Persistence of Anxiety/Depression Symptoms in Early Adolescence: A Prospective Study of Daily Life Stress, Rumination, and Daytime Sleepiness in a Genetically Informative Cohort

Hansell, Narelle K.; Strike, Lachlan; Zubicaray, Greig I. de; Thompson, Paul M.; McMahon, Katie L.; Wright, Margaret J.

doi:10.1017/thg.2022.26

Cited by 3 publications

(3 citation statements)

References 132 publications

(153 reference statements)

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“…This study suggests a positive correlation between rumination and anxiety. Rumination has been proved to be an important causal variable of anxiety ( Verstraeten et al, 2011 ; Hansell et al, 2022 ; Sun et al, 2022 ). As stated above, rumination is associated with anxiety in addition to depression.…”

Section: Discussionmentioning

confidence: 99%

“… Sun et al (2022) stated that rumination was independently associated with anxiety and depression. A study on anxiety/depression symptoms in early adolescence revealed that rumination accounted for a certain proportion of the changes in anxiety/depression in later stages ( Hansell et al, 2022 ). Rumination can positively predict anxiety.…”

Section: Introductionmentioning

confidence: 99%

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Physical activity and depression of Chinese college students: chain mediating role of rumination and anxiety

Liu,

Feng,

Guo

2023

Front. Psychol.

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ObjectiveTo explore the relationship between physical activity and depression among college students, as well as the mediating role of rumination and anxiety.MethodsA total of 1,292 Chinese college students were investigated by physical activity questionnaire, rumination scale, self-rating anxiety scale (SAS), and depression scale.Results(1) There was a significant negative correlation between physical activity and depression (r = −0.399, p < 0.01), and the direct path of physical activity on depression was significant (β = −0.399, t = −13.374, p < 0.01). (2) Physical activity negatively predicted rumination (β = −0.322, t = −10.440, p < 0.01) and anxiety (β = −0.222, t = −7.089, p < 0.01). Rumination positively predicted anxiety (β = 0.283, t = 9.017, p < 0.01) and depression (β = 0.267, t = 9.046, p < 0.01). Anxiety positively predicted depression (β = 0.262, t = 8.902, p < 0.01). (3) Rumination and anxiety play a significant mediating role between physical activity and depression. The mediating effect involves three paths: physical activity → rumination → depression (the mediating effect value: −0.076); physical activity → anxiety → depression (the mediating effect value: −0.052). Physical activity → rumination → anxiety → depression (the mediating effect value: −0.021).Conclusion(1) Physical activity can negatively predict the rumination, anxiety, and depression of college students, which means physical activity can reduce rumination, anxiety, and depression of college students. (2) Physical activity can not only directly affect the depression of college students, but also indirectly affect depression through the independent intermediary role of rumination and anxiety, and the chain mediation of rumination and anxiety.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Physical activity and depression of Chinese college students: chain mediating role of rumination and anxiety

Liu,

Feng,

Guo

2023

Front. Psychol.

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“…The QTAB study (Hansell, Strike, de Zubicaray, et al, 2022 ; O'Callaghan et al, 2021 ; Strike et al, 2023 ) focused on the period of late childhood/early adolescence, with brain imaging, cognition, mental health, and early life/family demographics data collected over two waves (wave 1: 9–14 years, wave 2: 10–16 years). The baseline QTAB wave includes imaging data for 211 families (422 individuals).…”

