By Wolfgang Hackl, CEO, OncoGenomX Inc., Allschwil, Switzerland

In women’s health, “free” digital tools occupy an especially sensitive space. Period trackers, fertility apps, pregnancy platforms, menopause programs, pelvic-floor wearables, contraception reminders, mental-health chatbots and symptom diaries have become essential resources for millions worldwide. For many, these tools fill longstanding gaps in clinical care, offering information, monitoring and community.

Yet women’s health data are uniquely intimate, politically vulnerable and commercially valuable. The same apps that help a woman identify a fertility window or track post-partum mood changes may also collect sexual history, location, device IDs, hormonal patterns, and behavioral clues that can be monetized or repurposed – sometimes without meaningful transparency.

The core ethical question is urgent: When does the data exchange that underpins “free” women’s health tools empower individuals, and when does it exploit them?

Across research and policy commentary, the fault lines remain the same – transparency, proportionality, control, fair value sharing, and protection from harm – but their stakes are heightened in women’s health.

The high-risk profile of women’s health data

The sensitivity of women’s health data is not abstract. It becomes dangerous in real-world contexts:

• Reproductive rights volatility – In jurisdictions with restrictive reproductive laws, menstrual cycle data, geolocation patterns around clinics, search histories and communication logs can be weaponized.
• Stigma and discrimination – Data related to miscarriage, abortion, infertility, menopause symptoms, mental health, sexual function or domestic violence can lead to insurance denial, unfair pricing, employment impacts or social vulnerability.
• Relationship and safety risk – Some apps collect or expose data that partners or third parties could misuse, from mood logs to location traces.
• Commercial targeting – Women are historically targeted with exploitative advertising around fertility supplements, weight loss, anti-aging and alternative therapies, often amplified by intimate behavioral data.

These risks transform the ethics of “free.” When a tool’s business model depends on collecting sensitive reproductive or behavioral attributes at scale, the user is no longer the beneficiary – the user is the product.

What women expect when sharing health data

Studies consistently show broad support among women for sharing data when it drives tangible health benefits—research, better care pathways, early diagnosis, or community insights. Trust collapses when data are:

• shared with advertisers, data brokers or insurers
• used for profiling, risk scoring or targeted pricing
• stored indefinitely or without clarity
• accessible to third parties unknown to the user

Women expect three things above all:

1. Radical transparency

Not euphemisms, not hidden trackers, not 30-page terms. Women want to know who sees what, why and how it will be protected.

2. Meaningful agency

Granular control – “yes” to sharing anonymized cycle data for research, “no” to targeted ads; “yes” to contributing to public-good datasets, “no” to third-party data inference.

3. Safety guarantees

Technical and legal safeguards that explicitly prohibit uses exposing women to legal, financial, physical or psychological risk.

Women’s health is not a sandbox for broad, open-ended data collection. When platforms request permissions unrelated to their core health function – photos, contacts, continuous location, device fingerprinting – alarm bells ring.

Exploitation patterns in “free” women’s health tools

Technical audits of menstrual and fertility apps show that many collect extraordinarily detailed data: cycle length, symptoms, sexual activity, pregnancy intentions, test results, mood logs, sleep, stress, location, device IDs, email metadata, and “other information.” Some share with dozens of third parties.

The exploitation signals are increasingly well understood:

• Opaque data pipelines to marketers, analytics firms and profiling engines
• Unbounded storage of sensitive reproductive histories
• Engagement-driven design that nudges users toward disclosing more
• Commercial re-use of intimate behavioral patterns unrelated to health
• Minimal or performative governance despite high-risk categories

When a woman logs cramps or sexual activity, the ethical baseline is higher than in general wellness apps. The potential harms – legal, social, relational – are uniquely gendered and often irreversible.

Value capture and the “women pay twice” problem

Women’s health technologies have become a multi-billion-dollar market. But the value chain often flows upward, not back to the users:

1. Women supply intimate, high-granularity data – Immense value for R&D, precision marketing, and investor storytelling.
2. Companies monetize the insights – Through partnerships, advertising, risk scoring or AI model development.
3. Women then purchase the resulting products – Including paid upgrades, supplements, or premium diagnostics whose innovation was subsidized by their data.

