Trinity College Dublin, Imperial College London, National Health Service UK
Literature Review, Theory Development, Participatory Design, Design Sketching, Graphic Design, Prototyping, Mobile, Web & Backend Development, Clinical Deployment, Study Management, Qualitative & Quantitative Data Analysis
Perinatal wellbeing is a public health priority with significant and long-lasting intergenerational effects. Every year, up to 15% of women are diagnosed with depression during pregnancy or within a year of giving birth. Perinatal depression affects women's quality of life, birth outcomes and children's emotional, cognitive, behavioural and social development. Suicide is the leading cause of maternal mortality within the United Kingdom (UK).
Treatment and support needs to be made available to those who require it, but in order to do so, effective programs of assessment and avenues of disclosure must be in place. In the context of the UK's National Health Service (NHS), mental health screening during pregnancy is currently carried out verbally and using paper-based questionnaires completed in waiting rooms. However, it is estimated that at least 50% of perinatal depression cases go undiagnosed. Although almost all midwives report asking women about their mental health during their first appointment, as few as one in ten women recall being asked.
The work of my doctoral dissertation
sought to support maternal mental health and wellbeing on a population scale, by establishing a case for the feasibility and design of mobile applications to support the self-report of psychological wellbeing and depression during pregnancy, facilitating access to care and support for those in distress.
Conducted under the supervision of Dr. Gavin Doherty at Trinity College Dublin, this transdisciplinary project asked how technology shapes the self-report of wellbeing, how users engage and are engaged in the honest disclosure of mental health concerns, how health professionals might act upon reports of psychological wellbeing, and how technology might contribute to our evolving conception of wellbeing and its pursuit.
This was a highly complex context for research and design, combining the individual significance of wellbeing during pregnancy, the real-world and long-term use of technology by an at-risk user group, a public health system's need to efficiently distribute resources, midwives' diverse work practices, social expectations, societal stigma, and researchers' motivations for data collection.
This work therefore entailed several years of close collaboration between HCI and public health researchers, pregnant women and a variety of health professionals including midwives, culminating in the first longitudinal clinical deployment of a mobile technology for antenatal mental health screening.
Tracing an idea from concept to reality, this work contributes knowledge concerning the conception, theory, measurement and design of wellbeing, self-report, user engagement and ecological momentary assessment technologies, including;
- A contribution to knowledge in the form of an enhanced understanding of design to support wellbeing in the context of antenatal mental healthcare; informed by qualitative analyses of the needs, values and motivations of women and health professionals, grounded in knowledge of the conception, theory and measurement of wellbeing, and realised in the design of BrightSelf — a mobile application and online platform for the self-report of wellbeing and depression during pregnancy.
- An understanding of the design of self-report technologies sensitive to the importance of how we both live and think about experience with respect to multiple time-frames; articulated in the form of a framework of multiple self-concepts of a sufficiently simple character to function as a practical heuristic and sense-making tool, linked to the features of the design space for self-report technologies, and expressed in terms of implications for design in the context of pregnancy.
- An improved understanding of the conception, theory, measurement and design of user engagement; informed by systematic literature review, augmented by women's and health professionals' reflections on the use of technology during pregnancy, actualised in the design of a protocol for the self-report of antenatal wellbeing and depression, and employed to support analysis of the results of a feasibility study with a randomised controlled trial design — ultimately contributing initial evidence for the design and feasibility of mobile applications to engage women in the self-report of wellbeing and depression, extend care to under-served and at-risk groups, enable longitudinal, momentary and retrospective data collection, overcome stigma, support disclosure, and foster trust between patients and health professionals.
Using BrightSelf, 355 pregnant women attending 14 NHS midwifery clinics across England provided 2,280 momentary and retrospective reports of their wellbeing in daily life over a period of 9 months. Women installed and engaged with this mobile application regardless of their age, education, number of children, marital status, employment status, past diagnosis of depression or level of wellbeing.
Thirty-nine women reported a risk of depression, self-harm or suicide using this technology and received immediate midwife support. Two-thirds of participants who received support in this way registered no risk of depression according to the standard screening methods employed in-clinic at baseline, and women spoke positively of the experience;
Through extensive description of this complete cycle of literature review, theory development, design research, technology and protocol design, clinical deployment, data analysis and reflection, this doctoral dissertation
presents a new understanding of the feasibility and design of mobile technologies for public health screening and research.
Doherty, K. (2019, March). Designing the Self-Report of Wellbeing in Pregnancy. Human-Computer Interaction PhD Thesis submitted to Trinity College Dublin. PDF
Doherty, K., Balaskas, A. & Doherty, G. (2020, August). The Design of Ecological Momentary Assessment Technologies. Interacting with Computers. PDF LINK
Doherty, K. & Doherty, G. (2019, January). Engagement in HCI: Conception, Theory and Measurement. ACM Computing Surveys (CSUR), 51(5), 99:1-99:39. PDF LINK
Doherty, K. & Doherty, G. (2018, February). The Construal of Experience in HCI: Understanding Self-Reports. International Journal of Human Computer Studies (IJHCS), 110, 63-74. PDF LINK
Doherty, K., Barry, M., Marcano-Belisario, J., Morrison, C., Car, J. & Doherty, G. (2019, November). Personal Information and Public Health: Design Tensions in Sharing and Monitoring Wellbeing in Pregnancy. International Journal of Human Computer Studies (IJHCS), 135, 102373. PDF LINK
Doherty, K., Barry, M., Marcano-Belisario, J., Arnaud, B., Morrison, C., Car, J. & Doherty, G. (2018, November). A Mobile App for the Self-Report of Psychological Well-Being During Pregnancy (BrightSelf): Qualitative Design Study. JMIR Ment Health, 5(4). PDF LINK
Barry, M., Doherty, K., Marcano-Belisario, J., Car, J., Morrison, C., & Doherty, G. (2017, May). mHealth for Maternal Mental Health: Everyday Wisdom in Ethical Design. CHI'17 (pp. 2708-2756). ACM. PDF LINK
Barry, M., Doherty, K., Doherty, G. (2016, July). Communicating “What's Not Said”: Mobile Apps for Psychological Wellbeing. International Journal of Sociotechnology and Knowledge Development (IJSKD), 8(3), 46-55. LINK
Doherty, K., Marcano-Belisario, J., Cohn, M., Mastellos, N., Morrison, C., Car, J., & Doherty, G. (2019, May). Engagement with Mental Health Screening on Mobile Devices: Results from an Antenatal Feasibility Study. CHI'19. ACM. PDF
Cohn, M., Mastellos, N., Doherty, K., Marcano-Belisario, J., Doherty, G., O'Donoghue, J., Majeed, A., & Car, J. (2017, October). Tablet Computers for Implementing NICE Antenatal Mental Health Guidelines - Feasibility Study. Sowerby e-Health Symposium.
Marcano-Belisario, J., Doherty, K., O'Donoghue, J., Ramchandani, P., Majeed, A., Doherty, G., Morrison, C. & Car, J. (2017, May). A Bespoke Mobile Application for the Longitudinal Assessment of Depression and Mood During Pregnancy: Protocol of a Feasibility Study. BMJ Open, 7(5). PDF LINK