Lessons learned from landscaping the Americas
Our global search for datasets under the Landscaping International Longitudinal Datasets project has revealed that the Americas (i.e., North, Central, and South America) are home to some of the world’s oldest, longest-running, and impactful longitudinal studies. The data and findings from some have enabled transformative research within fields like cancer and cardiovascular medicine, guided large-scale public health campaigns, and contributed to the formulation of medical tools for the awareness, diagnosis, treatment, and prevention of illnesses and conditions.
Mindful of their potential, we have been landscaping the world for longitudinal datasets that can facilitate similarly impactful research in mental health – one of the three ‘biggest health challenges facing humanity’ that the Wellcome Trust aims to address.
We have approached this aim with the recognition that different longitudinal datasets hold value for different types of research depending on the questions that are being asked.
The longitudinal datasets in the Americas are diverse in their focus, design, size, and scale. They are as sweeping as registries of millions of regional volunteers or as specific as the physical health outcomes of a couple of hundred participants from a selected ethnic group. A large proportion of the projects that host these datasets are based in North America, and more have been funded and will start soon, anticipating hundreds of thousands, even millions of participants and multimodal data collection. This, along with a gradual rise in longitudinal research initiatives in many countries across Central and South America as well, has cultivated the longitudinal data landscape of the entire region.
The existing longitudinal studies in the Americas are flourishing not only with decades worth of data but also lessons that can inform researchers and funders about how to progress in longitudinal research. Their credibility is primarily based on the substantial number of participants recruited and retained in many of the most impactful studies, especially as retention is a challenge faced by numerous studies from across the world. What is more, some have also been fruitful in implementing branch-off studies and following other family members, such as participants’ offspring. These generate such rich sources of data from across the lifespan and even across generations for research and innovation.
But how did these longitudinal studies from the Americas manage to do this, you ask? In my review of them, I have drawn upon three recurring themes occurring in most.
Firstly, I have noticed that studies do not choose quantity at the expense of quality. Interestingly, larger sample sizes and wider scopes of focus do not always equate to more or greater findings. Larger samples are valuable and have offered essential findings, especially as they are more likely to reflect the populations of interest, but they run the risk of not being able to retain their participants or collect as much in-depth data over time. Instead, the studies with a more targeted approach have datasets that are more manageable and sustainable.
Secondly, they foster relationships with their participants. Most of the studies with high retention and long, regular, and/or consistent follow-up are led by teams who acknowledge the time and contribution of their cohort members. They express their appreciation in the form of ‘Thank You’ messages or participant highlights on their study websites, or engage with participants through periodic newsletters and updates. These simple acts seem to be meaningful to those who kindly volunteer their time, and in my opinion, maintain the personal element of such studies.
Finally, many of these studies make use of what is already in place rather than starting from scratch. Established teams often make use of their acquired expertise and become responsible for multiple cohorts, for example the offspring of the original cohort or several birth cohorts. They also commonly implement other perspectives by creating meaningful collaborations with other teams, institutions, and sectors (e.g., academia and government), which seems to provide added value in such studies. I can imagine that this (benevolent) exploitation of resources may be what enables researchers and their colleagues to excel in other aspects of their studies.
What does this mean for longitudinal mental health research in the Americas?
The scope of mental health research is still not as extensive as physical health research, and perhaps unsurprisingly, our knowledge about mental health problems is still not equivalent to what we know about physical health topics such as cancer, cardiovascular diseases, and ageing. While there is not yet a cure for cancer, an antidote for heart attack, or a potion for eternal youth, longitudinal data have helped enrich our knowledge about and interventions for these conditions, giving us hope that this will soon be replicated in mental health. Thankfully, there is massive scope for utilising longitudinal data to make such discoveries.
We can consider the existing longitudinal datasets in the Americas for this endeavour, but we should be aware of the variation in the depth of assessment of mental health. A select few of the datasets we have identified in our search focus on mental health, some include few standard and non-standard items about symptoms, and many just address the mere presence or absence of a psychiatric diagnosis. There is a contrast between countries in this regard, with many more studies covering mental health in the United States and Canada.
However, the aforementioned lessons can guide us in how to maximise the potential of the existing cohorts, facilities, and teams in other countries in the Americas, even if they are not currently measuring mental health.
The opportunities in the Americas are abundant as the longitudinal data landscape is ever-growing and many large-scale initiatives are continuously underway. Our search for the datasets with the potential to answer questions about mental health is enabling us to also harvest other lessons cocooned within all types of datasets, not only in the Americas but across the world. Their teachings could be essential in guiding some next steps in mental health research. More imminently however, understanding the rich landscape from which they come is bringing us one step closer to supporting the Wellcome Trust in creating ‘a world in which no one is held back by mental health problems.’
Stay up to date with our project by following @L_Arseneault, @wellcometrust, @MQmentalhealth, and @ODIHQ on Twitter. Email us at landscaping-wellcome@kcl.ac.uk with any studies or information that may be useful for us to consider.
