Associations of Menstrual Cycle Tracking Application Use with Fertility Awareness and Fertility Health Knowledge: A Cross-Sectional Study

Background/Objectives: Menstrual cycle tracking applications (MCTAs) are widely used digital health tools that enable women to monitor menstrual characteristics and related symptoms. However, their association with fertility health knowledge and fertility awareness remains insufficiently understood. This study aimed to examine the associations of MCTA use, duration, frequency, and purpose with fertility health knowledge and fertility awareness among women of reproductive age attending a gynecology outpatient clinic. Methods: This descriptive, cross-sectional study included 484 women aged 18–49 years who attended the gynecology outpatient clinic of a private hospital in Istanbul, Türkiye, between 1 February and 1 June 2026. Data were collected using a Descriptive Information Form, the Fertility Health Knowledge Scale (FHKS), and the Fertility Awareness Scale (FAS). Descriptive statistics, independent-samples t-tests, one-way analysis of variance, Pearson correlation analyses, and simple linear regression analyses were performed. Results: MCTA users had significantly higher FHKS total, FAS cognitive awareness, FAS bodily awareness, and FAS total scores than non-users (p < 0.001). In the regression models, MCTA use explained 8.5% of the variance in FHKS scores (F = 44.771, R2 = 0.085, p < 0.001) and 6.6% of the variance in FAS scores (F = 33.884, R2 = 0.066, p < 0.001). Application-use duration was positively correlated with FHKS (r = 0.171, p < 0.001) and FAS (r = 0.144, p = 0.001) total scores. Use frequency was also positively correlated with FHKS (r = 0.217, p < 0.001) and FAS (r = 0.119, p = 0.009) total scores. Women using MCTAs as a symptom diary had the highest FHKS scores (117.35 ± 18.78). Conclusions: MCTA use was associated with higher fertility health knowledge and fertility awareness. MCTAs may be considered as adjunctive self-monitoring tools; however, recommendations should be cautious and limited to applications with transparent, evidence-based methods and clearly communicated limitations.