Evidence map›Paper›PMID 42676439›Full record

ArticleFrontiers in reproductive health2026

Exploring engagement patterns in a reproductive health app using the Technology Acceptance Model.

Alissa Kazakoff, Patricia K Doyle-Baker

Abstract read
In one paragraph

Article in Frontiers in reproductive health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Alissa KazakoffHuman Performance Lab, Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada.
Patricia K Doyle-BakerHuman Performance Lab, Faculty of Kinesiology, University of Calgary, Calgary, AB, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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.

Indexed as

menstrual cycle trackingmenstrual literacymHealthperceived ease of useTechnology Acceptance Modeluser engagement

Identifiers

PMID42676439
PMCPMC13526922

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.