Without mechanisms that guarantee affordability, open reporting or reinvestment into women’s health services, the model becomes extractive. Women contribute the raw material, then buy back the finished product at retail price.

Pathways to acceptable – and truly empowering – data use

Responsible data practice in women’s health requires stricter standards than generic “digital health ethics.” The following markers – derived from current scholarship—are especially critical in women’s health contexts:

1. Purpose-bound data practices

Tools should collect only what is strictly necessary for the health purpose. Fertility predictions do not require contact lists or persistent location tracking.

2. Prohibitions on harmful secondary uses

Contracts and code must explicitly block:

• insurance scoring
• law enforcement access without due process
• targeted advertising linked to reproductive data
• cross-platform tracking
• sale to data brokers

3. High-security architecture

Women’s health data should be treated like genomic or mental health data:

• encryption at rest and in transit
• zero-trust design
• independent security audits
• strict third-party access regimes

4. Governance designed for vulnerable contexts

Oversight bodies should include women’s health experts, legal scholars, and patient advocates, reviewing not just privacy compliance but real-world harm potential.

5. Fair value and reciprocity

If population-level reproductive or maternal health data fuel AI models, companies should commit to:

• affordability of products derived from those models
• investment in community health infrastructure
• transparency in data-driven improvements

This is not charity. It is ethical reciprocity.

The way forward: trust as a differentiator

Women’s health is evolving from niche to mainstream. With this visibility comes responsibility. Investors and innovators who treat data stewardship as a strategic asset – not a compliance hurdle—will define the next era of digital women’s health.

The future belongs to tools that:

• put safety ahead of scale
• align business models with women’s interests
• eliminate dark patterns
• prove that “free” does not mean “exploitative”
• create value with, not from, women

Ultimately, the line between acceptable data use and exploitation is shaped by one question:

Does this tool treat women as partners—or as data sources?

The companies that choose the former will earn the trust that defines the next generation of global women’s health innovation.

By Zahra Bhatti, founder, Véa

Women are achieving more than ever, yet many feel constantly mentally stretched and overwhelmed.

Emotional load has become the new glass ceiling.

What is Emotional Load?

Emotional load is not emotionality; it is the ongoing internal coordination of life – the feeling of carrying too much, tracking too much and anticipating too much.

It includes anticipating needs, noticing problems, remembering details, absorbing tension and managing the emotional atmosphere of others.

Sociologist Allison Daminger (2019) describes this as cognitive labour: the planning, organising and foresight that hold the fabric of daily functioning together.

Women disproportionately carry this work across cultures and industries.

They take on the psychological weight of remembering, checking in, smoothing conflict and holding the mental map of what everyone needs next.

This is layered on top of professional responsibilities and domestic expectations, forming a continuous background process that men, statistically, are less likely to absorb (ONS, 2016; Haupt et al., 2023).

The result is not busyness but fragmentation – the steady splitting of attention across competing emotional and logistical demands.

The Neuroscience Behind the Burden

The cognitive and emotional systems involved in emotional load are the same ones required for decision making, creativity and strategic thinking.

When they become overloaded, performance declines even in the most capable individuals. Working memory, the brain’s capacity to hold multiple pieces of information at once, is extremely limited. It breaks down under multitasking and rapid switching (Marois and Ivanoff, 2005).

Emotional monitoring, planning and interpersonal sensitivity draw from the same neural resources as focus and problem solving (Ochsner et al., 2012).

Emotional suppression – managing others’ emotions while sidelining one’s own – further increases cognitive fatigue (Goldin et al., 2008). Similarly, women are also biologically more reactive to relational stress.

Research indicates stronger amygdala responses to interpersonal tension (Bangasser et al., 2009) and a stress pattern known as tend-and-befriend, in which oxytocin amplifies emotional awareness rather than dampening it (Taylor et al., 2000).

