Impact of Individual and Job Characteristics on Nurses’ Scope of Practice in Spanish Hospital Units
Bibliographic record
Abstract
Background. Nurses are one of the largest and costliest groups in healthcare organizations; therefore, it is important to comprehend their scope of practice. Aim. To contribute to the improvement of nursing resource management in medical-surgical and Intensive Care Units by identifying factors that influence the scope of nursing practice. The hypothesis was that the activities carried out by nurses in medical-surgical units and intensive care units are influenced by individual and job-related factors, with job characteristics having an additive and moderating effect on individual characteristics. Materials and Methods. Cross-sectional correlational design to test the relationship between the individual and job characteristics on the nursing scope of practice measured by the Actual Scope of Nursing Practice (ASCOP) questionnaire. The sample consisted of 270 nurses. Linear mixed effects models analysis (LME) was used with the aleatory effect of the intensive care unit (ICU). Results. Belonging to the ICU decreased the scope of practice of nurses. We found a statistically significant effect of psychological demand, practice environment, role ambiguity, and growth need strength on the scope of nursing practice. The models explained a variance up to 24%. Conclusions. Although the survey results revealed the existence of broader scope of practice levels in Spanish hospital units than in the original Canadian study, the use of scope of nursing practice remains suboptimal. Higher levels on the psychological demand, the practice environment and in the individual growth need strength were related with a broader scope of practice. Otherwise, role ambiguity negatively affected the scope of practice. Implications for Nursing Management. This article provides an analysis of the impact of individual and job-related characteristics on the nursing scope of practice. It serves as a valuable resource for both managers and nurses, offering insights to improve nurses’ working conditions and obtain more efficient workforces.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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".