# “My sex-related data is more sensitive than my financial data and I want the
same level of security and privacy": User Risk Perceptions and Protective
Actions in Female-oriented Technologies

Maryam Mehrnezhad, Royal Holloway University of London, UK
<EMAIL_ADDRESS> Teresa Almeida, Umea University, Sweden, and
ITI/LARSyS, Portugal
<EMAIL_ADDRESS>
Abstract: The digitalization of the reproductive body has engaged myriads of
cutting-edge technologies in supporting people to know and tackle their
intimate health. Generally understood as female technologies (aka female-
oriented technologies or ‘FemTech’), these products and systems collect a wide
range of intimate data which are processed, transferred, saved and shared with
other parties. In this paper, we explore how the “data-hungry" nature of this
industry and the lack of proper safeguarding mechanisms, standards, and
regulations for vulnerable data can lead to complex harms or faint agentic
potential. We adopted mixed methods in exploring users’ understanding of the
security and privacy (SP) of these technologies. Our findings show that while
users can speculate the range of harms and risks associated with these
technologies, they are not equipped and provided with the technological skills
to protect themselves against such risks. We discuss a number of approaches,
including participatory threat modelling and SP by design, in the context of
this work and conclude that such approaches are critical to protect users in
these sensitive systems.

keywords: Intimate data, Cybersecurity and privacy, Female Technologies,
FemTech, Reproductive health

##  1 Introduction

Emerging technologies such as sensors and connected devices have already found
their way into several aspects of our lives including intimate and
reproductive health. Examples of such technologies include mobile apps for
fertility and period tracking, online forums and social media groups for
menopause support, and smart IoT devices for nursing such as a breast pump. In
such sensitive contexts, the introduction of modern technologies may either
advance equity or exacerbate multi-layered harms and risks such as
discrimination, bias in algorithms and datasets, and gender-based harassment
and violence. Such harms are complex and have less clear definitions in the
literature and can differentially put users at risk.

In this paper, we focus on digital technologies and the intimate body,
specifically digital technologies for reproductive health. These include the
latest developments in and categories of FemTech111The majority of the FemTech
industry talks about its users as ‘women’. Nonetheless, queer and trans-
venture-backed companies are gathering momentum and contributing to counter
inequality and provide safe and reliable health and care to members of diverse
and marginalized groups.. FemTech, a category referring to software, products,
and services that advance women’s health but that also stresses the commercial
value of female technologies [53], comprises a wealth of female technologies
and covers a wide range of intimate bodily topics, such as reproduction.
Indeed, the digitalisation of the reproductive body, which has contributed
deeply to widening knowledge around intimate health care issues that were
neglected or stigmatized, such as menstrual care or sexual health, can also
put users at risk and harm, for example, by tracking abortion or infertility
[45]. The use of digital reproductive health technologies can lead to their
users finding themselves threatened and in real danger, such as in violation
of (women’s) human rights. For instance, many of such consumer-facing
technologies fail to abide by the General Data Protection Regulation (GDPR)
and Health Insurance Portability and Accountability Act (HIPAA) in that they
continue to share valuable personal information with commercial entities in
ways in which users may not be fully aware [40], for instance, tracking of
pregnancy leading to pregnancy-based redundancy [2], where pregnancy-related
discrimination still fails to guarantee effective job protections i.e. not
being terminated or demoted due to taking parental/maternity leave. Previous
research shows that there is a lack of clarity in the law in relation to this
extremely sensitive data, and it is not clear who has the rights to these
data, or who could legally access them [59].

The significance of SP in intimate tech-mediated interactions, in particular,
that which traverse sexual and reproductive health care that are a subject of
and subject to the law, is critical to safeguard the life of many. While laws
may vary depending on e.g., country or systems of governance, there is a
notable concern that insufficient regulatory attention has been devoted to
this growing market, and that ambiguity in how the industry is regulated
leaves its users at risk of relying on technologies of as-yet unproven worth
[43]. The combination of the "data-hungry" nature of this industry and the
lack of proper safeguarding mechanisms, standards, and regulations that
account for these vulnerable data lead to new and complex harm where the
user’s security, privacy and safety can be at risk. Such harms result from a
complex interaction of societal processes driven by diverse stakeholders.
Consequently, user agency is increasingly fainting in such complex systems
where the user does not understand many parts of such an ecosystem. That is,
users of these technologies are not currently empowered (e.g., through what
are readily available technologies and tools) to gain a sense of
understanding, control, ownership, security, and trust in using such
technologies without risk and fear.

In this paper, we aim to understand user’s security and privacy perception,
actions, and expectations in FemTech. Our research questions include: RQ1:
What is a user’s general understanding of these systems and how do they
perceive the associated and potential harms and risks? RQ2: What protective
actions do users adopt and what are their desired security and privacy
features in these technologies?

We conducted mixed-methods user studies to investigate user perspectives of
how such intimate data flows in the FemTech ecosystem, with a focus on what
the risks are and what protective actions a user might take to protect
themselves against such harms. To do this, we first conducted an online survey
which we designed specifically to help us understand the general SP mental
models and patterns associated with this range of technologies. We publicised
our survey in a way that all potential users, i.e. women and other groups, of
such technologies could take part. Then, we reflected on the survey results as
widely applicable and explored examples of harms more explicitly by engaging
17 participants in an online story completion activity. This was an activity
focused on the feelings and protective actions of the participants when
encountering a risky scenario when using these technologies. Finally, we
conducted six individual interviews with a subset of participants from the
previous study to discuss their understanding in more depth. We then discuss
these issues through a set of approaches for designing new technologies and
systems, which can foreground values in the design of personal in intimate
data, in particular when designing for and with marginalized and vulnerable
populations [25, 30, 31, 15, 41, 42, 62].

Our contributions include: (i) designing and deploying mixed-methods user
studies to enquire user perception of risks and harms and their security and
privacy actions (potential and/or preferable), and (ii) exploring approaches
to design that treat SP as core concepts and values to better protect users in
these systems.

