Development and pilot testing of the graduate nurse transitional success scale to measure the transition to practice for the newly licensed registered nurse
Bibliographic record
Abstract
Background: The successful transition to independent practice of the Newly Licensed Registered Nurse (NLRN) secures patient safety and contribute to optimal patient outcomes. In a health care environment where patients present more acutely requiring more complex nursing care, the ability to ensure the NLRN’s successful transition to independent practice is crucial. A review of the literature identified a lack of a tested instrument to measure NLRN transitional success.Methods: An instrument was developed to meet this deficit. Content validity was established from the literature and from the review of the newly developed tool by an expert panel of nurses. Reliability of the instrument was tested with a sample of 50 self-identified NLRNs who completed the survey anonymously via Qualtrics®.Results: The final survey instrument consisted of 24 items rated using a 5-point Likert-type scale and five open ended questions. Internal consistency was assessed with Cronbach’s α with Total Score (24 items) α = .932 and the subcategories ranging from α = .770 (4 items) to α = .862 (4 items). Years of Experience was a statistically significant divider in terms of self-reported readiness, with those with 2-3 years' experience significantly different in mean total score from those with < 1 year and 1-2 years.Conclusions: The development of a tool to measure transitional success for the NLRN is possible. Further confirmatory Factor Analysis of the tool with different groups of NLRNs is required. A valid, reliable instrument to evaluate a successful transition to practice allows for individualized transition plans, orientation periods, and ultimately patient safety.
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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 | 0.009 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".