3-year PhD Projects

Supervisors

Dr Frances Meeten
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Frances.2.meeten@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/frances.2.meeten.html

Professor Colette Hirsch
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Colette.hirsch@kcl.ac.uk
Website: https://www.kcl.ac.uk/people/colette-hirsch

Dr Ryan Scott
University of Sussex, School of Psychology

Project Details

Background:  Repetitive negative thinking (RNT; e.g. uncontrollable worry and/or rumination) is a transdiagnostic feature of depression and generalised anxiety disorder. One cohort particularly vulnerable to developing anxiety and depression are young adults (aged 16 – 25). Learning to regulate emotions via inhibition of RNT is an important tool for psychological well-being. However, when young people are beginning to struggle with RNT, little support is available as symptoms are not (yet) severe enough to receive clinical intervention. Given the key role of RNT in the development and maintenance of anxiety and depression, developing evidence-based and accessible digital interventions that target RNT in young adults is a priority.

Novelty and Importance:  Anxiety and depression are experienced as a complex mix of cognitive, affective, behavioural, and physiological factors. To date, non-pharmacological interventions that focus on physiological symptoms of anxiety/depression remain largely unexploited. The neurovisceral integration model highlights the integration of body-mind processes, linking pre-frontal inhibitory processes to heart rate variability (HRV; the time between consecutive heart beats). Low HRV is associated with cognitive deficits in inhibitory control, which is also linked to uncontrollable worry and rumination. Paced-breathing offers one way to manipulate the dominant vagally-mediated component of HRV. Breathing at approximately six breaths per minute is known as resonance frequency breathing (RFB) and this maximises HRV. Extant literature links RFB to both reductions in anxiety and improved cognitive control. A likely hypothesis is that this technique would reduce RNT, however, the specific relationship between RFB and RNT has not been explored. RFB provides an exciting and accessible mechanism to support improved mental health, yet further research is required to exploit this mechanism for use in an online and ultimately standalone digital intervention.

Primary aim(s):

1. To consult with young adults with lived experience of anxiety and depression on the findings of the research and to hear their views about developing this research as an online intervention.
2. To use experimental methods to determine whether resonance frequency breathing (RFB) increases HRV and improves emotion regulation and RNT in young adults.
3. To develop an online multi-session training paradigm based on RFB and examine its impact on RNT in young adults.

Planned research methods and training provided: Acquisition and cleaning of physiological and cognitive task data and in open science practices.

Objectives / project plan

Year 1: Experimentally examine the effect of RFB on HRV, emotion regulation, and ability to disengage from RNT in lab tasks. Participants will be university students (aged 18-25) with high levels of RNT.

Year 2: Run online focus groups with young adults to inform the development of an online multi-session RFB intervention for RNT.

Year 2/3: Conduct a randomised controlled experiment examining an online multi-session RFB intervention for RNT with young adults and to seek extended feedback from participants upon finishing the study.

Two representative publications from supervisors

Publication 1:  Hirsch, C. R., Krahé, C., Whyte, J., Krzyzanowski, H., Meeten, F., Norton, S., & Mathews, A. (2021). Internet-delivered interpretation training reduces worry and anxiety in individuals with generalized anxiety disorder: A randomized controlled experiment. Journal of Consulting and Clinical Psychology, 89(7), 575–589. https://doi.org/10.1037/ccp0000660

Publication 2:  Meeten, F., Davey, G. C., Makovac, E., Watson, D. R., Garfinkel, S. N., Critchley, H. D., & Ottaviani, C. (2016). Goal Directed Worry Rules Are Associated with Distinct Patterns of Amygdala Functional Connectivity and Vagal Modulation during Perseverative Cognition. Frontiers in human neuroscience, 10, 553. https://doi.org/10.3389/fnhum.2016.00553

Keywords:  Repetitive negative thinking; Heart rate variability; Resonance frequency breathing; Emotion regulation; Translational research.

Maudsley BRC research themes

• Psychosis and Mood Disorders
• Digital Therapies

Supervisors

Dr Annie Jones
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Annie.s.jones@kcl.ac.uk
Website: https://scholar.google.com/citations?user=Hlpb7rgAAAAJ&hl=en&oi=sra

Professor Rona Moss-Morris
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Rona.moss-morris@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/rona.moss-morris.html

Dr Miranda Lomer
Department of Nutritional Sciences, Faculty of Life Sciences and Medicine

Project Details

Background:  Managing inflammatory bowel disease (IBD) often involves dietary modifications, particularly during periods of inflammation. Recent evidence has shown that food-related quality of life (FRQoL) is reduced in people living with IBD. Our current work in IBD has also highlighted that fears of food and related avoidance are prevalent, which may both reduce FRQoL but also result in disordered eating. Disorders such as avoidant restrictive food intake disorder (AFRID) are increasing in prevalence in IBD.

