Women's health recruitment
Recruit screened women for health research, in hours.
Stop paying for unqualified respondents. FeFe matches your study to women already screened by condition, treatment and cycle stage, so you fill faster and clean less data.
Most studies start filling within minutes
Free to set up. You only pay when you launch a study.
Unfilled places are refunded in full
I am researching for
Women's health is not a niche. It is an unbuilt research base.
Decades of underfunding left no reliable way to reach women by condition. General panels were never built for it, so studies get delayed, underpowered or quietly dropped, and the evidence gap widens.
The sample does not exist yet
General panels hold no condition history, so you pay to search for women who were never identified in the first place.
Recruitment outlasts the funding
Clinic and community recruitment takes months. Approvals expire, studies shrink, and the question goes unanswered.
The evidence ends up weak
Unverified diagnoses, bots and AI answers land in the dataset, and underpowered findings cannot change practice.
Compliance and traceability
Participants reconfirm their health details every six months. Every submission keeps its own quality record.
- Screened on diagnosis, not self-reported at survey start
- Exportable quality record per submission
- Invoice and procurement support
Explore by condition and category
Start with the condition. Then narrow by age, country, cycle stage, pregnancy and treatment.
Do not see your condition? Ask us and we screen for it.
FeFe builds the panel first. Women are screened by condition, treatment and cycle stage before your study exists.
<5%
of health research funding goes to women's health overall
<1%
goes to non-cancer women's health conditions
£1 in £3
is estimated to be wasted on poorly recruited or unusable studies
UK health research funding analysis and recruitment efficiency estimates.
How it works
Describe your sample
Set your criteria and add your survey link.
Add credit and launch
Pay by card. Matched women see the study at once.
Approve and pay
Approve in a click. Participants are paid instantly.
What it costs
Participants keep 100% of the reward. FeFe's fee covers verification, screening, quality checks and instant payouts.
We take a fixed share of the total study cost, so the fee is predictable before you set the reward.
- No subscription
- Unfilled places refunded
- Participants keep 100%
Corporate
40% of study cost
Pharma, brands, femtech and healthcare
Academic
30% of study cost
Universities and non-profits
Worked example
100 places at a £5 reward
- Participant rewards
- £500
- Corporate fee (40% of study cost)
- £333.33
- Corporate total
- £833.33
- Corporate cost per completed response
- £8.33
- Academic fee (30% of study cost)
- £214.29
- Academic total
- £714.29
- Academic cost per completed response
- £7.14
Free to set up. You only pay when you launch a study.
Prefer to talk it through first?
Why FeFe exists
Built by someone who kept being sent home.
I am still a pharmacy student at the University of Bath. For years I went back and forth with doctors, being told symptoms were normal when they were not.
It stopped feeling like personal misfortune and started looking like a systemic data gap. Women's health research is underfunded, and the studies that do exist struggle to reach the right women quickly.
FeFe's mission is to give women dismissed by healthcare systems a paid, active role in shaping its future, while cutting the wasted money spent on poorly recruited, unusable studies.
The industry I am building toward is one where researchers default to FeFe, and women's health is treated as thousands of distinct conditions instead of one box to tick.
Version one began in Our Sisterhood summer, turning that frustration into a recruitment platform researchers can actually rely on.
Mariana Matthews
Founder
Ethics, data and GDPR
Answers your ethics committee will ask for
FeFe is a recruitment layer. You keep your study, your instrument and your data, and we give you the paperwork trail to evidence how participants were reached and paid.
You own the research data
Responses are collected in your own survey tool. FeFe never takes ownership of your dataset.
Participants stay pseudonymous
Researchers see a FeFe participant ID, not names or contact details, unless you collect them yourself under your own consent.
Consent and withdrawal built in
Participants opt in per study, can stop at any point, and see your information sheet before they take part.
UK GDPR and a data processing agreement
We publish our processing terms and subprocessor list, so your DPIA and ethics application have something to cite.
Fair payment as standard
Participants earn at least £6 per hour and keep every penny, which clears most university fair-payment policies.
An auditable sampling trail
Every study keeps its criteria, invitation and quality record, so you can describe your sampling method precisely.
Ethics approval remains your responsibility. We supply the recruitment detail your committee asks for.
Common questions
How quickly can I collect data?
Once a study is live, matched participants see it immediately. Many complete the same day, depending on your criteria and reward.
How do you know participants are real women?
Everyone passes screening, an attention check, a written answer and an authenticity pledge before their first study, then reconfirms every six months.
Who owns the data we collect?
You do. Your study runs in your own survey tool, so responses land with you. FeFe holds the recruitment record, not your dataset.
Do we need ethics approval before recruiting?
Approval stays with you and your institution. You can add FeFe as the recruitment method in your application, and we provide the criteria, consent flow, payment rate and sampling trail your committee needs to see.
How is personal data handled under UK GDPR?
We act as processor for the recruitment we run for you, publish a data processing agreement and a subprocessor list, and pass participant IDs rather than names or contact details.
What stops bots and AI written answers?
We block automated study grabbing, check time on task against your estimate, and let you set an AI policy per study. Two confirmed AI written submissions and the participant is removed.