In other words, women are both socially expected and biologically primed to carry a greater share of emotional responsibility. Over time, this does not simply create stress – it creates a form of cognitive erosion.

How Emotional Load Becomes a Glass Ceiling

When mental bandwidth is consistently used to manage the emotional and relational needs of others, less of it is available for the types of thinking that leadership requires: long-term planning, deep focus, innovation and strategic clarity.

High emotional load siphons the cognitive resources needed for complex problem solving (Sweller, 1988). It pushes women into organisational and interpersonal roles that maintain team functioning but carry little formal recognition.

This invisible work gradually expands until it displaces higher-leverage opportunities. Many women describe a version of burnout that is not exhaustion but depletion: being mentally full yet intellectually under-stimulated, over-functioning yet under-supported.

Studies also show women are more likely to internalise this overload, interpreting burnout as a personal failing rather than a structural imbalance (Maslach and Leiter, 2016).

Emotional exhaustion remains one of the strongest predictors of women leaving organisations altogether (Leiter and Maslach, 2009); McKinsey & Company and LeanIn.Org, 2023).

This is the quiet barrier that does not show up in diversity reports – a barrier built not from corporate policy but from constant cognitive interruption.

Where Femtech Still Falls Short

The femtech ecosystem has made extraordinary progress but it still treats emotional and cognitive experience as peripheral.

Today we can track ovulation to the hour, optimise sleep through biometric sensors and monitor HRV daily. Yet, there is no equivalent system for understanding emotional load, cognitive fragmentation or the cumulative mental strain that shapes a woman’s day more than her steps or calories ever will.

Most wellbeing tools focus on surface-level state change – a meditation, a breathwork exercise, a quick reset. These are useful but do not resolve the deeper issue: the mind is full.

There is too much unprocessed emotional material, too many unresolved micro-tensions, too many open cognitive loops. Without integration, clarity does not return.

This gap is precisely why tools like Véa need to exist.

How Technology Can Reduce Cognitive Fragmentation

Technology cannot remove emotional load entirely but it can radically transform how women process and carry it. One of the most robust research findings in psychology is the effect of expressive writing.

Putting thoughts and emotions into words reduces amygdala activation (Lieberman et al., 2007), improves cognitive processing, decreases rumination and strengthens prefrontal regulation (Pennebaker and Smyth, 2016).

Journaling does what the overloaded mind cannot: it externalises, organises and integrates.

When combined with AI, this becomes even more powerful. AI can detect emotional patterns humans miss, surface unacknowledged stressors and nudge micro-reflections that prevent overload from building.

It can help women close mental loops before they accumulate into cognitive clutter.

Done correctly, this is not therapy mimicry but cognitive hygiene. It reduces fragmentation and restores mental bandwidth.

That restoration – not motivation, discipline or resilience – is what many women are missing.

Reframing a Key Metric in Women’s Health

If femtech is serious about advancing women’s wellbeing, it must recognise emotional load as a fundamental determinant of health, performance and possibility.

The next decade of innovation will not come from tracking more biological inputs but from understanding and reducing the cognitive and emotional burdens women carry invisibly every day.

This shift matters because capacity is not an infinite resource.

Emotional load drains the clarity women need to lead, create and thrive. Addressing it removes a barrier that has held women back quietly but powerfully. Women do not need more advice on balance – they need more mental space.

Femtech has transformed how we care for the body.

The next transformation is caring for the mind. This is the problem Véa was built to solve: helping women process, integrate and offload the cognitive and emotional weight that has gone unrecognised for far too long.

Learn more about Véa at veajournal.app/

References

Bangasser, D.A., Eck, S.R. and Ordoñes Sanchez, E. (2019). ‘Sex differences in stress reactivity in arousal and attention systems’, Neuropsychopharmacology, 44(1), pp. 129–139. doi: 10.1038/s41386-018-0137-2.

Daminger, A. (2019). ‘The Cognitive Dimension of Household Labor’, American Sociological Review, 84(4), pp. 609–633.