Currently, digital tools exist to treat psychological distress in patients with IBD (e.g. our COMPASS intervention) and to provide dietary advice to improve FRQoL for patients with IBD (see Cox et al., 2022). There is, however, a gap for support which bridges psychology and dietetics to address patients’ cognitive and affective responses to food, which could improve FRQoL and importantly, prevent disordered eating. Currently the psychosocial correlates of FRQoL and disordered eating in IBD are unknown. This project will therefore develop a theory- and evidence- based digital tool to target maladaptive cognitions and behaviours related to food, to improve FRQoL and prevent disordered eating in IBD.

Novelty and Importance

• This project will explore the psychosocial correlates of FRQoL and disordered eating in people living with IBD, and the impact of these on clinical outcomes.
• This project will create a novel digital tool targeting maladaptive cognitions and behaviours related to food, to improve FRQoL and prevent disordered eating in IBD.

Primary aim(s):  The primary aim of this project will be to develop a digital tool to target maladaptive cognitions and behaviours related to food, to improve FRQoL and prevent disordered eating in IBD. A secondary aim will be to explore the psychosocial correlates of FRQoL and disordered eating in IBD.

Planned research methods and training provided:  Statistical analysis training.

Objectives / project plan

Year 1: A systematic review exploring the modifiable psychosocial correlates of FRQOL and disordered eating in IBD.

Year 2: A cross-sectional, longitudinal study investigating food-related distress, cognitive and affective responses associated with maladaptive food behaviours in people living with IBD. An additional, nested qualitative study interviewing IBD patients with food-related distress to understand their beliefs, behaviours and impact.

Year 3: Development work for the digital intervention, including creation of a logic model identifying anticipated mechanisms of change from the preliminary research. Intervention development will utilise a co-design approach with PPI representatives. N of 1 study will be used for feasibility and acceptability testing of the intervention to understand mechanisms within individuals.

Two representative publications from supervisors

Publication 1:  Cox S, Czuber-Dochan W, Wall C, Clarke H, Drysdale C, Lomer M, Lindsay JO, Whelan K. Improving Food-Related Quality of Life in Inflammatory Bowel Disease through a Novel Web Resource: a feasibility randomised controlled trial 2022 Nutrients. 14, 20, DOI 10.3390/nu14204292 

Publication 2:  Sweeney, L., Windgassen, S., Artom, M., Norton, C., Fawson, S. & Moss-Morris, R. (2022) A Novel Digital Self-management Intervention for Symptoms of Fatigue, Pain, and Urgency in Inflammatory Bowel Disease: Describing the Process of Development.  JMRI Formative Research Vol. 6 (5) http://dx.doi.org/10.2196/33001

Keywords:  IBD; Digital intervention; Disordered eating; Food-related quality of life.

Maudsley BRC research themes

• Eating Disorders and Obesity
• Digital Therapies

Supervisors

Dr Amy Hardy
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: amy.hardy@kcl.ac.uk
Website: 1. https://kclpure.kcl.ac.uk/portal/amy.hardy.html  2. www.slowmotherapy.co.uk

Professor Philippa Garety
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: philippa.garety@kcl.ac.uk
Website: 1. https://kclpure.kcl.ac.uk/portal/philippa.garety.html  2. www.slowmotherapy.co.uk

Project Details

Background:  SlowMo is a new, digitally supported psychological therapy that reduces paranoia and promotes living well. In our large RCT, effects were also found for novel therapeutic targets, namely self-confidence, wellbeing, and quality of life. SlowMo will be extended to target these outcomes, developing new therapy modules using Inclusive, human-centred design.

Novelty and importance:  Talking therapy for psychosis need improved access, experience, and outcomes, particularly for marginalised groups (Bighelli et al, 2018; Morris et al, 2020). A central goal of SlowMo’s design brief was to promote equality in psychosis treatment. It has already demonstrated that known minoritised inequities in digital access and literacy did not impact outcomes in our RCT, validating its inclusive design (Garety et al, 2021; Hardy et al, 2022). This project is strongly positioned to deliver novel, inclusive benefits to service users and clinicians within the next 5 years.  

