A Data-Driven Clustering Method for Discovering Profiles in the Dynamics of Major Depressive Disorder Using a Smartphone-Based Ecological Momentary Assessment of Mood

• Published in: Frontiers in psychiatry Vol. 13; p. 755809
• Main Authors: van Genugten, Claire R, Schuurmans, Josien, Hoogendoorn, Adriaan W, Araya, Ricardo, Andersson, Gerhard, Baños, Rosa M, Berger, Thomas, Botella, Cristina, Cerga Pashoja, Arlinda, Cieslak, Roman, Ebert, David D, García-Palacios, Azucena, Hazo, Jean-Baptiste, Herrero, Rocío, Holtzmann, Jérôme, Kemmeren, Lise, Kleiboer, Annet, Krieger, Tobias, Rogala, Anna, Titzler, Ingrid, Topooco, Naira, Smit, Johannes H, Riper, Heleen
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 17.03.2022
• Subjects: cluster analysis; depression; ecological momentary assessment; heterogeneity; Medicin och hälsovetenskap; mood dynamics; mood instability; Psychiatry; mood dynamics; depression; mood instability; cluster analysis; ecological momentary assessment; heterogeneity

Although major depressive disorder (MDD) is characterized by a pervasive negative mood, research indicates that the mood of depressed patients is rarely entirely stagnant. It is often dynamic, distinguished by highs and lows, and it is highly responsive to external and internal regulatory processes....