Perfect- and typical-use effectiveness of the Dot fertility app over 13 cycles: results from a prospective contraceptive effectiveness trial
Open accessAbstract
OBJECTIVE: Dynamic Optimal Timing (Dot) is a smartphone application (app) that estimates the menstrual cycle fertile window based on the user's menstrual period start dates. Dot uses machine learning to adapt to cycles over time and informs users of 'low' and 'high' fertility days. We investigated Dot's effectiveness, calculating perfect- and typical-use failure rates. METHODS: This prospective, 13 cycle observational study (ClinicalTrials.gov NCT02833922) followed 718 women who were using Dot to prevent pregnancy. Participants contributed 6616 cycles between February 2017 and October 2018, providing data on menstrual period start dates, daily sexual activity and prospective intent to prevent pregnancy. We determined pregnancy through participant-administered urine pregnancy tests and/or written or verbal confirmation. We calculated perfect- and typical-use failure rates using multi-censoring, single-decrement life-table analysis, and conducted sensitivity, attrition and survival analyses. RESULTS: The perfect-use failure rate was calculated to be 1.0% (95% confidence interval [CI]: 0.9%, 2.9%) and the typical-use failure rate was 5.0% (95% CI: 3.4%, 6.6%) for women aged 18-39 (n = 718). Survival analyses identified no significant differences among age or racial/ethnic groups or women in different types of relationships. Attrition analyses revealed no significant sociodemographic differences, except in age, between women completing 13 cycles and those exiting the study earlier. CONCLUSION: Dot's effectiveness is within the range of other user-initiated contraceptive methods.
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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 [15]
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Real-world menstrual cycle characteristics of more than 600,000 menstrual cycles
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- Authors
- Jennings, V., Haile, L. T., Simmons, R. G., Spieler, J., & Shattuck, D.
- Affiliations
- Georgetown University (US)
- University of Utah (US)
- Independent Consultant in Population and Reproductive Health, Bethesda, MD, USA
- Corresponding author
- Jennings, Victoria
- Venue
- The European Journal of Contraception & Reproductive Health Care
- Publisher
- Informa UK Limited
- Published
- 2019-03-04
- Volume
- 24
- Issue
- 2
- Pages
- 148-153
- ISSN
- 1362-5187 (ISSN-L)
- 1473-0782
- OpenAlex
- W2922197041
- Cited by
- 41
- References
- 20
- Citations by year
- 2026: 5 · 2025: 7 · 2024: 4 · 2023: 5 · 2022: 4 · 2021: 4 · 2020: 8 · 2019: 4
- FWCI
- 4.60
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- The European Journal of Contraception & Reproductive Health Care (publishedVersion, cc-by-nc-nd)
- PubMed (publishedVersion)
- Funders
- USAID (AID-OAA-A-13-00083)
- 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
- menstrual cycle tracking, mobile application, contraception, fertility prediction, contraceptive effectiveness
- MeSH terms
- Smartphone, Contraceptive Effectiveness, Adult, Female, Fertility, Humans, Menstrual Cycle, Pregnancy, Prospective Studies, Natural Family Planning Methods, Young Adult, Mobile Applications
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