Primary aim(s`):  The aims of this PhD project are to:

1. Systematically review the usability of digital therapeutics for psychosis in relation to inequities (‘the digital divide’).
2. Employ inclusive, human-centred design to develop prototypes for targeting confidence, wellbeing, and quality of life in SlowMo.
3. Evaluate the feasibility, acceptability, and effects of targeting negative self-concept, wellbeing, and quality of life in SlowMo therapy in a case series (n = 5).
4. Evaluate the acceptability and effects of targeting negative self-concept, wellbeing, and quality of life in SlowMo therapy nested in a separately funded observational study (n = 150) of SlowMo delivered in routine care.

Planned research methods and training provided:  Training and supervision will be provided for literature searches, systematic reviews, clinical case series design, quantitative analysis, qualitative methods, PPI, and clinical skills. There will be an opportunity for a clinical placement at a national psychological therapy service, PICuP, where the first supervisor is based. Skills and knowledge in relation to human-centred design, co-design and product development will be developed in collaboration with our industry partners, Special Projects, an award-winning design studio.

Objectives / project plan:  To develop and evaluate novel therapeutic targets for integration into a new, evidence-based therapy for paranoia, SlowMo. The work will be conducted as a nested study in an observational evaluation.

Year 1:  1) systematic review on the usability of digital therapeutics for psychosis; 2) inclusive, human-centred design of prototypes in collaboration with interdisciplinary team.

Year 2:  3) Evaluation of prototypes using a case series design embedded in the SlowMo observation study.

Year 3:  4) Observation study evaluation of prototypes and project write-up.

Two representative publications from supervisors

Publication 1:  Hardy A, Ward T, Emsley R, Greenwood K, Freeman D, Fowler D, Kuipers E, Bebbington P, Garety P. Bridging the Digital Divide in Psychological Therapies: Observational Study of Engagement With the SlowMo Mobile App for Paranoia in Psychosis, JMIR Hum Factors 2022;9(3):e29725, doi: 10.2196/29725

Publication 2:  Garety P, Ward T, Emsley R, et al. Effects of SlowMo, a Blended Digital Therapy Targeting Reasoning, on Paranoia Among People With Psychosis: A Randomized Clinical Trial. JAMA Psychiatry. 2021;78(7):714–725. doi:10.1001/jamapsychiatry.2021.0326

Keywords:  Digital therapeutic; Psychosis; Paranoia; Human-centred design; Cognitive-behaviour therapy.

Maudsley BRC research themes

• Psychosis and Mood Disorders
• Digital Therapies

Supervisors

Dr Joanna Hudson
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Joanna.Hudson@kcl.ac.uk
Website: https://www.kcl.ac.uk/people/joanna-hudson

Professor Rona Moss-Morris
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Rona.moss-morris@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/rona.moss-morris.html

Project Details

Background:  COMPASS is a transdiagnostic digital therapeutic which effectively reduces psychological distress (symptoms of depression and anxiety) in people with long-term conditions based on randomized controlled trial (RCT) findings [2]. However, findings from the RCT showed that 93% of the sample accessing COMPASS were of white ethnicity. Steps to address this inequitable access needs urgent action given that BAME groups experience higher mortality because of their higher rates of underlying chronic physical health conditions [3].

Novelty and Importance:  This PhD will develop a novel care pathway to increase access to and use of COMPASS for BAME people experiencing depression and/or anxiety alongside their long-term condition(s). This will maximize patient, health service, and economic benefit by improving the socio-demographic reach of COMPASS.  

Primary aim(s):  To improve the socio-demographic reach of COMPASS – a digital therapeutic for treating depression and/or anxiety.

Planned research methods and training provided:  The person-based approach to intervention development will be used to inform ways of increasing referrals to COMPASS whilst also informing the adaptions needed to the “active ingredients” of COMPASS for its delivery in a therapist supported app format. Training in qualitative methods will be provided.

Objectives / project plan

Year 1: To generate a BAME stakeholder group consisting of patients and professionals by engaging with community groups, faith leaders, Improving Access to Psychological Therapy clinical leads, and clinical commissioners. This group will be used to develop a version of COMPASS that is culturally appropriate to the needs of BAME groups (COMPASS-BAME) and a linked care pathway to improve access to and uptake of care. The group will also support with study design for tasks to be completed throughout the PhD.  

To conduct a systematic review to evaluate cultural adaptations made to mental health treatment pathways and psychological interventions to support the needs of people of BAME ethnicity. 

Year 2: To conduct individual patient interviews and think-aloud methods with BAME groups to inform the design of COMPASS-BAME and its linked care pathway.

