Fertility Awareness · Effectiveness
Abstract
Objective
To assess six-cycle perfect and typical use efficacy of Dynamic Optimal Timing (Dot), an algorithm-based fertility app that identifies the fertile window of the menstrual cycle using a woman's period start date and provides guidance on when to avoid unprotected sex to prevent pregnancy.
Study Design
We are conducting a prospective efficacy study following a cohort of women using Dot for up to 13 cycles. Study enrollment and data collection are being conducted digitally within the app and include a daily coital diary, prospective pregnancy intentions and sociodemographic information. We used data from the first six cycles to calculate life-table failure rates.
Results
We enrolled 718 women age 18-39 years. Of the 629 women 18-35 years old, 15 women became pregnant during the first six cycles for a typical use failure rate of 3.5% [95% CI 1.7-5.2]. All pregnancies occurred with incorrect use, so we did not calculate a perfect use failure rate.
Conclusions
These findings are promising and suggest that the 13-cycle results will demonstrate high efficacy of Dot.
Implications
While final 13-cycle efficacy results are forthcoming, 6-cycle results suggest that Dot's guidance provides women with useful information for preventing pregnancy.
Topics
By this author
Technology · Wearable Devices
How Do Fertility-Tracking Technologies Define Ovulation and Anovulation? A Structured Landscape Analysis
Wallis B et al., 2026 · Contraception · Free to read
To characterize how commercially available fertility-tracking devices and wearables define ovulation and anovulation, evaluate available comparator evidence, and assess user burden across 19 selected technologies. We conducted a structured landscape analysis of 19 fertility-tracking devices and wearables available in the United States. Technologies were evaluated for biomarker type, operational definitions of ovulation and anovulation, comparator evidence, intended use, regulatory status, and user burden, among other variables. Technologies clustered into four major categories: luteinizing hormone (LH)-only devices, multi-hormone devices, basal body temperature (BBT)-based wearables, and BBT-based thermometers. LH-only devices generally defined ovulation by detecting an LH surge or peak; multi-hormone devices incorporated LH and/or pregnanediol-3-glucuronide (PdG) measurements; and BBT-based technologies relied on thermal shifts. Explicit definitions of anovulation were uncommon and were frequently inferred from the absence of ovulation-associated biomarkers. The existence and design of comparator evidence varied substantially across technologies. Most comparator studies relied on surrogate measures such as urinary or serum hormones, whereas few technologies had comparator evidence against physiological reference standards such as transvaginal ultrasound (TVUS). Comparator studies in irregular-cycle populations were uncommon despite frequent marketing of these devices as appropriate for users with irregular cycles. User burden varied substantially across technologies. Fertility-tracking technologies demonstrate substantial heterogeneity in operational definitions, comparator evidence, and user burden. Greater transparency regarding ovulation and anovulation definitions, clearer reporting of comparator evidence, and more representative evaluation in irregular-cycle populations are needed to support accurate interpretation and integration into reproductive healthcare.
Long Acting Methods · Intrauterine Devices
PASS, VAS, or satisfaction: A prospective observational study of IUD placement pain experiences
McAllaster S et al., 2026 · Contraception
To identify factors associated with unacceptable Patient Acceptable Symptom State (PASS) responses, Visual Analog Scale (VAS) scores, and satisfaction at time of intrauterine device (IUD) placement. Recruitment occurred at six Utah clinics between 6/24-2/25. Participants completed procedure surveys on demographics, reproductive history, anticipated pain, anxiety, and coping skills. Post-placement surveys assessed PASS responses, experienced pain by VAS (1-100mm) and satisfaction with IUD placement (5-point Likert scale). We determined factors associated with unacceptable PASS responses and a cut point delineating "low" vs "high" pain to assess measure associations. Of 194 participants, 21% (n = 41) reported an unacceptable PASS, which was associated with higher mean anticipated (65 mm vs 51 mm; padj=0.01) and experienced (76 mm vs 46 mm; padj<0.001) pain, prior sexual assault (55% vs 28%; padj=0.016), or violent death of someone close (25% vs 7%; padj=0.024). In controlled analysis, higher experienced pain predicted unacceptable PASS (OR:1.10;95%CI:1.06, 1.14). "High" pain (≥61mm) occurred in 44% of all participants. Of those with high pain, 55% reported an acceptable PASS response. History of prior pelvic exam (p = 0.02, padj 0.20), prior IUD placement (p = 0.003; padj 0.12), or violent death of someone close (p = 0.011; padj 0.13) influenced unacceptable PASS responses in this group. Of all participants, 21% reported dissatisfaction (n = 16) or neutral response (n = 24) regarding their IUD placement, among which only 13 reported an unacceptable PASS (32%). Satisfaction was influenced by mean VAS score (61 mm dissatisfied/neutral vs 50 mm satisfied; p = 0.01; padj 0.90). IUD placement pain level may influence satisfaction, but less than half of those with high pain (≥61mm) reported an unacceptable experience. IUD placement pain experiences are multi-dimensional and cannot be described by pain level alone. High levels of placement pain influence satisfaction and overlap but are not collinear with acceptability responses. Acceptability of IUD may be subject to temporal bias and influenced by whether their goals/needs are met and whether the pain was ultimately worth it.
