Incorporation of Pain in Dreams of Hospitalized Burn Victims
Bibliographic record
Abstract
It has been shown that realistic, localized painful sensations can be experienced in dreams either through direct incorporation or from past memories of pain. Nevertheless, the frequency of pain dreams in healthy subjects is low. This prospective study was designed to evaluate the occurrence and frequency of pain in the dreams of patients suffering from burn pain. Twenty-eight nonventilated burn victims were interviewed for 5 consecutive mornings during the first week of hospitalization. A structured-interview protocol was used to collect information on dream content, quality of sleep, and pain intensity and location. Patients were also administered the Impact of Event Scale to assess posttraumatic symptoms. Thirty-nine percent of patients reported 19 pain dreams on a total of 63 dreams (30%). Patients with pain dreams showed evidence of worse sleep, more nightmares, higher intake of anxiolytic medication, and higher scores on the Impact of Event Scale than did patents reporting dreams with no pain content. Moreover, patients with pain dreams also had a tendency to report more intense pain during therapeutic procedures. Although more than half of our sample did not report pain dreams, these results suggest that pain dreams do occur at a greater frequency in suffering populations than in normal volunteers. More importantly, dreaming about pain may be an added stress for burn patents and may contribute to both poor sleep and higher pain intensity, which could evolve into a cycle of pain-anxiety-sleeplessness.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".