Background: Smartphone applications (apps) that provide women with information about their daily fertility status during their menstrual cycles have the potential to become an important addition to the contraceptive method mix. However, if these apps claim to help a user prevent pregnancy, they must undergo similar rigorous research required for other contraceptive methods. Georgetown University's Institute for Reproductive Health (IRH) is conducting a prospective longitudinal efficacy trial on Dot, an algorithm-based fertility app designed to help women prevent pregnancy.Objective: Recruiting research participants who meet the criteria required of a contraceptive efficacy study and enrolling an adequate number to statistically assess the effectiveness of Dot is critical. Recruiting and enrolling participants for the Dot study involved making decisions based on research and analytic data, constant process modification, and close monitoring and evaluation of the effect of these modifications. The aim of this paper is to highlight decision points during the recruitment-enrollment process and the effect of modifications on enrollment numbers and demographics.Methods: Originally, the only option for women to enroll in the study was to do so over the phone with a study representative. Upon noticing low enrollment numbers, we examined the seven steps from the time a woman received the recruitment message until she completed enrollment, and made modifications accordingly. In Modification 1, we added call-back and voicemail procedures to increase the number of completed calls. Modification 2 involved employing a chat/instant message (IM) feature to facilitate study enrollment. In Modification 3, the process was fully automated to allow participants to enroll in the study without the aid of study representatives.Results: After these modifications were implemented, 719 women were enrolled in the study over a 6 month period. The majority of participants (68.7%) were enrolled during Modification 3, in which they had the option to enroll via phone, chat, or the fully automated process. Overall, 27.5% were enrolled via a phone call, 19.9% a chat/IM, and 50.9% directly through the fully automated process. With respect to the demographic profile of our study sample, we found a significant statistical difference in education level across all modifications (p<0.05) but not in age or race/ethnicity (p>0.05).
Conclusion:Our findings show that agile and consistent modifications to the recruitment and enrollment process were necessary to yield an appropriate sample size. An automated process resulted in significantly higher enrollment rates than one that required phone interaction with study representatives. While there were some differences in demographic characteristics of enrollees as the process was modified, in general our study population is diverse and reflects the overall United States population in terms of race/ethnicity, age, and education. Additional research is proposed to identify how differences in mode of enrollment a...