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Malliou-Becher MN et al., 2026 · Human reproduction (Oxford, England)
What are the variations in ovulation time and menstrual cycle characteristics among and within various individuals over the course of 12 menstrual cycles? There are considerable variations in both cycle length and ovulation time, with pronounced intra-individual variability over a 12-cycle observation period. Although it is commonly believed that healthy women have regular cycles with a predictable mid-cycle ovulation, more recent research shows a significant variation in cycle length and ovulation time. Previous studies have focused only on cycle length, often excluding cycles outside the 25-35-day range, thus limiting the understanding of natural variation; they have also lacked precise ovulation diagnostics or included small sample sizes, making it difficult to capture the full scope of cycle and ovulation variability. Similarly, a recent big data study, while valuable, was limited by a self-selected group and the absence of accurate ovulation diagnostics, reducing its generalizability. STUDY DESIGN, SIZE, This study was designed as a prospective long-term observational study, which involved collecting data from 1923 women with a total of 43 999 menstrual cycles from January 1985 to July 2019. After fulfilling the inclusion criteria, the main group consisted of 1051 women, all of whom contributed data for 12 cycles (12 612 cycles), including 420 conception cycles. PARTICIPANTS/MATERIALS, SETTING, Participants in the study were between 18 and 44 years of age at study entry and did not take any reproductive hormones. Women who were postpartum, breastfeeding, amenorrheic, or within a 3-month period after stopping hormonal contraception were excluded. Participants agreed to keep cycle records according to the symptothermal method, 'Sensiplan'. Ovulation time was determined using an evidence-based algorithm based on evaluating cervical mucus patterns and basal body temperature shifts, with ovulation time defined as the day before the temperature rise. Data analysis was descriptive, using absolute and relative frequencies, standard deviation, percentiles, and ranges. Age dependency was assessed using unpaired sample t-tests and one-way ANOVA. Linear regression was used to assess long-term trends. MAIN In 62.4% of women, cycle lengths varied by 1 week or more within 12 cycles. Accordingly, the time of ovulation varied by 1 week or more within 12 cycles in 54.8% of women, with 96.5% experiencing fluctuations of 4 days or more over the 12 months. The median spontaneous cycle length was 28 days, with a mean of 29.66 days (SD = 7.55). Only 52.7% of women consistently had cycle lengths between 23 and 35 days across all 12 cycles. Ovulation occurred most frequently between Days 12 and 16, with almost half of conceptions (45.7%) occurring after Day 16. A one-way analysis of variance revealed a significant reduction in mean cycle length with increasing age (P < 0.001), showing the shortest median cycle length of 27 days being in women aged 40-44 years. Age also impacted ovulation time, with women aged 35-39 years showing more stable ovulation patterns compared to younger women. Over the 34-year study period, average cycle length increased slightly but significantly (β = 0.0161, P = 0.0306), corresponding to approximately half a day. Intra-individual variability also showed a slight, but non-significant, upward trend (β = 0.0262, P = 0.2173). LIMITATIONS, Comorbidities such as hyperprolactinemia, obesity, and PCOS were not systematically excluded. However, by including only women with at least 12 cycles, the study largely avoided severe hormonal disorders. This study highlights the considerable individual variation of ovulation time and cycle length over 12 menstrual cycles. These findings contribute to a better understanding of fertility awareness, and highlight the implications for family planning and reproductive health management. STUDY FUNDING/COMPETING INTEREST(S): The authors declare no conflicts of interest. No funding was provided. N/A.
Frank-Herrmann P et al., 2026 · Fertility and Sterility
Gnoth C et al., 2020 · Archives of gynecology and obstetrics
Many physicians and other healthcare professionals are often asked questions on interfering factors for conception by couples with a desire for children. Such possible disturbances include, for example, the very common minor diseases, stress and also sexual intercourse during the suspected implantation period. Non-scientifically based statements about disturbances in conception cycles, as found in many layman publications and on the internet, can strongly unsettle couples with a desire for children and force them into corset of rules of conduct. Therefore, a systematic scientific evaluation of the impact of disturbances on conception is urgently needed. A search for possible disturbances in natural conception cycles together with up to three of the respective pre-cycles in a large cycle database from users of the symptothermal method of natural family planning in Germany was performed. Disturbances were qualified by scientific panel decision and analysed statistically with their effects on the chances of spontaneous conception. Mixed logistical regression models and survival time analyses were used. A total of 237 women with a total of 747 cycles could be included in the analysis. In 61% of all 237 conception cycles, disturbances occurred. The statistical analysis shows that disturbances in natural conception cycles unexpectedly increase the likelihood of pregnancy by an overall factor of 1.32 (95% CI 1.04-1.70). Sexual intercourse in the window of implantation does not decrease the chances of conception. Relaxation states at the time of ovulation and/or during the implantation period have no representable effect and do not increase the chance of pregnancy. Couples trying to conceive should at least be informed that disturbances in conception cycles, such as minor diseases, stress or sexual intercourse during the implantation period do not interfere with conception. Relaxation has no effect in favour of success. This takes away the guilty feeling of couples, fearing that they possibly did something wrong in cycles without the desired pregnancy.
