The Natural History of Insomnia: Acute Insomnia and First-onset Depression
Bibliographic record
Abstract
STUDY OBJECTIVES: While many studies have examined the association between insomnia and depression, no studies have evaluated these associations (1) within a narrow time frame, (2) with specific reference to acute and chronic insomnia, and (3) using polysomnography. In the present study, the association between insomnia and first-onset depression was evaluated taking into account these considerations. DESIGN: A mixed-model inception design. SETTING: Academic research laboratory. PARTICIPANTS: Fifty-four individuals (acute insomnia [n = 33], normal sleepers [n = 21]) with no reported history of a sleep disorder, chronic medical condition, or psychiatric illness. INTERVENTIONS: N/A. MEASUREMENTS AND RESULTS: Participants were assessed at baseline (2 nights of polysomnography and psychometric measures of stress and mood) and insomnia and depression status were reassessed at 3 months. Individuals with acute insomnia exhibited more stress, poorer mood, worse subjective sleep continuity, increased N2 sleep, and decreased N3 sleep. Individuals who transitioned to chronic insomnia exhibited (at baseline) shorter REM latencies and reduced N3 sleep. Individuals who exhibited this pattern in the transition from acute to chronic insomnia were also more likely to develop first-onset depression (9.26%) as compared to those who remitted from insomnia (1.85%) or were normal sleepers (1.85%). CONCLUSION: The transition from acute to chronic insomnia is presaged by baseline differences in sleep architecture that have, in the past, been ascribed to Major Depression, either as heritable traits or as acquired traits from prior episodes of depression. The present findings suggest that the "sleep architecture stigmata" of depression may actually develop over the course transitioning from acute to chronic insomnia.
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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 | 0.001 | 0.003 |
| 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) | 0.002 | 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".