Pain Specialists' Evaluation of Patient's Prognosis During the First Visit Predicts Subsequent Depression and the Affective Dimension of Pain
Bibliographic record
Abstract
OBJECTIVE: To examine the predictive value of physician's prognosis after patient's first visit to a pain specialty clinic. DESIGN: This is a prospective-longitudinal study in which patients completed questionnaires regarding their pain and psychological constructs before their first visit to a pain specialist and again after an average of 5 months. Physicians rated patient's prognosis immediately after the first visit. SETTING: This study was conducted at the outpatient specialty pain clinic at Soroka University Medical Center. PATIENTS: Forty-five chronic pain patients suffering from a range of nonmalignant pain conditions. OUTCOME MEASURES: Sensory and affective pain measured by the Short-Form McGill Pain Questionnaire and depressive symptoms measured by the Center for Epidemiological Studies-Depression Scale. RESULTS: Multiple regression analysis revealed that physician's rating of patient prognosis at Time 1 uniquely predicted subsequent depressive symptoms and affective pain but not sensory pain at Time 2 even after controlling for Time 1 levels of these variables. CONCLUSION: Physician's pessimistic evaluation of patient's prognosis after the first visit was longitudinally associated with an increase in depression and in the affective dimension of pain over time, but not with changes in the sensory component of pain. Referring to physician pessimism as a marker for pre-depressed patient may lead to early preventive interventions.
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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 | 0.006 |
| 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) | 0.002 | 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".