2.1 Study protocol
Identify possible causes and confounding factors of a health condition through the NETWORK OF VARIABLES
Imagine you want to design an experiment to understand how a factor affects a health condition, and you want to understand how other variables can affect this relationship. The first thing to do is to identify the factors that can relate to the problems, for instance a habit, a food intake or an environmental exposure. Citizens, especially those affected by the health problem, can help identify these factors based on their perception and first-hand knowledge of the problem.
Network of variables
This is a tool to engage citizens in the design of the study. It allows you to identify which variables need to be taken into account when designing a study, and to decide how they can be controlled or measured. Moreover, it contributes to identifying confounding variables, which is a key aspect of epidemiological studies as it prevents possible misleading interpretation of the cause and effect relationship of a problem. Controlling for confounding variables is very important to obtain the right conclusions from a study. If you ignore them you could end up with associations where in reality there are none, or fail to find associations where they do in fact exist.
Can air pollution affect students’ attention? Building a network of variables with students
An example of this is the Atenc!ó project in Barcelona. The project aims to assess whether air pollution in high schools can affect adolescents' cognitive functions. In the design phase of the project, students were invited to propose a set of factors that they believed could influence attention. A selection of those factors were included in the final questionnaire used in the study.
To identify potential factors that can cause a health outcome and that scientists might not have thought of.
To introduce the concept of confounder to citizens and help them think as an epidemiologist!
To help citizens learn the different relationships between variables in the problem under study and get an idea of its complexity.
To think in ways to improve the study design to strengthen the future conclusions of the study.
Introduce what a confounder is. Provide an intuitive explanation of what a confounder is and how to draw relationships between variables with arrows. See the supporting materials available in the toolbox to read an example of a confounder variable!
Identify and relate the variables. In small groups, participants list different factors that they think could influence the variable of interest and/or the health outcome investigated in the study. Each group of participants uses a sheet of paper to relate the variables listed before by drawing arrows. Arrows should go from the cause to the effect. If the drawing becomes too busy, they can draw separate ones for subsets of variables.
Select the variables
Participants need to look for variables that are in a path that links the variable of interest (e.g. smoking) with the health outcome (e.g. heart disease). A path is a collection of arrows that links two variables, no matter the direction of the arrows. We are only interested in finding paths that start from an arrow pointing to the variable of interest. The variables in those paths are the ones to be considered in the study; those are potentially confounding variables.
Decide how to control for the variables selected
Participants decide, for each of the variables selected in the previous step, if it can be controlled by design (and how it could be done) or else information on the variable should be collected (and which tools or devices could be used). See supporting information for more details.
Get the toolbox!
We share with you some of the tools that can be useful to carry out this activity.
Supporting information- Network of variables tool in action