##  2 Background and Related Work

FemTech is a somewhat controversial term [37, 12] understood as a subset of
health-related technologies that has specifically been designated to advance
and foreground the intimate health care needs of women. As such, while
focusing on women’s health and well-being to address “a niche" and
historically marginalized people, it has also been understood as an industry
prone to exacerbating gender disparity and excluding trans and non-binary
communities. Past the troubling terminology, this industry is composed of an
ever-growing number of technologies that aim to include a plurality of bodies
and genders. These include mobile applications (apps), connected devices and
online services covering menstruation, menopause, fertility, pregnancy,
nursing, sexual wellness, and reproductive health care, to name but a few
categories. The class of technologies is broad, ranging from stand-alone
mobile menstruation apps to illness-tracking wearables to IVF (In Vitro
Fertilisation) services on the blockchain. FemTech Analytics, a strategic
analytics agency focused specifically on this sector, predicts an industry
growth over $75-billion by 2025 [6]. The sector is booming, and along with the
numerous opportunities to both monetize and arguably improve women’s and other
marginalized groups health, these come with the increased security, privacy,
and safety risks associated with the collection of intimate health and medical
data, as required by many FemTech apps and devices222While FemTech may (need
to) expand beyond reproductive health, in this paper we explore these
technologies as they focus on the reproductive space (e.g., fertility
tracking, nursing, and menopause)..

In [47], we suggested that FemTech privacy should be looked at via different
lenses. These include the cases where someone has user personal data but the
user does not –inverse privacy [28], when peer pressure causes people to
disclose information to avoid the negative inferences of staying silent
–unraveling privacy [51], when the privacy of others (e.g., child, partner,
family, friend) also matters –collective privacy [10], and when systems should
also focus on the intersectional qualities of individuals and communities
–differential vulnerabilities [45]. Multiple threat actors have been
identified for these technologies by some recent work e.g., [28, 47]. These
interested parties include, but are not limited to: (Ex-)Partner and Family
[5, 65, 21], Employer and Colleagues [28, 18, 2, 70, 17, 35], Insurance Firms
[26, 54, 58], Cyber-criminals [45, 71, 53], Advertising Companies [39, 3, 59,
49, 24], Political and Religious Organisations [33, 50], Governments [49, 13,
11, 60, 7], and Medical and Research Companies [71, 52]. Such threat actors
may exploit these systems in various ways by performing attacks at different
points of the ecosystem e.g., human dimensions, hardware vulnerabilities,
attacks on datasets, IoT device, app and website exploits, etc. A number of
system studies have been performed on the SP practices of these technologies.
Examples include the analysis of the data collection practices of the period
tracking app ecosystem and their policies [59], measuring the tracking
practices of fertility apps and their compliance to the GDPR [45], and traffic
analysis and policy review (with focus on HIPPA [1]) of a subset of iOS apps
[28]. Very limited work has gone into the SP assessment of FemTech IoT devices
[69]. The cybersecurity community is yet to properly investigate the data
collection of these ecosystems, (lack of) implemented security and privacy-
enhancing technologies (PETs), the existing vulnerabilities, and potential
security measures to mitigate them.

While there is a body of research on the SP risks associated with these
systems, the human dimensions of these technologies are not explored well.
Previous research shows how the users of such technologies are already
marginalised by SP research, products, and tools. This includes e.g., not
having the actual end user in the life-cycle of the development of such
systems enabled by traditional threat modelling, and disparity in education
and SP knowledge [23, 46]. The personal characteristics and intersectionality
of the end users of such products have an impact on these systems too, which
is barely discussed in the literature. Measuring these risks comprehensively
via system studies and user studies is not straightforward and requires mixed
methods.

The SP of FemTech products can be investigated by looking into IoT hardware,
product websites, mobile apps, cloud detests, etc. However, the security and
privacy of the user and data in FemTech are more complex than in some other
contexts. Furthermore, due to the intimate nature of the data involved in
these technologies, social and cultural aspects need to be taken into account
too. A combination of multi-layered systems and sensitive data and
applications creates a new range of complex harms and risks. Complex harms
include ‘harms with a less clear definition’, which is within the scope of the
UK Government’s White Paper on Online Harms333We use UK Government’s White
Paper on Online Harms as reference for this research:
gov.uk/government/consultations/online$-$harms$-$white$-$paper and the related
Online Harms Bill. A taxonomy of organizational cyber-harms is suggested in
[9] where such harms are grouped within six main categories: Physical/Digital,
Economic, Psychological, Reputational, and Social/Societal. FemTech risks and
harms can fall into all these categories, alone or combined, and beyond.
Examples include abuse and loss of life, loss of job, shame and guilt, damaged
relationships, and public negative perception, all of which belong to the
categories described in [9]. Moreover, plenty of news articles, academic
papers, and popular science books (e.g. [71]) have included various examples
of complex harms and risks. These include influencing elections (e.g., [14])
and organised social media attacks, or LGBTQI+ support for both (digital and
physical) safety [32, 27], women’s experiences online outside of Western
perspectives [36, 38], vulnerable populations in the global south[8, 55, 57,
56], and people living with stigmatized conditions [19]. More examples include
cyberstalking, and stigmatised topics such as domestic violence and intimate
partner violence [68, 62], and algorithmic harms [66].

Moreover, the existing laws are incomplete and ineffective and are lacking in
protecting the user in various ways [59, 45, 28, 18, 17]. For instance, it is
not clear if and how FemTech data is covered by the “special category data"
within the GDPR framework or how this data can be protected against work
discrimination e.g., pregnancy redundancy. Similarly, it is unclear what is
classified as “medical” category vs. other groups (e.g. health and lifestyle)
in other relevant guidelines and laws e.g., the UK Medicines and Healthcare
products Regulatory Agency (MHRA) [29, 45]. It is indeed not clear which
stakeholder or party is responsible for the protection and how each party’s
practice influence others. Furthermore, the combination of multiple
technologies (e.g., mobile apps, IoT devices, cloud storage, AI and ML) in
these technologies can also lead to unpredicted and unintended consequences.
For instance, in the case of marginalised user groups, collecting data does
not necessarily only mean including them in the systems and might put them in
more danger of being profiled and fingerprinted online. All the above
dimensions influence user agency where the end user might feel less and less
in control of their data and how they understand, perceive, and practice their
SP rights. In this paper, we explore user’s SP understanding in FemTech to
shed light on the complexity of these systems and their harms from the user’s
point of view.

