Self-reported and actimetry-based cluster analysis of mood rhythmicity profiles in adolescents with and at risk for Major Depressive Disorder
Bibliographic record
Abstract
Greater self-perceived rhythmicity of mood-related symptoms and behaviors has been associated with depressive symptoms in the general public. We aimed to evaluate differences in adolescents at risk for or with a diagnosis of major depressive disorder (MDD) regarding perception of symptom rhythmicity and actimetry parameters. In this cross-sectional study, 96 adolescents were stratified into three groups based on either a diagnosis of MDD or on a composite score for the risk of developing depression: MDD, high risk (HR), and low risk (LR). Participants completed questionnaires regarding depressive symptoms (Mood and Feelings Questionnaire for adolescents) and self-perceived mood rhythmicity (Mood Rhythm Instrument for Youth - MRhI-Y). Actimetry data were collected for 10 continuous days and Non-Parametric Circadian Rhythm Analyses were performed. The MDD group reported higher MRhI-Y total scores, particularly in affective symptoms compared to both other groups. In spite of actimetry variables that did not correlate with MRhI-Y total scores, cluster analysis using MRhI-Y and actimetry revealed three distinct profiles corresponding to all groups. Identifying rhythmicity in mood-related behaviors in adolescents may help distinguish different groups at-risk for MDD and in a current depressive episode. Understanding these patterns could inform early interventions, potentially preventing the onset of the disorder in susceptible individuals.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".