Minimally invasive surgical practice: a survey of general surgeons in Ontario.
Bibliographic record
Abstract
INTRODUCTION: With the rapidly evolving techniques for minimally invasive surgery (MIS), general surgeons are challenged to incorporate advanced procedures into their practices. We therefore carried out a study to assess the state of MIS practice in Ontario. METHODS: A questionnaire was mailed to 390 general surgeons in Ontario. It addressed the surgeon's practice demographics, performance of both basic and advanced MIS procedures, the factors influencing this practice and the means of obtaining MIS training. RESULTS: Of the 390 general surgeons surveyed, 309 (79%) responded. Thirty-six of these were retired and were excluded from the analysis, leaving 273 available for study. The average age in the study group was 49.7 years; 247 (90%) were men. Of 272 who responded to the question, 116 (43%) had subspecialty training. The average surgeon's operating room (OR) time was 1.5 d/wk and the average waiting time for elective procedures was 4 weeks. We found that 257 (94%) respondents performed basic laparoscopic procedures, and 164 (60%) performed appendectomy; 135 (49%) performed at least 1 advanced laparoscopic procedure in their practice, although only 30 (22%) of these performed inguinal hernia repair. Using a Likert scale, we found that the most important factors influencing the incorporation of advanced laparoscopic procedures into surgical practice were a lack of OR time (median 4), lack of OR financial resources (median 4) and lack of training opportunities (median 4). Of surgeons responding to questions, 161 (64%) of 251 felt that the present medical environment did not allow them to meet standard-of-care requirements; they felt that it was the responsibility of academic surgical departments (214 [80%] of 268), the Canadian Association of General Surgeons (177 [68%] of 262) and the Ontario Association of General Surgeons (141 [53%] of 264) to provide continuing medical education courses for MIS training. CONCLUSION: The ability of practising general surgeons to incorporate advanced MIS procedures into their surgical practice remains a complex issue.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".