Table 1: Overall design of the study. Each section includes the types of questions from the participants (S = Story, Q = Question) I-a) Survey (general) | I-b) Survey (risk-related) | II) Story Completion Method | III) Interviews
---|---|---|---
\- Description & usage | \- Data type | \- S1: Mobile app and ads | \- Q1: Data flow
\- Pros & Cons | \- Security incidents | (Period and fertility tracking) | in the ecosystem
\- Ways of learning | & Data access | \- S2: Online search and ads/ | \- Q2: Data access
\- Incidents | \- Protective actions (general, FemTech) | misinformation (Menopause care) | \- Q3: Potential
| \- Desired security/privacy features | \- S3: IoT/app and other user access | Safeguarding
|  | (Nursing) | features

##  3 Methodology

We conducted a user study using mixed-methods (online survey, storytelling,
and individual interviews) and each method contributes to answer parts of our
RQs. Table 1 shows the design of our study. We recruited our participants in
the UK. According to FemTech Analytics 444femtech.health/femtech-market-
overview, the total amount of FemTech funding was $19.7 billion in December
2022 (+35% YoY). The UK has the biggest number of FemTech companies in Europe,
and comes second globally only after the US (UK: 10.5%, USA: 43.4% of the
whole market). In addition, the majority of this research team is based in the
UK and had access to a few platforms (e.g., UK’s National Innovation Centre
for Ageing (NICA) and UK-based FemTech organisation Women of Wearables (WoW))
to disseminate the user study invitations. We conducted our study between
August 2021 and July 2022. This survey and subsequent two-part studies had
ethical approval granted by the Ethics committee at [Anonymous] University. We
assigned a number to each participant and performed our analysis via that
number in order to anonymize our participants. We report our findings in the
paper in an anonymised way. Participation in this study was completely
voluntary and our participants could drop out at any stage as they were
informed about in the invitation email/message, consent forms and later
communications. We highlight that recruiting participants for this work was a
challenge and it took us several months to complete these studies; mainly due
to the lack of engagement from a diverse set of participants. Though, the
repetitive themes emerging from the three studies reassure the confidence in
our results.

Table 2: Demography of our participants Survey (102 Participants)
---
Age and Gender | 18-79 years old, 87 Female, 14 Male, 1 Non-Binary
Job | Ranging from PhD student, university staff, self-employed, to not working and retired
Story Completion Method (SCM) (17 Participants)
Age and Gender | 22-71 years old, 13 Female, 4 Male
Ethnicity | White British (9), White European (1), Black African (3), Middle Eastern Asian (4)
Job | Ranging from PhD student, university staff, self-employed, to not working and retired
Individual Interviews (6 Participants)
Age and Gender | 22, 28, 30, 32, 36, 71 years old, 5 Female, 1 Male
Ethnicity | White British (3), Black African (2), Middle Eastern Asian (1)
Status | Single (2), married/living with partner (4), with children (2), trying to conceive (1), postmenopausal (1)
Job | PhD student (3), university staff (1), not working (1) and retired (1)

###  3.1 Method 1: Survey

We designed an online survey (Appendix) to gain a general understanding of
user practices in FemTech and their SP concerns and protective actions.

##### Design Approach

Our survey had two sections. In the first section (General Questions), after a
brief introduction, we included questions about the general usage of FemTech
and the participants’ experiences in their own words. We then asked them about
the advantages and disadvantages of such technologies and how they have
learned about those technologies. In the second part (Security and Privacy),
we asked questions about the SP of FemTech. We asked what type of information
about themselves (e.g., name, age, contact info, lifestyle, sex activities,
medical records, etc.) they input when using such technologies and who they
think has access to their data. We then asked what forms of protective actions
they take in general and more specifically in regard to FemTech. Finally, we
asked our participants, in their opinion, what sorts of SP features should
exist in these technologies.

##### Participants

We distributed our survey via the newsletter of VOICE organisation555voice-
global.org/, which is a part of UK’s National Innovation Centre for Ageing
NICA 666uknica.co.uk/ working with researchers, industry, and end users across
the UK and beyond. We also distributed our survey via
WOW777womenofwearables.com/ which is a UK-based leading global organisation
active in FemTech. We also recruited survey participants via social media and
mailing lists of the authors and team members. 102 participants completed our
survey. At the end of the survey, we asked our participants if they were
willing to take part in the further parts of our studies by providing us with
their email addresses. This section was voluntary, and 70 participants left
their emails for further communication.

##### Data Collection and Analysis

Our survey was designed in Google Forms. Our method of processing the
collected data was a mix of quantitative and qualitative analysis. The results
for some of the questions are presented by stacked bar figures. For our free-
text style questions, we conducted a thematic analysis [16]; taking an
inductive approach and allowing the data to determine our themes. We
facilitated a conventional line-by-line coding [34] of all the responses. Two
of the authors contributed to the analysis by coding and extracting the key
themes independently. For more complex and lengthy comments, we assigned
multiple themes to them. The researchers discussed these themes to agree on
potential inconsistencies and also chose the user comments that represent such
themes for inclusion in the paper.

###  3.2 Method 2: Story Completion

In this part of our study, we used the story completion method (SCM). SCM is a
method that allows for creative enquiry and imaginative engagement with one’s
own experience as well as trying out someone else’s shoes and can encourage
people to consider the implications of social problems in ways that do not
involve direct questioning [73]. As a research method, story completion is a
generative technique for eliciting narrative data [22]. This qualitative
research method has also seen a growing interest when researching sensitive
topics, for example [74, 67].

##### Design Approach

This activity involved the participants in speculating the user’s protective
thoughts and actions within a variety of FemTech-related -and potentially
risky- scenarios by engaging in the creative process of completing a story. We
presented participants with a set of three story prompts (‘stems’) for them to
complete. These story stems involved scenarios using digital technologies, to
produce written narratives about situations faced by fictional protagonists.
Each of the scenarios was created based on the SP concerns and protective
actions reported by our participants in the survey. These stories were
carefully designed across the range of FemTech products (mobile apps, online
websites, IoT devices) and applications therein (fertility tracking, menopause
aid, nursing), and potential risks (user profiling and tracking,
misinformation, and violating others’ privacy). Our story prompts include:

  * •

Story 1 (mobile apps and ads): Alex downloads a free period tracking app to
keep an eye on their fertility window. The next day Alex receives multiple
email ads about baby’s clothing and toys. What does Alex think? What happens
next?

