Bibliographic record
Abstract
PURPOSE: Context has a critical influence on individuals' behaviors and is essential to understanding lapses in professionalism, yet little is known about contextual factors relevant to practicing physicians. This study used standardized professionalism dilemmas, or challenges, to explore practicing internists' reasoning in their handling of typical challenges. METHOD: In spring 2011, the authors created several professional challenges relevant to physicians in practice and conducted five focus groups with practicing internists (n = 40). Each group discussed five or six of the challenges, and the facilitators specifically asked what the participants would do and why. The authors used constructivist grounded theory to analyze the transcripts. RESULTS: The scenarios were effective in eliciting discussion and debate. Analysis revealed many guiding principles (e.g., patient welfare, keeping patients happy) that influenced physicians in their approach to professionalism challenges, but these principles were highly context-dependent. The authors found individuals' responses to be malleable and subject to much modification depending on input from peers. Responses often shifted in an iterative and complex manner, depending on factors such as the "type" of patients (including the physician's personal feelings toward them), the nature of the illness or diagnosis, and the physician's relationships with others. CONCLUSIONS: Despite recognizing and articulating basic guiding principles of professionalism, physicians' approaches to professional challenges were subject to multiple, interdependent, idiosyncratic forces unique to each situation. A deeper understanding of these factors and how they interact is critical for the development of strategies to teach and evaluate professionalism in practice.
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 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 | 0.006 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.023 |
| Scholarly communication | 0.007 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.027 | 0.012 |
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".