Etiopathology and neurobiology of obsessive-compulsive disorder: focus on biological rhythms and chronotherapy
Bibliographic record
Abstract
Abstract: This review examines biological rhythms in persons with obsessive–compulsive disorder (OCD) and their potential relevance to the pathophysiology and treatment of this disorder. In some cases of OCD, the expression of affective, cognitive, and behavioral symptoms may be influenced by circadian and seasonal rhythms, and this could possibly interact with other neurophysiological factors. Further work is required to characterize circadian profiles linked to OCD, but findings thus far highlighted delays in both the sleep–wake cycle and melatonin secretion, as well as reduced circadian rhythmicity of body temperature. It is proposed that these changes in behavioral and endogenous rhythms may increase one’s vulnerability to obsessive–compulsive symptoms. Accordingly, obsessive–compulsive symptoms appear to be more severe in individuals with lower circadian amplitude and often worsen in the afternoon and evening. An increasing number of studies reported encouraging outcomes following the integration of sleep and circadian-based treatments in the management of OCD. There is a need for larger controlled trials evaluating the efficacy of chronotherapies in the context of OCD. Keywords: chronobiology, circadian rhythms, sleep–wake cycle
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".