Sharing personal data about daily behaviours and mental health can be useful for clinical monitoring, peer-support and science, but such disclosure may also bring negative consequences. How can we design open-access platforms that are beneficial for individuals and society?
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Background:
Passive data collected from smartphones, such as time spent on screen, location and text messages can be used for the assessment of affective states and behaviours [1]. Such personal and detailed data can be employed as a tool for self-reflection, an approach often used for encouraging behavioural change. Further uses of the data may involve opening the access of the self-tracked data to clinicians, peers, family members or researchers [2]. However, such sensitive data contains intimate details of the individuals' lives, which can result in uncomfortable disclosures [3]. A major issue with data containing mental health assessments is the social stigma and discrimination that may come with it [4]. This often leads to the reluctance to be part of behavioural monitoring initiatives, even though they could be beneficial for the understanding of mental illnesses.
Therefore, the contribution of this PhD will come in the form of a conceptual framework [5] with design guidelines that can inform the development of future open access platforms. The methodological approach involves putting potential participants of such platforms in the center of the design process. Through qualitative and quantitative methods, this PhD aims at understanding their motivations, concerns and preferences when it comes to allowing the use of behavioural monitoring for research. The target group consists of young adults, who were found to be underrepresented in existing platforms for health surveillance. Young mental health research and care could be aided by behavioural monitoring, however, the lack of acceptance is a barrier for recruitment [6]. With the results of this research, hopefully, it will be possible to better understand what is missing to make participation more attractive to younger segments of the population, without compromising their autonomy and privacy [7].
Project objectives:
- To identify barriers and enabler for participation on behavioural monitoring research platforms
- To investigate design directions that could contribute to the acceptance of such platforms
- To organise design guidelines in a conceptual framework for future platforms development
References:
[1] Darius A Rohani, Maria Faurholt-Jepsen, Lars Vedel Kessing, and Jakob E Bardram. 2018. Correlations Between Objective Behavioral Features Collected From Mobile and Wearable Devices and Depressive Mood Symptoms in Patients With Affective Disorders: Systematic Review. JMIR Mhealth Uhealth 6, 8 (13Aug 2018), e165.
[2] Ross JS and Krumholz HM. 2016. Open access platforms for sharing clinical trial data.JAMA316, 6(2016), 666.
[3] Justin Petelka, Lucy Van Kleunen, Liam Albright, Elizabeth Murnane, Stephen Voida, and Jaime Snyder. 2020. Being (In) Visible: Privacy,Transparency, and Disclosure in the Self-Management of Bipolar Disorder. InProceedings of the 2020 CHI Conference on Human Factors in ComputingSystems. 1–14
[4] Christina Kelley, Bongshin Lee, and Lauren Wilcox.2017. Self-tracking for mental wellness: understanding expert perspectives and student experiences. In Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems. ACM, 629–641.
[5] Gabriela Marcu, Jakob E Bardram, and Silvia Gabrielli.2011. A framework for overcoming challenges in designing persuasive monitoring and feedback systems for mental illness. In2011 5th International Conference on Pervasive Computing Technologies for Healthcare (Pervasive Health) and Workshops. IEEE,1–8.
[6] Camille Nebeker, John Harlow, Rebeca Espinoza Giacinto, Rubi Orozco-Linares, Cinnamon S. Bloss, and Nadir Weibel. 2017. Ethical and regulatory challenges of research using pervasive sensing and other emerging technologies: IRB perspectives. AJOB Empirical Bioethics 8, 4 (2017), 266–276.
[7] John Rooksby, Alistair Morrison, and Dave Murray-Rust. 2019. Student Perspectives on Digital Phenotyping: The Acceptability of Using SmartphoneData to Assess Mental Health. InProceedings of the 2019 CHI Conference on Human Factors in Computing Systems. ACM, 425.