Exploring registered nurses’ attitudes towards post graduate education in Australia-instrument development
Bibliographic record
Abstract
Normal 0 false false false EN-AU X-NONE X-NONE Background: Nursing education is designed to prepare competent nurses to meet the current and future health care needs of society. Changes to nursing education, especially at post graduate level, will therefore likely be influenced by the on-going developments in healthcare and socio-economic factors. Objective: The primary objective of this study is to develop and validate an instrument that explores the beliefs of Registered Nurses about Postgraduate education in the context of specialist nursing practice in Australia (specialty education). Methods: The Nurses ’ Attitudes Towards Post Graduate Education (NATPGE) instrument was sent to an expert panel to undertake judgment-quantification (content validity testing). Content Validity Index (CVI) based on expert ratings of relevance was used as a method of quantifying content validity for the NATPGE instrument. A convenience sample of 25 registered nurses was selected from four major Queensland tertiary hospitals to assess the face validity of the instrument. A random sample of 100 registered nurses from the Nurses and Midwives e-Cohort Study (NMeS) were invited to participate in test-retest procedures to assess the reliability of NATPGE overtime. The instrument was administered at two different time points, 3 weeks apart, under similar conditions. Results: Content and face validity was assessed using descriptive statistics. For the test-retest reliability, data were analysed on an item by item basis to calculate the intra-rater reliability using the weighted kappa (k w ) statistic. The NATPGE instrument attained moderate test-retest reliability. 80% of the items on the instrument reached a fair to moderate agreement between the test and retest. Conclusions: There is a need for development of a robust psychometric instrument to explore Registered Nurses’ Attitudes Towards Post Graduate Education (NATPGE) and this research is the first step in addressing this need.
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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 | 0.001 |
| 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 | 0.003 |
| 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".