ArticleThe British journal of clinical psychology2022
Emotion network density is a potential clinical marker for anxiety and depression: Comparison of ecological momentary assessment and daily diary.
Article in The British journal of clinical psychology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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22 citing papers in PubMed, 34 citations in OpenAlex.
- The benefits of mindfulness training for momentary mindfulness and emotion regulation: A randomized controlled trial for adolescents exposed to chronic stressors.Journal of consulting and clinical psychology · 2024Trial
- Momentary effects of life stressors on mindfulness and emotion regulation difficulties among adolescents exposed to chronic stressors.Stress and health : journal of the International Society for the Investigation of Stress · 2024Trial
- Temporal dynamics of daily diabetes-specific burdens using intensive longitudinal data: the central role of feelings of guilt within a multilevel network analysis.Diabetologia · 2026Article
- Complex affect dynamics offer limited incremental value for cross-sectional prediction of psychological and behavioural variables in cross-validated models.BMC medicine · 2026Article
- When Negative Emotions Stick Together: Interconnectedness Explains How Emotion Regulation Strategies Shape Distress.Journal of youth and adolescence · 2026Article
- Characterizing emotion dynamics in remitted depression: A network approach using ecological momentary assessment.Journal of mood and anxiety disorders · 2026Article
- The Impact of Emotion Network Density on Psychological Distress in Chinese Parents of Children with Autism: A Daily Diary Study.Journal of autism and developmental disorders · 2026Article
- Mapping the dynamics of idiographic network models to the network theory of psychopathology.Behavior research methods · 2026Article
- Exploring within and between associations of momentary mindfulness and emotion regulation and the moderating effects of mental health among adolescents.Journal of research on adolescence : the official journal of the Society for Research on Adolescence · 2026Article
- Emotion rigidity in adolescents prospectively predicts future depressive symptoms assessed via self-report and clinical interview.Behaviour research and therapy · 2025Article
- Fluctuations in Daily Happiness and Nervousness Based on Depressive and Anxious Symptoms in Adolescents or Young Adults Across 3 Latin American Cities: Experience Sampling Study.JMIR formative research · 2025Article
- Affective forecasting dynamics as an early intervention target in depression: evidence from ecological monitoring and temporal network analysis.Frontiers in psychiatry · 2025Article
- A socioemotional network perspective on momentary experiences of family conflict in young adults.Family process · 2024Article
- The Emergence of Organized Emotion Dynamics in Childhood.Affective science · 2024Article
- Machine Learning and Bayesian Network Analyses Identifies Psychiatric Disorders and Symptom Associations with Insomnia in a national sample of 31,285 Treatment-Seeking College Students.Research square · 2024Article
- Elevated emotion network connectivity is associated with fluctuations in depression.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Short-term exposure sequences and anxiety symptoms: a time series clustering of smartphone-based mobility trajectories.International journal of health geographics · 2023Article
- Dense Sampling Approaches for Psychiatry Research: Combining Scanners and Smartphones.Biological psychiatry · 2023Review
- The roles of caregivers and friends in adolescent daily emotion dynamics.Social development (Oxford, England) · 2023Article
- Emotion network density in burnout.BMC psychology · 2021Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
Abstract
objectivesUsing two intensive longitudinal data sets with different timescales (90 minutes, daily), we examined emotion network density, a metric of emotional inflexibility, as a predictor of clinical-level anxiety and depression.
designMobile-based intensive longitudinal assessments.
methods119 participants (61 anxious and depressed, 58 healthy controls) completed ecological momentary assessment (EMA) to rate a variety of negative (NE) and positive emotions (PE) 9 times per day for 8 days using a mobile phone application. 169 participants (97 anxious and depressed and 72 healthy controls) completed an online daily diary on their NE and PE for 50 days. Multilevel vector autoregressive models were run to compute NE and PE network densities in each data set.
resultsIn the EMA data set, both NE and PE network densities significantly predicted participants' diagnostic status above and beyond demographics and the mean and standard deviation of NE and PE. Greater NE network density and lower PE network density were associated with anxiety and depression diagnoses. In the daily diary data set, NE and PE network densities did not significantly predict the diagnostic status.
conclusionsGreater inflexibility of NE and lower inflexibility of PE, indexed by emotion network density, are potential clinical markers of anxiety and depressive disorders when assessed at intra-daily levels as opposed to daily levels. Considering emotion network density, as well as the mean level and variability of emotions in daily life, may contribute to diagnostic prediction of anxiety and depressive disorders. PRACTITIONER POINTS: Emotion network density, or the degree to which prior emotions predict and influence current emotions, indicates an inflexible or change-resistant emotion system. Emotional inflexibility or change resistance over a few hours, but not daily, may characterize anxiety and depressive disorders. Inflexible negative emotion systems are associated with anxiety and depressive disorders, whereas inflexible positive emotion systems may indicate psychological health. Considering emotional inflexibility within days may provide additional information beyond demographics and mean level and variability of emotions in daily life for detecting anxiety and depressive disorders.
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