Finding Depression’s Breaking Point
Ingrid Van de Leemput from Wageningen University and Research Center in Holland and Angelique Cramer from the University of Amsterdam collaborated on a study which was aimed at finding the point between healthy mood and depression and how effective technology might be in predicting that critical juncture.
Everyone feels sad or anxious at some point. A situation at work overwhelms you, a friend is unkind or someone disappoints our expectation. The more time that is needed to bounce back from those negative feelings was shown to strongly correlate to the likelihood that a person would be depressed. In fact, the study’s findings closely resembled outcomes on a mathematical model the researchers devised to predict how mood reports would relate to an eventual tipping point for depression.
The 600 plus study participants were asked to record their emotions for a period of five or six days. Some of the participants had pre-existing diagnosed depression and other participants had no depression prior to the study. The study subjects were interrupted 10 times throughout their day by their smartphone asking them to note how intensely they felt sad, anxious, content or cheerful. Two months later the subjects completed a more comprehensive questionnaire used to measure clinical depression.
At the conclusion of the study period 13 percent of the study participants showed evidence of becoming more depressed. This figure parallels well with what happens in the general population. On the other hand, the daily record of mood proved highly predictive for formerly non-depressed individuals sliding toward depression. When the daily record showed prolonged negative mood this heralded oncoming depression.
While healthy people move on emotionally rather quickly after an unpleasant interaction, people edging toward depression may still feel badly even days afterward. Cogitating on problems and holding onto negative feelings are symptoms of depression, developing a feedback loop that can lead to full-blown depression. This is why “bounce back” time is so predictive.
Social scientist Stephen Gilman commented on the study, saying that the ultimate goal of this type of research is to prevent episodes of depression. At the very least, an app that aids mood recording could help doctors and therapists keep track of patient wellness.