Evidence map›Paper›PMID 40799838›Full record

ArticleDigital health

Algorithms, allyship, and advice: A qualitative analysis of fertility tracker marketing.

Kate Sheridan Clay, Sue Ziebland, John Powell

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. A Tale as Old as Time: Contraception Concerns in the 21st Century.Open access journal of contraception · 2026
    Article
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

3 authors.

Kate Sheridan ClayNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.ORCID https://orcid.org/0009-0001-9779-4825
Sue ZieblandNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.
John PowellNuffield Department of Primary Care Health Sciences, Oxford University, Oxford, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Objective: Proponents of 'Femtech', digital technology targeting women, frame them as instruments of women's empowerment that will revolutionise digital care. Its critics argue industry uses the moniker to popularise platforms that surveil reproductive data for profit. This qualitative analysis critically examines the marketing language used to promote digital interventions for managing infertility and discusses implications for users. Methods: We use an inductive thematic analysis approach to assess advertising for 15 top fertility tracking applications. Using both Foucauldian critical theory and feminist theory, we identified a code set and major themes connecting marketing content to broader rhetoric around (in)fertility, gender equality, and power dynamics in health care. Results: The main themes identified are: an emphasis on technological rather than human intelligence, allyship, online safety, and reliable advice. Reliance on non-human support is emphasised across multiple themes, and the framing of contested issues such as privacy and security is explored after the introduction of anti-abortion legislation in the United States, where many of the platform companies and users are based. Conclusion: We demonstrate how company marketing encourages users to centre digital tracking technologies in their fertility journeys. In doing so, Femtech marketers place the complex burden of reproductive labour on women's shoulders while offering a digital reprieve (for a fee).

Indexed as

Digital healthinfertilityreproductive health

Identifiers

PMID40799838
PMCPMC12340364

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.