The quality of obtaining surgical informed consent
Bibliographic record
Abstract
BACKGROUND: Informed consent goes beyond signing a form; it is a process of providing necessary information, helping patients make an informed decision, and actively participate in their treatment. AIM/OBJECTIVE: This study aimed to assess the quality of obtaining surgical informed consent in hospitals affiliated with Tehran University of Medical Sciences. Research design/participants/context: In a cross-sectional, descriptive-analytical study, 300 patients were chosen through stratified sampling from seven hospitals affiliated with Tehran University of Medical Sciences. Data were collected using a questionnaire developed by the researchers and analyzed using descriptive and analytical statistics on SPSS software. Ethical considerations: Ethical approval of this study was granted by Tehran University of Medical Sciences research ethics committee. Written informed consent for participation was obtained. The participants were reassured that their information will be used anonymously and their answers will not affect their treatment and care. FINDINGS: The mean score of quality of acquisition of informed consent was 17.13 out of 35, indicating that the quality falls in the inappropriate category. The results indicate that 48% of the signatories do not even read the form before signing it. Among the 52% who did read the consent form, 61.3% mentioned varying degrees of incomprehensibility of the consent form and 94.2% mentioned the presence of incomprehensible technical, medical and legal vocabulary. Only 12% and 18% of respondents reported that they were not in hurry and they had no fear or anxiety, respectively, when signing the form. The quality of obtaining informed consent was higher in women, younger patients, patients with higher education, and those who had special surgeries. DISCUSSION: This study shows a poor practice in obtaining surgical informed consent in Iran. It seems necessary to consider fundamental changes in the process of acquiring consent based on the temporal and local conditions of the patients.
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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 | 0.113 | 0.266 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".