Work-related factors influencing home care nurse intent to remain employed
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
BACKGROUND: Health care is shifting out of hospitals into community settings. In Ontario, Canada, home care organizations continue to experience challenges recruiting and retaining nurses. However, factors influencing home care nurse retention that can be modified remain largely unexplored. Several groups of factors have been identified as influencing home care nurse intent to remain employed including job characteristics, work structures, relationships and communication, work environment, responses to work, and conditions of employment. PURPOSE: The aim of this study was to test and refine a model that identifies which factors are related to home care nurse intentions to remain employed for the next 5 years with their current home care employer organization. METHODOLOGY/APPROACH: A cross-sectional survey design was implemented to test and refine a hypothesized model of home care nurse intent to remain employed. Logistic regression was used to determine which factors influence home care nurse intent to remain employed. FINDINGS: Home care nurse intent to remain employed for the next 5 years was associated with increasing age, higher nurse-evaluated quality of care, having greater variety of patients, experiencing greater meaningfulness of work, having greater income stability, having greater continuity of client care, experiencing more positive relationships with supervisors, experiencing higher work-life balance, and being more satisfied with salary and benefits. PRACTICE IMPLICATIONS: Home care organizations can promote home care nurse intent to remain employed by (a) ensuring nurses have adequate training and resources to provide quality client care, (b) improving employment conditions to increase income stability and satisfaction with pay and benefits,
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it