Role discrepancy: is it a common problem among nurses?
Bibliographic record
Abstract
AIM: This paper reports a study of nurses' perceptions of the differences between ideal and actual nursing roles, how these perceptions differ according to length of experience and the factors that might contribute to these perceived differences. BACKGROUND: The literature suggests that nurses tend to experience role discrepancy or a mismatch between their ideal and actual roles. Although it has been assumed that experienced nurses perceive less role discrepancy than inexperienced nurses, either because the former adjust themselves to their actual practice or because they have the expertise to improve their practice, this assumption has not been tested. METHODS: A survey design was used and the data were collected in 2003. Selected items from the Jefferson Survey of Attitudes Toward Physician-Nurse Inventory and the Staff Nurse Role Conception Inventory were administered to 216 Registered Nurses in Victoria, Australia to measure their perceptions of ideal and actual nursing roles. Data were analysed using a t-test and regression analysis. RESULTS: Nurses with more clinical experience rated their ideal and actual nursing roles more positively than those with less experience. However, the results showed that both groups of nurses experienced the same degree of role discrepancy. Both groups perceived strong role discrepancy in the areas of organizational decision-making and provision of patient education. Experienced nurses also perceived moderate role discrepancy in developing nursing care plans and in the freedom to initiate referrals. CONCLUSIONS: Role discrepancy cannot be resolved by having more clinical experience. While clinical experience enhances nurses' conceptions of their ideal roles, it can also lead to role discrepancy if there are organizational barriers that prevent nurses from engaging in their ideal roles. It is important to find a way whereby nurses can actualize their ideal views of practice in the current healthcare environment.
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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 | 0.000 | 0.000 |
| 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 | 0.001 |
| 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".