Informed consent for cataract surgery: What patients do and do not understand
Bibliographic record
Abstract
PURPOSE: To determine patients' understanding and opinions about the usefulness of the informed consent (IC) document for cataract surgery and evaluate the deterioration in the effectiveness of verbal and written IC over time. SETTING: Academic tertiary care center. METHODS: Multiple-choice questionnaires addressing specific information about cataract surgery were distributed to patients. The questionnaires covered topics such as treatment, risk, and outcome probabilities (assessed preoperatively and postoperatively); terminology commonly used in IC; and patients' opinions about IC. Scores were calculated and compared using paired and unpaired t tests. RESULTS: Twenty-six patients thought that their legal autonomy would be waived by signing a consent form. Patients who took part in a standardized discussion of IC before testing scored 73.4% versus 23.4% in a control group who received no IC counseling (P<.001). Patient recall of outcome probabilities significantly decreased between preoperative and postoperative testing (61.2% to 44.0%) when IC was given verbally but improved to 75.0% when patients were given written information to take home. CONCLUSIONS: Patients about to consent to cataract surgery had a reasonable grasp of basic terminology. A standardized IC discussion was effective in educating patients. Patients considered IC to be important and expected all pertinent information to be communicated. Patient recall of outcome probabilities was poorer than that of nonnumeric facts; however, memory decay may be slowed by providing supporting take-home literature.
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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 | 0.046 | 0.196 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.004 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.004 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".