Elina Salla, Project coordinator, M3S, University of Oulu

We know more than before about the experiences of neurodivergent women, but objective longitudinal data on their everyday lives remains limited. Wearable and sensor-based technologies could help make visible phenomena that are easily missed in research and healthcare encounters, such as accumulated strain, recovery and sleep. For this to be meaningful, technologies need to be developed on the basis of representative data, and measurement data needs to be interpreted in relation to the individual’s own experience.

The everyday experiences of neurodivergent women have remained partly outside the scope of research, healthcare and technology development (Attoe & Climie, 2023). Although understanding of neurodivergence has increased in recent years, research evidence, clinical practices and technological solutions still rely partly on a limited understanding of how neurodivergence appears in everyday life. This affects who is identified, what kind of information is collected and what kinds of solutions are developed. In ADHD, for example, girls and women are often identified later than boys, and their symptom profiles may differ from the models through which ADHD has historically been studied and diagnosed (Young et al., 2020).

Current knowledge is still largely based on questionnaires, interviews and other subjective assessments. These forms of knowledge are necessary, because neurodivergent people’s own experiences are central to understanding their wellbeing and support needs. At the same time, there is considerably less objective longitudinal data on everyday life. We therefore know relatively little about how everyday patterns develop over time, how they relate to each other and how they are reflected in functioning and wellbeing.

Health technologies, including smartwatches, smart rings and bed sensors, make it possible to examine these patterns from another perspective. Their value is in the possibility of following change over time. Longitudinally collected data can complement experiential knowledge and help identify variation that does not become visible in single measurements or healthcare appointments. Used carefully, these technologies could support a more comprehensive understanding of neurodivergent women’s wellbeing and health (Olinic et al., 2025).

The use of such technologies also requires caution. If measurement technologies, research designs or analytical methods are based on data that does not represent the experiences of neurodivergent women, existing biases may be strengthened. Underrepresentation in research datasets and in the development of measurement solutions means that the information produced by these tools remains incomplete. Technology may then reproduce the same limitations that it is expected to help address.

More research is needed on what sensor-based measurements actually reflect in the everyday lives of neurodivergent women, how this information should be interpreted and how it can be used in research and healthcare.

References

Attoe, D. E., & Climie, E. A. (2023). Miss. Diagnosis: A systematic review of ADHD in adult women. Journal of Attention Disorders, 27(7), 645–657. https://doi.org/10.1177/10870547231161533

Olinic, M.-S., Stretea, R., & Cherecheș, C. (2025). Wearables in ADHD: Monitoring and intervention—Where are we now? Diagnostics, 15(18), 2359. https://doi.org/10.3390/diagnostics15182359

Young, S., Adamo, N., Ásgeirsdóttir, B. B., Branney, P., Beckett, M., Colley, W., … Woodhouse, E. (2020). Females with ADHD: An expert consensus statement taking a lifespan approach providing guidance for the identification and treatment of attention-deficit/hyperactivity disorder in girls and women. BMC Psychiatry, 20, 404. https://doi.org/10.1186/s12888-020-02707-9