29 Aug Exploring current data collection practices to improve global health research

Consistent, dependable data is the core of any research study.

But how accurate is the data being collected when it comes to global health research studies? Senior Researcher Rene Gerrets says not as reliable as we might think – and he’s committed to exploring how practices can change to improve the quality of research in the field.

Dr. Gerrets, AIGHD Academic Staff, co-authored the recently published articles Why pseudo matters to global health and the Masking and making of fieldworkers and data in postcolonial global health research contexts. The latter paper focuses on various influences on data collection and how he says, this can undermine production of reliable data. The articles were published in Critical Public Health as part of the special issue Pseudo matters in public and global health.

“Whenever you conduct research in development, you rely a lot on intermediaries such as local research partners and field workers. Sometimes, the link between the principal investigator in one country and the field workers in a second country is weak, which can cause a host of problems including data fabrication. This is a big problem because we need reliable data to be able to trust our research results,” he said.

According to Gerrets, we must look at the structure of research projects to fully understand the problem. Since many international researchers rely on a local group of field workers to collect data, it can be challenging to ensure consistency in the way the data is collected, especially if the researcher is not physically working alongside the team. For instance, differences in ethical frameworks and methods between the researcher and the local team can result in disparities in the data.

“Take the example of a mother and child who are enrolled in a clinical trial, who often receive better care or subsidized care as part of the trial. If that child happens to die, the field worker might record the data from another child in the household while reporting it as data from the first child. In this way, the mother can still receive access to healthcare as part of the clinical trial, while community members may consider the field workers’ decision as ethically appropriate. This and many similar scenarios take place in developing countries and we need to understand this better to improve the quality of the data,” he continues.

Researchers operate under a bioethical framework, many times prioritizing the data of the clinical trial. The field worker, on the other hand, operates with a local community ethic. So far, there has been limited room to discuss such issues in the research community.

“Researchers have long labelled data fabrication as a simple case of fraud. Our research shows that there is much more going on in the field and worth further exploring. Ultimately, we want to encourage researchers to think about how they structure their field work, and how they deal with issues of data fabrication. Unless we have reliable data, we do not have strong publications and true results.”

Gerrets thinks that there are solutions to the data quality problems that are taking place today.

“The purpose of the publications is to show that there are ways of improving data collection methods, by for example spending more time together with field workers, to understand their motivations and challenges. Researchers can also ensure that field workers are compensated better for the data collection that they do, and that there is a better collaboration between the field worker and the researchers. This will lead to better quality data and publications.”

Read the full series of articles.