User Risk Perceptions and Protective Actions in FemTech in the UK and Iran

The digitalisation of the reproductive body has engaged myriads of cutting-edge technologies to support people in understanding and managing their intimate health. Generally understood as female technologies (FemTech), these products and systems collect a wide range of intimate data, predominantly related to sexual and reproductive health. This sensitive data is then processed, transferred, saved, and shared with other parties. The data-hungry nature of this industry and the lack of proper safeguarding mechanisms, standards, and regulations for this vulnerable data can lead to complex harms or diminished user agency. In this paper, we adopted mixed methods, including an online survey and a Story Completion Method (SCM), to explore user understanding of the security and privacy (SP) of these technologies. We conducted online user studies in two countries: the UK and Iran, in English and Farsi (Persian), respectively. We recruited 102 UK and 130 Iranian participants for our surveys, and 17 UK and 34 Iranian participants for our SCM studies. Our findings show that while users can speculate on the range of harms and risks associated with these technologies, they are not necessarily presented and equipped with the technical skills to protect themselves. We identified a larger gap in the Iranian group compared to the UK group, which can be attributed to factors such as differences in data protection regulations between the two countries. This comparative study highlights how disparate data protection frameworks and unique cultural contexts can shape user vulnerability to FemTech risks. We discuss how participatory threat modelling and Security and Privacy by Design are critical to protecting users in these sensitive systems.

Authors

Institutions

Publication Details

Journal
ACM Transactions on Social Computing
Published
2026-05-12
DOI
https://doi.org/10.1145/3816003
Primary Topic
Innovative Human-Technology Interaction
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

User Risk Perceptions and Protective Actions in FemTech in the UK and Iran

Maryam Mehrnezhad, Ehsan Toreini, Teresa Almeida
ACM Transactions on Social Computing
Innovative Human-Technology Interaction
article

User Risk Perceptions and Protective Actions in FemTech in the UK and Iran

Maryam Mehrnezhad, Ehsan Toreini, Teresa Almeida
article en

Abstract

The digitalisation of the reproductive body has engaged myriads of cutting-edge technologies to support people in understanding and managing their intimate health. Generally understood as female technologies (FemTech), these products and systems collect a wide range of intimate data, predominantly related to sexual and reproductive health. This sensitive data is then processed, transferred, saved, and shared with other parties. The data-hungry nature of this industry and the lack of proper safeguarding mechanisms, standards, and regulations for this vulnerable data can lead to complex harms or diminished user agency. In this paper, we adopted mixed methods, including an online survey and a Story Completion Method (SCM), to explore user understanding of the security and privacy (SP) of these technologies. We conducted online user studies in two countries: the UK and Iran, in English and Farsi (Persian), respectively. We recruited 102 UK and 130 Iranian participants for our surveys, and 17 UK and 34 Iranian participants for our SCM studies. Our findings show that while users can speculate on the range of harms and risks associated with these technologies, they are not necessarily presented and equipped with the technical skills to protect themselves. We identified a larger gap in the Iranian group compared to the UK group, which can be attributed to factors such as differences in data protection regulations between the two countries. This comparative study highlights how disparate data protection frameworks and unique cultural contexts can shape user vulnerability to FemTech risks. We discuss how participatory threat modelling and Security and Privacy by Design are critical to protecting users in these sensitive systems.

ACM Transactions on Social Computing
Royal Holloway University of London (GB), University of Surrey (GB), Instituto Superior de Educação e Ciências (PT)
Gender equality
Openalex Percentile: Top 4%
Innovative Human-Technology Interaction
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.