A global mental health perspective of the Landscaping report

This month sees the launch of the ground-breaking report on Landscaping International Longitudinal Datasets for mental health. It is ground-breaking in several respects.

This is the first study to identify longitudinal datasets for mental health from all regions of the world, compiling over 3,000 datasets from 146 countries.

It was also completed with astonishing speed. The Landscaping project was commissioned by the Wellcome Trust in September 2022, and by the launch of the report in July 2023, a massive database had been compiled, providing access to valuable longitudinal data for researchers around the world.

The way this has been done is also ground-breaking. The research team at King’s College London, led by Louise Arseneault worked together in a participatory process, with a Lived Experience Expert group, the charity MQ Mental Health Research and the non-profit organisation the Open Data Institute to complete the study. This included a wide consultation process, and the development of a Theory of Change for the project, to maximise participation and broader impact.  

Why is longitudinal data so important for mental health?

Many mental health studies, particularly in low and middle-income countries, are cross-sectional. That is, they examine the characteristics of a research sample at a single point in time. This enables us to say whether a particular exposure or characteristic is associated with a particular mental health outcome. But it does not allow us to say anything about the causal relationship between an exposure and a mental health outcome. For example, many studies show that people living in circumstances of multi-dimensional poverty are more likely to experience depression than those who are better off. But this does not tell us anything about the causal relationship between poverty and depression. In short, are people depressed because they are poor, or poor because they are depressed?

Longitudinal datasets allow us to answer this question because they allow us to explore temporal relationships – for example whether depression precedes reduced income or the other way round. This, in turn, allows us to develop more targeted policies and interventions to break cycles of poverty and depression.

For those of us working in the field of global mental health, international longitudinal datasets are therefore invaluable. They allow us to track the drivers and consequences of inequities in mental health globally. And they enable us to identify key intervention targets and advocate for the needs of some of the most marginalised and vulnerable people on the planet.

So, what are the main findings of the report?

The findings provide valuable new knowledge in four main categories:

• Richness of mental health measures for depression, anxiety, psychosis and beyond,

• Value in targeted populations, including high-risk, under-represented groups, those in under-represented locations and ageing populations, 

• Diverse forms of data, including wearables, mobile phones, biological and genetic data, and routinely collected data, and

• Mental health data embedded in important social contexts, such as the COVID pandemic, natural disasters, geopolitical factors and embedded interventions.

What the Landscaping report also shows is that there are key gaps in our knowledge. Some of these are related to world regions. For example, there are relatively few long-standing and routine datasets in Africa and south Asia. Additionally, only 100 out of the 3,068 datasets were sufficiently large, had granular assessments and included data on participants between 14 and 30 years of age. And of those, only 10% were primarily focused on mental health, indicating that most longitudinal datasets were set up for purposes other than mental health, though some included mental health measures.

Moving forward, there are important opportunities to enrich the longitudinal datasets that have been compiled through this Landscaping project.

The existing samples in these datasets can be better preserved and expanded, for example through diversification and improved retention of study participants. Measures can be improved, and new data collected, including through the harmonisation of instruments and further work on their cultural validation and adaptation. Infrastructure and connectivity of datasets can be improved, for example to enhance their use and discoverability. And finally, the involvement of Lived Experience Experts and engagement with local communities can be strengthened.

These opportunities are particularly relevant in low and middle-income countries, where 25% of the longitudinal datasets were found. These datasets provide valuable insights into mental health challenges in these frequently under-researched regions. They also provide opportunities for capacity building of mental health research, and linking the datasets to current mental health research capacity building initiatives, such as the African Mental Health Research Initiative (AMARI). Such findings are well aligned with the recommendations of a recent meeting on mental health research in Africa, convened by the Academy of Medical Sciences and the Academy of Science of South Africa in Johannesburg in November 2022. The recommendations included the need to strengthen and diversify data sources, particularly on the social determinants of mental health in vulnerable populations, and to collect longitudinal epidemiological data, explore causal pathways and identify intervention targets.

This is an exciting time for the burgeoning field of global mental health research, both to engage with these datasets, and to explore opportunities for their enrichment, to address key gaps in our knowledge.

Since its inception in 2007, the field of global mental health has broadened from an initial focus on scaling up treatments in low and middle-income countries, to a greater understanding of the social determinants of mental health and the development, evaluation and scaling up of prevention and promotion interventions. This broader agenda is well aligned with the objectives of this report, namely, to enrich our understanding of the complex interactions of brain, body and environment over the life course, and to build a community of global mental health researchers who are committed to reducing inequities in mental health around the world.