Dynamics of daily positive and negative affect and relations to anxiety and depression symptoms in a transdiagnostic clinical sample
Bibliographic record
Abstract
BACKGROUND: Despite interest in transdiagnostic dimensional approaches to psychopathology, little is known about the dynamic interplay of affecting and internalizing symptoms that cut across diverse mental health disorders. We examined within-person reciprocal effects of negative and positive affect (NA, PA) and symptoms (depression and anxiety), and their between-person associations with affective dynamics (i.e., affect inertia). METHODS: Individuals currently receiving treatment for psychological disorders (N = 776) completed daily assessments of affect and symptoms across 14 treatment days (average). We used dynamic structural equation modeling to examine daily affect-symptom dynamics. RESULTS: Within-person results indicated NA-symptom reciprocal effects; PA only predicted subsequent depression symptoms. After accounting for changes in mean symptoms and affect over time, NA-anxiety and PA-depression relations remained particularly robust. Between-person correlations indicated NA inertia was positively associated with NA-symptom effects; PA inertia was negatively associated with PA-symptoms effects. CONCLUSIONS: Results suggest that transdiagnostic affective treatment approaches may be more useful for reducing internalizing symptoms by decreasing NA compared to increasing PA. Individual differences in resistance to shifting out of affective states (i.e., high NA vs. PA inertia) may be a useful marker for developing tailored interventions.
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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 | 0.001 | 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".