Smartphone apps that provide women with information about their daily fertility status during their menstrual cycles can contribute to the contraceptive method mix. However, if these apps claim to help a user prevent pregnancy, they must undergo similar rigorous research required for other contraceptive methods. Georgetown University's Institute for Reproductive Health is conducting a prospective longitudinal efficacy trial on Dot (Dynamic Optimal Timing), an algorithm-based fertility app designed to help women prevent pregnancy.
Objective
The aim of this paper was to highlight decision points during the recruitment-enrollment process and the effect of modifications on enrollment numbers and demographics. Recruiting eligible research participants for a contraceptive efficacy study and enrolling an adequate number to statistically assess the effectiveness of Dot is critical. Recruiting and enrolling participants for the Dot study involved making decisions based on research and analytic data, constant process modification, and close monitoring and evaluation of the effect of these modifications.
Methods
Originally, the only option for women to enroll in the study was to do so over the phone with a study representative. On noticing low enrollment numbers, we examined the 7 steps from the time a woman received the recruitment message until she completed enrollment and made modifications accordingly. In modification 1, we added call-back and voicemail procedures to increase the number of completed calls. Modification 2 involved using a chat and instant message (IM) features to facilitate study enrollment. In modification 3, the process was fully automated to allow participants to enroll in the study without the aid of study representatives.
Results
After these modifications were implemented, 719 women were enrolled in the study over a 6-month period. The majority of participants (494/719, 68.7%) were enrolled during modification 3, in which they had the option to enroll via phone, chat, or the fully automated process. Overall, 29.2% (210/719) of the participants were enrolled via a phone call, 19.9% (143/719) via chat/IM, and 50.9% (366/719) directly through the fully automated process. With respect to the demographic profile of our study sample, we found a significant statistical difference in education level across all modifications (P<.05) but not in age or race or ethnicity (P>.05).
Conclusions
Our findings show that agile and consistent modifications to the recruitment and enrollment process were necessary to yield an appropriate sample size. An automated process resulted in significantly higher enrollment rates than one that required phone interaction with study representatives. Although there were some differences in demographic characteristics of enrollees as the process was modified, in general, our study population is diverse and reflects the overall United States population in terms of race/ethnicity, age, and education. Additional research is proposed to identify how differences in mode of enrollment and demographic characteristics may affect participants' performance in the study.
Trial Registration
ClinicalTrials.gov NCT02833922; http://clinicaltrials.gov/ct2/show/NCT02833922 (Archived by WebCite at http://www.webcitation.org/6yj5FHrBh).
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.
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.
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.
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.
Simmons RG et al., 2017·JMIR research protocols·Free full text on PubMed Central
Some 222 million women worldwide have unmet needs for contraception; they want to avoid pregnancy, but are not using a contraceptive method, primarily because of concerns about side effects associated with most available methods. Expanding contraceptive options-particularly fertility awareness options that provide women with information about which days during their menstrual cycles they are likely to become pregnant if they have unprotected intercourse-has the potential to reduce unmet need. Making these methods available to women through their mobile phones can facilitate access. Indeed, many fertility awareness applications have been developed for smartphones, some of which are digital platforms for existing methods, requiring women to enter information about fertility signs such as basal body temperature and cervical secretions. Others are algorithms based on (unexplained) calculations of the fertile period of the menstrual cycle. Considering particularly this latter (largely untested) group, it is critical that these apps be subject to the same rigorous research as other contraceptive methods. Dynamic Optimal Timing, available via the Dot app as a free download for iPhone and Android devices, is one such method and the only one that has published the algorithm that forms its basis. It combines historical cycle data with a woman's own personal cycle history, continuing to accrue this information over time to identify her fertile period. While Dot has a theoretical failure rate of only 3 in 100 for preventing pregnancy with perfect use, its effectiveness in typical use has yet to be determined.
The study objective is to assess both perfect and typical use to determine the efficacy of the Dot app for pregnancy prevention.
