Informed Consent: Exploring Surgical Residents' Beliefs, Attitudes and Practices
Bibliographic record
Abstract
Patients rely on the knowledge and skill of the physician proposing treatment to relay information and inform their decision-making. In academic medical centres (AMCs), surgical trainees frequently request consent on behalf of an attending surgeon. There is a paucity of knowledge regarding the frequency of this practice and any associated impacts on surgical trainees. This study poses the following queries: (1) Are surgical residents requesting informed consent (IC) while perceiving themselves to possess insufficient knowledge to facilitate the IC process? (2) If yes, what motivates a resident to request IC with inadequate knowledge? (3) Do residents experience an emotional response? (4) What, if any, support mechanisms are sought? Surgical residents in a Canadian urban AMC (n = 38) completed a survey designed to assess how surgical trainees complete the process of IC as well as probe beliefs and attitudes associated with its execution. This study finds that surgical residents frequently seek consent from patients while perceiving themselves insufficiently informed to discuss the risks and benefits of proposed procedures. The majority of participants (82%) indicated that they had personally requested consent while believing themselves inadequately aware of relevant surgical risks. Surgical trainees see this as a significant issue, feel motivated to complete the IC process due to perceived pressures, experience emotional distress and commonly seek collegial support. A cohort of residents from various surgical departments reported requesting IC while possessing inadequate knowledge to inform patient decision-making. Management of this reality could better ensure that the surgical environment both safeguards patients and enhances trainee education.
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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 | 0.015 | 0.054 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| 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".