Development of Professionalism Assessment Scale for Nurse Educator
Bibliographic record
Abstract
Nursing profession began with a genuine desire to serve and care for others, combined with a sense of compassion and commitment. Nurse Educator play a vital role in the health care system globally. The professionalism and performance of Nurse Educators, link closely to the productivity and quality of services they provide. It is important to identify factors influencing professionalism of Nurse Educators if the quality of education in the organizations to be improved. A non experimental methodological study was carried out to develop professionalism assessment scale for Nurse Educator. The conceptual framework used to guide this study was Healthy Work Environments for Nurses-Components, Factors and Outcomes developed by Registered Nurses’ Association of Ontario in 2007. Scale was prepared under five stages i;e conceptualization and item generation, preliminary evaluation, administration to development sample, analysis of scale development data and scale refinement and validation. Psychometric qualities of the scale such as validity (content, convergent, divergent and know group) and reliability (internal consistency and stability) was determined at preliminary level. After preliminary evaluation, scale was introduced to 30 Nurse Educators of various nursing institutions using judgmental sampling technique. SPSS was used for statistical analysis. Factor analysis approach was used to determine construct validity of the scale. Principal component analysis (extraction method) was used to determine total variance of scale items which resulted into extraction of nine components (domains of professionalism) of scale based on Eigen value =1. Further Varimax with Kaiser Normalization (Rotation Method) was performed to determine scale items correlation and all 34 scale's items were positively correlated and retained in the scale (Based on factor loading of 0.4). Reliability (internal consistency) of scale was determined. Cronbach's Alpha is used to determine internal consistency (p=.926) where as test retest method was used to determine scale's stability (p=.89) and scale found to be reliable. Domain wise correlation were also calculated which indicates high internal consistency among all nine domains of scale. Finally scale user's norms were established.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".