Experiences of healthcare providers caring for pregnant individuals with substance use disorder
Nantume A et al., 2025 · Drug and alcohol dependence · Free full text on PubMed Central
Substance use disorder (SUD) during pregnancy is associated with an increased risk of adverse maternal and neonatal outcomes, yet many patients face significant barriers to accessing treatment, including experiencing bias and stigma from healthcare providers. To inform improvements in care delivery, this study explored the experiences of healthcare providers who care for pregnant individuals with SUD. Researchers conducted seven focus group discussions (FGD) and fifteen in-depth interviews (IDI) using semi-structured guides, with participants drawn from both rural and urban hospital settings across Utah. All discussions were audio recorded, transcribed verbatim, and examined using the Template Analysis approach. Among FGD participants (n = 37), the sample was predominantly white (94.6 %), female (86.5 %), rural (89.2 %), and comprised of nurses (78.4 %). The IDI sample (n = 15) was more gender diverse (60 % female), had greater representation of physicians (53.3 %), and a higher proportion of urban participants (60.0 %). Template analysis revealed four major themes. First, providers held a range of perceptions toward pregnant individuals with SUD, reflecting both stigma and empathy. Second, many emphasized the importance of building trust through nonjudgmental communication and emotional support. Third, providers reported high levels of burnout, particularly due to limited resources and systemic barriers. Finally, participants highlighted knowledge gaps related to SUD clinical care and confusion around regulatory requirements like mandatory reporting. Despite the challenges described, many providers expressed strong dedication to delivering compassionate, person-centered care. The findings underscore the need for targeted provider education, institutional policies that reduce care barriers, and increased community and institutional resources to better support patients with SUD during pregnancy.
Effectiveness · Typical and Perfect Use
Evaluating Pregnancy Rates in Fertility Awareness-Based Methods for Family Planning: Simulated Comparison of Correct Use to Avoid, Method-Related, and Total Pregnancy Rates
Stanford JB et al., 2024 · Linacre Q · Free full text on PubMed Central
Fertility awareness-based methods (FABMs), also known as natural family planning (NFP), enable couples to identify the days of the menstrual cycle when intercourse may result in pregnancy ("fertile days"), and to avoid intercourse on fertile days if they wish to avoid pregnancy. Thus, these methods are fully dependent on user behavior for effectiveness to avoid pregnancy. For couples and clinicians considering the use of an FABM, one important metric to consider is the highest expected effectiveness (lowest possible pregnancy rate) during the correct use of the method to avoid pregnancy. To assess this, most studies of FABMs have reported a method-related pregnancy rate (a cumulative proportion), which is calculated based on all cycles (or months) in the study. In contrast, the correct use to avoid pregnancy rate (also a cumulative proportion) has the denominator of cycles with the correct use of the FABM to avoid pregnancy. The relationship between these measures has not been evaluated quantitatively. We conducted a series of simulations demonstrating that the method-related pregnancy rate is artificially decreased in direct proportion to the proportion of cycles with intermediate use (any use other than correct use to avoid or targeted use to conceive), which also increases the total pregnancy rate. Thus, as the total pregnancy rate rises (related to intermediate use), the method-related pregnancy rate falls artificially while the correct use pregnancy rate remains constant. For practical application, we propose the core elements needed to assess correct use cycles in FABM studies. Fertility awareness-based methods (FABMs) can be used by couples to avoid pregnancy, by avoiding intercourse on fertile days. Users want to know what the highest effectiveness (lowest pregnancy rate) would be if they use an FABM correctly and consistently to avoid pregnancy. In this simulation study, we compare two different measures: (1) the method-related pregnancy rate; and (2) the correct use pregnancy rate. We show that the method-related pregnancy rate is biased too low if some users in the study are not using the method consistently to avoid pregnancy, while the correct use pregnancy rate obtains an accurate estimate. SHORT In FABM studies, the method-related pregnancy rate is biased too low, but the correct use pregnancy rate is unbiased.
Related research
Effectiveness · Typical and Perfect Use
Perfect- and typical-use effectiveness of the Dot fertility app over 13 cycles: results from a prospective contraceptive effectiveness trial
Jennings V et al., 2019 · Eur J Contracept Reprod Health Care · Free to read
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 perfectand typical-use failure rates. 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 perfectand typical-use failure rates using multi-censoring, single-decrement life-table analysis, and conducted sensitivity, attrition and survival analyses. 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. Dot's effectiveness is within the range of other user-initiated contraceptive methods.
