A randomised trial of photograpic reinforcement during postoperative counselling after diagnostic laparoscopy for pelvic pain
Bibliographic record
Abstract
OBJECTIVE: To measure the effect of seeing a photograph of the pelvic findings at laparoscopy. SETTING: Two university teaching hospitals. METHOD: A randomised-controlled trial. SUBJECTS: Two hundred thirty-three women undergoing diagnostic laparoscopy for the investigation of chronic pelvic pain. INTERVENTIONS: At operation a Polaroid print was taken of the pelvis. If this was of satisfactory quality, the patient was randomly allocated to either see, or not see, the print during the postoperative consultation. MAIN OUTCOMES: Pain severity and pain belief scores at 3 and 6 months. ANALYSIS: By intention to treat. RESULTS: Postoperative consultations with photographs did not improve immediate understanding and satisfaction with the consultation. In addition, compared to controls, both patients and doctors did not perceive particular benefit for communication from the photograph. There was a consistent trend to more pain in the photographic reinforcement group and more negative pain beliefs. At 3 months, the average within person differences showed some benefit in visual analogue pain scores, McGill affect scores, 'permanence' and 'self-blame' scores. These benefits were not statistically significant. At 6 months, there was a consistent pattern of benefit from pain severity and pain beliefs, again these benefits were not statistically significant. CONCLUSION: No clear benefits result from showing patients photographs of their pelvis.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".