A meta-analysis of emotional regulation outcomes in psychological interventions for youth with depression and anxiety

Daros, Alexander R.; Haefner, Sasha A.; Asadi, Shayan; Kazi, Sharifa; Rodak, Terri; Quilty, Lena C.

doi:10.1038/s41562-021-01191-9

Cited by 47 publications

(36 citation statements)

References 83 publications

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“…The recognition of emotion is a major research direction of affective computing, which had been widely used to detect depression ( 1 , 2 ). Emotion is crucial to the quality and scope of human daily experience ( 3 ).…”

Section: Introductionmentioning

confidence: 99%

Depression Assessment Method: An EEG Emotion Recognition Framework Based on Spatiotemporal Neural Network

et al. 2022

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The main characteristic of depression is emotional dysfunction, manifested by increased levels of negative emotions and decreased levels of positive emotions. Therefore, accurate emotion recognition is an effective way to assess depression. Among the various signals used for emotion recognition, electroencephalogram (EEG) signal has attracted widespread attention due to its multiple advantages, such as rich spatiotemporal information in multi-channel EEG signals. First, we use filtering and Euclidean alignment for data preprocessing. In the feature extraction, we use short-time Fourier transform and Hilbert–Huang transform to extract time-frequency features, and convolutional neural networks to extract spatial features. Finally, bi-directional long short-term memory explored the timing relationship. Before performing the convolution operation, according to the unique topology of the EEG channel, the EEG features are converted into 3D tensors. This study has achieved good results on two emotion databases: SEED and Emotional BCI of 2020 WORLD ROBOT COMPETITION. We applied this method to the recognition of depression based on EEG and achieved a recognition rate of more than 70% under the five-fold cross-validation. In addition, the subject-independent protocol on SEED data has achieved a state-of-the-art recognition rate, which exceeds the existing research methods. We propose a novel EEG emotion recognition framework for depression detection, which provides a robust algorithm for real-time clinical depression detection based on EEG.

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Section: Introductionmentioning

confidence: 99%

Depression Assessment Method: An EEG Emotion Recognition Framework Based on Spatiotemporal Neural Network

et al. 2022

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“…Every day, people use words to identify and communicate about their emotional experiences ( 15 – 17 ). Difficulties with emotion regulation [i.e., the ways in which people modify or manage their emotional experiences ( 18 , 19 )] are robustly connected to psychopathology ( 20 – 22 ), and successful therapy operates through changing patients’ emotion regulation habits ( 23 – 26 ). Consequently, finding a linguistic signature of poor emotion regulation could measure levels of psychopathology and their remission over treatment at a large scale.…”

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confidence: 99%

Linguistic measures of psychological distance track symptom levels and treatment outcomes in a large set of psychotherapy transcripts

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et al. 2022

Proc. Natl. Acad. Sci. U.S.A.

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Significance Using language to “distance” ourselves from distressing situations (i.e., by talking less about ourselves and the present moment) can help us manage emotions. Here, we translate this basic research to discover that such “linguistic distancing” is a replicable measure of mental health in a large set of therapy transcripts ( N = 6,229). Additionally, clustering techniques showed that language alone could identify participants who differed on both symptom severity and treatment outcomes. These findings lay the foundation for 1) tools that can rapidly identify people in need of psychological services based on language alone and 2) linguistic interventions that can improve mental health.

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“…The active ingredients approach applies and extends these ideas beyond psychological therapies to any intervention that may prevent or reduce symptoms of anxiety and depression, from the biological to the societal. For example, while some of the papers in this Collection address putative active ingredients of existing psychological therapies (for example: emotion regulation 6 , social relationships 7 , problem solving 8 , decentering 9 and helpful thinking patterns 10 ), others use this same approach but apply it to the neurobiological domain (for example psychobiotics 11 ) or look at how individuals use an active ingredient comment in everyday life (for example, emotional awareness via ecological momentary assessment 12 ). Our focus on conceptual clarity in defining active ingredients complements our commitment to bring conceptual clarity, and where possible some core measures, to how we consider impact in terms of outcomes 13 .…”

Section: Seek Conceptual Claritymentioning

confidence: 99%

Searching for active ingredients to combat youth anxiety and depression

2021

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A meta-analysis of emotional regulation outcomes in psychological interventions for youth with depression and anxiety

Cited by 47 publications

References 83 publications

Depression Assessment Method: An EEG Emotion Recognition Framework Based on Spatiotemporal Neural Network

Depression Assessment Method: An EEG Emotion Recognition Framework Based on Spatiotemporal Neural Network

Linguistic measures of psychological distance track symptom levels and treatment outcomes in a large set of psychotherapy transcripts

Searching for active ingredients to combat youth anxiety and depression

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