  * •

Story 2 (Internet search and ads): Morgan goes online and browses the
internet, searching for common symptoms of menopause. The next time Morgan
logs on to Instagram and Facebook, both feeds are full of ads for boosting sex
drive and weight loss. What does Morgan think? What happens next?

  * •

Story 3 (IoT device/app and user access): Ashley has been using a ‘smart’
breast pump that connects to an app and is shared within the family. This is a
breast pump that can track breastfeeding and give tips to support parents in
meeting their goals. In the meantime, Ashley’s partner has received an alert
regarding the baby’s feeding schedule and weight and feels upset that it is
not according to their plans. What does Ashley think? What happens next?

These three story prompts adopted gender neutrality in the naming of the three
fictional protagonists and their respective hypothetical scenarios.

##### Participants

Following the initial survey, we invited the 70 participants who declared an
interest in our follow-up studies to take part in this activity. We sent the
participants an email invitation and a link to this activity. 17 participants
completed the activity in an anonymous way. Participants were asked to spend a
maximum of 15 minutes writing on each scenario and there was no maximum or
minimum amount of words requested.

##### Data Collection and Analysis

We created a Google Form and shared it with our participants. This form
included the three story prompts designed for the participants to first,
reflect on what someone else might ‘think’ and second, the potential action
that someone might take. The minimum amount of words entered was four (“don’t
like, uninstall it") and the maximum was 269. Similar to the previous section,
we used a process of thematic analysis to extract themes as we report in the
results. This method provided our participants with an excellent opportunity
to think about the end user of the same products that they use and/or don’t
use, their feelings, risks, and potential protective actions.

###  3.3 Method 3: Individual Interviews

Our final method included one-to-one online interviews with our participants
and asking them to reply to the questions by drawing their answers as well as
describing their sketches.

##### Design Approach

The goal of this activity was to reflect on the user’s response to the
previous activities and have an in-depth discussion about the FemTech
ecosystem. More specifically, we wanted to observe the understanding of the
user about the data flow and sharing and their understanding of the big
picture. This was done via one-to-one interviews by asking our participants to
draw some parts of their answers and thoughts about these questions. After a
brief introduction, two authors of the paper asked three concrete questions as
below:

  * •

Question 1 (Data flow): In any form of FemTech solution (low tech (e.g., off-
the-shelf pregnancy test), shopping website, GP system, mobile app, IoT
device), how do you think your data might be transferred beyond your own
device? What are the connections in this ecosystem? Can you please doodle
something for us? Where do you think this data will end up (any possible
place)?

  * •

Question 2 (Data access):In such an ecosystem, who do you think might have
access to your data (e.g., yourself, partner, family/friends, social media,
employer, colleagues, government, GP/NHS, council/police, product company,
advertising companies, researchers, general public, etc.)? Please identify
them in your sketch and complete it if necessary.

  * •

Question 3 (Safeguarding features): In this ecosystem, how do you think user
data and their privacy and security can be protected? Please give us three
concrete ideas and highlight them in the sketch.

##### Participants

We invited the 17 participants who completed the SCM activity to volunteer for
a one-to-one interview with the authors of the paper by sending them an email.
Six participants agreed to take part. All interviews took place online and we
used the video conferencing tool Zoom to conduct these virtual meetings.
Interviews lasted between 30 and 60 minutes. As a thank you, we gave a £30
amazon voucher to the participants who completed all three studies. This was
communicated with the participants before taking part in the interviews.

##### Data Collection and Analysis

We recorded the online interviews with the participants using the video
conferencing tool Zoom. The interviews were transcribed by one of the authors,
they were anonymized by assigning a number to each participant and no
personally identifiable information was kept on file. Similar to the previous
sections, we conducted an inductive thematic analysis to extract the emerging
themes by assigning preliminary codes and searching for patterns across the
interviews. During the interview, we asked each participant to draw a sketch
on paper and send a scan or image of it to us via email. Following this
activity, we ended up with six sketches, in addition to the user comments on
their drawings, reflecting the user’s understanding of the these systems, the
stakeholders, data flow and access and suggested mechanisms to reduce risks.

###  3.4 Limitations

We composed our research around the general term “FemTech" which is applied to
a wide range of technologies in our studies while explaining that this is a
term used by the industry sector and these systems are not limited to women.
We acknowledge that the range of FemTech is wide. Though our previous research
[10, 47] shows that they all collect a similar range of sensitive user data.
In addition, the general patterns identified in the survey are informative and
provide input to other parts of this paper as well as potential future work.
We did not apply any filters when inviting our participants to further studies
and invited them by relying on their expression of interest. This was
partially due to challenges in participant recruitment and we wanted to have
as many participants as possible. However, we also did not want to apply any
potentially biased filter and wanted to include participants from any
demographics within the UK. Our survey had multiple questions which might have
caused survey fatigue. However, the response to the open-text questions
suggests that the participants stayed engaged with the study until the end. We
also analysed the effect of random answers for each participant and did not
find any visible patterns. We conducted our studies in the UK, which has a
diverse population and is a country of multiple identities in Europe. We
acknowledge that further studies are required across different user groups and
we leave that as future work.

##  4 Findings

Generally, participants in the online survey study described FemTech as a
series of technologies supporting female and women’s health including
“physical, mental and sexual health". Examples of use which was seen across
the user responses in the free-text questions included period, fertility,
ovulation and pregnancy tracking. Our participants chose a number of ways in
which they have learned about FemTech including personal research (46%),
partner/family/friend (34%), online ad (24%), colleague/work (10%),
school/university (8%), health centre/clinic or NHS (7%), TV/Radio (4%), and
traditional ads (1%).

When we asked about the advantages of these technologies (via itemized
questions as well as free-text boxes for extra items, demonstrated in Table
3), 72% believed that “They are easy to use", 60% chose “They increase my
knowledge about my/partner’s body", 56% said “They can be personalised", 48%
chose “Everyone can have access to them", 43% believed "They are non-
intrusive", 42% said “They are cost-effective", 18% chose “They are accurate".
Those who chose The Others category, mentioned other advantages such as
“[FemTech] help partners and family for planning various things such as trips,
and parties" and “[They are] relatively anonymous".

###  4.1 Perceived Harms and Risks

####  4.1.1 General Perception

Via different parts of our studies, we asked our participants questions
relating to their understanding of the risks and harms associated with
FemTech. For instance, we asked about the advantages and disadvantages of
these technologies as reported in Table 3, as well as their lived experiences
regarding any incidents when using these technologies.

