Accuracy of perception of ovulation day in women trying to conceive

Fertility and infertility uses of menstrual apps from the perspectives of healthcare providers and patients

BACKGROUND

Menstrual cycle tracking apps are increasingly used by those trying to conceive as well as those diagnosed and treated for infertility. However, the small amount of existing research about the use of these apps does not include the perspectives of healthcare providers.

AIMS

This study explores how healthcare providers describe the role of menstrual apps in fertility and infertility health care, and how this compares with patients' views.

MATERIALS AND METHODS

Responses were collected from an online survey (n = 37 providers and n = 89 patients) and online focus groups (n = 4 providers and n = 6 patients) and analysed using reflexive thematic analysis.

RESULTS

Healthcare providers, as well as some patients, expressed doubts about the accuracy of app estimates of the timing of ovulation. By contrast, many patients, but no healthcare providers, were enthusiastic about ovulation estimates provided by their apps. Apps were described by both groups as having a role in diagnosing and treating infertility, with healthcare providers emphasising the calendar history function of the apps supporting treatment, and patients focused on recognising and diagnosing infertility.

CONCLUSIONS

This exploratory study suggests that apps are viewed by both healthcare providers and patients as having a potential role in fertility and infertility healthcare. Although patients and app users are attentive to app estimates of ovulation timing, healthcare providers are sceptical.

Prediction of ovulation: new insight into an old challenge

Ultrasound monitoring and hormonal blood testing are considered by many as an accurate method to predict ovulation time. However, uniform and validated algorithms for predicting ovulation have yet to be defined. Daily hormonal tests and transvaginal ultrasounds were recorded to develop an algorithm for ovulation prediction. The rupture of the leading ovarian follicle was a marker for ovulation day. The model was validated retrospectively on natural cycles frozen embryo transfer cycles with documented ovulation. Circulating levels of LH or its relative variation failed, by themselves, to reliably predict ovulation. Any decrease in estrogen was 100% associated with ovulation emergence the same day or the next day. Progesterone levels > 2 nmol/L had low specificity to predict ovulation the next day (62.7%), yet its sensitivity was high (91.5%). A model for ovulation prediction, combining the three hormone levels and ultrasound was created with an accuracy of 95% to 100% depending on the combination of the hormone levels. Model validation showed correct ovulation prediction in 97% of these cycles. We present an accurate ovulation prediction algorithm. The algorithm is simple and user-friendly so both reproductive endocrinologists and general practitioners can use it to benefit their patients.

Timed intercourse for couples trying to conceive

BACKGROUND

Many factors influence fertility, one being the timing of intercourse. The 'fertile window' describes a stage in the cycle when conception can occur and is approximately five days before to several hours after ovulation. 'Timed intercourse' is the practice of prospectively identifying ovulation and, thus, the fertile window to increase the likelihood of conception. Methods of predicting ovulation include urinary hormone measurement (luteinising hormone (LH) and oestrogen), fertility awareness-based methods (FABM) (including tracking basal body temperatures, cervical mucus monitoring, calendar charting/tracking apps), and ultrasonography. However, there are potentially negative aspects associated with ovulation prediction, including stress, time consumption, and cost implications of purchasing ovulation kits and app subscriptions. This review considered the evidence from randomised controlled trials (RCTs) evaluating the use of timed intercourse (using ovulation prediction) on pregnancy outcomes.

OBJECTIVES

To evaluate the benefits and risks of ovulation prediction methods for timing intercourse on conception in couples trying to conceive.

SEARCH METHODS

We searched the Cochrane Gynaecology and Fertility (CGF) Group Specialised Register, CENTRAL, MEDLINE, and Embase in January 2023. We also checked the reference lists of relevant studies and searched trial registries for any additional trials.

SELECTION CRITERIA

We included RCTs that compared methods of timed intercourse using ovulation prediction to other forms of ovulation prediction or intercourse without ovulation prediction in couples trying to conceive.

DATA COLLECTION AND ANALYSIS

We used standard methodological procedures recommended by Cochrane to select and analyse studies in this review. The primary review outcomes were live birth and adverse events (such as depression and stress). Secondary outcomes were clinical pregnancy, pregnancy (clinical or positive urinary pregnancy test not yet confirmed by ultrasound), time to pregnancy, and quality of life. We assessed the overall quality of the evidence for the main comparisons using GRADE methods.

