Addressing the turnover issue among new nurses from a generational viewpoint
Bibliographic record
Abstract
AIM: To investigate the relationship between dimensions of the psychosocial work environment and the intent to quit among a new generation of nurses. BACKGROUND: As a new generation of nurses enters the workforce, we know little about their perception of their current work environment and its impact on their intent to stay. METHOD: A self-administered questionnaire was distributed to 1002 nurses. RESULTS: The nurses who intended to quit their positions perceived a significant effort/reward imbalance as well as a lack of social support. The nurses who intended to quit the profession perceived a significant effort/reward imbalance, high psychological demands and elevated job strain. CONCLUSION: The balance between the level of effort expended and reward received plays an important role in young nurses' intent to leave. IMPLICATIONS FOR NURSING MANAGERS: Nurse Managers must offer Nexters, from the beginning of their career, a meaningful work and supportive environment. Without the efforts of the organization to improve the work environment and support nurses, this generation may not feel valued and move to another organization that will support them or another career that will offer fulfilment.
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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 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".