Year 3: To test the feasibility of implementing the COMPASS-BAME intervention and its linked care pathway.

Two representative publications from supervisors

Publication 1:  Hulme K, Hudson JL, Picariello F, Seaton N, Norton S, Wroe A, Moss-Morris R. Clinical efficacy of COMPASS, a digital cognitive-behavioural therapy programme for treating anxiety and depression in patients with long-term physical health conditions: a protocol for randomised controlled trial. BMJ Open. 2021 Oct 25;11(10):e053971. doi: 10.1136/bmjopen-2021-053971. PMID: 34697123; PMCID: PMC8557248.

Publication 2:  Seaton N, Moss-Morris R, Norton S, Hulme K, Hudson J. Mental health outcomes in patients with a long-term condition: analysis of an Improving Access to Psychological Therapies service. BJPsych Open. 2022 Jun 1;8(4):e101. doi: 10.1192/bjo.2022.59. PMID: 35640903; PMCID: PMC9230614.

Keywords:  Digital therapeutic; Black Asian and Minority Ethnic Groups (BAME); Psychological Distress/Depression/Anxiety; Physical Long-Term Conditions; Multi-morbidity.

Maudsley BRC research themes

• Digital Therapies

Supervisors

Professor Robert Stewart
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience
Email: robert.stewart@kcl.ac.uk
Website: https://www.kcl.ac.uk/people/professor-robert-stewart

Dr Christoph Mueller
Department of Psychological Medicine, Institute of Psychiatry, Psychology and Neuroscience
Email: christoph.mueller@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/christoph.mueller.html

Project Details

Background:  Many people with mental disorders are prescribed multiple medications for other conditions, many of which have unwanted and potentially harmful side-effects. Due to the complexity of treatment regimens and multiple conditions being managed, it is difficult for clinicians to have an overview of all the potential impacts of polypharmacy. The Medichec application is a decision support tool which highlights potentially harmful side effects, including central anticholinergic action, drowsiness, dizziness, bleeding risk, electrolyte disturbances, constipation, and ECG abnormalities. Medichec has recently been expanded in its functionality and has already been successfully embedded in routine clinical services.

Novelty and Importance:  This project will be the first evaluating outcomes of common medication side effects in large clinical populations of mental health service users. The student will work towards integrating information on medication side effects into the range of dashboards currently under development to support clinical care. This will generate novel interventions ready for early feasibility evaluations. Although likely to focus on older patient populations (including those with dementia) where polypharmacy most commonly occurs (and is associated with higher risks of side-effects), we anticipate taking a disorder-agnostic approach to maximise potential applicability of findings in mental healthcare, aware that polypharmacy and its problems may have an impact at any age.

Primary aims:  Using the Clinical Record Interactive Search (CRIS) system, a state-of-the-art electronic health record (EHR) data analytic platform, the student will:

1. Examine the impact of known side effect profiles on patient outcomes including mortality, hospitalisation, and cognitive impairment/decline and variations in impact by mental health condition.
2. Carry out nested matched studies in samples of patients prescribed specific medication groups, to determine whether receipt of medication with known side-effects is associated with more adverse outcomes compared to receipt of other medications from the same class (e.g., antidepressants with bleeding risk compared to antidepressants without bleeding risk).
3. Integrate this information on medication side-effects into informative dashboards for clinical feedback and evaluate their application.
   

Planned research methods and training provided:  The student will gain skills in epidemiology and advanced statistical analysis, including techniques to simulate randomized trials and applied research using health records data. The CRIS team and Centre of Translational Informatics infrastructure have supported more than 200 research publications in mental health clinical informatics.

Objectives / project plan

Year 1: Literature reviews and analyses for Objective 1.

Year 2: Analyses for Objective 2 and input to dashboard design

Year 3: Dashboard functionality implementation and early-stage evaluation; thesis preparation.

Two representative publications from supervisors

Publication 1:  Mbazira, A, Bishara, D, Perera, G, Rawlins, E, Webb, S, Archer, M, Balasundaram, B, Shetty, H, Tsamakis, K, Taylor, D, Sauer, J, Stewart, R & Mueller, C. Sedation-associated medications at dementia diagnosis, their receptor activity, and associations with adverse outcomes in a large clinical cohort. Journal of the American Medical Directors Association 2022; 23: 1052-1058. https://doi.org/10.1016/j.jamda.2021.12.038

Publication 2:  Bishara, D, Perera, G, Harwood, D, Taylor, D, Sauer, J, Stewart, R & Mueller, C. 'The Anticholinergic Effect on Cognition (AEC) Scale - Associations with mortality, hospitalisation and cognitive decline following dementia diagnosis. International Journal of Geriatric Psychiatry 2020; 35: 1069-1077. https://doi.org/10.1002/gps.5330

Keywords:  Pharmacoepidemiology; Medication side-effects; Polypharmacy; Clinical Decision Support Tools; Applied clinical informatics.

