Evidence map›Paper›PMID 40463855›Full record

ArticleOxford open digital health2025

Flowing data: women's views and experiences on privacy and data security when using menstrual cycle tracking apps.

Sarika Mohan, Judy Jenkins

Abstract read
In one paragraph

Article in Oxford open digital health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Review
  4. Review
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.

Sarika MohanHealth Data Science, Swansea University Medical School, Swansea University, Health Data Science Building, Office Number 102 First Floor, Singleton Park, Swansea SA2 8PP, UK.ORCID https://orcid.org/0009-0005-5938-3020
Judy JenkinsHealth Data Science, Swansea University Medical School, Swansea University, Health Data Science Building, Office Number 102 First Floor, Singleton Park, Swansea SA2 8PP, UK.ORCID https://orcid.org/0000-0002-6722-600X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Menstrual cycle tracking apps are mobile applications that help female users track their menstrual cycle and gain future period predictions. Although these apps have advantages, they have been criticized for their lack of accuracy in prediction and poor adherence to privacy laws. This qualitative study aimed to explore the experiences and perceptions of users of period tracking apps with a focus on data security and privacy. Twenty-five female users between 19 and 38 years of age who have experience with menstrual app usage were interviewed via online video conferencing tools using a semi-structured interview technique. Data analysis was done using inductive thematic analysis, and eight themes were identified. The participants stated that they prefer apps that provide good period predictions and have a better user interface. They also expressed a desire to have ownership over their data and their access and that the apps should provide clearer privacy statements. The results of this study are vital for app developers to consider when designing or updating their apps to ensure that it is suited for a diverse group of end users. They must also implement stricter data protection measures so users can trust the apps with their information. Further research needs to be conducted to gain insights from different cohorts of users.

Indexed as

data privacyfem-techinformation securityperiod tracking appspersonal informaticsuser experience

Identifiers

PMID40463855
PMCPMC12131320

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

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.