Effectiveness · Typical and Perfect Use
Natural Cycles app: contraceptive outcomes and demographic analysis of UK users
Pearson JT et al., 2021 · Eur J Contracept Reprod Health Care · Free to read
Digital fertility awareness-based contraception offers an alternative choice for women who do not wish to use hormonal or invasive methods. The aim of this study was to investigate the key demographics of current users of the Natural Cycles app and assess the contraceptive outcomes of women preventing pregnancy in a UK cohort of women. This was a real world observational prospective observational study. The typical-use effectiveness of the method was calculated using both 13-cycle cumulative probability of pregnancy (life table analysis) and Pearl Index for the entire study cohort. Perfect-use PI was calculated using data from cycles where sexual intercourse during the fertile window was marked as protected and no unprotected sex was recorded on fertile days. 12,247 women were included in the study and contributed an average of 9.9 months of data for a total of 10,066 woman years of exposure. The mean age of the cohort was 30, mean BMI 23.4, the majority were in a stable relationship (83.2%) and had a university degree or higher (83%). The one year typical use, PI was 6.1 (95% CI: 5.6, 6.6) and with perfect-use was 2.0 (95% CI: 1.3, 2.8). 13 cycle pregnancy probability was 7.1%. This is the first study which describes the use of a digital contraceptive by women in the UK. It describes the demographics of users and how they correlate with the apps effectiveness at preventing pregnancy.
Effectiveness · Typical and Perfect Use
Contraceptive Effectiveness of an FDA-Cleared Birth Control App: Results from the Natural Cycles U.S. Cohort
Pearson JT et al., 2020 · J Womens Health (Larchmt)
Digital fertility awareness-based methods of birth control are an attractive alternative to hormonal or invasive birth control for modern women. They are also popular among women who may be planning a pregnancy over the coming years and wish to learn about their individual menstrual cycle. The aim of this study was to assess the effectiveness of the Natural Cycles app at preventing pregnancy for a cohort of women from the United States and to describe the key demographics of current users of the app in such a cohort. This prospective real-world cohort study included users who purchased an annual subscription to prevent pregnancy. Demographics were assessed through answers to in-app questionnaires. Birth control effectiveness estimates for the entire cohort were calculated using 1-year pearl index (PI) and 13-cycle cumulative pregnancy probability (Kaplan-Meier life table analysis). The study included 5879 women who contributed an average of 10.5 months of data for a total of 5125 woman-years of exposure. The average user was 30 years old with a body mass index of 24 and reported being in a stable relationship. With typical use, the app had a 13-cycle cumulative pregnancy probability of 7.2% and a 1-year typical use PI of 6.2. When the app was used under perfect use, the PI was 2.0. The data presented in this study give insights into the cohort of women using this app in the United States, and provide country-specific effectiveness estimates. The contraceptive effectiveness of the app was in line with previously published figures from Natural Cycles (PI of seven for typical use and two for perfect use).
Effectiveness · Fertile Window Estimation
Time to Pregnancy for Women Using a Fertility Awareness Based Mobile Application to Plan a Pregnancy
Favaro C et al., 2021 · J Womens Health (Larchmt) · Free full text on PubMed Central
Time to pregnancy (TTP) is a biomarker of fecundability and has been associated with behavioral and environmental characteristics; however, these associations have not been examined in a large population-based sample of application (app) users. This observational study followed 5,376 women with an age range of 18 to 45 years who used an app to identify their fertile window. We included women who started trying to conceive between September 30, 2017 and August 31, 2018. TTP was calculated as the number of menstrual cycles from when the user switched to "Plan" mode up to and including the cycle in which they logged a positive pregnancy test. We examined associations with several characteristics, including age, gravidity, body mass index, cycle length and cycle length variation, frequency of sexual intercourse, and temperature measuring frequency. Discrete time fecundability models were used to estimate fecundability odds ratios. For the complete cohort the 6-cycle and 12-cycle cumulative pregnancy probabilities were found to be 61% (95% confidence interval [CI]: 59-62) and 74% (95% CI: 73-76), respectively. The median TTP was four cycles. The highest fecundability was associated with an age of less than 35 years, with cycle length variation <5 days and logging sexual intercourse on at least 20% of days added (the proportion of days in which intercourse was logged) (11.5% [n = 613] of entire sample). This group achieved a 6and 12-cycle cumulative pregnancy probability of 88% (95% CI: 85-91) and 95% (95% CI: 94-97), respectively, and a TTP of 2 cycles. Natural Cycles was an effective method of identifying the fertile window and a noninvasive educational option for women planning a pregnancy. Women under age 35 with regular cycles showed a high pregnancy rate.
Fertility Awareness › Effectiveness › Typical and Perfect Use
Victoria H Jennings, Liya T Haile, Rebecca G Simmons, Hanley M Fultz, Dominick Shattuck
V Jennings, L Haile, Becky Simmons, R Simmons, H Fultz, D Shattuck
PMID 30316782 30316782 DOI 10.1016/j.contraception.2018.10.002 10.1016/j.contraception.2018.10.002 Jennings et al. 2019, Jennings 2019