The presence of humanistic caring before enrolling in nursing undergraduate programs: Perceptions of nursing students and nurses
Bibliographic record
Abstract
Background and objective: Learning to become a humanistic and caring practitioner is expected by nursing regulatory bodies. Previous investigations revealed that several pedagogical activities used in nursing education programs could facilitate this learning process. There are also studies that underscored the contributions of non-academical experiences to humanistic caring practices. This paper describes nursing students’ and nurses’ lived experiences prior to nursing that contribute to the development of humanistic caring.Methods: The study drew on interpretive phenomenology and 26 participants were individually interviewed. Benner’s (1994) method was adapted and concretized into five iterative phases of phenomenological analysis that cooccurred with data collection.Results: Six themes emerged from the interpretation process, describing how humanistic caring is developed before enrolling in nursing. First, there are natural humanistic and caring dispositions. Second, there are experiences 1) involving family members, 2) related to the public sector, 3) associated with a friend, 4) featuring an encounter with a nurse, and 5) related to spirituality. Overall, relationships that participants had previously developed appeared to be at the core of the development of their humanistic caring.Conclusions: The findings strongly suggest that nursing students hold a variable degree of natural dispositions. These inclinations are enhanced through experiences inextricable to human life that will most likely generate learning. Nursing students thus start their education with a definite potential to humanize care. To facilitate the development of humanistic caring, educators may encourage students to reflect on and become aware of their past experiences and learning.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".