The influence of psychosocial stress on functional connectivity and neuroendocrine markers in adolescents with depressive and comorbid anxiety disorders: a study protocol
Bibliographic record
Abstract
Background Psychosocial stress is a major risk factor for adolescent depression and anxiety, impacting neurodevelopment through hypothalamic-pituitary-adrenal axis and oxytocinergic system dysregulation. Stress-related alterations in fronto-limbic resting-state functional connectivity (rsFC) have been linked to depression and anxiety disorders, yet the role of oxytocin in these processes remains unclear. Existing research often excludes comorbid anxiety or focuses on adults, limiting insights into developmental trajectories and stress-related brain changes in youth. This study aims to investigate the association of peripheral oxytocin, cortisol, and α-amylase and fronto-limbic rsFC in response to psychosocial stress in adolescents with depressive disorders, comparing those with and without comorbid anxiety disorders and healthy controls. Methods This study will include a total of 90 participants (aged 12–17 years), comprising three groups (n = 30 per group): (1) adolescents with Major depressive disorder (MDD), (2) MDD with comorbid anxiety disorder, and (3) healthy controls. After a clinical examination and psychometric assessment, participants undergo Magnetic Resonance Imaging to assess rsFC before and after stress induction. Furthermore, Diffusion Tensor Imaging is conducted. Psychosocial stress is induced using the Montreal Imaging Stress Task, which requires participants to solve arithmetic tasks under time and social pressure. Saliva samples are collected at multiple time points to analyse oxytocin, cortisol and α-amylase levels. Discussion This study offers valuable insights into the neurobiological mechanisms of stress in adolescents with depression and comorbid anxiety disorders. By examining the relationship between fronto-limbic rsFC and endocrine responses, the findings may inform the development of more targeted interventions, such as neuromodulation techniques, to improve treatment outcomes for this vulnerable population.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.020 | 0.004 |
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".