Table 3: Users views on the advantages and disadvantages (Survey) Advantages | User % | Disadvantages | User %
---|---|---|---
Easy to use | 72 | Share user information | 65
Increase knowledge | 60 | Not accessible to all | 29
Personalised features | 56 | Not easy to use | 28
Easy access to all | 48 | Not accurate | 28
None-intrusive to body | 43 | Biased | 26
Cost-effective | 42 | Expensive | 10
Accurate | 18 | Others | 5
Others | 5 |  |

Our participants chose a number of issues that they believed to be the
disadvantages of such technologies. 65% of the participants believed that
“They share user information with third parties or sell to them", 29% chose
“They are not accessible to all user groups", followed by 28% choosing “Using
such technologies is not easy for certain users", 28% choosing “They are not
accurate" and another 26% believing that “They only work for certain user
groups and have bias", and 10% said that “They are expensive". Among those who
chose “Others" (5%), a few said that Governments or other entities may “track
women" via these technologies, and others said these technologies may change
what is considered as “normal".

On the experiences about any unpleasant incidents, among the 12 replies, five
said the inaccuracy of FemTech has led them to lose their fertile days and/or
have experienced or heard of an unwanted pregnancy. For example, one
participant noted “My wife lost a few months when she wanted to get pregnant
since the app was not accurate about the fertile days". Another said: “I have
heard of women being overdue with their period and the algorithms showing them
advertising for baby stuff before they even managed to tell their partners or
anybody else. Not ok." Five users said their privacy and security have been at
risk e.g., they have noticed that they have been tracked via seeing
personalised ads without their consent. Other examples given by users included
not having a backup of their data and leaking their data. Finally, two
participants said that these technologies set the bar too high and cause
stress for the users e.g., regarding what is a “normal period" and what “milk
volume" is enough for a baby. For instance, one participant said: “They can be
misleading and often put unwanted pressure on a person that their body should
be behaving in a certain manner. Without these apps, there was less awareness
and perhaps less stress and anxiety around “what is normal”".

As it can be observed in these responses, some of the immediate risks were of
concern to a greater percentage of our participants. For instance, the
majority of our participants (65%) could infer that sharing user data can be
an issue in these technologies. This concern was also reflected in users’
lived experiences (extracted from users’ comments). This particular concern
informed the design of the stories of study 2. In addition, around 30% of the
participants believed that these technologies are not accurate and one quarter
believe that they can be biased. These can create serious harms to the user
e.g., unplanned pregnancy, experiencing anxiety in conceiving, wrong mentality
about body norms, etc.

####  4.1.2 Data and Access

We also directly asked our participants about the types of data collected in
these technologies as well as who might access this data. We listed a range of
FemTech data and allowed the users to choose them as well as add items which
were not listed. This list had a few items informed by our previous studies
([10, 47]) including: period-related info (chosen by 60% of the participants),
user info (name, age, gender) (50%), contact info (40%), emotional and
physical symptoms and lifestyle information (each 35%), sexual activities
(25%), medical information, pregnancy information and information about
reproductive organs (each 10%), users’ social media, baby, photos (each 5%).
We presented this list to the user to remind them of the wide range of user
data that can be collected by these technologies. Previous work [10, 47, 59]
shows that these technologies collect all the categories of intensely. We
observed that such data collection is more than what our participants
reported. And this is the case for most data types (self-entered, automatic,
sensors) across the majority of FemTech categories.

Figure 1: Users’ views on data access (Survey)

We asked our participants who they think has access to this data. We provided
a list, partially informed by previous research (ibid), and allowed them to
add new items via a text box. As reported in Fig. 1, after the app/device
company (78%), the ads companies category was the most selected one (50%). 40%
of the participants chose the OS of the hosting device, and 30% picked third
parties such as medical clinics and insurance companies. Over 10% believed
that GP/NHS, government, and/or partner can have access to this data. Those
who chose others mentioned different entities e.g., “whom the company decides"
and “anti-abortion groups". Our previous work has indeed highlighted that all
these entities are interested in such data and the data collection and sharing
is not always transparent in these technologies [10, 47] .

We also asked the participants if they have ever experienced any SP incident
when using such technologies. Among the 40 participants who provided answers
to this question, 10 participants said no, 15 said they are “not sure", “it is
possible", however, they “might not be aware" of such an incident. For
instance, one said: “I’m not sure how I would tell. I pretty much expect that
somewhere in the fine print I have implicitly agreed to all kinds of
pernicious data sharing…". 15 participants listed specific incidents. Eight of
them said they have been bothered by personalised ads, four said they have not
given any explicit consent for their sensitive data to be collected and shared
by these apps, and three said they have experienced a password leak. For
instance, one participant said: “As advertisement have been sent to me I am
sure third parties access to my data that I had entered." Another one said:
“Yes, I received personalized ads. I also don’t see any privacy alert
according to GDPR".

Throughout our user studies, we aimed to gain an understanding of the user
perception of the FemTech ecosystem and the data access and flow beyond the
user’s device. This was reflected in our online survey and further on in our
one-to-one interviews. As previously discussed, around half of the
participants in the online survey recognised that different stakeholders
(e.g., third parties) may have access to FemTech data (Fig. 1). In addition,
all six participants in the interviews also recognised that such data can be
transferred to third parties via the FemTech company and with or without the
user’s consent. This was reflected in their drawings. Despite that, these six
participants had different views of how other interested parties (e.g., NHS,
government, insurance companies, etc.) may or may not have access to FemTech
data. Fig 3 shows two examples of such drawings. As one can see, these
participants anticipate that multiple third parties may have access to this
data and re-share it with others too. Through our discussions, we identified a
high level of uncertainty among our participants about how this ecosystem
works and what risks threaten them. This was also reflected in our online
survey where multiple users said that they don’t know if and how their data is
shared beyond their device. All these six participants also highlighted that
they do not know if this data is protected by the relevant law e.g., the GDPR
and were hesitant to speculate on all the potential parties and their access
to such data.