Maudsley BRC research themes

• Informatics

Supervisors

Professor Richard Dobson
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience
Email: Richard.j.dobson@kcl.ac.uk
Website: https://www.kcl.ac.uk/people/richard-dobson  Twitter: @richdobson

Dr Zina Ibrahim
Department of Biostatistics and Health Informatics, Institute of Psychiatry, Psychology and Neuroscience
Email: zina.ibrahim@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/zina.ibrahim.html

Arijit Patra, Phil Scordis
UCB Pharma UK

Project Details

Background:  Electronic Health Records (EHRs) hold detailed longitudinal information about each patient's health status and disease progression, the majority of which (~80%) are stored within unstructured text. This data provides the opportunity to transform care through learning from the data available on other patients.

Rare neurological conditions are challenging in that they often have diverse clinical presentations, with a relatively small and variable number of patients in different healthcare systems. This project will develop Machine Learning (ML) workflows for automated diagnosis, prognosis and modeling of trajectories associated with rare neurological disorders, leveraging EHRs and natural language processing, and accounting for limited and imbalanced data environments.

The work may also leverage the emerging field of Digital Twins, the idea that we can use AI and large amounts of digital data within EHRs to accurately mimic real-world patients allowing users to model possible scenarios and outcomes on the twin’s real-world counterpart. As the patient data landscape is increasingly multimodal, models that can aggregate multiple data streams in EHR data are desirable.

Characterisation of the rare neurological conditions will leverage existing tools already developed and deployed within partner Trusts such as CogStack, a platform which has a near real-time feed from the EHR system within KCH (>1m patients), SLaM and GSTT, MedCAT for Named Entity Recognition and Linking of the text, and Foresight, a novel transformer-based pipeline that uses a GPTv2/3 language modelling approach to structure and organize EHRs and anticipate a range of future medical events such as:

• Predict the risk of diseases; 2) Simulate patient future; 3) Suggest diagnoses; 4) Suggest medications or procedures for multiple conditions.

Novelty and Importance:  The project will develop Machine Learning (ML) workflows for automated diagnosis, prognosis and modeling of trajectories associated with rare neurological disorders, leveraging Electronic Health Records (EHRs).

Primary aim(s):

Planned research methods and training provided:  Software development, Natural Language Processing, Data Analysis, Patient engagement, Research communication.

Objectives/project plan

Year 1: Exploratory data analysis and scoping; literature review; define problem statements and disorder priorities.

Year 2: Build ML workflows for analytics on EHR for problem statements defined in Year 1; Explore initial results; insights to clinical trial design.

Year 3: Write thesis and communicate key findings to stakeholders.

Two representative publications from supervisors

Publication 1:  Kraljevic, Z, Searle, T, Shek, A, Roguski, L, … & Dobson, RJB 2021, 'Multi-domain clinical natural language processing with MedCAT: The Medical Concept Annotation Toolkit', Artificial Intelligence in Medicine, vol. 117, 102083.

Publication 2:  Bean, D., Kraljevic, Z., Shek, A., Teo, J.T. and Dobson, R., 2022. Hospital-wide Natural Language Processing summarising the health data of 1 million patients. medRxiv.

Keywords:  Health informatics; Natural Language Processing; Artificial Intelligence; Electronic Health Records; Machine Learning.

Maudsley BRC research themes

• Child Mental Health and Neurodevelopmental Disorders
• Informatics
• Trials, Genomics and Prediction
• Neuroimaging
• Experimental Medicine and Novel Therapeutics

Supervisors

Dr Whitney Scott
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: 1. whitney.scott@kcl.ac.uk  2. whitney.scott@gstt.nhs.uk
Website: Whitney Scott - Research Portal, King's College, London (kcl.ac.uk)

Dr Kirsty Bannister
Department of Pharmacology and Therapeutics, Faculty of Life Sciences and Medicine
Email: Kirsty.bannister@kcl.ac.uk
Website: https://bannisterlab.com

Professor K Ray Chaudhuri
Department of Basic & Clinical Neuroscience, Institute of Psychiatry, Psychology and Neuroscience

Project Details

Background:  Pain is a globally recognized and under addressed issue in Parkinson’s disease, the fastest growing neurodegenerative disease worldwide (Seppi, Chaudhuri et al., 2019). Pain and related disability in Parkinson’s are influenced by a complexity of biopsychosocial factors that vary according to patient subgroups/the individual (Bannister et al., 2021).

