Introduction to surveys and longitudinal data: mental health and well-being research in the UK

Presenter(s): Mark Elliot, Eoin McElroy, Sally McManus

This resource is focused on the use of secondary data (analysis) for the study of mental health and well-being. The resources cover the various data sources that can be used and the types of quantitative analysis that can be conducted using these data.

Also included are links to datasets containing data about mental health and well-being in the UK, including a range of relevant cross sectional surveys. The three videos will cover cohort and household panel studies; cross sectional surveys; and an overview of a study investigating the trajectory of well-being.

Cohort and household panel studies

This video will outline the various types of longitudinal studies that are hosted in the UK, with a particular focus on birth cohorts. It will provide guidance on how to source and access longitudinal data and offer guidance on how to harmonize variables across studies. It will also provide links to key resources to learn more about longitudinal data in the UK.

Cross sectional surveys

The UKDS archive includes datasets suitable for examining different aspects of mental health, including prevalence, inequalities and the treatment gap. This session focuses on using repeated cross sectional surveys with high quality assessments of different mental health conditions, in particular the Adult Psychiatric Morbidity Survey (APMS) series. While longitudinal sources are better for analysing individual trajectories and for making causal inferences, a survey series like APMS is ideal for other purposes, like producing temporal trends in population prevalence. Some of the issues analysts need to consider when doing this type of research will be discussed, such as checking for consistency in questions, mode, and sample coverage. Please note that the session describes research results on self-harm and domestic violence.

An analysis of well-being

This video describes a study carried out by Jennifer Murphy and Mark Elliot, which investigated the trajectory of well-being over the course of the first wave of the COVID pandemic. The study sought to determine whether the change in well-being is distributed equally across the population, using online survey responses from the COVID-19 modules of Understanding Society. These data show no evidence of a social gradient in well-being related to the pandemic. In fact, well-being was shown to be highly elastic in this period, indicating a national level of resilience which cut across the usually observed health inequalities.

The UK Data Archive.

Supporting materials

About the author

Mark Elliot is a Professor of Social Statistics at the University of Manchester. Professor Elliot has been central to the field of confidentiality and privacy since 1996. Professor Elliot collaborates widely with non-academic partners, particularly with national statistical agencies where he has been a key influence on disclosure control methodology used in censuses and surveys and where the SUDA software that he developed in collaboration with colleagues in Computer Science at Manchester is used.

Primary author profile page

• Published on: 26 June 2023
• Event hosted by: Manchester
• Keywords: surveys | longitudinal data |
• To cite this resource:

  Mark Elliot, Eoin McElroy, Sally McManus. (2023). Introduction to surveys and longitudinal data: mental health and well-being research in the UK. National Centre for Research Methods online learning resource. Available at https://www.ncrm.ac.uk/resources/online/all/?id=20811 [accessed: 22 November 2024]