Anticipation or avoidance: internal medicine resident experiences performing invasive bedside procedures
Bibliographic record
Abstract
Background: Internal Medicine (IM) residents are required to perform bedside procedures for diagnostic and therapeutic purposes. Residents' experiences with procedures vary widely, for unclear reasons. Objective: To explore IM residents' experiences with performing bedside procedures and to identify barriers and facilitators to obtaining sufficient experience. Methods: Using an inductive, thematic approach, we conducted five individual semi-structured interviews and one focus group with seven IM residents (12 residents in total) during the 2017-2018 academic year at a Canadian tertiary care centre. We used iterative, open-ended questions to elicit residents' experiences, and barriers and facilitators, to performing bedside procedures. Transcripts were analyzed for themes using Braun and Clarke's method. Results: We identified four themes 1) Patient-specific factors such as body habitus and procedure urgency; 2) Systems factors such as time constraints and accessibility of materials; 3) Faculty factors including availability to supervise, comfort level, and referral preferences, and 4) Resident-specific factors including preparation, prior experiences, and confidence. Some residents expressed procedure-related anxiety and avoidance. Conclusion: Educational interventions aimed to improve procedural efficiency and ensure availability of supervisors may help facilitate residents to perform procedures, yet may not address procedure-related anxiety. Further study is required to understand better how procedure-averse residents can gain confidence to seek out procedures.
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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 | 0.003 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".