Paul is a Professor of Health Services and Workforce Research and a member of the Mental Health and Addictions Research Group (MHARG) in the Department of Health Sciences, and holds a joint appointment with the Hull York Medical School (HYMS).
Paul graduated from the University of Newcastle-upon-Tyne with a medical degree and an intercalated BMedSci(Hons) in psychopharmacology. Paul was later awarded a Medical Doctorate (MD) for his work developing and validating the Family Perceptions Scale - a tool designed to explore and measure subjective family functioning in adolescents. Paul was previously supported in his research by a HEFCE Clinical Senior Lecturer Fellowship, hosted at Durham University (2009-2014) where he spent some time as co-director for the Centre for Medical Education Research.
Paul’s academic work is focussed on eliciting and measuring psychological phenomena (psychometrics) and linking these to outcomes. This enables us to make predictions about people’s future behaviours or performance. For example, how likely is it, if a particular person is accepted into medical school, that they will exhibit unprofessional behaviour as a student or qualified doctor? Consequently, as a quantitative methodologist Paul draws from both the ‘individual differences’ psychology tradition as well as epidemiology. More recently Paul has been applying the predictive modelling approaches offered by machine learning.
Paul has extended, and applied quantitative methods in order to address important issues in relation to health services, and in particular, the healthcare workforce. Paul believes that workforce policies and practices are a ‘healthcare technology’; that is, they often largely determine the quality and safety of patient care. Thus, they are worthy of a firm evidence base in their own right.
The health workforce
In 2015 Paul was awarded a National Institute for Healthcare Research (NIHR) Career Development Fellowship. Along with other grant funding, this funded a five year programme of work on selection, including regulation, of the medical and healthcare workforce. Paul’s work has substantially contributed to ‘evidence-based medical selection’ with the goal of improving both the diversity and quality of the medical workforce, and thus patient care. Paul is a founder member of the UK Medical Education Research Database (UKMED) research subgroup. The UKMED is, globally, a unique, longitudinal educational database, capturing routinely arising information on UK registered doctors, from medical school application through to Consultant level. Paul’s research on health professions selection covers three, overlapping, themes:
-The role and impact of cognitive (‘intelligence’) and academic achievement in medical selection;
high school grades, in combination with performance on cognitive (‘aptitude’) tests have traditionally been the mainstay of medical school selection. Nevertheless, there was a dearth of evidence relating to the predictive validity and the impact of the use of these metrics on the diversity (or otherwise) of the medical profession. Paul has led a programme of research providing much needed evidence in this area, in order to inform medical selection policy and practice.
-‘Non-cognitive’ abilities/traits; There is a growing recognition of the importance of these personal traits and interpersonal abilities (e.g. ‘conscientiousness’) to the safe and effective practise of healthcare. Their absence often comes starkly to light when serious professionalism lapses are identified. The problems posed by self-report measures, and the resource intensive nature of face-to-face assessments has encouraged the widespread adoption of the situational judgment test (SJT) format in various career stages of medical selection. SJTs depicted a scenario that challenge professional judgement and a candidate usually provides a response which demonstrates they understand how to best react to the situation. Paul’s research has increased our knowledge of how SJTs might work in the context of health staff selection as well as some of the predictors of fitness to practice issues in students and doctors.
-‘Differential attainment’ in medical training; understanding issues relating to differences in educational achievement during clinical training between varying groups of doctors is essential in a global medical workforce market. This is because physicians frequently practise in countries other than those they qualified from. However, it is also a highly sensitive and complex matter with implications for equality, as well as standards of patient care and professional regulation. Paul’s work has been able to identify the degree of attainment gaps across medical specialties, and between different groups of doctors, according to world region of qualification. More recently, Paul explored these in more detail in relation to psychiatric postgraduate clinical examinations.
Other health services research
Paul has applied his passion for quantitative methods to a range of issues in health services, particularly those that relates to the delivery of mental health care. Paul’s earlier work focused on evaluating early intervention in psychosis services for young people affected by severe mental illness. Paul also helped to lead some of the early work adapting and evaluating ‘Behavioural Activation’ (BA) for the treatment of adolescent depression. Paul is now a member of the research team undertaking a fully powered trial of the intervention as part of the Community-delivered Behavioural Activation
Training for Depression in Adolescents (ComBAT) study, funded via an NIHR programme grant for applied research. More generally, Paul has an interest in how predictive methods, including machine learning, can be applied to both research and the routine clinical data, in order to inform the development of health services.
Paul continues to practice as a Consultant in the Forensic Psychiatry of Adolescence, holding an honorary contract with Tees, Esk and Wear Valleys NHS Foundation Trust. As such, Paul has had an interest in clinical risk assessment and previously developed and validated the CARAS risk assessment system as part of a knowledge transfer partnership project (imosphere.com/care-and-support-tools/child-and-adolescent-risk-assessment/).
Paul has extensive experience and expertise in exploiting routinely arising data in order to address important health services issues. Paul has a particular interest in the health workforce and much of his research in recent years has focussed on selection, assessment and regulation of the healthcare workforce. As a ‘psychometric epidemiologist’ Paul aims to measure individual differences in the workforce and aims to use these to make predictions about future educational and, ultimately, clinical performance.
The work of Paul and his team has substantially contributed to ‘evidence-based medical selection’ with the goal of improving the diversity and quality of the medical workforce, and thus patient care. For example, by providing evidence in relation to ‘grade discounting’ for medical school applicants applying from educationally disadvantaged backgrounds. Paul is a founder member of the UK Medical Education Research Database (UKMED) research subgroup. The UKMED is, globally, a unique, longitudinal educational database, capturing routinely arising information on UK registered doctors, from medical school application through to Consultant level.
Paul has previously received research funding from the General Medical Council (the UK Medical Regulator), the Department of Health and Social Care (DHSC) for England as well as the University Clinical Aptitude Test (UCAT) Board, that oversees the selection assessment used by most British Medical Schools. From 2016 to 2021 Paul held an NIHR Career Development Fellowship. This funded a five year programme of work initially focussed on predictive modelling in medical selection and creating a situational judgment testing system designed to support values based recruitment (VBR) in mental health services.
From a methodological perspective Paul, as lead for the DREAMS network has been developing new approaches to understanding and communicating the effectiveness of personnel selection methods. Paul has also led work understanding how situational judgment testing can be used to enhance healthcare workforce selection. Paul also an interest in how artificial intelligence can be used to enhance health services and previously worked on an EPSRC funded project evaluating novel, model based approaches to prediction using machine learning.
Paul is interested in supervising PhD students in the following areas: quantitative research in the area of clinical education and workforce issues, as they relate to health services.