by Ann Mullen, Director of Health Education at Cycle Technologies 

With all the media attention lately on family planning apps, it's no wonder we are all trying to get our hands on them.  Everyone wants to have a piece of the next revolutionary idea, and being able to manage fertility through a smartphone app could be the future of family planning and contraception. It is grassroots. It is by popular demand. It puts women in control. It’s high tech.  Data show that women are seeking them out and evidence shows that these methods can be highly effective.  

The reality is that evidence-based fertility awareness methods are effective and backed by years of research and testing. Efficacy trials show that the effectiveness range is 95 - 99% for these methods in perfect use and 80-88% in typical use – on par or better than other user-directed contraceptive options.

Editor’s note: Check out the webinar to learn more about scientifically tested and researched fertility awareness methods.


Interestingly, while more and more women are using fertility awareness methods, and apps are making these methods easier and more accessible, many in the medical community are now promoting IUD’s and implants (also known as long acting reversible contraception or LARC’s) as the first recommendation over all other forms of family planning. 


Does anyone else think that a woman's wishes and interests may not be well served when she is being pushed toward one form of birth control?


Fortunately, the medical community is beginning to take a first, second and third look at the new, improved birth control apps. Most importantly, women are finding family planning options that work for them.


As more women request information, as more women share that information among their friends, and as more women look for viable birth control options, there is a responsibility to provide them with a full-range of contraceptive choices.

Tags: fertility awareness apps, family planning, birth control, typical use vs. perfect use, FAM effectiveness, calendar-based methods

Comments are closed for this post.