Understanding how one’s body and cycle works can be a very empowering experience. While Take Charge of Your Fertility (TCOYF) is a great book to get further insight and learning about how the body works and how to track fertility parameters, such as how cervical mucus changes throughout the cycle, it is very different from Natural Cycles in many ways.
TCOYF “rules”
In the book, TCOYF provides “rules” to follow in order to take charge of one’s fertility. They are slightly modified from the so-called Symptothermal method (STM), which combines cervical mucus tracking with basic, manual temperature tracking.
Symptothermal method limitations
The symptothermal method has a high risk of error for two reasons:
- Establishing whether one is fertile or not in the beginning of the cycle solely based on cervical mucus requires a lot of training and is a big responsibility on the woman, which increases the risk of error.
- The rudimentary rules to determine a temperature shift is highly error-prone and does not take statistics or previous cycles into account. It relies on single temperature values, which is not reliable as many things can affect a single night’s reading. This is a problematic area to get wrong as the potential of mistaking highly fertile days near or during ovulation is high.
Symptothermal method effectiveness
In general, the effectiveness of the TCOYF rules has never been clinically validated. The book refers to the Contraceptive Technology book and claims based on this that the Symptothermal method’s effectiveness of 2% typical use failure rate, which is based on a single German study. This is misleading and taken out of context. TCOYF omits the fact that the Contraceptive Technology book also mentions that in addition to the German study “multiple other studies generated substantially higher estimates, up to 33% for typical use”. The Contraceptive Technology book also states that “We find the results for the symptothermal method (study conducted in Germany) unbelievable, although we cannot identify any errors in study design or analysis.”
Reading the German study in more detail reveals that the women in the study had to take a 3 month long in-person course before they entered the study. This means that the participants of the study were highly trained on the method as well as highly dedicated and are a poor example of real-life situations. This is confirmed by the very low rate of women having unprotected intercourse on days marked as fertile in the study, which is different from what we see among our users in real life. The study also excludes women that have irregular cycles for instance. The slightly modified rules in the TCOYF book have never been studied.
Natural Cycles’ Algorithm
Natural Cycles is different from TCOYF as its algorithm learns over time and adopts to each woman’s unique cycle.
Natural Cycles effectiveness
With Natural Cycles algorithm being cleared as a medical device for birth control both by the FDA in the US and in Europe, rigorous prospective clinical studies have been performed to establish the effectiveness among all types of cohorts. Natural Cycles algorithm’s method failure is 0.5%, while the perfect use effectiveness was shown to be 98-99% (1-2% failure rate) and the typical use effectiveness is 93% (7% failure rate). The FDA confirmed after a lot of scrutiny that Natural Cycles is as effective for women with irregular cycles as regular ones.
Other differences between Natural Cycles & TCOYF
- While TCOYF is a book, Natural Cycles comes in the form of an app - allowing us to monitor the effectiveness on a monthly basis, which is also part of our post-market follow up as a medical device.
- The TCOYF states that if one only uses temperature and not cervical mucus one should not trust pre-ovulatory non-fertile (green) days as one cannot predict ovulation in advance based on temperature only. Although the last part is true, Natural Cycles algorithm learns from a users individual cycle pattern with time and has a generous buffer before ovulation day, taking the cycle irregularities into account. The algorithm is optimized to have the same pregnancy risk for early-cycle non-fertile green days and late-cycle green days (after a patch of red). This takes into account that the fertility rate 4 or 5 days before ovulation is low, while ovulation day and the days leading up to it are highly fertile days that are important to get right. What it says in the book about not trusting green days before ovulation thus does not really make sense in the case of Natural Cycles and is written for women that only use the simple rules of the book which gives no guidance.
- Natural Cycles algorithm uses proper statistical tests to confirm that ovulation has happened, by comparing the temperature curve to what that particular woman’s ovulation pattern and temperature pattern looks like during ovulation. It can therefore sometimes be more than 3 high temperatures (which is what TCOYF basic rules state) and sometimes less, depending on the data and statistical significance. If Natural Cycles instead would use the simple 3-over-6 rule of TCOYF to confirm ovulation, the method failure rate would be much higher than what it is.