MAIN RESULTS

This review update included seven RCTs involving 2464 women or couples. Four of the five studies from the previous review were included in this update, and three new studies were added. We assessed the quality of the evidence as moderate to very low, the main limitations being imprecision, indirectness, and risk of bias. Urinary ovulation tests versus intercourse without ovulation prediction Compared to intercourse without ovulation prediction, urinary ovulation detection probably increases the chance of live birth in couples trying to conceive (risk ratio (RR) 1.36, 95% confidence interval (CI) 1.02 to 1.81, 1 RCT, n = 844, moderate-quality evidence). This suggests that if the chance of a live birth without urine ovulation prediction is 16%, the chance of a live birth with urine ovulation prediction is 16% to 28%. However, we are uncertain whether timed intercourse using urinary ovulation detection resulted in a difference in stress (mean difference (MD) 1.98, 95% CI -0.87 to 4.83, I² = 0%, P = 0.17, 1 RCT, n = 77, very low-quality evidence) or clinical pregnancy (RR 1.09, 95% CI 0.51 to 2.31, I² = 0%, 1 RCT, n = 148, low-quality evidence). Similar to the live birth result, timed intercourse using urinary ovulation detection probably increases the chances of clinical pregnancy or positive urine pregnancy test (RR 1.28, 95% CI 1.09 to 1.50, I² = 0, 4 RCTs, n = 2202, moderate-quality evidence). This suggests that if the chance of a clinical pregnancy or positive urine pregnancy test without ovulation prediction is assumed to be 18%, the chance following timed intercourse with urinary ovulation detection would be 20% to 28%. Evidence was insufficient to determine the effect of urine ovulation tests on time to pregnancy or quality of life. Fertility awareness-based methods (FABM) versus intercourse without ovulation prediction Due to insufficient evidence, we are uncertain whether timed intercourse using FABM resulted in a difference in live birth rate compared to intercourse without ovulation prediction (RR 0.95, 95% CI 0.76 to 1.20, I² = 0%, 2 RCTs, n = 157, low-quality evidence). We are also uncertain whether FABM affects stress (MD -1.10, 95% CI -3.88 to 1.68, 1 RCT, n = 183, very low-quality evidence). Similarly, we are uncertain of the effect of timed intercourse using FABM on anxiety (MD 0.5, 95% CI -0.52 to 1.52, P = 0.33, 1 RCT, n = 183, very low-quality evidence); depression (MD 0.4, 95% CI -0.28 to 1.08, P = 0.25, 1 RCT, n = 183, very low-quality evidence); or erectile dysfunction (MD 1.2, 95% CI -0.38 to 2.78, P = 0.14, 1 RCT, n = 183, very low-quality evidence). Evidence was insufficient to detect a benefit of timed intercourse using FABM on clinical pregnancy (RR 1.13, 95% CI 0.31 to 4.07, 1 RCT, n = 17, very low-quality evidence) or clinical or positive pregnancy test rates (RR 1.08, 95% CI 0.89 to 1.30, 3 RCTs, n = 262, very low-quality evidence). Finally, we are uncertain whether timed intercourse using FABM affects the time to pregnancy (hazard ratio 0.86, 95% CI 0.53 to 1.38, 1 RCT, n = 140, low-quality evidence) or quality of life. No studies assessed the use of timed intercourse with pelvic ultrasonography.

AUTHORS' CONCLUSIONS

The new evidence presented in this review update shows that timed intercourse using urine ovulation tests probably improves live birth and pregnancy rates (clinical or positive urine pregnancy tests but not yet confirmed by ultrasound) in women under 40, trying to conceive for less than 12 months, compared to intercourse without ovulation prediction. However, there are insufficient data to determine the effects of urine ovulation tests on adverse events, clinical pregnancy, time to pregnancy, and quality of life. Similarly, due to limited data, we are uncertain of the effect of FABM on pregnancy outcomes, adverse effects, and quality of life. Further research is therefore required to fully understand the safety and effectiveness of timed intercourse for couples trying to conceive. This research should include studies reporting clinically relevant outcomes such as live birth and adverse effects in fertile and infertile couples and utilise various methods to determine ovulation. Only with a comprehensive understanding of the risks and benefits of timed intercourse can recommendations be made for all couples trying to conceive.

