Risk communication in cataract surgery
Bibliographic record
Abstract
PURPOSE: Risk communication is an integral aspect of shared decision-making and evidence-based patient choice. There is currently no recommended way of communicating risks and benefits of cataract surgery to patients. This study aims to investigate whether the way this information is presented influences patients' perception of how risky surgery will be. METHODS AND ANALYSIS: Two-arm parallel randomised study and patients referred for cataract surgery were assigned to receive information framed either positively (99% chance of no adverse effects) or negatively (1% chance of adverse effects). Subsequently, patients rated their perceived risk of experiencing surgical side effects on a 1-6 scale. RESULTS: This study included 100 patients, 50 in each study group. Median (IQR) risk perception was 2 (1-2) in the positive framing group and 3 (1-3) in the negative framing group (p<0.0001). Risk framing was the only factor that was significant in risk perception, with no differences found by other patient clinical or demographic characteristics. CONCLUSION: Patients who received positive framing reported lower risk scores for cataract surgery than patients who received negative framing. Patient factors were not identified as significant determinants in patients' perceived risk. Larger longitudinal studies are warranted to further investigate.
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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 | 0.004 | 0.027 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".