ArticleReproductive health2018
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.
Article in Reproductive health, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It has been retracted, and should not be counted. Cited by 6 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
6 citing papers in PubMed, 20 citations in OpenAlex.
- Reliability of Cycle Applications for Pregnancy Planning and Contraception: A Systematic Review.Mayo Clinic proceedings. Digital health · 2025Review
- Advances in Precision Health and Emerging Diagnostics for Women.Journal of clinical medicine · 2019Review
- Clarifications concerning the commentary "Published analysis of contraceptive effectiveness of Daysy and DaysyView app is fatally flawed".Reproductive health · 2019Article
- Retraction Note: 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.Reproductive health · 2019Article
- Article
- Published analysis of contraceptive effectiveness of Daysy and DaysyView app is fatally flawed.Reproductive health · 2018Article
Corrections and comments
- Retraction · 2019-05-14Error in Analyses · Error in Methods · Objections by Author(s) · Unreliable Results and/or Conclusions ·
- Retracted
Authors and funding
14 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDaysy 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.
resultIn 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.
conclusionIt 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.