Using Hormone Data and Age to Pinpoint Cycle Day within the Menstrual Cycle

Background and Objectives: Menstrual cycle tracking is essential for reproductive health and overall well-being. However, there is still an over-reliance on estimations that standard cycles are 28 days long, divided evenly between the follicular and luteal phases. Due to the variability of cycle length and cycle phase lengths, common methods of identifying where an individual is in their cycle are often inaccurate. This study used daily hormone monitoring obtained through a remote hormone-monitoring platform to evaluate hormone levels across a menstrual cycle to identify nuances in the follicular and luteal phases in individuals of different age groups. Materials and Methods: This study used a remote fertility testing system that quantitatively tracks luteinizing hormone (LH) and pregnanediol-3-glucuronide (PdG) through urine tests read by an AI-powered smartphone app. The study analyzed cycle data from 1233 users with a total of 4123 evaluated cycles. Daily levels for LH and PdG were monitored across multiple cycles. Results: This study determined that calculated cycle lengths tended to be shorter than user-reported cycle lengths. Significant differences were observed in cycle phase lengths between age groups, indicating that follicular phase length declines with age while luteal phase length increases. Finally, the study found that if an individual's age, first cycle day, and current hormone levels are known, population-level hormone data can be used to pinpoint which cycle phase and cycle day they are in with 95% confidence. Conclusions: At-home hormone monitoring technologies can allow patients and clinicians to track their cycles with greater precision than when relying on textbook estimations. The study's findings have implications for fertility planning, clinical management, and general health monitoring. Prior to this study, no standard existed for pinpointing where a person was in their cycle through only one measure of LH and PdG. These findings have the potential to fill significant gaps within reproductive healthcare and beyond.

Validation of urinary reproductive hormone measurements using a novel smartphone connected reader

Home use tests to monitor hormone trends during the menstrual cycle have been available over-the-counter for a long time. However, these tests often depend upon manual readouts and hence may lead to false analysis. Furthermore, a lot of these tests are also not quantitative. The aim of this study was to evaluate the accuracy of the quantitative home-based fertility monitor, Inito Fertility Monitor (IFM) and to use it to identify novel hormone trends in natural menstrual cycles. There were two aspects to our analysis: (i) Evaluating the efficacy of Inito Fertility Monitor in the measurement of urinary Estrone-3-glucuronide (E3G), Pregnanediol glucuronide (PdG) and Luteinizing hormone (LH), and (ii) A retrospective study of patients' hormone profiles using IFM. To evaluate the efficacy, the recovery percentage of the three hormones from IFM was evaluated using standard spiked solutions, the accuracy of measurement was calculated and the correlation between reproducible values from IFM and ELISA was established. During the validation of IFM, novel hormone trends were also observed. In order to reinforce the observations, a second group of 52 women was recruited. Assessment of the accuracy of IFM and evaluation of the volunteer urine samples was performed in a laboratory. Home assessment of hormone analysis was carried out using IFM. For the validation study, 100 women aged 21-45 years with cycle lengths ranging from 21 to 42 days were recruited. The participants had no previously diagnosed infertility conditions and their cycle lengths did not vary for more than 3 days from the expected cycle length. Daily first morning urine samples were collected from these 100 women. For the second group, 52 women were selected meeting the same criteria set for the validation study and IFM was provided to these women for testing at home. Coefficient of variation and recovery percentage of IFM with respect to laboratory based ELISA. Percentage occurrence of novel hormone trends and AUC analysis of a novel criteria identified for confirming ovulation. We observed that with all three hormones, IFM had an accurate recovery percentage. We found that the assay has an average CV of 5.05% in PdG measurement, 4.95% in E3G measurement and 5.57% in LH measurement. Furthermore, in predicting the concentration of E3G, PdG and LH in urine samples, we show that IFM has a high correlation with ELISA. In this study, we could also reproduce hormones trends across the menstrual cycle that have been observed by previous studies. We also identified a novel criterion for earlier confirmation of ovulation which could accurately distinguish ovulatory from anovulatory cycles with 100% specificity and had an area under the ROC curve of 0.98. In addition, we identified a new hormone trend which could be observed in 94.5% of the ovulatory cycles. The Inito Fertility Monitor is an effective tool for calculating the urinary concentrations of E3G, PdG and LH and can also be used to provide accurate fertility scores and confirm ovulation. We show that certain hormone trends associated with urinary E3G, PdG and LH could be accurately captured using IFM. In addition, we report a novel criterion for earlier confirmation of ovulation compared to existing criteria. Finally, we present a novel hormone pattern associated with most of the menstrual cycles by examining hormone profiles from the volunteers recruited for the clinical trial.Trial registration: The trial is registered at the current controlled trials ISRCTN registry #ISRCTN15534557.

