Nursing students' understanding of the Fundamental of Care: A cross sectional study in five countries
Bibliographic record
Abstract
Aim and objective. To explore the accuracy with which nursing students can identify the fundamentals of care. Background. A challenge facing nursing is ensuring the fundamentals of care are provided with compassion and in a timely manner. How students perceive the importance of the fundamentals of care may be influenced by the content and delivery of their nursing curriculum. As the fundamentals of care play a vital role in ensuring patient safety and quality care, it is important to examine how nursing students identify these care needs. Design. Cross‐sectional descriptive design. Methods. A total of 398 nursing students (pre‐ and postregistration) from universities in Sweden, England, Japan, Canada and Australia participated. The Fundamentals of Care Framework guided this study. A questionnaire containing three care scenarios was developed and validated. Study participants identified the fundamentals of care for each of the scenarios. All responses were rated and analysed using ANOVA. Results. The data illustrate certain fundamentals of care were identified more frequently, including communication and education; comfort and elimination, whilst respecting choice, privacy and dignity were less frequently identified. The ability to identify all the correct care needs was low overall across the pre‐ and postregistration nursing programmes in the five universities. Significant differences in the number of correctly identified care needs between some of the groups were identified. Conclusions. Nursing students are not correctly identifying all a patient's fundamental care needs when presented with different care scenarios. Students more frequently identifying physical care needs and less frequently psychosocial and relational needs. The findings suggest educators may need to emphasise and integrate all three dimensions. Relevance to clinical practice. To promote students' ability to identify the integrated nature of the fundamentals of care, practising clinicians and nurse educators need to role model and incorporate all the fundamental care needs for their patients.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".