Factors associated with rushed and missed resident care in western <scp>C</scp>anadian nursing homes: a cross‐sectional survey of health care aides
Bibliographic record
Abstract
AIMS AND OBJECTIVES: To describe the nature, frequency and factors associated with care that was rushed or missed by health care aides in western Canadian nursing homes. BACKGROUND: The growing number of nursing home residents with dementia has created job strain for frontline health care providers, the majority of whom are health care aides. Due to the associated complexity of care, health care aides are challenged to complete more care tasks in less time. Rushed or missed resident care are associated with adverse resident outcomes (e.g. falls) and poorer quality of staff work life (e.g. burnout) making this an important quality of care concern. DESIGN: Cross-sectional survey of health care aides (n = 583) working in a representative sample of nursing homes (30 urban, six rural) in western Canada. METHODS: Data were collected in 2010 as part of the Translating Research in Elder Care study. We collected data on individual health care aides (demographic characteristics, job and vocational satisfaction, physical and mental health, burnout), unit level characteristics associated with organisational context, facility characteristics (location, size, owner/operator model), and the outcome variables of rushed and missed resident care. RESULTS: Most health care aides (86%) reported being rushed. Due to lack of time, 75% left at least one care task missed during their previous shift. Tasks most frequently missed were talking with residents (52% of health care aides) and assisting with mobility (51%). Health care aides working on units with higher organisational context scores were less likely to report rushed and missed care. CONCLUSION: Health care aides frequently report care that is rushed and tasks omitted due to lack of time. RELEVANCE TO CLINICAL PRACTICE: Considering the resident population in nursing homes today--many with advanced dementia and all with complex care needs--health care aides having enough time to provide physical and psychosocial care of high quality is a critical concern.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".