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Simple ‘emotionometer’ predicts depression relapse as successfully as clinical interview

08 October 2012

Depression is a very common disorder, and after recovery there is a high chance of relapse. Research by the department of Clinical Psychology of the University of Groningen (together with the Academic Medical Center Amsterdam (AMC)), appearing this week in PLoS One, reveals that depression relapse can be predicted just as successfully with a simple ‘emotiometer’ as with the gold standard, the clinical interview.

In total, 172 patients who had recovered from depression were followed for 5½ years. Patients who rated their mood more as more sombre at a single measurement moment with a simple emotionometer turned out to relapse into depression quicker. For a long time it was thought that fluctuations in emotion were a vulnerability factor for relapse. The results of current research question whether emotional reactivity is as crucial as always thought.

The emotionometer is wonderfully simple; it is a scale – depicted as a thermometer – on which the patient marks his or her mood. It turns out that this emotionometer can predict the time until a relapse over a period of 5½ just as well as the gold standard for charting depressive symptomatology, the Hamilton Depression Rating Scale. A sombre mood at one point in time thus appears to be a good predictor and much simpler to measure than the differentiated symptomatology measured by clinicians.

This discovery has implications for research on the development of depression and triggers for relapse, as well as for the development of new treatments for depression. The emotion thermometer is a simple timesaving instrument that can easily be used by people with depression. At the moment, the University of Groningen is conducting follow-up research on the various application possibilities (e.g. via SMS and internet) for the emotionometer in national studies (www.doorbreek-depressie.nl).

Note for the press

More information: Gerard van Rijsbergen
Last modified:04 July 2014 9.34 p.m.
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