Major Depression and Insomnia in Chronic Pain
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
OBJECTIVES: Insomnia and depression are common problems for people with chronic pain, and previous research has found that each is correlated with measures of pain and disability. The goal of this study was to examine the combined impact of major depression and insomnia on individuals with chronic pain. METHODS: The participants were patients with chronic musculoskeletal pain who underwent evaluation at an interdisciplinary treatment center. On the basis of semistructured interviews, participants were classified in three groups depending on whether they: (1) met criteria for major depression with insomnia (n = 38); (2) had insomnia without major depression (n = 58); or (3) had neither insomnia nor major depression (n = 47). The groups were then compared on self-report measures that included the McGill Pain Questionnaire, the Beck Depression Inventory, and the Multidimensional Pain Inventory. RESULTS: Participants with major depression and insomnia reported the most difficulty on measures of affective distress, life control, interference, and pain severity, although the insomniac patients without major depression also had elevated scores on some measures. In regression analyses, insomnia severity ratings did not contribute uniquely to the prediction of psychosocial problems when depression was controlled, but they did contribute to the prediction of pain severity. CONCLUSIONS: These results suggest that patients with chronic pain and concurrent major depression and insomnia report the highest levels of pain-related impairment, but insomnia in the absence of major depression is also associated with increased pain and distress.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.001 |
| 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 | 0.001 |
| 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