Institute of Psychiatry, Psychology & Neuroscience
Quick Find: Centre for Military Health Research (1 item) | Department of Biostatistics & Health Informatics (4 items)
Centre for Military Health Research
If you are interested in the VMHC then please contact [email protected] to be added to the wait list as we hope to release a small number of additional tickets (plus there may be some cancellations) prior to the conference date.
The health and wellbeing of Veterans, and their families, is a topic frequently discussed in parliament and in the media. The King’s Centre for Military Health Research (KCMHR) has been running a mental health focused conference for many years which have been kindly supported by Forces in Mind Trust (FiMT)
We are delighted that, in 2023, we will also be hosting the FiMT Research Centre conference. These two conferences will be held consecutively on the 7th and 8th March 2023 at the Royal College of Psychiatrists, near to Tower Hill underground station. The first day will be the traditional King’s Centre for Military Health Research (KCMHR) Veterans’ Mental Health Conference (7th March). The second day will be the FiMT Research Centre conference which will be run along with our partners, RAND Europe. Each conference will have a comprehensive agenda in order to provide delegates with an opportunity to hear the latest research, and to network with colleagues who are interested in the health, wellbeing and success of the Armed Forces Community.
The Standard Fee is £99 per day which includes all refreshments, lunch, drinks, canapé reception (and an early evening of the 7th March 2023 for delegates attending either day), free WiFi and a certificate of attendance.There will be a discount for delegates purchasing tickets for both days and a separate discount for up to two delegates from any COBSEO member organisation who are attending the mental health conference on the 7th March 2023.
Department of Biostatistics & Health Informatics
The course provides a comprehensive introduction to trial design features used to mitigate bias, important aspects of trial design, conduct, analysis and reporting, and challenges and solutions for conducting RCTs with some focus on behavioural interventions. This will include some coverage of methods for elucidation of treatment mechanisms (e.g. mediation). Throughout the course the emphasis will be on practical issues faced by researchers in the conduct and analysis of RCTs through the lens of the mental health setting, and participants will be provided with skills to design, conduct and analyse rigorous RCTs in this research area.
This course requires an application to be made, please see more information tab on how to apply. Some practical sessions will involve analyses and interpretation using practice data sets using the Stata and/or R programs. Stata and R syntax will be provided and explained, but some familiarity with software, especially Stata, is necessary, and individuals should have some knowledge of fitting regression models. Successful participants will need to bring their own laptop computer to the course with working installations of: 1) Stata version 14 or higher, 2) the R program.
This course is run over a one-month period (2 x three-hour sessions per week), followed by a workshop with invited speakers, and is aimed at PhD students and researchers working in applied psychometrics. The course provides a comprehensive introduction to the fundamental ideas of psychometric theory and their implementation and is taught by Dr Silia Vitoratou and Prof Andrew Pickles.
Live remote access of in-person sessions will be available for those who cannot attend on campus.
Starting from the scale construction and gradually moving to the most recent statistical methods employed in measurement, the course provides a complete methodological framework for applied researchers. While the classical test theory ideas on reliability and validity, often used in the literature, are presented, the more methodologically sound item response theory counterparts are explained (difficulty and discrimination, item and total characteristic and information curves).
For the measurement of the latent variable(s) the course presents exploratory and confirmatory factor analysis (EFA and CFA) for numerical data. For categorical data, both the item response theory approach (IRT; 2-parameter logistic, grated response and partial credit models) as well as the item factor analysis model (IFA; both with regard to EFA and CFA). The course also presents the methods to explore measurement differences (measurement invariance) between groups (MG CFA), measurement differences due to covariates (MIMIC models), and measurement differences between raters or time points (longitudinal IFA), for all types of data.
Learning Outcomes. Subject-specific: Knowledge, Understanding and Skills
At the end of the course the students should be able to demonstrate subject-specific knowledge, understanding and skills and have the ability to:
Learning Outcomes. General: Knowledge, Understanding and Skills
On successful completion of this module the student should be able to:
The course provides an introduction to the nature of medical text, and the technical and organisational challenges encountered when processing.
The course will be based around practical examples and widely used NLP tools.
The course aims to provide an introduction to the major techniques of natural language processing, and to provide participants with the skills to create their own NLP applications, using both rules based and statistical approaches. Methods will be introduced for extracting structured information from text, and for automatically classifying text, together with the selection of data for training and for evaluation.
The course will discuss aspects of NLP that are specific to medical and biomedical texts, and develop a critical awareness of the issues associated with these texts. Participants will be equipped with the skills needed to analyse their own language processing problems, to design and test solutions, and to understand the limitations of those solutions.
The course will provide a practical instruction in the use of some widely used tools in NLP, including nltk (a Python toolkit).
Learning Outcomes: Subject specific: Knowledge, Understanding and Skills
On successful completion of this module the student should be able to