{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,14]],"date-time":"2026-10-14T18:59:34Z","timestamp":1792004374290,"version":"4.4.0"},"reference-count":36,"publisher":"Oxford University Press (OUP)","issue":"10","license":[{"start":{"date-parts":[[2020,9,10]],"date-time":"2020-09-10T00:00:00Z","timestamp":1599696000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000071","name":"National Institute of Child Health and Human Development","doi-asserted-by":"publisher","id":[{"id":"10.13039\/100000071","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,10,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>STUDY QUESTION<\/jats:title>\n                    <jats:p>To what extent does the use of mobile computing apps to track the menstrual cycle and the fertile window influence fecundability among women trying to conceive?<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>SUMMARY ANSWER<\/jats:title>\n                    <jats:p>After adjusting for potential confounders, use of any of several different apps was associated with increased fecundability ranging from 12% to 20% per cycle of attempt.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>WHAT IS KNOWN ALREADY<\/jats:title>\n                    <jats:p>Many women are using mobile computing apps to track their menstrual cycle and the fertile window, including while trying to conceive.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>STUDY DESIGN, SIZE, DURATION<\/jats:title>\n                    <jats:p>The Pregnancy Study Online (PRESTO) is a North American prospective internet-based cohort of women who are aged 21\u201345 years, trying to conceive and not using contraception or fertility treatment at baseline.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>PARTICIPANTS\/MATERIALS, SETTING, METHODS<\/jats:title>\n                    <jats:p>We restricted the analysis to 8363 women trying to conceive for no more than 6 months at baseline; the women were recruited from June 2013 through May 2019. Women completed questionnaires at baseline and every 2 months for up to 1 year. The main outcome was fecundability, i.e. the per-cycle probability of conception, which we assessed using self-reported data on time to pregnancy (confirmed by positive home pregnancy test) in menstrual cycles. On the baseline and follow-up questionnaires, women reported whether they used mobile computing apps to track their menstrual cycles (\u2018cycle apps\u2019) and, if so, which one(s). We estimated fecundability ratios (FRs) for the use of cycle apps, adjusted for female age, race\/ethnicity, prior pregnancy, BMI, income, current smoking, education, partner education, caffeine intake, use of hormonal contraceptives as the last method of contraception, hours of sleep per night, cycle regularity, use of prenatal supplements, marital status, intercourse frequency and history of subfertility. We also examined the impact of concurrent use of fertility indicators: basal body temperature, cervical fluid, cervix position and\/or urine LH.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>MAIN RESULTS AND THE ROLE OF CHANCE<\/jats:title>\n                    <jats:p>Among 8363 women, 6077 (72.7%) were using one or more cycle apps at baseline. A total of 122 separate apps were reported by women. We designated five of these apps before analysis as more likely to be effective (Clue, Fertility Friend, Glow, Kindara, Ovia; hereafter referred to as \u2018selected apps\u2019). The use of any app at baseline was associated with 20% increased fecundability, with little difference between selected apps versus other apps (selected apps FR (95% CI): 1.20 (1.13, 1.28); all other apps 1.21 (1.13, 1.30)). In time-varying analyses, cycle app use was associated with 12\u201315% increased fecundability (selected apps FR (95% CI): 1.12 (1.04, 1.21); all other apps 1.15 (1.07, 1.24)). When apps were used at baseline with one or more fertility indicators, there was higher fecundability than without fertility indicators (selected apps with indicators FR (95% CI): 1.23 (1.14, 1.34) versus without indicators 1.17 (1.05, 1.30); other apps with indicators 1.30 (1.19, 1.43) versus without indicators 1.16 (1.06, 1.27)). In time-varying analyses, results were similar when stratified by time trying at study entry (&amp;lt;3 vs. 3\u20136 cycles) or cycle regularity. For use of the selected apps, we observed higher fecundability among women with a history of subfertility: FR 1.33 (1.05\u20131.67).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>LIMITATIONS, REASONS FOR CAUTION<\/jats:title>\n                    <jats:p>Neither regularity nor intensity of app use was ascertained. The prospective time-varying assessment of app use was based on questionnaires completed every 2 months, which would not capture more frequent changes. Intercourse frequency was also reported retrospectively and we do not have data on timing of intercourse relative to the fertile window. Although we controlled for a wide range of covariates, we cannot exclude the possibility of residual confounding (e.g. choosing to use an app in this observational study may be a marker for unmeasured health habits promoting fecundability). Half of the women in the study received a free premium subscription for one of the apps (Fertility Friend), which may have increased the overall prevalence of app use in the time-varying analyses, but would not affect app use at baseline. Most women in the study were college educated, which may limit application of results to other populations.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>WIDER IMPLICATIONS OF THE FINDINGS<\/jats:title>\n                    <jats:p>Use of a cycle app, especially in combination with observation of one or more fertility indicators (basal body temperature, cervical fluid, cervix position and\/or urine LH), may increase fecundability (per-cycle pregnancy probability) by about 12\u201320% for couples trying to conceive. We did not find consistent evidence of improved fecundability resulting from use of one specific app over another.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>STUDY FUNDING\/COMPETING INTEREST(S)<\/jats:title>\n                    <jats:p>This research was supported by grants, R21HD072326 and R01HD086742, from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, USA. In the last 3 years, Dr L.A.W. has served as a fibroid consultant for AbbVie.com. Dr L.A.W. has also received in-kind donations from Sandstone Diagnostics, Swiss Precision Diagnostics, FertilityFriend.com and Kindara.com for primary data collection and participant incentives in the PRESTO cohort. Dr J.B.S. reports personal fees from Swiss Precision Diagnostics, outside the submitted work. The remaining authors have nothing to declare.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>TRIAL REGISTRATION NUMBER<\/jats:title>\n                    <jats:p>N\/A.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1093\/humrep\/deaa176","type":"journal-article","created":{"date-parts":[[2020,7,13]],"date-time":"2020-07-13T15:13:13Z","timestamp":1594653193000},"page":"2245-2252","source":"Crossref","is-referenced-by-count":39,"title":["Fecundability in relation to use of mobile computing apps to track the menstrual cycle"],"prefix":"10.1093","volume":"35","author":[{"given":"Joseph B","family":"Stanford","sequence":"first","affiliation":[{"name":"Office of Cooperative Reproductive Health, Division of Public Health, Department of Family and Preventive Medicine, University of Utah, Salt Lake City, UT, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sydney 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