Section: Methodsmentioning

confidence: 99%

Heritability of cerebellar subregion volumes in adolescent and young adult twins

Strike,

Kerestes,

McMahon

et al. 2024

Human Brain Mapping

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Twin studies have found gross cerebellar volume to be highly heritable. However, whether fine‐grained regional volumes within the cerebellum are similarly heritable is still being determined. Anatomical MRI scans from two independent datasets (QTIM: Queensland Twin IMaging, N = 798, mean age 22.1 years; QTAB: Queensland Twin Adolescent Brain, N = 396, mean age 11.3 years) were combined with an optimised and automated cerebellum parcellation algorithm to segment and measure 28 cerebellar regions. We show that the heritability of regional volumetric measures varies widely across the cerebellum ( 47%–91%). Additionally, the good to excellent test–retest reliability for a subsample of QTIM participants suggests that non‐genetic variance in cerebellar volumes is due primarily to unique environmental influences rather than measurement error. We also show a consistent pattern of strong associations between the volumes of homologous left and right hemisphere regions. Associations were predominantly driven by genetic effects shared between lobules, with only sparse contributions from environmental effects. These findings are consistent with similar studies of the cerebrum and provide a first approximation of the upper bound of heritability detectable by genome‐wide association studies.

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Predicting generalized anxiety disorder among Chinese depressed adolescents: an explanable machine learning approach (Preprint)

Geng,

Wang,

Liang

et al. 2023

Preprint

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BACKGROUND Anxiety disorders have high lifetime comorbidity (45.7%) with depression and the co-occurrence of depression and anxiety constitutes greater mental health burden and impact on quality of life than depression symptoms alone. This necessitates the prediction of anxiety disorders in depressed adolescents, and the identification of key risk factors as well as their interactions for early prevention. OBJECTIVE The current research leverages an explainable machine learning approach to develop a predictive model that evaluates the predictive pertinence of diverse factors. Meanwhile, the interactions between different risk factors and validity of factor significance measures were investigated. METHODS We recruited 2316 depressed adolescents through the Chinese Adolescent Depression Cohort (CADC) and collected 34 predictive factors for model construction. The Light Gradient Boosting Machine (LightGBM) prediction model and Shapley Additive Explanations (SHAP) algorithm were implemented for in-depth interpretation of the predictive importance of different factors. Furthermore, Chi-square Automatic Interaction Detection (CHAID) and ordinal logistic regression were used to explore the factor interactions and validate the SHAP value-based factor importance, respectively. RESULTS Nine key risk factors were identified. Besides the depressive symptoms, rumination, perceived stress, sleep quality, alexithymia, peer victimization, academic stress level, emotion-focused coping, and parental overprotect were recognized as key risk factors for onset of anxiety. In addition, resilience was recognized as the protective factor. Interaction analysis results indicate that adolescents experiencing severe depression symptoms are more vulnerable to alexithymia and severe anxiety. For adolescents with low depressive symptoms but high alexithymia, they are more likely to develop into severe anxiety and depression when their alexithymia exceeds a threshold of 3.5. Three high-risk subgroups for severe anxiety were detected by the CHAID decision tree: (1) adolescents with severe depression symptoms, (2) with moderate depression symptoms and high rumination, (3) with severe depression symptoms and high alexithymia. Three low-risk subgroups are: (1) adolescents with low depression and rumination, (2) with low depression, low alexithymia, and more parental care, (3) with low depression, moderate rumination, and moderate academic stress. CONCLUSIONS Utilizing an explainable machine learning approach enables us to identify the risk and protective factors of anxiety disorders among depressed adolescents. While depressive symptoms play a critical role in the prediction of anxiety, the comorbidity of depression and anxiety is driven by additional factors such as alexithymia and rumination. These findings suggest the clinical workers take into consideration of the above risk and protective factors as well as their interactions to develop appropriate therapy for the prevention of comorbid anxiety with depression.

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Persistence of Anxiety/Depression Symptoms in Early Adolescence: A Prospective Study of Daily Life Stress, Rumination, and Daytime Sleepiness in a Genetically Informative Cohort

Cited by 3 publications

References 132 publications

Physical activity and depression of Chinese college students: chain mediating role of rumination and anxiety

Physical activity and depression of Chinese college students: chain mediating role of rumination and anxiety

Heritability of cerebellar subregion volumes in adolescent and young adult twins

Predicting generalized anxiety disorder among Chinese depressed adolescents: an explanable machine learning approach (Preprint)

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