Development of ownership of patient care during clerkship
Bibliographic record
Abstract
Background: is a concept that embodies a number of professionalism attributes and involves a feeling of strong commitment and responsibility towards patient care. Little is known about how the embodiment of this concept develops in the earliest stages of clinical training. The goal of this qualitative study is to explore the development of ownership of patient care in clerkship. Methods: Using qualitative descriptive methodology, we conducted twelve one-on-one in-depth semi-structured interviews with final-year medical students at one university. Each participant was asked to describe their understanding and beliefs with regards to ownership of patient care and discuss how they acquired these mental models during clerkship, with emphasis on enabling factors. Data were inductively analyzed using qualitative descriptive methodology and with professional identity formation as the sensitizing theoretical framework. Results: Ownership of patient care develops in students through a process of professional socialization that includes enabling factors such as role modelling, student self-assessment, learning environment, healthcare and curriculum structures, attitudes of and treatment by others, and growing competence. The resulting ownership of patient care is manifested as understanding patients' needs and values, engaging patients in their care, and maintaining a strong sense of accountability for patients' outcome. Conclusion: An understanding of how ownership of patient care develops in early medical training and the associated enabling factors can inform strategies aimed at optimizing this process, such as designing curricula with more opportunities for longitudinal patient contact and fostering a supportive learning environment with positive role modelling, clear attribution of responsibilities, and purposefully granted autonomy.
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 | 0.011 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.009 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".