Novelty and Importance:  Pain assessment in Parkinson’s is often cross-sectional and relies on retrospective recall. Ecological momentary assessment (EMA) enables intensive real-time assessment of pain and psychosocial factors, thus overcoming these limitations (May et al., 2018), where network analysis of EMA data can be produced for subgroups and individuals. Combining EMA with in-depth sensory profiling (whereby psychophysical measures are combined with questionnaire data to build a sensory profile), would allow identification of important targets for personalized treatments and will contribute to the development of early phase clinical trials. Explaining EMA/sensory profiling data networks to patients may enable them to make sense of key factors associated with their pain/related disability.

Primary aim(s):  Use EMA and sensory profiling to understand the temporal dynamics between pain and psychosocial factors in Parkinson’s to inform personalized pain management approaches.

Planned research methods and training provided

• Systematic review
• Psychophysics; clinical assessment of Parkinson nonmotor and motor state
• EMA
• Qualitative methods (semi-structured interviews with thematic analysis)

The student will attend training courses on each method. They will benefit from the primary supervisor’s collaboration with Professor Geert Crombez who has expertise in EMA. They will have access to the Clinical Centre of Research Excellence at KCH. Excellent learning and networking opportunities will be provided.

Objectives / project plan

Year 1: Systematic review of measures to assess pain and its psychosocial correlates in Parkinson’s to inform selection/development of EMA items. Develop the EMA protocol. Cognitive interviews with 5-7 patients to ensure the content validity of the EMA items.

Year 2 and 3: Approximately 60 patients with Parkinson’s and chronic pain will be recruited for a baseline assessment including phenotyping of sensory profiles (using static and dynamic quantitative sensory testing correlated with questionnaire data including pain scores according to the King’s Parkinson’s Pain Scale), followed by the EMA study. The EMA study will involve approximately 5-7 assessments/day (up to 14 days). Analysis of baseline phenotyping and EMA data. Qualitative interviews with a subset of participants (n=15-20). Interviews will explore the clinical utility of sharing personalized networks from EMA data with patients as a potential intervention to support behavioural change.

Two representative publications from supervisors

Publication 1:  Scott W, Arkuter C, Kioskli K, Kemp H, McCracken LM, Rice ASC, & Williams ACdC. (2018). Psychosocial factors associated with persistent pain in people with HIV: a systematic review with meta-analysis. PAIN, 159, 2461-2476.

Publication 2:  Cummins T, McMahon SB, Bannister K. The impact of paradigm and stringent analysis parameters on measuring a net conditioned pain modulation effect: A test, re-test, control study. Eur J Pain, 2020. Doi: 10.1002/ejp.1681. (https://pubmed.ncbi.nlm.nih.gov/33065759/)

Keywords:  Chronic pain; Parkinson's; Ecological Momentary Assessment; Behavioural Medicine; Personalized Medicine.

Maudsley BRC research themes

• Pain and Addictions

Supervisors

Dr Matthew Howard
Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience
Email: Matthew.howard@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/matthew.howard.html

Dr Kirsty Bannister
Department of Pharmacology and Therapeutics, Faculty of Life Sciences and Medicine
Email: Kirsty.bannister@kcl.ac.uk
Website: https://bannisterlab.com

Dr Jan Hoffmann
Wolfson Centre for Age Related Diseases, Institute of Psychiatry, Psychology and Neuroscience

Project Details

Background:  Persistent pain is associated with dysfunction of nociceptive processing at multiple sites within the neuroaxis. Central sensitization (CS), one of the underlying mechanisms wherein neuronal activity in the dorsal horn of the spinal cord is facilitated, may persist without ongoing peripheral signalling. Our labs have characterised an experimental medicine model of CS in humans using a directly translated rodent-protocol. We have demonstrated reliable elicitation of CS-like symptomatology, as indicated by secondary hyperalgesia, following high frequency electrocutaneous stimulation (HFS).  We have also demonstrated resting-state networks (RSNs) in the spinal cord with similar reliability estimates to those reported in the brain. In the proposed work we will characterise the presence of spinal sensitization using HFS, imaging perturbed RSNs and responses to normally innocuous stimuli in the brain and spinal cord.

