Improving usability and pregnancy rates of a fertility monitor by an additional mobile application: results of a retrospective efficacy study of Daysy and DaysyView app

Reprod Health. 2018 Mar 2;15(1):37. doi: 10.1186/s12978-018-0479-6.

Abstract

Background: Daysy is a fertility monitor that uses the fertility awareness method by tracking and analyzing the individual menstrual cycle. In addition, Daysy can be connected to the application DaysyView to transfer stored personal data from Daysy to a smartphone or tablet (IOS, Android). This combination is interesting because as it is shown in various studies, the use of apps is increasing patients´ focus on their disease or their health behavior. The aim of this study was to investigate if by the additional use of an App and thereby improved usability of the medical device, it is possible to enhance the typical-use related as well as the method-related pregnancy rates.

Result: In the resultant group of 125 women (2076 cycles in total), 2 women indicated that they had been unintentionally pregnant during the use of the device, giving a typical-use related Pearl-Index of 1.3. Counting only the pregnancies which occurred as a result of unprotected intercourse during the infertile (green) phase, we found 1 pregnancy, giving a method-related Pearl-Index of 0.6. Calculating the pregnancy rate resulting from continuous use and unprotected intercourse exclusively on green days, gives a perfect-use Pearl-Index of 0.8.

Conclusion: It seems that combining a specific biosensor-embedded device (Daysy), which gives the method a very high repeatable accuracy, and a mobile application (DaysyView) which leads to higher user engagement, results in higher overall usability of the method.

Keywords: Body basal temperature; FABM; Female contraception; Fertility awareness based method; Fertility monitor; Mobile application.

Publication types

  • Retracted Publication

MeSH terms

  • Adult
  • Female
  • Fertility / physiology*
  • Humans
  • Mobile Applications*
  • Ovulation Detection / methods*
  • Pregnancy
  • Pregnancy Rate*
  • Retrospective Studies
  • Smartphone / statistics & numerical data*