Goldin, P.R., McRae, K., Ramel, W. and Gross, J.J. (2007). ‘The Neural Bases of Emotion Regulation: Reappraisal and Suppression of Negative Emotion’, Biological Psychiatry, 63(6), pp. 577–586.

Haupt, A. and Gelbgiser, D. (2023). ‘The gendered division of cognitive household labor, mental load, and family–work conflict in European countries’, European Societies, 26(3), pp. 828–854.

Leiter, M.P. and Maslach, C. (2009). ‘Nurse turnover: the mediating role of burnout’, Journal of Nursing Management, 17(3), pp. 351–359.

Leiter, M.P. and Maslach, C. (2016). ‘Understanding the Burnout Experience: Recent Research and Its Implications for Psychiatry’, World Psychiatry, 15(2), pp. 103–111.

Lieberman, M.D., Eisenberger, N.I., Crockett, M.J., Tom, S.M., Pfeifer, J.H. and Way, B.M. (2007). ‘Putting feelings into words: Affect labeling disrupts amygdala activity in response to affective stimuli’, Psychological Science, 18(5), pp. 421–428.

McKinsey & Company and LeanIn.Org. (2023). Women in the Workplace 2023. Available at: https://womenintheworkplace.com/ (Accessed: 1st December 2025).

Marois, R. and Ivanoff, J. (2005). ‘Capacity limits of information processing in the brain’, Trends in Cognitive Sciences, 9(6), pp. 296–305.

Ochsner, K.N. and Gross, J.J. (2008). ‘Cognitive Emotion Regulation: Insights from Social Cognitive and Affective Neuroscience’, Current Directions in Psychological Science, 17(2), pp. 153–158.

Office for National Statistics. (2016). Women shoulder the responsibility of unpaid work. London: ONS. Available at: https://www.ons.gov.uk/employmentandlabourmarket/peopleinwork/earningsandworkinghours/articles/womenshouldertheresponsibilityofunpaidwork/2016-11-10#:~:text=Women%20carry%20out%20an%20overall,to%20cooking%2C%20childcare%20and%20housework (Accessed: 1st December 2025).

Pennebaker, J.W. and Smyth, J.M. (2016). Opening Up by Writing It Down: How Expressive Writing Improves Health and Eases Emotional Pain. New York: Guilford Press.

Sweller, J. (1988). ‘Cognitive Load During Problem Solving: Effects on learning’, Cognitive Science, 12(2), pp. 257–285.

Taylor, S.E., Klein, L.C., Lewis, B.P., Gruenewald, T.L., Gurung, R.A. and Updegraff, J.A. (2000). ‘Biobehavioral Responses to Stress in Females: Tend-and-befriend, not fight-or-flight’, Psychological Review, 107(3), pp. 411–429.

By Celine Vignal, co-founder of Seesaw Health

The past year marked a turning point in femtech.

After a decade of steady progress, 2025 delivered a wave of innovations that pushed women’s health technology into a more mature, data-driven, and clinically integrated era.

From AI-enhanced hormone analytics to nervous-system biofeedback, companies shifted away from generic wellness and moved toward precision, personalisation, and validated outcomes.

With women now representing more than 80 per cent of household healthcare decisions and nearly 50 per cent of the global workforce, the demand for tools that reflect biological realities and not just generalised averages, has never been stronger.

Major Developments in 2025: From Hormone Intelligence to Pelvic Care

One of the most notable advancements in 2025 was the rapid evolution of AI-powered fertility and hormone-tracking technologies.

Fertility platforms expanded beyond ovulation prediction to offer multi-hormone modeling, giving users clearer insights into perimenopause, thyroid interplay, and metabolic patterns.

The industry also saw a surge in devices capable of real-time hormone detection, supporting more personalised care for women across all life stages.

Menopause tech continued its expansion.

What began five years ago as symptom-logging apps has now grown into integrated care platforms offering telehealth, digital coaching, non-hormonal treatment plans, and AI-based flare-up predictions.

