The Performance of Fertility Awareness-based Method Apps Marketed to Avoid Pregnancy
Open accessAbstract
INTRODUCTION: In recent years there has been an explosion in the development of medical apps, with more than 40,000 apps now available. Nearly 100 apps allow women to track their fertility and menstrual cycles and can be used to avoid or achieve pregnancy. Apps offer a convenient way to track fertility biomarkers. However, only some use evidence-based fertility awareness-based methods (FABMs), which with ideal use have rates of effectiveness similar to those of commonly used forms of hormonal birth control. Since having a baby or preventing a pregnancy are important responsibilities, it is critical that women and couples have access to reliable, evidence-based apps that allow them to accurately track their fertility. METHODS: We developed a tool to evaluate and rate fertility apps. This tool is specifically designed to help couples avoid pregnancy. RESULTS: Results showed that the majority of fertility apps are not based on evidence-based FABMs or include a disclaimer discouraging use for avoiding pregnancy. However, at least 1 app in each FABM category (except symptohormonal methods) had a perfect score on accuracy. CONCLUSION: Relying solely on an app to use an FABM, without appropriate training in the method, may not be sufficient to prevent pregnancy.
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Fertility awareness based apps are becoming increasingly popular for contraception and pregnancy planning.
“and they are becoming increasingly popular for contraception14–17 and pregnancy planning.18”
From Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles (2019) · cites this paper as [17]
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- Authors
- Duane, M., Contreras, A., Jensen, E. T., & White, A.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Venue
- The Journal of the American Board of Family Medicine
- Published
- 2016-07-01
- Volume
- 29
- Issue
- 4
- Pages
- 508-511
- ISSN
- 1557-2625 (ISSN-L)
- 1558-7118
- OpenAlex
- W2473946841
- Cited by
- 110
- References
- 8
- Citations by year
- 2026: 9 · 2025: 4 · 2024: 10 · 2023: 14 · 2022: 11 · 2021: 14 · 2020: 15 · 2019: 11 · 2018: 13 · 2017: 5 · 2016: 3 · 2015: 1
- FWCI
- 10.61
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- The Journal of the American Board of Family Medicine (publishedVersion)
- PubMed (publishedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- UNC Libraries
- Topics
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Reproductive Health and Contraception
- Health Sciences › Health Professions › General Health Professions › Mobile Health and mHealth Applications
- Health Sciences › Medicine › Reproductive Medicine › Reproductive Health and Technologies
- Keywords
- fertility awareness-based methods, fertility tracking apps, menstrual cycle tracking, contraception, fertility indicators, contraceptive effectiveness
- MeSH terms
- Contraception, Family Planning Services, Female, Humans, Medical Informatics Applications, Pregnancy, Natural Family Planning Methods, Biomarkers, Practice Guidelines as Topic, Evidence-Based Medicine, Fertile Period
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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