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Updated: Sep 2, 2026
An Application for Pairing with Wearable Devices to Monitor Personal Health Status
Published on: February 3, 2022
Exploring engagement patterns in a reproductive health app using the Technology Acceptance Model
Alissa Kazakoff1, Patricia K Doyle-Baker1,2,3
1Human Performance Lab, Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada.
Background:
Menstrual tracking apps are widely used, yet research on what drives sustained engagement remains limited. Most studies rely on self-reported use, with few incorporating real-time behavioural data or validated theoretical frameworks such as the Technology Acceptance Model (TAM).
Objective:
This study examined associations between engagement with a reproductive health app offering menstrual tracking functionality and TAM constructs over a 90-day period using both survey and direct app usage data. Changes in menstrual literacy were also assessed to evaluate the app's educational impact.
Methods:
Participants (n = 293) were recruited via social media and completed baseline and follow-up surveys including TAM measures of perceived usefulness (PU), perceived ease of use (PEOU), trust, and menstrual literacy indicators (confidence and information sufficiency). Real-time app engagement data were collected continuously, and participants were categorized into high- and low-engaged groups based on actual use. Paired t-tests and multivariate regression analyses were used to assess changes over time and differences between groups.
Results:
At baseline, no differences were observed in TAM constructs between high- and low-engaged users. By follow-up, PEOU declined significantly in low-engaged users while high-engaged users maintained higher perceived ease of use (p < 0.05). Confidence in menstrual knowledge increased in both groups whereas information sufficiency did not change significantly. Feature usage showed that 98% tracked menstrual cycles, 73% tracked symptoms, and 42% tracked exercise. The app was rated as moderate quality (uMARS mean=3.1).
Conclusion:
Integrating TAM constructs with real-time usage data provides new insight into engagement with a reproductive health app used for menstrual tracking. Findings underscore the importance of PEOU for sustained engagement and point to gains in users' confidence in their menstrual knowledge. Future work should include more diverse participants.
