Mood instability as a precursor to depressive illness: A prospective and mediational analysis
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Mood instability levels are high in depression, but temporal precedence and potential mechanisms are unknown. Hypotheses tested were as follows: (1) mood instability is associated with depression cross-sectionally, (2) mood instability predicts new onset and maintenance of depression prospectively and (3) the mood instability and depression link are mediated by sleep problems, alcohol abuse and life events. METHOD: Data from the National Psychiatric Morbidity Survey 2000 at baseline (N = 8580) and 18-month follow-up (N = 2413) were used. Regression modeling controlling for socio-demographic factors, anxiety and hypomanic mood was conducted. Multiple mediational analyses were used to test our conceptual path model. RESULTS: Mood instability was associated with depression cross-sectionally (odds ratio: 5.28; 95% confidence interval: [3.67, 7.59]; p < 0.001) and predicted depression inception (odds ratio: 2.43; 95% confidence interval: [1.03-5.76]; p = 0.042) after controlling for important confounders. Mood instability did not predict maintenance of depression. Sleep difficulties and severe problems with close friends and family significantly mediated the link between mood instability and new onset depression (23.05% and 6.19% of the link, respectively). Alcohol abuse and divorce were not important mediators in the model. CONCLUSION: Mood instability is a precursor of a depressive episode, predicting its onset. Difficulties in sleep are a significant part of the pathway. Interventions targeting mood instability and sleep problems have the potential to reduce the risk of depression.
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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 | 0.001 |
| 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 it