Major Depressive Disorder and Sleep Disturbance in Patients with Chronic Pain
Bibliographic record
Abstract
BACKGROUND: Disturbed sleep is a common problem in both chronic pain and major depressive disorder (MDD). Moreover, many patients with chronic pain are depressed. OBJECTIVES: To examine the effects of depression on the sleep behaviour of chronic pain patients by comparing patients who did or did not meet diagnostic criteria for MDD. METHODS: A total of 60 patients with chronic musculoskeletal pain underwent structured diagnostic interviews for MDD and insomnia, and completed questionnaires assessing pain severity, disability, sleep quality, beliefs and attitudes about sleep, and sleep hygiene. For four consecutive days, they also completed a sleep diary, and reported on sleep hygiene practices and presleep arousal. RESULTS: Thirty-three patients (55%) met diagnostic criteria for MDD, most of whom (n=32 [97%]) also fulfilled criteria for insomnia disorder. Insomnia was also common among patients without MDD (21 of 27 [78%]). Participants with MDD had higher self-reports of pain, disability, dysfunctional beliefs about sleep, and, on a prospective basis, greater presleep arousal and poorer sleep hygiene. However, diary assessments of specific sleep parameters (eg, sleep onset latency, total sleep time, sleep efficiency) did not differ between the groups. DISCUSSION: Chronic pain patients with comorbid MDD exhibited more dysfunctional beliefs about sleep, poorer sleep hygiene practices and greater presleep arousal; however, diary-recorded sleep characteristics may not differ from those of patients without MDD. Chronic pain itself may disturb sleep so extensively that MDD introduces little additive effect. CONCLUSION: MDD in chronic pain may be related to the cognitive and behavioural aspects of insomnia, rather than to an incremental disturbance in the initiation or maintenance of sleep.
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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 | 0.002 |
| 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) | 0.002 | 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".