Figure 2: How users protect their privacy and security in general vs. FemTech
(Survey)

###  4.2 Reported Protective Actions

####  4.2.1 General Protective Actions

We asked our survey participants about the ways that they generally protect
their online SP in FemTech in two open-text questions. Fig. 2 shows the themes
that were visible in the answers provided by our participants. As one can see,
47% of the participants use Antivirus and more than 30% opt-out of cookies to
protect their general online SP. Other methods include secure passwords (e.g.,
password managers, changing passwords, different passwords for different
accounts) (23%), and other forms of PETs such as Tor, DuckDuckGo, and reading
privacy policies (17%). 15% of our participants said that they only use a
trusted app/tech and/or only use the technologies that they need in a minimal
way. 11% said they only input the minimal data that will make the app/tech
function well. 10% of the participants said they use other ways of protecting
themselves via e.g., personal research, providing false data, using multiple
accounts, managing social media, system updates, etc. 8% said they make sure
they don’t fall victim to a spam attack, and 7% said they use secure browsers
and private browsing via e.g., incognito mode. 6% the participants said they
use the biometric features of their mobile devices to protect themselves and
5% said they used VPN. Only around 7% said they do nothing to protect their
online SP.

In contrast, 32% of the participants said they do nothing specifically to
protect their FemTech privacy and security. Providing minimal user data into
these technologies was the most popular method, selected by 24% of the
participants. For example, one participant said: “not entering too much info
especially medical and sex-related ones since they are super sensitive".
Another participant said: “I do not share anything else than my period
details. I do not feel safe and doubt these applications." Other methods
included antivirus, cookie opt-out, secure passwords, other PETs, and using
trusted technologies. For instance, one participant said: “Use only limited
ones. Not third party downloads except NHS app, though that’s likely to have
same data issues but have to accept this. Opted out of data sharing from NHS
via govt website." As it can be seen Fig. 2, most protective actions are
general practices for the users rather than specific to FemTech. The only
exemption is providing “minimal user data". This protection method is rather
interesting since it implies that these participants realise the intimate
nature of FemTech data and do not see any benefit in providing such data to
these apps. For instance, one participant said: “I only provide minimum data
to make the app work with a fake name and nothing more."

Table 4: Feelings and protective actions in SCM (NA: no feelings were described in the story) Story | Story Actor | Feelings (no. of users) | Actions (no. of users)
---|---|---|---
1\. Mobile app and ads | Alex | Negative (14), Neutral (2), | Uninstall/Switch app (11), Review settings (4),
|  | NA (1) | Others (4)
2\. Online search and ads | Morgan | Negative (13), Neutral (1), | Review browser/cookies settings (7), Limit/Stop
|  | NA (3) | internet search (6), Click ads (5), Others (3)
3\. IoT device/app and access | Ashley | Negative (15), Neutral (1), | Review settings (8), Stop using (6),
|  | NA (2) | Discuss with partner (6), Seek help (6)

####  4.2.2 Potentially Risky Scenarios

We also analysed the data collected via our SCM. 17 participants completed
this activity and reported their thoughts of potential security or privacy
invasions as described in each story (Section 3.2). The results are reported
in Table 4. While we asked our participants about what would the user in each
story think and what happens next, they mainly reported on feelings and
protective actions. The majority of the participants believed that the users
of these stories would feel negative about the experience. This was reflected
by the use of terms such as “angry", “annoyed", ‘upset", “incandescent",
“spied on", “not in-control", “not empowered", “worried", “concerned",
“tracked", “bothered", “shocked", “irritated", etc. For instance, one of the
participants wrote: “Alex sees the emails and is concerned about their phone
monitoring what they do. Although this isn’t the first time they’ve received
ads about things they’ve recently searched or downloaded, the more personal
and sensitive aspect of this application has them worried. This application
captures information about their health, Alex views this information as
sensitive and personal and doesn’t feel comfortable with any aspect of this
being shared. …".

In terms of the actions that the users of these stories might take, our
participants came up with multiple ideas. In the case of the use of the period
tracking app and baby clothing/toys ads, the majority of the participants
suggested that Alex would uninstall the app or switch to a new app with better
SP features. Four participants said that Alex would review the app settings or
their Google privacy settings and make modifications.

In the case of the second story, Morgan searching the internet for menopause
symptoms, seven participants said that Morgan should review their browser
settings and/or opt-out of cookie notices for a more private search
experience. Six participants said that this experience would make Morgan more
cautious and they might limit or stop their use of internet search. Three
participants mentioned that Morgan is likely from an older generation and is
less confident and equipped to take any protective actions. Alex and Morgan
were referred to mainly as she, but sometimes as he in these stories and one
time non-binary.

In the case of Ashley and the shared use of a smart breast pump app, eight
participants envisioned that Ashley would review the settings and modify the
access of their partner. Six said that Ashley would stop using the device and
app altogether, another six said that they will have a discussion with their
partner about app privacy setting and/or their goals for feeding the baby, and
another six said that they will seek help from GP, family, friend, etc. to
support their breastfeeding goals. As one can see, the majority of these
protective actions are related to protecting the privacy of the users. Ashley
was mainly assumed female in the stories, one time male and one time non-
binary.

Previous research (e.g., [23]) suggests that security and privacy-protective
actions are closely associated with (and predicted by) particular negative
feelings in the context of online tracking on websites. Our results are in
line with those findings where the majority of the SCM’s participants describe
negative feelings for the story actors and then suggest concrete protective
actions. While we did not directly ask about the feelings of our survey
participants, 65% of the participants chose “share user information" as the
main disadvantage of such technologies. When we analysed our data, we found
out that those participants also chose more items for protective actions (both
in general and for FemTech, Fig. 2). While further studies and more
participants are needed to confirm these results, we believe that the
participant’s protective actions in these intimate health digital technologies
are also associated with their negative feelings.

Table 5: Desired security and privacy features (Survey) Security and Privacy Feature | User %
---|---
Security mechanisms | 30
(password, encryption, biometrics, anonymisation, etc.) |
Transparency, enforcement guarantee | 28
User consent, user control | 24
No idea, not important, not possible | 20
Not share/sell, local storage | 16
Minimal data collection | 7
Trusted entities | 3
By design (security, privacy, expert, women) | 3
Others (cloud backup, education) | 3

###  4.3 Expected Security and Privacy Features

We concluded our survey by asking what types of SP features would the
participants like to see in these technologies. This was an open-text
question. We analysed the responses and extracted multiple desired features,
as shown in Table 5. 30% of our participants suggested various forms of
security mechanisms including multi-factor authentication, encryption,
biometrics, and anonymisation. For instance, one participant said: “User login
details should be handled securely, use multi-factor authentication for
account set up and potentially for login if the app handles highly sensitive
data. An easy to understand privacy policy that is clearly displayed to the
user and outlines that user data isn’t shared should alleviate user concerns
regarding the privacy of their data".

