The Relationships Between the Geriatric Practice Environment, Nursing Practice, and the Quality of Hospitalized Older Adults’ Care
Bibliographic record
Abstract
PURPOSE: To test the relationships between the geriatric practice environment, geriatric nursing practice, and overall quality of care for older adults and their families as reported by nurses working in hospitals, while controlling for nurse and hospital characteristics. DESIGN: A cross-sectional tailored survey design was employed. A questionnaire was mailed to a randomly selected sample of nurses whose primary practice area was medicine, surgery, geriatrics, emergency, or critical care in acute care hospitals in Ontario, Canada. METHODS: Participants (N = 2,005) working in 148 hospitals responded to validated measures of the geriatric practice environment, geriatric nursing practice, overall quality of care for older adults and their families, and nurse and hospital characteristics. The relationships were tested using structural equation modeling. FINDINGS: Controlling for nurse and hospital characteristics, the geriatric practice environment had a statistically significant positive relationship of large magnitude with both geriatric nursing practice (β = 0.52) and overall quality of care (β = 0.92); however, the indirect relationship between the geriatric practice environment and overall quality of care, mediated by geriatric nursing practice, was not significant (β = -0.02). Final model fit was acceptable, with the root mean square error of approximation = 0.07, comparative fit index = 0.93, and Tucker-Lewis Index = 0.87. CONCLUSIONS: A strong geriatric practice environment positively and directly influences geriatric nursing practice and overall quality of care for older adults and their families but does not appear to influence overall quality of care indirectly through geriatric nursing practice. CLINICAL RELEVANCE: The results can be used as the basis for promoting practice environments that support overall quality of care and geriatric nursing practice in acute care hospitals.
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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 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".