Cited by 80Mobile Health and mHealth ApplicationsReproductive Health and ContraceptionReproductive Health and Technologies

Plausibility of Menstrual Cycle Apps Claiming to Support Conception

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Freis, Alexander, Freundl-Schütt, Tanja, Wallwiener, Lisa-Maria, Baur, Sigfried, Strowitzki, Thomas, Freundl, Günter, Frank-Herrmann, Petra·2018·Frontiers in Public Health

Abstract

The interval of peak fertility during the menstrual cycle is of limited duration, and the day of ovulation varies, even in women with fairly regular cycles. Therefore, menstrual cycle apps identifying the "fertile window" for women trying to conceive must be quite precise. A deviation of a few days may lead the couple to focus on less- or non-fertile days for sexual intercourse and thus may be worse than random intercourse. The aim of the present investigation was to develop a scoring system for rating available apps for determining the fertile window and secondarily pilot test 12 apps currently available in both German and English (consisting of 6 calendar-based apps: Clue Menstruations- und Zykluskalender, Flo Menstruationskalender, Maya-Mein Periodentracker, Menstruationskalender Pro, Period Tracker Deluxe, and WomanLog-Pro-Kalender; 2 calculothermal apps: Ovy and Natural Cycles; and 4 symptothermal apps: myNFP, Lady Cycle, Lily, and OvuView). The calendar-based apps were investigated by entering several series of cycles with varying lengths, whereas the symptom-based apps were examined by entering data of cycles with known temperature rise, cervical mucus pattern, and clinical ovulation. The main criteria for evaluating the cycle apps were as follows: (1) What methods/parameters were used to determine the fertile window? (2) What study results exist concerning that underlying method/parameters? (3) What study results exist concerning the app itself? (4) Was there a qualified counseling service? The calendar-based apps predicted the fertile days based on data of previous cycles. They obtained zero points in our scoring system, as they did not comply with any of the evaluated criteria. Calculothermal apps had similar deficits for predicting the most fertile days and produced suboptimal results (Ovy 3/30 points and Natural Cycles 2/30 points). The symptothermal apps determined the fertile days based on parameters of the current cycle: Lady Cycle scored 20/30 points, myNFP 20/30 points, Lily 19/30 points, and OvuView 11/30 points. We concluded that the available cycle apps vary according to their underlying scientific quality and clear rating criteria have been suggested. Three of the tested apps were judged to be eligible for further study. The scientific evaluation of cycle apps depends on good prospective studies undertaken by independent investigators who are free of commercial bias.

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  1. [20]Künkel T Die Selbstbeobachtung der Frau durch die symptothermale Methode der natürlichen Familienplanung (NFP) unter besonderer Berücksichtigung von Zyklusphänomenen, Störfaktoren und Praktikabilität der Methode [Dissertation]. Duesseldorf, Germany: Medizinische Fakultät der Universität Düsseldorf (1994).

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Authors
Freis, A., Freundl-Schütt, T., Wallwiener, L.-M., Baur, S., Strowitzki, T., Freundl, G., & Frank-Herrmann, P.
Affiliations
  • Heidelberg University (DE)
  • Düsseldorf University Hospital (DE)
  • Ludwig-Maximilians-Universität München (DE)
Venue
Frontiers in Public Health
Published
2018-04-03
Volume
6
Pages
98-98
ISSN
2296-2565 (ISSN-L)
OpenAlex
W2795961229
Cited by
80
References
40
Citations by year
2026: 6 · 2025: 5 · 2024: 10 · 2023: 12 · 2022: 9 · 2021: 10 · 2020: 15 · 2019: 9 · 2018: 4
FWCI
14.51
Type
journal article
Language
en
Open access
Licence
cc-by
Locations
  • Frontiers in Public Health (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Open access LMU (Ludwid Maxmilian's Universitat Munchen) (submittedVersion, cc-by)
Topics
  • Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
  • Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Reproductive Health and Contraception
  • Health Sciences › Medicine › Reproductive Medicine › Reproductive Health and Technologies
Keywords
fertility monitoring, fertile window, ovulation prediction, conception, symptothermal method, basal body temperature, cervical mucus, scoring system, app quality assessment, natural family planning

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