Complete Cycle Mapping Using a Quantitative At-Home Hormone Monitoring System in Prediction of Fertile Days, Confirmation of Ovulation, and Screening for Ovulation Issues Preventing Conception

Background and Objectives: To achieve pregnancy, it is highly beneficial to identify the time of ovulation as well as the greater period of fertile days during which sperm may survive leading up to ovulation. Confirming successful ovulation is also critical to accurately diagnose ovulatory disorders. Ovulation predictor kits, fertility monitors, and tracking apps are all available to assist with detecting ovulation, but often fall short. They may not detect the full fertile window, provide accurate or real-time information, or are simply expensive and impractical. Finally, few over-the-counter products provide information to women about their ovarian reserve and future fertility. Therefore, there is a need for an easy, over-the-counter, at-home quantitative hormone monitoring system that assesses ovarian reserve, predicts the entire fertile window, and can screen for ovulatory disorders. Materials and Methods: Proov Complete is a four-in-one at-home multihormone testing system that utilizes lateral flow assay test strips paired with the free Proov Insight App to guide testing of four hormones-FSH, E1G, LH, and PdG-across the woman's cycle. In a pilot study, 40 women (including 16 with a fertility-related diagnosis or using fertility treatments) used Complete for one cycle. Results: Here, we demonstrate that Proov Complete can accurately and sensitively predict ovarian reserve, detect up to 6 fertile days and confirm if ovulation was successful, in one easy-to-use kit. Ovulation was confirmed in 38 cycles with a detectable PdG rise. An average of 5.3 fertile days (from E1G rise to PdG rise) were detected, with an average of 2.7 days prior to LH surge. Ovulation was confirmed via PdG rise an average of 2.6 days following the LH surge. While 38/40 women had a PdG rise, only 22 had a sustained PdG level above 5 μg/mL throughout the critical implantation window, indicating ovulatory dysfunction in 16 women. Conclusions: Proov Complete can detect the entire fertile window of up to 6 fertile days and confirm ovulation, while also providing information on ovarian reserve and guidance to clinicians and patients.

Pregnancy resumption following contraceptive discontinuation: Hazard survival analysis of the Indonesia Demographic and Health Survey Data 2007, 2012 and 2017

Objective

The objective of this research is to estimate the probability of pregnancy resumption after discontinuing reversible contraceptives—pills, injectables, implants and IUDs, and to examine the factors associated with the resumption of fertility.

Method

The study uses pregnancy calendar data from Indonesia Demographic and Health Surveys (IDHS) of 2007, 2012 and 2017. A hazard model survival method is used for estimating the time needed to resume pregnancy since discontinuing reversible contraceptives. Retrospective data on 4,573; 5,183 and 5,989 episodes of reversible contraceptive discontinuation at the three surveys respectively have been analysed.

Results

This study shows that women regained fecundity within one year of discontinuing IUD, pill, injectables or implants. Women using IUD could resume their pregnancy faster than those using implants, pills and injectables. Over the three IDHS 2007, 2012 and 2017 the age-specific percentages of women becoming pregnant after one year of contraceptive discontinuation vary between 72 and 85 for IUD, 75 and 81 for pills, 72 and 76 for implants and 64 and 67 for injectables, with the percentages being higher among younger women. The analysis further shows that length of contraceptive use, parity, prior sexually transmitted infections, knowledge of fertile period, household wealth status and place of residence have no impact on occurrence of pregnancy after contraceptive discontinuation.

Conclusion

The analysis disproves a myth that reversible contraceptives make women infertile. Depending on the type of reversible contraceptive used, 65% to 85% of the women were able to conceive after one year of discontinuation.

Increased Chance of Live Birth Following Use of Connected Ovulation Test System: Outcome Results from a Randomized Controlled Trial

Background: Natural conception requires intercourse to occur during the fertile window of a woman's menstrual cycle. This follow-up study of a randomized controlled trial aimed to determine whether the use of a urine ovulation test system, which tracks elevations in both luteinizing hormone and an estradiol metabolite, increases the likelihood of live births in women trying to conceive.

Materials and Methods: In the home-based trial, 844 women aged 18–40 years who were attempting to conceive were randomized 1:1 into the test or control arms. Volunteers participated for up to two full cycles and conducted digital pregnancy tests, collected urine samples, and kept a menstrual diary to determine pregnancy status. In this follow-up, all pregnant volunteers were asked to complete a form on final pregnancy outcome.

