The experience and understanding of clinical judgment of internationally educated nurses
Bibliographic record
Abstract
Clinical judgment is critical to the development of professional knowledge, as it supports the reasoning necessary for nursing practice. However, the literature indicates that a significant number of novice practitioners in health care do not meet entry-to-practice expectations for clinical judgment and have difficulty transferring knowledge and theory into practice, regardless of educational preparation and credentials. In the Ontario health-care environment, Internationally Educated Nurses (IENs) are considered novice practitioners. This study explores IENs’ experience and understanding of clinical judgment when engaged in a simulated clinical environment and in stimulated recall and reflective practice. The research employs qualitative descriptive open-ended exploratory and interpretive methods, informed by constructivism and transformative-learning theories. The participants (four IENs, aged 27-37, who were attending a university academic bridging program) participated in three interactive simulated clinical activities using high-fidelity SimMan™ manikins; each simulated activity was followed by a stimulated recall session and a focus group. The simulated activities were videotaped and stimulated recall and focus groups were audiotaped. Tanner’s Model of Clinical Judgment was used to guide this process. Thematic analysis uncovered six themes pertaining to IEN’s experience and understanding of clinical judgment: the shift from expert to novice, the need to rethink cultural competence and culturally competent care, the acknowledgement that culture and diversity are integral to understanding clinical judgment, the role of communication as a means to understanding clinical judgment, the recognition of unlearning as a way to understanding clinical judgment, and the phenomenon of unknowing as a dimension of understanding clinical judgment.
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 | 0.003 | 0.009 |
| 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".