Decision Making and the Longitudinal Monitoring of Mood

"There is a clinical need to better understand the relationships between mental health and cognitive processes in humans. Deficits in associative memory and reinforcement learning processes have been documented in depression and anxiety (e.g., Lawlor et al., 2019; Paulus & Yu, 2012). Furthermore, research suggests that differences in performance on such tasks may also be able to differentiate between disease phenotypes (e.g., Murphy et al., 2001). This project aims to identify novel cognitive biomarkers for key symptoms of anxiety and depression disorders, which could be used either for understanding treatment targets or as useful treatment response indicators.
I will explore human decision-making processes through the longitudinal monitoring of mood states in naturalistic environments. Specifically, affective state, associative memory, and decision-making processes will be monitored using a mobile application, and modelled using computational techniques. There is currently a lack of cognitive assessment tools for both mood state and decision-making performance that can be successfully applied outside of laboratory environments. In avoiding the artificial mood manipulations traditionally used for this type of research, this project would strengthen the value of previous work in this field through development of a novel scientific tool (Gillan & Rutledge, 2021), which could also be repurposed into a therapeutic tool.
The aim of this project would be to develop a gamified decision-making task within a mobile application that also records ecological momentary assessment of mood states and can assess associative memory. Computational modelling techniques (for example Bayesian network models or causal inference methods) can then be applied onto the data collected through the longitudinal monitoring of participants. Therefore, the development of an effective mobile monitoring application will be key to the success of this project. As such, the project will involve participant engagement throughout the design process and trial stages to understand usability requirements through iterative design. Although initial participant studies are likely to utilise analogue populations, interviews and/or focus groups could be held with patient populations during the development process. Accordingly, smaller scale fast-fail study designs will be primarily used to determine what elements of affective state change will be feasible to detect. The monitoring application will likely employ shortened versions of existing psychometrically validated measures such as the PANAS (Watson et al., 1988)/ I-PANAS-SF (Thompson, 2007), the Daily Stress Inventory (Brantley et al., 1987), and the Weekly Stress Inventory Short-form (Brantley et al., 2006). There may also be potential for collaboration with Cambridge Cognition to utilise alternate cognitive assessment measures, however this is yet to be confirmed.
Although the timeline of this project is still being planned and likely to adapt as the project progresses, the first year will include the initial app development stages and fast-fail trials. As the project develops, larger-scale multi-participant studies will be conducted on analogue populations first, with potential for assessment on clinical populations towards later stages of the project. Computational modelling will be applied in tandem throughout all stages of the project to understand the complex interactions between outcome measures and decision-making performance. Through longitudinal assessment of decision-making in externally valid settings the evaluation of behavioural parameters will be more reliable and accurate for further application into clinical assessment frameworks. Therefore, this work will be important to further understanding of cognitive biomarkers for certain mental health disorders."

Impact on Health and Care
The CDT primarily addresses the most pressing needs of nations such as the UK - namely the growth of expenditure on long term health conditions. These conditions (e.g. diabetes, depression, arthritis) cost the NHS over £70Bn a year (~70% of its budget). As our populations continue to age these illnesses threaten the nation's health and its finances.

Digital technologies transforming our world - from transport to relationships, from entertainment to finance - and there is consensus that digital solutions will have a huge role to play in health and care. Through the CDT's emphasis on multidisciplinarity, teamwork, design and responsible innovation, it will produce future leaders positioned to seize that opportunity.

Impact on the Economy
The UK has Europe's 2nd largest medical technology industry and a hugely strong track record in health, technology and societal research. It is very well-placed to develop digital health and care solutions that meet the needs of society through the creation of new businesses.

Achieving economic impact is more than a matter of technology. The CDT has therefore been designed to ensure that its graduates are team players with deep understanding of health and social care systems, good design and the social context within which a new technology is introduced.

Many multinationals have been keen to engage the CDT (e.g. Microsoft, AstraZeneca, Lilly, Biogen, Arm, Huawei ) and part of the Director's role will be to position the UK as a destination for inwards investment in Digital Health. CDT partners collectively employ nearly 1,000,000 people worldwide and are easily in a position to create thousands of jobs in the UK.

The connection to CDT research will strongly benefit UK enterprises such as System C and Babylon, along with smaller companies such as Ayuda Heuristics and Evolyst.

Impact on the Public
When new technologies are proposed to collect and analyse highly personal health data, and are potentially involved in life or death decisions, it is vital that the public are given a voice. The team's experience is that listening to the public makes research better, however involving a full spectrum of the community in research also has benefits to those communities; it can be empowering, it can support the personal development of individuals within communities who may have little awareness of higher education and it can catalyse community groups to come together around key health and care issues.

Policy Makers
From the team's conversations with the senior leadership of the NHS, local leaders of health and social care transformation (see letters from NHS and Bristol City Council) and national reports, it is very apparent that digital solutions are seen as vital to the delivery of health and care. The research of the CDT can inform policy makers about the likely impact of new technology on future services.

Partner organisation Care & Repair will disseminate research findings around independent living and have a track record of translating academic research into changes in practice and policy.

Carers UK represent the role of informal carers, such as family members, in health and social care. They have a strong voice in policy development in the UK and are well-placed to disseminate the CDTs research to policy makers.

STEM Education
It has been shown that outreach for school age children around STEM topics can improve engagement in STEM topics at school. However female entry into STEM at University level remains dramatically lower than males; the reverse being true for health and life sciences. The CDT outreach leverages this fact to focus STEM outreach activities on digital health and care, which can encourage young women into computer science and impact on the next generation of women in higher education.

For academic impact see "Academic Beneficiaries" section.