Results: Overall, 247 (29.3%) of the 844 volunteers reported a pregnancy; final outcome data were available for 198 pregnancies. For cycle one, the live birth rate was 16.4% for the test group and 8.5% for the control group (odds ratio: 2.12; 95% confidence interval [CI]: 1.34–3.35; p = 0.001). For cycles one and two combined, the live birth rate was 24.5% and 17.5% for the test and control groups, respectively (odds ratio: 1.53; 95% CI: 1.07–2.19; p = 0.023). The proportion of miscarriages was not significantly different between both groups and 78% of pregnancies resulted in a live birth.

Conclusions: The increased conception rate observed following the use of the Clearblue Connected Ovulation Test System was found to translate into an increased live birth rate.

Clinical Trial Registration number: NCT03424590.

Real-life insights on menstrual cycles and ovulation using big data

STUDY QUESTION

What variations underlie the menstrual cycle length and ovulation day of women trying to conceive?

SUMMARY ANSWER

Big data from a connected ovulation test revealed the extent of variation in menstrual cycle length and ovulation day in women trying to conceive.

WHAT IS KNOWN ALREADY

Timing intercourse to coincide with the fertile period of a woman maximises the chances of conception. The day of ovulation varies on an inter- and intra-individual level.

STUDY DESIGN, SIZE, DURATION

A total of 32 595 women who had purchased a connected ovulation test system contributed 75 981 cycles for analysis. Day of ovulation was determined from the fertility test results. The connected home ovulation test system enables users to identify their fertile phase. The app benefits users by enabling them to understand their personal fertility information. During each menstrual cycle, users input their perceived cycle length into an accessory application, and data on hormone levels from the tests are uploaded to the application and stored in an anonymised cloud database. This study compared users’ perceived cycle characteristics with actual cycle characteristics. The perceived and actual cycle length information was analysed to provide population ranges.

PARTICIPANTS/MATERIALS, SETTING, METHODS

This study analysed data from the at-home use of a commercially available connected home ovulation test by women across the USA and UK.

MAIN RESULTS AND THE ROLE OF CHANCE

Overall, 25.3% of users selected a 28-day cycle as their perceived cycle length; however, only 12.4% of users actually had a 28-day cycle. Most women (87%) had actual menstrual cycle lengths between 23 and 35 days, with a normal distribution centred on day 28, and over half of the users (52%) had cycles that varied by 5 days or more. There was a 10-day spread of observed ovulation days for a 28-day cycle, with the most common day of ovulation being Day 15. Similar variation was observed for all cycle lengths examined. For users who conducted a test on every day requested by the app, a luteinising hormone (LH) surge was detected in 97.9% of cycles.

LIMITATIONS, REASONS FOR CAUTION

Data were from a self-selected population of women who were prepared to purchase a commercially available product to aid conception and so may not fully represent the wider population. No corresponding demographic data were collected with the cycle information.

WIDER IMPLICATIONS OF THE FINDINGS

Using big data has provided more personalised insights into women’s fertility; this could enable women trying to conceive to better time intercourse, increasing the likelihood of conception.

STUDY FUNDING/COMPETING INTERESTS

The study was funded by SPD Development Company Ltd (Bedford, UK), a fully owned subsidiary of SPD Swiss Precision Diagnostics GmbH (Geneva, Switzerland). I.S., B.G. and S.J. are employees of the SPD Development Company Ltd.

Increased Likelihood of Pregnancy Using an App-Connected Ovulation Test System: A Randomized Controlled Trial

Background: Women trying to conceive are increasingly using fertility-tracking software applications to time intercourse. This study evaluated the difference in conception rates between women trying to conceive using an application-connected ovulation test system, which measures urinary luteinizing hormone and an estrogen metabolite, versus those trying without using ovulation testing.

Materials and Methods: This home-based study involved 844 volunteers aged 18–40 years seeking to conceive. Volunteers randomized to the test arm were required to use the test system for the duration of the study while those randomized to the control arm were instructed not to use ovulation testing. Pregnancy rate differences across one and two cycles between the two groups were examined.

Results: Volunteers in the test (n = 382) and control arms (n = 403) had similar baseline demographics. The proportion of women pregnant after one cycle was significantly greater in the test arm (25.4%) compared with the control arm (14.7%; p < 0.001). After two cycles, there continued to be a greater proportion of women pregnant in the test arm compared with the control arm (36.2% vs. 28.6%; p = 0.026). In the test arm, volunteers had intercourse less frequently per cycle compared with those not using ovulation testing (9 [range: 1–60] vs. 10 [range: 1–50]; p = 0.027), but were more likely to target intercourse to a particular part of their cycle compared with those not using ovulation testing (88.5% vs. 57.8%; p < 0.001).