Novelty and Importance:  Characterising mechanisms of spinal secondary hyperalgesia as a proxy measure of CS will provide major new insights regarding how pain is represented in the CNS in humans. At last it will be possible to examine biomarkers for CS while providing an avenue to examine proposed therapeutic entities for patients with CS pathophysiology.

Primary aim(s):

• To establish fMRI readouts of experimental medicine models of central sensitization-evoking paradigms in brain, brainstem and spine.T
• To consider inter-relationships between fMRI, psychometric and psychophysical readouts of HFS-induced sensitization.

Planned research methods and training provided: fMRI acquisition and analysis, DFNS training for psychophysics, psychometric and psychophysics analysis.

Objectives / project plan

Year 1: Submit ethical approvals; receive training in psychometric and psychophysical assessment and HFS; commence pilot data collection and perform preliminary analyses, quality control assessments and power calculations;

Year 2: Disseminate pilot findings within the lab; pre-register study acquisition, collation/processing and analysis pipelines at Open Science Foundation (www.osf.io); collect multimodal HFS data in full; commence thesis writing;

Year 3: Complete data collection; perform quality control assessments and data analysis; present results at BRC and international conferences (e.g HBM/IASP); submit primary analyses for peer-review; submit final thesis to examiners and receive viva voce

Other notable aspects of the project

Important:  This project is intended for someone with prior experience in performing fMRI experiments, such that it can be completed within three years. 

As a secondary objective, multivariate analysis methodologies will be used to pathophysiological states from existing multimodal (psychometric, psychophysical and fMRI) datasets. These analyses de-risk unexpected delays (e.g. COVID restrictions).

Two representative publications from supervisors

Publication 1:  https://www.biorxiv.org/content/10.1101/2022.11.25.517919v1

Publication 2:  https://doi.org/10.1016/j.neuroimage.2020.117178

Keywords:  Pain; fMRI; Brain; Spinal cord; Psychophysics.

Maudsley BRC research themes

• Pain and Addictions
• Neuroimaging
• Experimental Medicine and Novel Therapeutics

Supervisors

Dr Evangelos Vassos
Social, Genetic and Developmental Psychiatry, Institute of Psychiatry, Psychology and Neuroscience  
Email: Evangelos.vassos@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/evangelos.vassos.html

Professor Cathryn Lewis
Social, Genetic and Developmental Psychiatry, Institute of Psychiatry, Psychology and Neuroscience
Email: Cathryn.lewis@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/cathryn.lewis.html

Project Details

Background:  Polygenic scores (PGS) capture an individual’s genetic loading for a disorder. They are widely applied in research studies are strongly associated with diagnosis. Our research group has made substantial contribution to genetic discovery studies and developed novel PGS methods.  Although PGS research studies are developing rapidly, many challenges remain in moving polygenic scores to the clinic.

Novelty and Importance:  This project will use the astounding advances in polygenic medicine to stratify patients with psychiatric disorders into meaningful subgroups with distinct clinical characteristics. This important step will identify the value of PGS for interventions and accelerate translation into clinical trials.

Primary aim(s):  Using data from large population and clinical cohorts, this project will identify mental disorders where patients with high polygenic scores form distinct subgroups, for example with differential exposure to environmental factors, clinical presentation, and response to treatment.  This will highlight target areas where PGS may have clinical utility.

Planned research methods and training provided:  The student will establish collaborations with UK Biobank, GLAD and the Psychiatric Genomics Consortium (PGC) to calculate PGS for mental disorders including depression, schizophrenia, bipolar disorder, anxiety. Cases at high and at average genetic risk will be compared for differential exposure to environmental risk (e.g. trauma), clinical characteristics (e.g. severity), and treatment response.

Specific questions include:

1. Does high PGS define individuals with specific clinical profiles that dissect disorder heterogeneity?
2. For each disorder, what are optimal PGS thresholds and clinical/risk factors that show a meaningful difference between cases?

• Does the clinical presentation between subgroups justify the design of relevant clinical trials?

The student will have a regularly reviewed personal development plan, identifying development targets and gaps in training. As part of the Statistical Genetics Unit, led by Professor Lewis, the student will build genetic analysis skills. They will collaborate with researchers internationally and connect with enthusiastic and supportive peer networks in the Maudsley BRC and SGDP Centre.

Objectives / project plan

Year 1: Identify cohorts, establish collaborations for genetic and phenotypic data, undertake training in genetic analysis. Calculate polygenic scores in population and clinical cohorts.

