Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study.

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Title: Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study.
Authors: Driver, Christina1 cdriver@usc.edu.au, Boyes, Amanda1, Mohamed, Abdalla Z.1, Levenstein, Jacob M.1, Parker, Marcella1, Hermens, Daniel F.1
Source: Journal of Youth & Adolescence. May2024, Vol. 53 Issue 5, p1029-1046. 18p.
Subject Terms: *Longitudinal method, *Quality of life, Cross-sectional method, Functional connectivity, Research funding, Psychological distress, Cluster analysis (Statistics), Mental health, White matter (Nerve tissue), Artificial neural networks, Well-being
Abstract: Wellbeing is protective against the emergence of psychopathology. Neurobiological markers associated with mental wellbeing during adolescence are important to understand. Limited research has examined neural networks (white matter tracts) and mental wellbeing in early adolescence specifically. A cross-sectional diffusion tensor imaging analysis approach was conducted, from the Longitudinal Adolescent Brain study, First Hundred Brains cohort (N = 99; 46.5% female; Mage = 13.01, SD = 0.55). Participants completed self-report measures including wellbeing, quality-of-life, and psychological distress. Potential neurobiological profiles using fractional anisotropy, axial, and radial diffusivity were determined via a whole brain voxel-wise approach, and hierarchical cluster analysis of fractional anisotropy values, obtained from 21 major white matter tracts. Three cluster groups with significantly different neurobiological profiles were distinguished. No significant differences were found between the three cluster groups and measures of wellbeing, but two left lateralized significant associations between white matter tracts and wellbeing measures were found. These results provide preliminary evidence for potential neurobiological markers of mental health and wellbeing in early adolescence and should be tracked longitudinally to provide more detailed and robust findings. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Youth & Adolescence is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study.
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  Data: <searchLink fieldCode="JN" term="%22Journal+of+Youth+%26+Adolescence%22">Journal of Youth & Adolescence</searchLink>. May2024, Vol. 53 Issue 5, p1029-1046. 18p.
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  Data: *<searchLink fieldCode="DE" term="%22Longitudinal+method%22">Longitudinal method</searchLink><br />*<searchLink fieldCode="DE" term="%22Quality+of+life%22">Quality of life</searchLink><br /><searchLink fieldCode="DE" term="%22Cross-sectional+method%22">Cross-sectional method</searchLink><br /><searchLink fieldCode="DE" term="%22Functional+connectivity%22">Functional connectivity</searchLink><br /><searchLink fieldCode="DE" term="%22Research+funding%22">Research funding</searchLink><br /><searchLink fieldCode="DE" term="%22Psychological+distress%22">Psychological distress</searchLink><br /><searchLink fieldCode="DE" term="%22Cluster+analysis+%28Statistics%29%22">Cluster analysis (Statistics)</searchLink><br /><searchLink fieldCode="DE" term="%22Mental+health%22">Mental health</searchLink><br /><searchLink fieldCode="DE" term="%22White+matter+%28Nerve+tissue%29%22">White matter (Nerve tissue)</searchLink><br /><searchLink fieldCode="DE" term="%22Artificial+neural+networks%22">Artificial neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22Well-being%22">Well-being</searchLink>
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  Data: Wellbeing is protective against the emergence of psychopathology. Neurobiological markers associated with mental wellbeing during adolescence are important to understand. Limited research has examined neural networks (white matter tracts) and mental wellbeing in early adolescence specifically. A cross-sectional diffusion tensor imaging analysis approach was conducted, from the Longitudinal Adolescent Brain study, First Hundred Brains cohort (N = 99; 46.5% female; Mage = 13.01, SD = 0.55). Participants completed self-report measures including wellbeing, quality-of-life, and psychological distress. Potential neurobiological profiles using fractional anisotropy, axial, and radial diffusivity were determined via a whole brain voxel-wise approach, and hierarchical cluster analysis of fractional anisotropy values, obtained from 21 major white matter tracts. Three cluster groups with significantly different neurobiological profiles were distinguished. No significant differences were found between the three cluster groups and measures of wellbeing, but two left lateralized significant associations between white matter tracts and wellbeing measures were found. These results provide preliminary evidence for potential neurobiological markers of mental health and wellbeing in early adolescence and should be tracked longitudinally to provide more detailed and robust findings. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
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  Data: <i>Copyright of Journal of Youth & Adolescence is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Value: 10.1007/s10964-024-01939-2
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        Text: English
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      – SubjectFull: Longitudinal method
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      – SubjectFull: Quality of life
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      – SubjectFull: Cross-sectional method
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      – SubjectFull: Functional connectivity
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      – SubjectFull: Research funding
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      – SubjectFull: Psychological distress
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      – SubjectFull: Cluster analysis (Statistics)
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      – SubjectFull: Mental health
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      – SubjectFull: White matter (Nerve tissue)
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      – SubjectFull: Artificial neural networks
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      – SubjectFull: Well-being
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      – TitleFull: Understanding Wellbeing Profiles According to White Matter Structural Connectivity Sub-types in Early Adolescents: The First Hundred Brains Cohort from the Longitudinal Adolescent Brain Study.
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              M: 05
              Text: May2024
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              Y: 2024
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