Conclusion: Using the test system to time intercourse within the fertile window increases the likelihood of conceiving within two menstrual cycles.

Can apps and calendar methods predict ovulation with accuracy?

OBJECTIVE

The accuracy of prediction of ovulation by cycle apps and published calendar methods was determined by comparing to true probability of ovulation.

METHODS

A total of 949 volunteers collected urine samples for one entire menstrual cycle. Luteinizing hormone was measured to assign surge day, enabling probability of ovulation to be determined across different cycle lengths. Cycle-tracking apps were downloaded. As none provided their methodology, four published calendar-based methods were also examined: standard days, rhythm, alternative rhythm and simple calendar method. The volunteer ovulation data was applied to the app/calendar methods to determine their accuracy.

RESULTS

Mean cycle length was 28 days (range: 23-35); 34% of women believed they had a 28-day cycle, but only 15% did. No LH surge was seen for 99 women. Most likely day of ovulation for a 28-day cycle was day 16 (21%). Accuracy of ovulation prediction was no better than 21% by the apps. The standard days and rhythm methods were most likely to predict ovulation (70% and 89%, respectively) but had very low accuracy.

CONCLUSIONS

Ovulation day varies considerably for any given menstrual cycle length, thus it is not possible for calendar/app methods that use cycle-length information alone to accurately predict the day of ovulation. National Clinical Trial Code: NCT01577147. Registry website: www.clinicaltrials.gov .

Oral contraceptives modulate the muscle metaboreflex in healthy young women

There are known sex differences in blood pressure regulation. The differences are related to ovarian hormones that influence β-adrenergic receptors and the transduction of muscle sympathetic nerve activity. Oral contraceptives (OC) modulate the ovarian hormonal profile in women and therefore may alter the cardiovascular response. We questioned if OC would alter the absolute pressor response to static exercise and influence the day-to-day variability of the response. Healthy men (n = 11) and women (n = 19) completed a familiarization day and 2 experimental testing days. Women were divided into those taking (W-OC, n = 10) and not taking (W-NC, n = 9) OC. Each experimental testing day involved isometric handgripping exercise, at 30% of maximal force, followed by circulatory occlusion to isolate the metaboreflex. Experimental days in men were 7-14 days apart. The first experimental testing in W-OC occurred 2-7 days after the start of the active phase of their OC. Women not taking OC were tested during the early and late follicular phase of the menstrual cycle as determined by commercial ovulation monitor. The increase in mean arterial pressure (MAP) during exercise was significantly lower in W-NC (95 ± 4 mm Hg) compared with men (114 ± 4 mm Hg) and W-OC (111 ± 3 mm Hg) (P < 0.05), with the differences preserved during circulatory occlusion. The rise in MAP was significantly correlated between the 2 testing days in men (r = 0.72, P < 0.01) and W-OC (r = 0.77, P < 0.05), but not in W-NC (r = 0.17, P = 0.67), indicating greater day-to-day variation in W-NC. In conclusion, OC modulate the exercise pressor response in women and minimize day-to-day variability in the exercise metaboreflex.

Women's experiences of ovulation testing: a qualitative analysis

Background

The introduction of home digital ovulation tests (OTs) has provided a simple solution for women wishing to optimise the timing of intercourse when trying to conceive. However, despite this, very little is understood about women’s experiences of using these tests.

Methods

We carried out qualitative, semi-structured telephone interviews with women who were seeking to conceive (not actively undergoing clinical investigation/fertility treatment) from the general UK population. The interviews were conducted following participation in a randomised controlled trial (RCT) in which participants were either provided with digital home OTs to assist in timing intercourse (n = 18) or advised to have intercourse every 2–3 days (n = 18). The interviews were digitally recorded, transcribed and then analysed using Framework analysis to identify the themes.

Results

Data saturation was reached after 36 interviews. The use of the OT appeared to elicit 10 key themes, which could be described within the context of three overarching issues: 1) a positive impact (understanding the menstrual cycle, confirming when ovulating, emotional support, improving the relationship), 2) a negative impact (changing sex life and relationship with their partner, the emotional consequences of prolonged use, questions and uncertainty about what their results mean for them) and 3) the experiences of trying to conceive in general (use of clinical guidance and emotional experience).

