Frequency and experience in the use of menstrual cycle monitoring applications by Brazilian women

Eur J Contracept Reprod Health Care. 2021 Aug;26(4):291-295. doi: 10.1080/13625187.2021.1884222. Epub 2021 Feb 22.

Abstract

Objectives: This study aimed to evaluate frequency and experience in the use of menstrual cycle monitoring applications (apps) by Brazilian women.

Methods: A cross-sectional study was performed through an online survey, announced in social media women's groups, among menstruating Brazilian women aged ≥18 years. The instrument collected sociodemographic, sexual, menstrual and technology usage data of all the women who agreed to participate.

Results: Of the 1160 participants, 71.2% used a menstrual cycle monitoring app. The principal motivation for using menstrual cycle apps was to track the menstrual cycle (94.3%), followed by pregnancy avoidance (49.5%). Users rated the apps with a mean 4.4 (standard deviation 0.65) stars out of five. There was a greater likelihood of using an app among women who used behavioural contraceptive methods (odds ratio [OR] 1.8; 95% confidence interval [CI] 1.2, 2.7; p = 0.01), barrier methods (OR 1.6; 95% CI 1.1, 2.5; p = 0.02) and copper- or silver/copper-bearing intrauterine devices (IUDs) (OR 1.9; 95% CI 1.1, 3.5; p = 0.04) and a lower likelihood among women who used hormonal contraception (OR 0.5; 95% CI 0.3, 0.8; p = 0.00) and permanent contraception (OR 0.1; 95% CI 0.0, 0.4; p = 0.00).

Conclusion: The use of menstrual cycle monitoring apps was quite widespread in the studied group. Satisfaction with app use was considered adequate. The use of menstrual cycle apps was associated with the use of behavioural contraceptive and barrier methods as well as IUDs.

Keywords: Contraception; menstrual cycle; menstruation; mobile applications; women.

MeSH terms

  • Adult
  • Contraception
  • Cross-Sectional Studies
  • Female
  • Humans
  • Intrauterine Devices
  • Menstrual Cycle* / physiology
  • Menstruation* / physiology
  • Mobile Applications / statistics & numerical data*
  • Pregnancy