Frank-Herrmann P et al., 2017 · Arch Gynecol Obstet
To analyze cumulative pregnancy rates of subfertile couples after fertility awareness training. A prospective observational cohort study followed 187 subfertile women, who had received training in self-observation of the fertile phase of the menstrual cycle with the Sensiplan method, for 8 months. The women, aged 21-47 years, had attempted to become pregnant for 3.5 years on average (range 1-8 years) before study entry. Amenorrhea, known tubal occlusion and severe male factor had been excluded. An additional seven women, who had initially been recruited, became pregnant during the cycle immediately prior to Sensiplan training: this is taken to be the spontaneous pregnancy rate per cycle in the cohort in the absence of fertility awareness training. The cumulative pregnancy rate of subfertile couples after fertility awareness training was 38% (95% CI 27-49%; 58 pregnancies) after eight observation months, which is significantly higher than the estimated basic pregnancy rate of 21.6% in untrained couples in the same cohort. For couples who had been seeking to become pregnant for 1-2 years, the pregnancy rate increased to 56% after 8 months. A female age above 35 (cumulative pregnancy rate 25%, p = 0.06), couples who had attempted to become pregnant for more than 2 years (cumulative pregnancy rate 17%, p < 0.01), all significantly reduce the chances of conceiving naturally at some point. Training women to identify their fertile window in the menstrual cycle seems to be a reasonable first-line therapy in the management of subfertility.
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).
Starling MS et al., 2018 · mHealth · Free full text on PubMed Central
The rapid proliferation of fertility apps has created a market that has the potential to address the needs of women and couples worldwide. Some women who seek to prevent pregnancy are making behavioral decisions based on information they receive from fertility apps, yet fertility apps may not always be accurate and reliance on them could lead to unintended pregnancies. Little research has been done to understand who uses fertility apps for pregnancy prevention, how those who use them perceive their efficacy, and their preferences for how apps should be designed and presented to accurately assist them in preventing pregnancy. A web-based pilot survey was launched through Facebook recruiting women who either currently use a fertility app for pregnancy prevention or intend to use one in the future. Data collected from 1,000 women surveyed user preferences around fertility app characteristics, including aesthetics, features, functionality, and reputation. User knowledge about fertility and reproduction was assessed, and knowledge categories were created. Chi-square tests assessed differences in app characteristic preferences according to knowledge category. Additional qualitative analyses on free-text answers explored which features of apps are important to users when they search for one to use. Approximately one quarter (23.1%) of survey respondents reported currently using a fertility app or had used one in the recent past, and 76.9% reported intention to use one in the future. A majority of both current and intended users (65.4%) had some knowledge of fertility and reproduction, while 16.5% had very little knowledge. 18.1% reported receiving prior provider counseling on using a fertility-awareness based method. Users across all knowledge groups said it was very important for apps to be science-based and that they identify fertile days during the menstrual cycle. Women who use or wish to use apps to prevent pregnancy are seeking apps that are scientifically sound and provide them personalized information around their potential fertility. However, most fertility apps women reported using lack the capability for true fertility-awareness based method application for accurate, reliable pregnancy prevention. More research is needed to evaluate apps for efficacy and accuracy preventing pregnancy. Collaborations between app developers and women's health experts are encouraged, as well as informed consumerism campaigns.
Shattuck D et al., 2018 · JMIR mHealth and uHealth · Free full text on PubMed Central
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. 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. 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. 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). 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. ClinicalTrials.gov NCT02833922; http://clinicaltrials.gov/ct2/show/NCT02833922 (Archived by WebCite at http://www.webcitation.org/6yj5FHrBh).
Haile LT et al., 2018 · mHealth
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.