Conclusions

Overall, the use of home OTs were found to affect women’s thoughts and feelings in multiple ways during attempts to conceive. Although some women reported a range of negative experiences when using OTs, they also reported similar negative experiences when trying to conceive without using the tests. However, there were many positive themes associated with OT use, including an increased understanding of the menstrual cycle, confirmation of ovulation timing and providing a source of help and support when trying to conceive. Overall, when women are trying to conceive, ensuring they have access to high-quality information, including use of OT, may be of benefit to help address some of the questions and uncertainties that were raised by the participants in this study.

Trial registration number

NCT01084304

Electronic supplementary material

The online version of this article (doi:10.1186/s12978-015-0103-y) contains supplementary material, which is available to authorized users.

Self-identification of the clinical fertile window and the ovulation period

OBJECTIVE

To assess the sensitivity and specificity of the self-identified fertile window.

DESIGN

Observational study.

SETTING

Not applicable.

PATIENT(S)

A total of 107 women.

INTERVENTION(S)

Women recorded cervical mucus observation and basal body temperature daily while undergoing daily ovarian ultrasound.

MAIN OUTCOME MEASURE(S)

The biological fertile window, defined as the 6 days up to and including the day of ovulation; and the 2-day ovulation window, defined as the day before and the day of ovulation.

RESULT(S)

The self-identification of the biological fertile window by the observation of any type of cervical mucus provides 100% sensitivity but poor specificity, yielding a clinical fertile window of 11 days. However, the identification of the biological fertile window by peak mucus (defined as clear, slippery, or stretchy mucus related to estrogen) yielded 96% sensitivity and improved specificity. The appearance of the peak mucus preceded the biological fertile window in less than 10% of the cycles. Likewise, this type of mucus identified the ovulation window with 88% sensitivity.

CONCLUSION(S)

These results suggest that, when perceived accurately, more accurate clinical self-detection of the fertile window can be obtained by identification of peak mucus. This may improve efforts to focus intercourse in the fertile phase for couples with fertility concerns.

Knowledge, attitudes, and practices regarding conception and fertility: a population-based survey among reproductive-age United States women

OBJECTIVE

To assess overall knowledge, attitudes, and practices related to conception and fertility among reproductive-age women in the United States.

DESIGN

Online survey of a cross-sectional sample of 1,000 women.

SETTING

United States, March 2013.

PATIENT(S)

Women aged 18-40 years.

INTERVENTION(S)

None.

MAIN OUTCOME MEASURE(S)

Knowledge, attitudes, and practices regarding selected topics in reproductive health.

RESULT(S)

Forty percent of women across all age groups expressed concerns about their ability to conceive. Yet one-third of women were unaware of adverse implications of sexually transmitted infections, obesity, or irregular menses for procreative success, and one-fifth were unaware of the effects of aging. Approximately 40% were unfamiliar with the ovulatory cycle. Overall, younger women (18-24 years) demonstrated less knowledge regarding conception, fertility, and ovulation, whereas older women tended to believe in common myths and misconceptions. Respondents in all age groups identified women's health care providers (75%) and Web sites (40%) as top sources of reproductive health-related information; however, engagement with providers on specific factors affecting fertility is sparse.

CONCLUSION(S)

Knowledge regarding ovulation, fertility, and conception is limited among this sample of reproductive-age US women. Future initiatives should prioritize improved provider engagement and accurate information dissemination in Web-based venues.

Pilot test and validation of the peak day method of prospective determination of ovulation against a handheld urine hormone monitor

Background

Transient exposures may influence fertility and early embryonic development. To assess the time of conception in vivo and conduct concurrent biomonitoring, ovulation must be identified prospectively. We report on the development and validation of a simple, prospective method, the Peak Day method, to determine likely day of ovulation based upon daily observations of cervical fluid.

Methods

We recruited 98 women to learn the Peak Day method from a brochure, 26 of whom concurrently used the method with blinded daily urine hormone monitoring (estrone glucuronide and luteinizing hormone). All women were instructed to complete an exposure questionnaire immediately upon identifying ovulation. Briefly, the exposure questionnaire captured time-varying and transient exposures such as medication use, water consumption, and amount of sleep. We assessed timely completion of the exposure questionnaire, agreement of women’s estimated day of ovulation (EDO) and the EDO by expert review, and agreement between the EDO by expert review and by blinded urine monitoring.

Results

Of 147 cycles evaluated, women selected an EDO in 130 (88%) and subsequently completed the periovulatory exposure questionnaire in 122 (94%) cycles. Of the 26 cycles evaluated with blinded hormonal monitoring, the Peak Day “best quality” algorithm, based upon cervical fluid, identified ovulation ± 3 days of the urine monitor in 24 cycles (92%).

