{"title":"与非判断意识相关的静息状态功能连通性可预测多种消极情绪测量结果","authors":"Yi-Sheng Wong, Savannah Siew, Junhong Yu","doi":"10.1007/s12671-024-02413-7","DOIUrl":null,"url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Objectives</h3><p>In recent years, an increasing number of studies have highlighted the usefulness of the Five Facet Mindfulness Questionnaire (FFMQ) in identifying varying levels of trait mindfulness. As higher trait mindfulness (as reflected by higher FFMQ scores) has been associated with fewer negative affective symptoms, a thorough understanding of the neural correlates associated with FFMQ scores would inform the development of more individualized mindfulness interventions. The current study investigated how individual differences in trait mindfulness are related to different resting-state functional connectivity patterns, and whether these patterns could predict negative affective symptoms.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>We analyzed data from 71 adults (age range: 20–45 years) from the Max Planck Institute-Leipzig Mind-Brain-Body dataset. Participants completed the FFMQ, the Beck Depression Inventory-II, and the Hospital Anxiety and Depression Scale, underwent resting-state functional magnetic resonance imaging scans and reported the content of thought emerged during the scanning session. Network-based statistics were used to identify resting-state networks that were significantly associated with the FFMQ facets. The strengths of these networks were then used to predict negative affective symptoms.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Results indicated that higher scores on the facets of act with awareness and nonjudge were associated with fewer negative affective symptoms. The network-based statistics revealed networks of edges that were significantly associated with the facet of nonjudge. Moreover, this network significantly predicted multiple measures of negative affect. There were no networks that were significantly associated with other facets.</p><h3 data-test=\"abstract-sub-heading\">Conclusions</h3><p>These findings provide evidence at the neural level to suggest that the facet of nonjudge is inversely linked to negative affective symptoms.</p><h3 data-test=\"abstract-sub-heading\">Preregistration</h3><p>This study was not preregistered.</p>","PeriodicalId":18523,"journal":{"name":"Mindfulness","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-07-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Resting-State Functional Connectivity Associated with Non-Judgmental Awareness Predicted Multiple Measures of Negative Affect\",\"authors\":\"Yi-Sheng Wong, Savannah Siew, Junhong Yu\",\"doi\":\"10.1007/s12671-024-02413-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<h3 data-test=\\\"abstract-sub-heading\\\">Objectives</h3><p>In recent years, an increasing number of studies have highlighted the usefulness of the Five Facet Mindfulness Questionnaire (FFMQ) in identifying varying levels of trait mindfulness. As higher trait mindfulness (as reflected by higher FFMQ scores) has been associated with fewer negative affective symptoms, a thorough understanding of the neural correlates associated with FFMQ scores would inform the development of more individualized mindfulness interventions. The current study investigated how individual differences in trait mindfulness are related to different resting-state functional connectivity patterns, and whether these patterns could predict negative affective symptoms.</p><h3 data-test=\\\"abstract-sub-heading\\\">Methods</h3><p>We analyzed data from 71 adults (age range: 20–45 years) from the Max Planck Institute-Leipzig Mind-Brain-Body dataset. Participants completed the FFMQ, the Beck Depression Inventory-II, and the Hospital Anxiety and Depression Scale, underwent resting-state functional magnetic resonance imaging scans and reported the content of thought emerged during the scanning session. Network-based statistics were used to identify resting-state networks that were significantly associated with the FFMQ facets. The strengths of these networks were then used to predict negative affective symptoms.</p><h3 data-test=\\\"abstract-sub-heading\\\">Results</h3><p>Results indicated that higher scores on the facets of act with awareness and nonjudge were associated with fewer negative affective symptoms. The network-based statistics revealed networks of edges that were significantly associated with the facet of nonjudge. Moreover, this network significantly predicted multiple measures of negative affect. There were no networks that were significantly associated with other facets.</p><h3 data-test=\\\"abstract-sub-heading\\\">Conclusions</h3><p>These findings provide evidence at the neural level to suggest that the facet of nonjudge is inversely linked to negative affective symptoms.</p><h3 data-test=\\\"abstract-sub-heading\\\">Preregistration</h3><p>This study was not preregistered.</p>\",\"PeriodicalId\":18523,\"journal\":{\"name\":\"Mindfulness\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.1000,\"publicationDate\":\"2024-07-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Mindfulness\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1007/s12671-024-02413-7\",\"RegionNum\":2,\"RegionCategory\":\"心理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"PSYCHIATRY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Mindfulness","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1007/s12671-024-02413-7","RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"PSYCHIATRY","Score":null,"Total":0}
Resting-State Functional Connectivity Associated with Non-Judgmental Awareness Predicted Multiple Measures of Negative Affect
Objectives
In recent years, an increasing number of studies have highlighted the usefulness of the Five Facet Mindfulness Questionnaire (FFMQ) in identifying varying levels of trait mindfulness. As higher trait mindfulness (as reflected by higher FFMQ scores) has been associated with fewer negative affective symptoms, a thorough understanding of the neural correlates associated with FFMQ scores would inform the development of more individualized mindfulness interventions. The current study investigated how individual differences in trait mindfulness are related to different resting-state functional connectivity patterns, and whether these patterns could predict negative affective symptoms.
Methods
We analyzed data from 71 adults (age range: 20–45 years) from the Max Planck Institute-Leipzig Mind-Brain-Body dataset. Participants completed the FFMQ, the Beck Depression Inventory-II, and the Hospital Anxiety and Depression Scale, underwent resting-state functional magnetic resonance imaging scans and reported the content of thought emerged during the scanning session. Network-based statistics were used to identify resting-state networks that were significantly associated with the FFMQ facets. The strengths of these networks were then used to predict negative affective symptoms.
Results
Results indicated that higher scores on the facets of act with awareness and nonjudge were associated with fewer negative affective symptoms. The network-based statistics revealed networks of edges that were significantly associated with the facet of nonjudge. Moreover, this network significantly predicted multiple measures of negative affect. There were no networks that were significantly associated with other facets.
Conclusions
These findings provide evidence at the neural level to suggest that the facet of nonjudge is inversely linked to negative affective symptoms.
期刊介绍：
Mindfulness seeks to advance research, clinical practice, and theory on mindfulness. It is interested in manuscripts from diverse viewpoints, including psychology, psychiatry, medicine, neurobiology, psychoneuroendocrinology, cognitive, behavioral, cultural, philosophy, spirituality, and wisdom traditions. Mindfulness encourages research submissions on the reliability and validity of assessment of mindfulness; clinical uses of mindfulness in psychological distress, psychiatric disorders, and medical conditions; alleviation of personal and societal suffering; the nature and foundations of mindfulness; mechanisms of action; and the use of mindfulness across cultures. The Journal also seeks to promote the use of mindfulness by publishing scholarly papers on the training of clinicians, institutional staff, teachers, parents, and industry personnel in mindful provision of services. Examples of topics include: Mindfulness-based psycho-educational interventions for children with learning, emotional, and behavioral disorders Treating depression and clinical symptoms in patients with chronic heart failure Yoga and mindfulness Cognitive-behavioral mindfulness group therapy interventions Mindfulnessness and emotional regulation difficulties in children Loving-kindness meditation to increase social connectedness Training for parents and children with ADHD Recovery from substance abuse Changing parents’ mindfulness Child management skills Treating childhood anxiety and depression
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