a cellular phone that provide calendars for fertility and ovulation prediction were assessed. Cycles were standardized to 28 days in length, 4 days of menses, and the last menstrual period was set to January 1, 2015. The predicted date of ovulation and fertility window generated were compared with an actual estimated date of ovulation on cycle day 15, January 15, and a fertile window consisting of cycle day 10 to cycle day 15, the day of ovulation plus the preceding 5 cycle days, January 10-15. RESULTS: Data from 20 web sites and 33 apps were collected. Of all the web sites and apps used, one web site and three apps predicted the precise fertile window. CONCLUSION: Web sites and electronic apps used by the general public to predict fertile windows are generally inaccurate, although the clinical effect of this inaccuracy is unknown. Although they all include the most fertile cycle day, the range of the fertility window varies widely. Patients who are trying to conceive with the assistance of calendars generated from web sites and electronic apps should be counseled on the inaccuracy of these modalities.

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Several studies have shown that calendar apps are not accurate in identifying the fertile window.
“It is, therefore, unsurprising that several studies have shown that calendar apps are not accurate in identifying the fertile window.35–38”
From Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles (2019) · cites this paper as [35]
Many fertility tracking apps purport to predict ovulation based on cycle length characteristics alone, which can have extremely low predictive accuracy.
“Apps to track fertility are increasingly being used among women who are seeking to conceive, and many purport to predict ovulation based on cycle length characteristics alone, which can have extremely low predictive accuracy (Moglia et al. 2016; Setton et al. 2016; Johnson et al. 2018).”
From Real-life insights on menstrual cycles and ovulation using big data (2020) · cites this paper as Setton et al. 2016

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The Accuracy of Websites and Cellular Phone Applications in Predicting the Fertile Window [12G]
Setton, R. A., Tierney, C. H., & Tsai, T. (2016) · Obstetrics and Gynecology · doi:10.1097/01.aog.0000483896.97718.ee · Cited by 3 · see citing works
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Rebar, R. W. (2016) · Journal watch · doi:10.1056/nejm-jw.na41559
Use of Cycle Length Alone to Predict Ovulation, as Predicted by Apps, is Highly Inaccurate [19G]
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Authors: Setton, R., Tierney, C., & Tsai, T.
Affiliations: New York Hospital Queens (US)
ORCID: Setton, Robert
Venue: Obstetrics & Gynecology
Publisher: Ovid Technologies (Wolters Kluwer Health)
Published: 2016-07
Volume: 128
Issue: 1
Pages: 58-63
ISSN: 0029-7844 (ISSN-L)
DOI: 10.1097/aog.0000000000001341
OpenAlex: W2368581083
Cited by: 50
References: 19
Citations by year: 2026: 3 · 2025: 7 · 2024: 1 · 2023: 1 · 2022: 9 · 2021: 6 · 2020: 8 · 2019: 6 · 2018: 5 · 2017: 1 · 2016: 3
FWCI: 9.30
Type: journal article
Language: en
Open access: closed
Locations: Obstetrics and Gynecology (publishedVersion)
PubMed (publishedVersion)
Topics: Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
Health Sciences › Medicine › Reproductive Medicine › Reproductive Health and Technologies
Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Reproductive Health and Contraception
Keywords: fertility prediction, fertile window, ovulation prediction, menstrual cycle, fertility awareness
MeSH terms: Data Accuracy, Adult, Female, Fertility, Humans, Prognosis, Natural Family Planning Methods, Internet, Cell Phone, Fertile Period, Mobile Applications

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The accuracy of web sites and cellular phone applications in predicting the fertile window

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