Webinar: The Catalogue of Mental Health Measures: Discovering the depths of mental health data in UK

Date:

11/02/2021

Organised by:

UK Data Service, The University of Essex, Institute of Psychiatry, Psychology & Neuroscience

Presenter:

Louise Arseneault and Bridget Bryan (Kings College London), and Beate Lichtwardt (UK Data Service)

Level:

Entry (no or almost no prior knowledge)

Contact:

Christine Dorisamy-Pillai
cdoris@essex.ac.uk
07952751414

video conference logo

Venue: Online

Description:

Online, 16.00-17.30 GMT

 

This webinar is jointly organised by the UK Data Service, The University of Essex, and the Institute of Psychiatry, Psychology & Neuroscience, Kings College London.

This webinar will introduce the new Catalogue of Mental Health which provides access to information on mental health and wellbeing measures in British cohort and longitudinal studies. The webinar will be useful for researchers from across different disciplines and career stages. The Catalogue may be particularly useful for early career researchers utilising data that has already collected and researchers less familiar with the mental health field – but it may also hold some surprises for experienced mental health researchers! It is an interactive session, please bring your laptop, IPad or mobile phone so you can try it out!

Overview of the talk

Mental health awareness has been steadily increasing in recent years. Estimates of the extent and adverse impacts of mental health problems underline the urgent need for more research to better understand the causes and the consequences of mental ill health, and to identify the most effective interventions. Existing longitudinal and cohort studies provide unique opportunities to answer key questions related to population mental health and wellbeing. But what has been collected? By who? When? And, how?As part of a CLOSER-funded research project, the Institute of Psychiatry, Psychology & Neuroscience, Kings College London, has developed a searchable catalogue to help people find information about existing measures of mental health and wellbeing in UK cohort and longitudinal studies. The Catalogue of Mental Health Measures compiles and organises information about mental health measures in over 30 (and counting!) UK cohort and longitudinal studies. It features descriptions of the studies and the measures of mental health and wellbeing they have collected, as well as information about statistical resources and training. The catalogue improves the visibility and accessibility of these measures, making it easier for researchers from across different disciplines to make use of the incredibly rich mental health data currently available in the UK’s longitudinal studies

Many studies have initiated additional phases of data collection to examine the impact of COVID-19 and the lockdown on mental health and wellbeing. We have recently updated the Catalogue with new information on those important measures. We will browse the COVID data collection timeline to find information about the mental health data collected by the cohort studies during the pandemic.

Attendees can expect from this webinar to:

  • gain a better appreciation of the value of cohort and longitudinal studies for mental health and wellbeing research
  • discover new data resources and mental health measures
  • learn how to use the Catalogue of Mental Health Measures
  • know how to find and access the relevant longitudinal data.

The first 60 minutes of the webinar will be devoted to presentations from Louise Arseneault and Bridget Bryan (Kings College London), and Beate Lichtwardt (UK Data Service), followed by a Q&A session.

If you have any queries or require further information about this event, please contact booking@ukdataservice.ac.uk

Cost:

Free

Website and registration:

Region:

International

Keywords:

Data Collection, Qualitative Data Handling and Data Analysis, Quantitative Data Handling and Data Analysis

Related publications and presentations:

Data Collection
Qualitative Data Handling and Data Analysis
Quantitative Data Handling and Data Analysis

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