Conclusions

With simple written instructions, women can identify an estimated day of ovulation and perform periovulatory exposure assessment. The Peak Day method is highly cost-effective and could be applied by researchers to target periconceptional or very early developmental stage exposure assessment.

Home ovulation tests and stress in women trying to conceive: a randomized controlled trial

STUDY QUESTION

Does the use of a digital home ovulation test have any effect on the level of stress in women seeking to conceive?

SUMMARY ANSWER

No difference was found in levels of stress between women using digital ovulation tests to time intercourse compared with women who were trying to conceive without any additional aids: in addition, their use did not negatively impact time to conception in users but may provide additional benefits, including an increased understanding of the menstrual cycle, reassurance and confidence in focusing conception attempts to the correct time in the cycle.

WHAT IS KNOWN ALREADY

It has been suggested that timing of intercourse in such a way that it coincides with ovulation by using ovulation tests can lead to emotional distress; however, no study has been conducted to investigate this hypothesis specifically, until now.

STUDY DESIGN, SIZE AND DURATION

The study was performed over two complete menstrual cycles as a prospective, randomized, controlled trial including quantitative and qualitative methods. The intervention (test) group were given digital ovulation tests to time intercourse to the most fertile time of the cycle and the control group were provided with the current National Institute for Health and Clinical Excellence guidelines for increasing the chances of conception (intercourse every 2-3 days) and asked not to use any additional methods to time when ovulation occurs.

PARTICIPANTS/MATERIALS, SETTING AND METHODS

A total of 210 women who were seeking to conceive were recruited from the general UK population. A total of 115 women were randomized to the test group and 95 to the control group through block randomization. The positive and negative affect schedule (PANAS) and the Perceived Stress Scale (PSS) were used to measure subjective stress levels, the Short-Form 12 health survey was used as a measure of general health and well-being and urine samples were measured for biochemical markers of stress including urinary cortisol. Qualitative data were collected in the form of a telephone interview upon study completion.

MAIN RESULTS AND THE ROLE OF CHANCE

There was no evidence for a difference either in total stress as measured using the PSS or in total positive or negative affect using the PANAS questionnaire between the test and control groups at any time point for the duration of the study. During cycle 1, for example, on Day 6, the difference in total stress score (test-control) was -0.62 [95% confidence interval (CI) -2.47 to 1.24] and on the day of the LH surge, it was 0.53 (95% CI -1.38 to 2.44). In addition, no correlation was observed between time trying to conceive and levels of stress, or between age and levels of stress, and no evidence was found to show that stress affected whether or not a pregnancy was achieved. There is also no evidence that the biochemistry measurements are related to whether a pregnancy was achieved or of a difference in biochemistry between the treatment groups. The use of digital ovulation tests did not negatively affect time to conception and with an adequately sized study, could potentially show improvement. To ensure that the results of this study were not affected by chance, we used a number of different methods for measuring stress, each of which had been independently validated.

LIMITATIONS AND REASONS FOR CAUTION

Randomization occurred before the start of the study because of the need to provide the ovulation tests in readiness for Day 6 of the first cycle. As a consequence, a number of women fell pregnant during this period (22 and 13 in the test and control groups, respectively). A further 15 women were either lost to follow-up or withdrew consent prior to study start. Pregnancy rate was higher overall in the test group, so to ensure that there were sufficient data from women who failed to become pregnant in the test group, we implemented an additional biased recruitment. This second cohort may have been different from the first, although no significant differences were observed between the two phases of recruitment for any of the information collected upon admission to the study.

WIDER IMPLICATIONS OF THE FINDINGS

Women who seek medical advice while trying to conceive should not be discouraged by health care professionals from using digital ovulation tests in order to time intercourse. The cohort of women recruited to this study initially had no evidence of infertility and were looking to conceive in a non-medical setting. A separate study to assess the impact of home ovulation tests in a subfertile population would be of interest and complementary to the present study.

STUDY FUNDING/COMPETING INTERESTS

This study was funded by SPD Swiss Precision Diagnostics, GmbH, manufacturer of Clearblue(®) pregnancy and ovulation tests. SPD Development Company Ltd is a wholly owned subsidiary of SPD Swiss Precision Diagnostics GmbH; together referred to as SPD.

TRIAL REGISTRATION NUMBER

NCT01084304 (www.clinicaltrials.gov).