28% participants expected to see more transparency at various stages of data
collection, processing, transferring and sharing in FemTech. One participant
said: “I think they should be transparent about their algorithms and data
sharing e.g.,open-source code". Another said: “It should be clearer who is
viewing your data and how this will be used". Another one said: “[there should
be] Full privacy guarantees from companies". 24% of the participants said user
control and consent should be included in these technologies. Two example
comments include: “I think the app should clearly explain the use of data to
user and provide easy opt out options" and “A clause to tick if you don’t wish
to share information with third parties". 20% of the participants said they
either don’t know or it is not important, or it is not possible to protect
user data in such technologies. A participant said: “No such thing if someone
can hack the White House they can certainly hack these things". 16% of the
participants said that this data should not be shared or sold. For example,
one said: “I’m not sure that there can ever be 100% security/trust, but
avoiding selling data to shady third parties is a must."

Other suggested methods include minimal data collection and local storage,
anonymisation, development of such products by trusted entities, focusing on
the design phase, and others. For example, one said: “Not requiring irrelevant
personal information while signing up to the application. For example, there’s
no point for your home address information to be required while signing up for
a period tracking application." Another one said: “Everything should be backed
up on the cloud anonymous and only the user should access to it". Another
comment said: “I would feel a lot more secure if something was made by the NHS
or something similar, at least they can be held to account. Generally, I want
more specific guarantees that data isn’t being sold and/or what the app
publisher does with the data". Some other participants said that “security
researchers", “other experts", and “women" should be involved in the design
processes.

Similarly, in the SCM activity and our interviews, the participants recognised
the level of sensitivity of the data and the required safeguarding mechanisms
and protective actions. In both survey and SCM studies, our participants
suggested concrete and effective SP methods to be embedded in these
technologies. For instance, in our interviews, the participants believed that
more safeguarding mechanisms should be in place to protect this data. The same
SP features presented in Table 5 came up in the interviews e.g., the use of
strong passwords, user consent and transparency in the policies, and not
sharing the data with third parties. When asked for concrete security ideas
for SP protection, two of our participants suggested similar mechanisms
adopted by “banking systems" e.g., second-factor authentication and biometrics
since they believed that this data is “as sensitive" or “even more sensitive"
than financial records. For example, one of our participants said: “My sex-
related data is definitely more sensitive than my financial data. It is very
personal and should be protected with the same SP features of banking systems
or even more". These suggested SP features are particularly interesting since
they are distant from those that users are using in practice. As reported in
Fig. 2, our participants do not use any significant technology-based
protective method for FemTech. Indeed, the most popular method is providing
minimal user data into these solutions – a method that is only applied by less
than a quarter of our participants. The lack of appropriate SP methods in the
current practices and its impact on user perception and practice are clearly
recognised across different sections of our studies.

Figure 3: Examples of drawings of the ecosystem by participants in the
Interviews

##  5 Discussion

In this section, we discuss the results of our mixed-method study and
introduce a number of approaches to consider in the design and development of
these systems. Our results show that:

(i) Users recognise that FemTech data is sensitive and they feel negative
about the (potential) risks of these technologies. We surveyed a plurality of
people and used open and creative methods for them to explore capacity,
choice, and action in relation to this intimate digital health ecosystem. What
emerged shows that there is both a need and an opportunity to improve current
practices and lessen risks. An example of an approach for doing that includes
accounting for human values throughout the design process. While this approach
may introduce more challenges for the developers, a ‘Value Sensitive Design’
(VSD) [30, 31] inspired approach can contribute to improve user experience in
the context of FemTech. VSD is an approach that has been successfully used in
the design of SP features of IT systems including security features and
privacy-enhancing tools in web browsers [48, 75] and ethical design of AI and
ML e.g., in conversational agents [72]. Similar work has gone into VSD and
user groups such as older adults [72] and children [76].

(ii) Users are not sure how these systems work, what are the data flow and
recipients, and what are their rights in the law. We suggest SP by design to
be regarded as a safeguarding paradigm in the design and development of these
products. Security by design refers to a series of processes and approaches in
the life-cycle of the system and calls for the design and development of
software products and capabilities to be foundationally secure. Similarly,
privacy by design calls for privacy to be taken into account throughout the
whole engineering process of a system. The seven foundational principles of
privacy by design are (1) Proactive not reactive; Preventative not remedial,
(2) Privacy as the default, (3) Privacy embedded into design, (4) Full
functionality – positive-sum, not zero-sum, (5) End-to-end security– life-
cycle protection, (6) Visibility and transparency, and (7) Respect for user
privacy [20]. When the above principles are incorporated in the system’s life-
cycle, they improve the chances of treating each system case by case; as
opposed to developing a general system following general methods e.g., threat
modelling tools, where key threats to these sensitive systems might not be
identified. Some of the above principles were partially mentioned by our
participants as their preferred SP features of FemTech (Table 5). Accordingly,
incorporating SP by design in FemTech systems can significantly improve these
technologies; helping to consider the ‘actual’ end user rather than the
‘abstract’ user throughout the system life-cycle.

(iii) Participants suggest reasonable and effective SP methods to be embedded
in these technologies. These results emphasise the extent to which our
participants, i.e. users, have a somewhat confused understanding of how they
can be in control of such systems and data and/or are not equipped with the
tools and skills to protect themselves from the potential harms. We advocate
for employing participatory threat modelling and incorporating marginalised
populations’ experiences in the modelling of the threats of a system [62, 63].
By exploring the range of harms in FemTech, we highlight how the complexity of
these risks can make them difficult to be identified by traditional tools and
methods. For instance, the nature and dimensions of such threats are sometimes
seen as side concerns [61]. Additionally, by conducting our user studies, we
have concluded that these risks and harms can indeed be recognised by the
participants. For instance, sharing user information was the top disadvantage
of FemTech as reported by 65% of the survey’s participants, a risk that would
not be treated as an “attack” in conventional cybersecurity literature [61].
The confusion that was expressed by our participants across the three studies
of how these systems work (e.g., data access and flow) clearly conflicts with
the way these technologies are advertised; i.e. empowering the user.
Contrarily, these sensor-enabled and smart devices and apps create a new range
of threats and risks that did not exist before. Hence, the classic threat
modelling tools are not responding to them. Slupska, Duckworth, and Neff [64]
discuss how women, particularly women of colour, and queer people are targets
of complex harms disproportionately e.g., via online harassment, stalking, and
image-based sexual abuse. Threat models are, however, the result of the
worldview of security experts as opposed to the lived experiences of the end
users. Accordingly, such threats are often dismissed as a “privacy concern”
outside the scope of real cybersecurity research [61].

