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

Abstract

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).

Figures

Figure 1

Schedule of events and numbers of volunteers at each time point during the study. In total, 354 women were able to be contacted to participate in the study. Of those, 255 volunteers were eligible to participate and 45 did not return their consent. This left a final study population of 210. Reasons for withdrawal from the study include: no longer trying to conceive (n = 6), unable to carry out the study (n = 4), health reasons (n = 10), protocol violation (n = 3), unwanted randomization to the control group (n = 2) and no reason given (n = 2). LTFU, lost to follow-up (n = 19). *1 volunteer did not provide complete data prior to randomization. Day of predicted ovulation for the control group was based on self-reported average cycle length information collected upon admission to the study.

Figure 2

Kaplan–Meier estimate of time to conception for all volunteers recruited to the study with 95% confidence limits represented by the pink and blue areas surrounding the lines. Time to conception is based on time from recruitment to the study. Censored data indicate women who are lost to follow-up, for any reason, at the time indicated. Numbers at risk in each randomization group are given along the x-axis. Attrition of volunteers is due either to achieving a pregnancy or to completion of study.

Figure 3

Kaplan–Meier estimate of time to conception for volunteers excluding those that exited the study prior to Cycle 1. The 95% confidence limits are represented by the pink and blue areas surrounding the lines. Time to conception is based on time from recruitment to the study. Censored data indicate women who are lost to follow-up, for any reason, at the time indicated. Numbers at risk in each randomization group are given along the x-axis. Attrition of volunteers is due either to achieving a pregnancy or to completion of study.

Figure 4

Loadings plot based on PCA fitted to all the data including all the questionnaires, biochemical markers and demographic characteristics. Principal component 1 (x-axis) relates to the trends observed between the positive and negative questions/responses from the PANAS and PSS questionnaires and principal component 2 (y-axis) is related to the positive and negative questions/responses from the SF-12 questionnaire. Two measurements that are close to each other are positively correlated and measurements that are diagonally opposite each other are negatively correlated. Clear separation is evident between the positive and negative responses to the PANAS questionnaire (purple and yellow dots, respectively) and to the PSS questionnaire as depicted by the two populations of orange dots observed. Bioc: Biochemistry marker, Demo: Demographic characteristic, Pos: Positive and Negative Affect Schedule (PANAS) Positive affect, Neg: PANAS: Negative affect, PSS: Perceived Stress Scale (PSS) Total Stress, Ment: Short Form 12 (SF12) Mental, Phys: SF12 Physical, SF12 Total score. On graph: Individual questions colour coded according to questionnaire, otherwise as indicated, Try Conceive: length in time trying to conceive (months), Pre-Study: length of pre-study period (days), BMI; Body Mass Index, Cre: Creatinine (g/dl), Cor: Cortisol (μg/dl), E3G: Estrone-3-Glucuronide (ng/ml), ECR: E3G:Creatinine ratio, CCR: Cortisol:Creatinine ratio.

Figure 5

Loadings plot based on PCA fitted to all the data except individual questions and focusing on biochemical markers. Principal component 1 (x-axis) relates to the stress score and principal component 2 (y-axis) relates to the correlations between biochemical markers. Two measurements that are close to each other are positively correlated and measurements that are diagonally opposite each other are negatively correlated. The biochemistry data (green dots) are grouped close to the centre of the plot showing that there is no clear separation either between the two randomization groups or between the study outcomes. Bioc: Biochemistry marker, Demo: Demographic characteristic, Pos: Positive and Negative Affect Schedule (PANAS) Positive affect, Neg: PANAS: Negative affect, PSS: Perceived Stress Scale (PSS) Total Stress, Ment: Short Form 12 (SF12) Mental, Phys: SF12 Physical, SF12 Total score. On graph: Tot: Total score colour coded according to questionnaire, otherwise as indicated, Try Conceive: length in time trying to conceive (months), Pre-Study: length of pre-study period (days), BMI; Body Mass Index, Cre: Creatinine (g/dl), Cor: Cortisol (μg/dl), E3G: Estrone-3-Glucuronide (ng/ml), ECR: E3G:Creatinine ratio, CCR: Cortisol:Creatinine ratio.