Year 2:  Compare clinical features in high v. average PGS cases, identifying disorders and PGS thresholds that characterize clinically meaningful subgroups of patients.

Year 3: Develop student-led project to characterise genetic subtypes of specific conditions (e.g.for treatment resistant depression). Write up and submit thesis.

Two representative publications from supervisors

Publication 1:  Lewis CM, Vassos E. Polygenic Scores in Psychiatry: On the Road from Discovery to Implementation. Am J Psychiatry. 2022 Nov 1;179(11):800-806. doi: 10.1176/appi.ajp.20220795.

Publication 2:  Lewis CM, Vassos E. Polygenic risk scores: from research tools to clinical instruments. Genome Med. 2020 May 18;12(1):44. doi: 10.1186/s13073-020-00742-5. 

Keywords:  Mental health; Genetics; Risk prediction; Personalised medicine.

Maudsley BRC research themes

• Trials, Genomics and Prediction

Supervisors

Professor Dame Til Wykes
Department of Psychology, Institute of Psychiatry, Psychology and Neuroscience
Email: Til.wykes@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/til.wykes.html

Dr Hannah Belcher
Department of Health Service and Population Research, Institute of Psychiatry, Psychology and Neuroscience
Email: Hannah.belcher@kcl.ac.uk
Website: https://kclpure.kcl.ac.uk/portal/hannah.belcher.html

Project Details

Background:  The views of service users and healthcare professionals are vital for implementing novel treatments. This requires acceptability of the procedures involved and effectiveness evidence. Often efficacy depends on providing treatments to individuals or groups based on stratification, personalization, or tailoring procedures. These involve blood tests, scans and cognitive or genetic testing and there is little evidence of their acceptability to service users. In addition, efficacy is established on effects on a single primary outcome, but service users and healthcare staff may want to balance all potential outcomes (e.g., symptoms, cognition, and functioning).

Novelty and Importance:  Understanding the views of therapy end users is vital for translating clinical evidence into services. This PhD will test procedures that can be built into trials to make stratification more acceptable and discover barriers vital for implementation. We will also test, for the first time, the weighting of efficacy outcomes from the end users’ view. There is one stratification study and one Discrete Choice Experiment (DCE) in mental health both by us, but the remaining study on Multi-Criterion Decision Modelling is novel in mental health.

Primary aims:  To understand service user preferences for personalization assessments and assemble a novel method for considering the effects of treatments.

Planned research methods and training provided:  A mixed methods set of studies involving co-design and development with service users, qualitative methods, and quantitative statistics. Training in qualitative methods, best practice in service user involvement, statistical methods, and familiarization with assessments used in mental health trial design.

Objectives / project plan:  (1) Focus groups to determine questions for a Discrete Choice Experiment (DCE) survey, (2) A DCE to discover what attributes service users will accept and avoid using trade-offs of stratification elements, (3) multi-criterion decision modelling (MCDM) with service user and healthcare staff participants who rank outcomes to produce weights for a more nuanced outcome decision. We can use these weights to [re]interpret the results of a large trial. All studies will investigate whether ethnicity, gender or subjective medication side effects influence the results.

Year 1:  Systematic review of methods (DCE, MCDM), Study ethics and R&D completed, focus groups to develop the DCE questionnaire, Qualitative research methods training. Publication 1.

Year 2:  DCE survey, analysis Recruitment to MCDM using primary and secondary outcomes of a completed trial Publication 2 Complete MCDM and analyse Publication 3.

Year 3:  Publication 3 MCDM, Thesis write-up and further publications prepared.

Two representative publications from supervisors

Publication 1:  JILKA S., HUDSON G., JANSLI S.M., NEGBENOSE E., WILSON E., ODEI C.M., MUTEPUA M. & WYKES T. (2021) How to make study documents clear and relevant: the impact of patient involvement. BJPsych Open 7, e202, 108; doi: 10.1192/bjo.2021.1040.

Publication 2:  Paul McCrone, Iris Mosweu, Deokhee Yi, Tamatha Ruffell, Bethan Dalton, Til Wykes, Patient Preferences for Antipsychotic Drug Side Effects: A Discrete Choice Experiment, Schizophrenia Bulletin Open, Volume 2, Issue 1, January 2021, sgab046, https://doi.org/10.1093/schizbullopen/sgab046

Keywords:  Service users; PPI; Psychosis; Stratification; Efficacy.

Maudsley BRC research themes

• Psychosis and Mood Disorders
• Trials, Genomics and Prediction