Epistemic (in)justice in self-monitoring platforms for mental health

It is well known that in psychiatry the relationship between medical professional and client/ patient is structurally asymmetric. In the past, psychiatrists sometimes disregarded patients’ experiences and suggestions on the grounds of their medical authority. Patients were deemed to lack understanding of their own illness or disorder. This dismissal of patients’ knowledge can be considered as an instance of epistemic injustice, that is, injustice done to someone in their capacity as knower (Fricker, 2007). With the rise of client/patient-led organizations since the 1980s (such as the Hearing Voices Network, Mind Platform and Mind Ypsilon), clients/patients, family, informal caregivers (and professionals) aim at minimizing this type of injustice. Through digitalization and internet 2.0, people with mental health problems today can increasingly assert their voices and knowledge through online platforms , which indeed may strengthen their position as knower. In addition to this communicative function, which contributes to (knowledge) community building, digitization is also increasingly used within psychiatry to design online self-monitoring platforms. For instance, an app on a smartphone that can be used by people diagnosed with schizophrenia which can help to predict a relapse and as such can help people to manage their disorder (Henson et al, 2021). These kinds of apps are based on digital phenotyping: the continuous and in situ collection of “passive” data (quality of sleep, heart rate (variation), intonation, pedometer, geolocation, activity on social media), and “active” data (surveys, questions) through personal digital devices.
Through AI a specific “digital phenotype” can be identified, which is claimed to have the potential to facilitate personalized care and cure. In our paper we will discuss how this data-driven psychiatry could impact epistemic justice in (clinical) care. Since these kinds of digital applications involve self-monitoring, they are presented as having the potential to strengthen the position of clients/patients. But on the other hand, if these apps are predominantly based on “passive” data, then we can question whether the knowledge and experience of the client/patient still matters. If the “active” experience of clients/patients is downplayed one could say that in such cases clients/patients in their capacity of knowers are wronged by the machine/algorithm. In our paper we will first briefly present a digital phenotyping project that is currently being done at the Academic Collaborative Center for Digital Health & Mental Wellbeing at Tilburg University. Through this case study we wish to explore the possible tension between the kind of self-knowledge generated by self-monitoring platforms, on the one hand, and intuitive and sensorial (self-)knowledge, on the other hand.