Companies are increasingly leveraging longitudinal data to help identify early markers for sleep disruptions, cardiovascular risk, and mood instability, issues that disproportionately affect midlife women yet have historically lacked attention.

Meanwhile, menstrual and pelvic-health technology advanced significantly.

In 2025, startups brought to market more precise ways to monitor menstrual patterns, pelvic floor function, and chronic conditions like endometriosis.

We saw a rise in devices that combine sensor technology with therapeutic guidance. This reflects a deeper shift: women’s health problems long dismissed as “normal” are now being re-examined through a scientific lens, supported by better data and better tools.

Maternal health also benefited from this momentum.

Remote monitoring platforms now help track blood pressure, glucose variability, and stress biomarkers throughout pregnancy and postpartum, improving early detection for conditions like preeclampsia and gestational diabetes.

Importantly, many of these solutions are being built with inclusivity in mind, aiming to reduce disparities that have persisted for decades.

The Role of Nervous-System Data in Personal Health

Throughout 2025, the value of autonomic data—the signals that reflect how the body responds to stress—gained recognition as a critical element of women’s health.

New biosensors and software have made it possible to measure parasympathetic activity in real time, offering a window into how the nervous system modulates inflammation, pain, hormonal stability, and emotional regulation.

This represents a major shift: instead of using stress-reduction apps that rely solely on self-report or generic protocols, people can now see how their body responds physiologically in the moment.

Beyond wellness applications, this kind of data has important potential for chronic conditions that affect women disproportionately.

Autonomic dysregulation plays a role in migraines, IBS, endometriosis, PCOS, anxiety disorders, and perimenopause symptoms.

Tools that help women understand and regulate their stress response could become a critical layer of preventive care.

Predictions for 2026: Relying on Body Data

1. Nervous-system biomarkers will become as common as heart-rate data

In 2026, real-time stress measures, such as vagal tone, respiratory patterns, and autonomic balance, will increasingly appear in wearables and therapeutic devices.

Seesaw Health is one example of this trend, offering sensor-driven insights into parasympathetic activity to personalise breathwork and recovery.

We’re also seeing early signals from devices integrating sensors directly into earbuds and ambient sensors that adapt lighting and sound based on autonomic patterns.

2. Pelvic and menstrual health will enter a precision-care era

Expect more clinical validation and early-detection tools.

Startups are already piloting AI-powered ultrasound analysis for early endometriosis suspicion and pelvic-floor trainers like Perifit that adjust programmes based on muscle response rather than user guesswork.

High-resolution menstrual-mapping platforms will expand beyond risk scoring to offer cycle-specific care recommendations.

3. AI-driven coaching will personalise daily health decisions

Virtual health assistants will combine biological data with contextual signals to offer just-in-time guidance like Maven Clinic.

Some tools are already experimenting with flare-up prediction for PMDD or endometriosis, and with workout-modification engines that adapt intensity based on inflammation, sleep debt, and stress load.

As these models mature, daily self-care routines could become far more adaptive.

4. Menopause platforms will formalise into mainstream care

With over one billion women projected to be in perimenopause or menopause by 2030, insurers and health systems are beginning to integrate menopause-specific care pathways.

Tools offering cognitive-support modules, cardiovascular risk tracking, and metabolic change monitoring will likely become standard, especially those like Elektra Health combining telemedicine care with evidence-based education.

5. The consumer–clinician bridge will narrow

Women increasingly expect their digital tools to generate data they can share with providers.

In 2026, more apps will automatically produce structured summaries for clinicians, covering pain patterns, autonomic signals, cycle changes like Mira Fertility, or medication effects.

Early pilots are underway exploring integration of pelvic sensor data into PT workflows and autonomic summaries into functional medicine assessments.

About the Author

Celine Vignal is the co-founder of Seesaw Health focused on female physiology, stress regulation, and preventive care.

Her work centers on translating complex nervous-system science into accessible tools and biofeedback parasympathetic breathwork methods that support everyday resilience and nervous system balance.