Understanding and investigating phenomena such as networks and systems is common in many scientific fields. Network psychometric analysis is a novel statistical technique used to examine psychological data and allows us to view psychological phenomena as systems of interacting entities (e.g., specific symptoms).
At the PATH lab, we are interested in using network analysis to explore interactions between individual mental health symptoms. We want to identify symptoms that are most central and influential (compared to other symptoms of the same condition), for different groups, such as people with diabetes. According to network theory, central and influential symptoms (for example, the depressive symptom of “feelings of failure”) are likely to be highly involved in the development and maintenance of mental health conditions (for example, depression) and are therefore potentially powerful targets for interventions. Research at the PATH lab also uses network analysis to investigate comorbidity between two or more mental health conditions. Using network analysis in this way, we can look at how mental health conditions spread from one to another, through particularly strong cross-condition connections between individual symptoms, also known as bridges. For example, a strong bridging connection may be found between the anxiety symptom of “uncontrollable worry” and the depressive symptom of “feelings of failure”. This would identify these symptoms, and their connection, as a potential target for treatment to reduce comorbidity between these conditions.
In a publication from the PATH lab (linked here), we found that regimen-related and physician-related diabetes distress problems are the most central and influential symptoms of diabetes distress (as measured by the DDS-17) in a cohort of adults with type 2 diabetes. We also found feelings of failure and worry to be potential bridges between the mental health conditions assessed (anxiety, depression, and diabetes distress). If you would like to read more about this study you can read it here.
McInerney, A. M., Lindekilde, N., Nouwen, A., Schmitz, N., & Deschenes, S. S. (2022). Diabetes distress, depressive, and anxiety symptoms in people with type 2 diabetes: a network analysis approach to understanding comorbidity. Diabetes Care.
The UCD PATH Lab 