Mental Health Epidemiology

Research Overview

The Mental Health Epidemiology Unit leads the design and analysis of studies of mental health outcomes, including studies of suicide and self-harm. We have deep expertise in the following areas.

Surveillance and monitoring of suicide and self-harm

The ongoing monitoring of suicide, self-harm and other mental health outcomes is essential for responding to major events such as the Covid-19 pandemic. We specialise in methods for evaluating changes in suicide rates over time, for instance, interrupted time series analysis and join point analysis. We also have expertise in detecting space and time clusters and have undertaken a number of studies of suicide clusters.

Cohort studies and data-linkage studies of suicide, self-harm and other mental health outcomes

Successful data-linkage studies, especially those captured from emergency department and hospital admission datasets, require a deep understanding of how the hospital system works and therefore what the data mean. These studies also require expertise in data security, data management and data analysis. We have a strong track record of doing all of these things. We have led the analysis of numerous longitudinal datasets and have expertise in all the major methods (survival analysis, mixed effects models and generalised estimating equations for binary and count outcomes). Cohort and data linkage studies that we have been involved in have appeared in some of the world’s leading general medical journals.

Intervention studies

While mental health intervention studies draw on many of the methods used in other fields, there are also important challenges that need to be addressed for a successful trial. One challenge is that, unlike trials in other areas of medicine and public health, health outcomes are generally based on a change in symptoms on a self-report instrument (as opposed to a hard outcome like a diagnosis from a pathology test). Another challenge is that the interventions themselves are often complex and conducted in an environment where treatment as usual also comprises a heterogenous set of interventions (e.g., wide availability of antidepressants, access to cognitive behavioural therapy and other established treatments). These and other challenges do not invalidate trials in this setting but do mean that expertise working in this context is essential for a successful study. We have considerable experience conducting trials in mental health, for instance undertaking rigorous and robust sample size calculations, developing strong trial designs and conducting defendable analyses, ensuring that studies we are involved in are published in high-impact journals.

Data synthesis studies

Meta-analysis has become an important tool for summarising the available evidence. We have been involved in a number of different data synthesis studies in suicide prevention. We are especially adept at converting a variety of different measures of association into a common metric for analysis. We have also contributed to the development of new methodology for assessing bias in synthesis studies of exposures operating at the population level (e.g., media exposure) and developed new methods for meta-analysing rare events.

Tel: +61 3 8344 0908


A/Prof Matthew Spittal (Unit Head, Associate Professor of Biostatistics)

Dr Angela Clapperton (Senior Research Fellow)

Dr Katrina Scurrah (Senior Research Fellow and Biostatistician)

Dr Lay San (Tiffany) Too (Research Fellow)

Leo Roberts (Data Manager)

Phillip Law (Research Fellow)

Sangsoo Shin (PhD Candidate)

Research Projects

This Research Group doesn't currently have any projects

Faculty Research Themes

School Research Themes

Prevention and management of non-communicable diseases (including cancer), and promotion of mental health, Disparities, disadvantage and effective health care

Key Contact

For further information about this research, please contact Unit Head A/Professor Matthew Spittal

Department / Centre

Centre for Mental Health

Unit / Centre

Mental Health Epidemiology

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