Job Satisfaction Among Multiple Sclerosis Certified Nurses
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Several studies document high levels of job satisfaction among certified nurses, but no study has examined job satisfaction and factors influencing job satisfaction of certified multiple sclerosis (MS) nurses. This study tested a theoretical model proposing that two organizational factors, colleague relationships and benefits, will predict job satisfaction. Job satisfaction was represented by four factors: autonomy, professional status, professional growth, and time efficiency. Participants included MS nurses certified for 6 months or more practicing mostly in three countries (Canada, Great Britain, and the United States) who anonymously completed the Misener Nurse Practitioner Job Satisfaction Scale, an overall job satisfaction rating, and demographic information. Findings indicate that colleague relationships and benefits significantly estimated organization structure and that autonomy, professional status, professional growth, and time efficiency significantly estimated job satisfaction; furthermore, organization factors such as colleague relationships and benefits significantly predict job satisfaction. Among the countries, several statistically significant differences were observed between job satisfaction factors as well as items in both organization and job satisfaction subscales. Average factor scores among the countries were mostly rated satisfactory. The International Organization of Multiple Sclerosis Nurses Executive Board plans to use the study findings to see how it needs to focus efforts as an organization toward enhancing and standardizing MS care and develop MS nurse professionalism worldwide.
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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 | 0.002 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it