The Attrition and Migration Behaviour among Hungarian Radiographers
Bibliographic record
Abstract
INTRODUCTION: Organizations are social systems where human resources are the most important factors. In recent years, healthcare employers have assigned a high priority to the recruitment of educated health professionals. The aim of our study was to identify the possible reasons behind the migration and attrition behaviour among Hungarian radiographers. We were interested whether the professional staff have ideas across borders which can be connected with attrition.MATERIAL & METHODS: In our cross-sectional retrospective study we used a self designed questionnaire and the Effort-Reward Imbalance (ERI) Questionnaire’s shortened version. Our target group were active radiographers with BSC radiography degree. The study sample counted 216 radiographers (n=216). For data analysis we used the SPSS 13.0. Variance analysis, paired sample T-test, Chi-square test, linear regression and descriptive statistics were used with the performed probability of 95% (p<0.05).RESULTS: 30.6% of responders (n=66) were considering working abroad, 40.3% (n=87) of responders remain in Hungary. At the age group of 20–30 we can observe significant relationship between the working opportunity abroad (p=0.001). The migration tendency was specific for radiographers with no children (n=54). We found a significant relationship between the working ability abroad and the radiographers’ years spent working in the healthcare system (p=0.008). 41.7% of respondents (n=90) think that it would be a favorable option to making a career change. We also found a significant relationship between the possibility of working abroad and the desire for higher wages and the lack of making career advancements as a radiographer (p=0.001; p=0.001).CONCLUSION: Correlation of our results with similar research was difficult because very few researchers put their interest into radiographers. In respect to other healthcare workers (eg.: nurses, physiotherapists) our result correlate well with the literature. Our research provides a broad view of the migration and attrition tendency among Hungarian radiographers and its underlying causes. According to our study changes should be implemented in the Hungarian system to keep the younger radiographers home.
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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 | 0.007 | 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 | 0.013 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 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".