Several recent papers (e.g., [44]) have shown and discussed how the gray area
in different laws (general data protection, health, and medical systems and
devices) and lack of coverage for FemTech data provide opportunities to
exploit the user data. The ‘Data Protection by Design and by Default’ (DPbD)
is defined by the GDPR as a requirement for the service providers to put in
place appropriate technical and organisational measures to implement the data
protection principles effectively and safeguard individual rights [4]. The ICO
website provides a series of guidelines to help the service providers to
practice the DPbD. However, even within the available guidelines (which are
failing to include FemTech data), developers fail to practice them and require
support to help them meet the DPbD requirement imposed by GDPR [25]. We invite
the academic researchers as well as industrial and regulatory bodies to
proactively work on the SP of FemTech to enable the delivery of more privacy-
preserving products for the end user.

##  6 Conclusion

The variety of products (websites, IoT devices, mobile apps, etc.) in the
FemTech ecosystem and the data interaction with diverse end users and other
stakeholders create a range of new and complex harms. This introduces more
challenges in establishing user agency in these socio-technical systems. In
this paper, we explore these issues via an empirical enquiry composed of three
mixed-methods user studies in the UK. The results of our online survey (n=102)
highlight that 65% of our participants recognised that sharing user
information is a disadvantage of these technologies. The results of our SCM
reveal that our participants (n=17) mainly felt negatively about such data
sharing and its consequences. In addition, the results of our interviews (n=6)
provide an indication that the users identified the complex nature of the
FemTech data and systems. Throughout all these studies, our participants also
expressed uncertainty in understanding these systems and risks as well as
their rights regarding the SP protection that they need to get from other
stakeholders e.g., lawmakers, service providers, and the government.

We discussed the incorporation of the current methods such as VSD and
participatory threat modelling for including marginalised populations’
experiences in the design and implementation of these sensitive systems. By
integrating such concepts and methods into the general guidelines and
approaches for SP by design, the sector can build the next generation of
FemTech solutions to be privacy-preserving and secure.

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##  Appendix A User Study Template for Online Survey

[General description]

[1-3: Demo questions]

4\. In your own words, please describe what are FemTech and what do they do?

5\. What forms of FemTech do you use (or have used)? Please give examples and
how and when do (did) you use them?

6\. How did you learn about these technologies? (multiple choices)

  * •

Personal research

  * •

Online ad

  * •

Traditional ad (leaflet, …)

  * •

Family/Friend

  * •

Colleague

  * •

School/University

  * •

NGO/Charity

  * •

Health centre/clinic or NHS

  * •

TV/Radio

  * •

Others (please name)

7\. What type of data do you enter in these technologies about yourself (e.g.
name, email, medical records, sexual activities, etc.)? Please list all.

8\. What type of data do you enter in these technologies about yourself?
(multiple choices)

  * •

Name

  * •

Photo

  * •

Age/Gender

  * •

Contact info (mobile, email, ads)

  * •

Social media (Facebook, Instagram, Twitter, …)

  * •

Lifestyle (weight, height, diet, exercise, sleep, …)

  * •

Period info (start, end, cycle days, evaluation days, …)

  * •

Sexual activities (type, date, contraceptive, orgasm, …)

  * •

Reproductive organs (cervical mucus, … )

  * •

Pregnancy info (test result, medical info, weight gain, body change, …)

  * •

Baby info (nursing, sleep cycles, …)

  * •

Physical symptoms (headache, insomnia, constipation, …)

  * •

Emotional symptoms (happy, upset, energised, tired, anxious, …)

  * •

Medical info (medication type, dose, blood pressure, …)

  * •

Others (please name)

9\. Why do you use such technologies? Please explain.

10\. In your opinion, what are the benefits of using such technologies? Please
explain.

11\. In your opinion, what are the benefits of using such technologies?
(multiple choices)

  * •

They are cost-effective

  * •

Everyone can have access to them

  * •

They are accurate

  * •

It is easy to use them

  * •

They can be personalised

  * •

They are non-intrusive to body

  * •

They increase my knowledge about my body

  * •

Others (please specify)

12\. In your opinion, what are the disadvantages of using such technologies?
Please explain.

13\. In your opinion, what are the disadvantages of using such technologies?
(multiple choices)

  * •

They are expensive

  * •

They are not accessible to all user groups

  * •

Using such technologies are not easy for certain users

  * •

They are not accurate

  * •

They only work for certain user groups and have bias

  * •

They share user information with third parties or sell to them

  * •

Others (please specify)

14\. Have you (or someone you know) ever experienced an unpleasant incident as
a result of using such technologies? (e.g. unwanted pregnancy or stress of
losing fertile days). Please explain.

15\. Who do you think has access to your data when using FemTech? (multiple
choices)

  * •

Your GP/NHS

  * •

Your partner

  * •

Your family/friend/co-worker

  * •

Your employer

  * •

The company making the app/device

  * •

Operating system of mobile/PC (e.g. Apple, Google. Microsoft)

  * •

Third parties such as medical clinics and insurance companies

  * •

Third parties such as advertising companies

  * •

The government

  * •

The public

  * •

Others (please name)

16\. Have you (or someone you know) ever experienced a cybersecurity/privacy
incident as a result of using such technologies? (e.g. sharing your data
without consent). Please explain.

17\. What do you generally do to protect your online privacy and security?
Please explain.

18\. What to you specifically do to protect your FemTech privacy and security?
Please explain.

19\. In your opinion, what sorts of security and privacy features should be
included in such technologies to make you use them without risk and fear?
Please explain.

20\. If you have any other comments about FemTech, please write them here.