Gray matter characteristics associated with trait anxiety in older adults are moderated by depression
Bibliographic record
Abstract
BACKGROUND: Structural gray matter characteristics of anxiety remain unclear. The aim of this study was to assess the influence of current depressive symptoms and history of depression on the gray matter characteristics of trait anxiety. METHODS: Structural magnetic resonance imaging (MRI) data from 393 individuals aged 65 years or older were used. Regions of interest (ROIs) included the amygdala, anterior cingulate cortex (ACC), insula, orbitofrontal cortex (OFC), and temporal cortex. Trait anxiety was measured by the State-Trait Anxiety Inventory (STAI). Depression and depressive symptoms were measured using DSM-IV criteria and the Center for Epidemiological Studies Depression Scale (CESD). RESULTS: After adjustments for sociodemographics and health-related variables, anxiety had a significant influence on the gray matter characteristics in all cortical ROIs. First, in participants without depression antecedents, higher trait anxiety was associated with a larger cortical thickness in all cortical ROIs. Second, in participants with a previous history of depression, higher trait anxiety was associated with a smaller cortical thickness in all cortical ROIs. CONCLUSIONS: These results suggest that anxiety is related to cortical thickness differently in healthy older adults and in older adults with psychiatric antecedents. Anxiety associated with thinner cortical areas could reflect symptoms of a specific type of depression or a vulnerability to develop depression.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".