To determine actual use efficacy, the Institute for Reproductive Health is partnering with Cycle Technologies, which developed the Dot app, to conduct a prospective efficacy trial, following 1200 women over the course of 13 menstrual cycles to assess pregnancy status over time. This paper outlines the protocol for this efficacy trial, following the Standard Protocol Items: Recommendations for Intervention Trials checklist, to provide an overview of the rationale, methodology, and analysis plan. Participants will be asked to provide daily sexual history data and periodically answer surveys administered through a call center or directly on their phone.
Funding for the study was provided in 2013 under the United States Agency for International Development Fertility Awareness for Community Transformation project. Recruitment for the study will begin in January of 2017. The study is expected to last approximately 18 months, depending on recruitment. Findings on the study's primary outcomes are expected to be finalized by September 2018.
Reproducibility and transparency, important aspects of all research, are particularly critical in developing new approaches to research design. This protocol outlines the first study to prospectively test both the efficacy (correct use) and effectiveness (actual use) of a pregnancy prevention app. This protocol and the processes it describes reflect the dynamic integration of mobile technologies, a call center, and Health Insurance Portability and Accountability Act-compliant study procedures. Future fertility app studies can build on our approaches to develop methodologies that can contribute to the evidence base around app-based methods of contraception.
ClinicalTrials.gov NCT02833922; https://clinicaltrials.gov/ct2/show/NCT02833922 (Archived be WebCite at http://www.webcitation.org/6nDkr0e76).
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.
Jennings VH et al., 2019·Contraception·Free to read
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.
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.
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.
These findings are promising and suggest that the 13-cycle results will demonstrate high efficacy of Dot.
While final 13-cycle efficacy results are forthcoming, 6-cycle results suggest that Dot's guidance provides women with useful information for preventing pregnancy.
The advent of new technological approaches to family planning has the potential to address unmet need in low- and middle-income countries. Provision of fertility awareness-based apps have the ability to provide accessible, direct-to-user fertility information to help women achieve their reproductive goals. The CycleBeads app, a digital platform for the Standard Days Method (SDM), a modern method of family planning, helps women achieve or prevent pregnancy, or track their cycles using the only their period start dates.
Brief social marketing campaigns were launched by the app developer to monitor cost and distribution of the CycleBeads app, understand the user profile, and assess user experience. Monitoring and evaluation through in-app micro surveys occurred over a 6-cycle period in seven countries: Egypt, Ghana, India, Jordan, Kenya, Nigeria, and Rwanda. In-app micro-surveys were utilized to collect data around demographics, mode of use of the app, prior experiences with family planning, and satisfaction to better understand women's interactions with the apps, and the possibility for meeting unmet need. Analyzes focused on women who were using the app to prevent pregnancy or track their cycles.
Social media campaigns proved to be an easy, low-cost approach to advertising the CycleBeads app. As a result, 356,520 women downloaded the app, and the cost to the advertiser per download ranged from $0.17-0.69. A majority of app users were between 20-29 years old, married or in exclusive relationships. Overall, 39.9% of users were using the app to prevent pregnancy, 38.5% to plan a pregnancy, and 21.6% were tracking their cycles. Among the users preventing pregnancy, 64.1% of women had not used a family planning method 3 months before downloading the CycleBeads app. One-third of users who were using the app to track their cycles, reported that they had not been using any form of family planning. In all seven countries, nearly 60% of women reported that they would definitely recommend the CycleBeads app to a friend, indicating their satisfaction with the app.
Our main findings indicate that a social media campaign is a low-cost approach to making the CycleBeads app accessible to women. The app addresses multiple reproductive intentions and attracts a diverse demographic of users across different life stages. For many women the app was the first modern method they used in the last 3 months, showing that fertility awareness-based apps have the potential to address an unmet need. Future studies should focus on changes in behavior during the fertile window, partner communication, and future family planning intentions.
Dominick Shattuck, Liya T Haile, Rebecca G Simmons
D Shattuck, L Haile, Becky Simmons, R Simmons
PMID 29678802 29678802 DOI 10.2196/mhealth.3335 10.2196/mhealth.3335 Shattuck et al. 2018, Shattuck 2018
