ArticleFrontiers in psychiatry2022
A Data-Driven Clustering Method for Discovering Profiles in the Dynamics of Major Depressive Disorder Using a Smartphone-Based Ecological Momentary Assessment of Mood.
Article in Frontiers in psychiatry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Beyond the current state of just-in-time adaptive interventions in mental health: a qualitative systematic review.Frontiers in digital health · 2025Pooled it
- Identifying treatment response classes to transcranial direct current stimulation from daily ecological momentary assessment patterns in patients with depression.The international journal of neuropsychopharmacology · 2026Trial
- Digital mood phenotyping predicts short- and long-term suicidal ideation across a two-year timescale.Molecular psychiatry · 2026Article
- How Variability Is Addressed in Interventions for Neurodiverse Conditions: Implications for Stuttering.Journal of speech, language, and hearing research : JSLHR · 2026Article
- From Theory to Practice: Developing the MOBILE Intervention for Adults with Depression.Healthcare (Basel, Switzerland) · 2025Article
- Towards clinical subtypes in schizophrenia: integrating cognitive, functional, and digital phenotyping assessments.Molecular psychiatry · 2025Article
- Tinnitus Measured in Everyday Life: A Literature Review of Ecological Momentary Assessment Studies.Journal of the Association for Research in Otolaryngology : JARO · 2025Review
- Functional Relationships of Binge Drinking and Alcohol-Related Problems With Posttraumatic Stress Symptoms in a Pilot Sample of Veterans.Journal of dual diagnosis · 2025Article
- Heterogeneity of resilience and the curvilinear relationship between childhood trauma and resilience among people with schizophrenia.Frontiers in psychiatry · 2023Article
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Authors and funding
23 authors.
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Abstract
Background: 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. Mood dynamics can be defined as a combination of mood variability (the magnitude of the mood changes) and emotional inertia (the speed of mood shifts). The purpose of this study is to explore various distinctive profiles in real-time monitored mood dynamics among MDD patients in routine mental healthcare. Methods: Ecological momentary assessment (EMA) data were collected as part of the cross-European E-COMPARED trial, in which approximately half of the patients were randomly assigned to receive the blended Cognitive Behavioral Therapy (bCBT). In this study a subsample of the bCBT group was included ( Results: Overall, four profiles were identified, which we labeled as: (1) "very negative and least variable mood" ( Conclusions: The real-time monitoring conducted in the present study provides some preliminary indications of different patterns of both average mood and mood variability among MDD patients in treatment in mental health settings. Such varying patterns were not found for emotional inertia.
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