Direct and Indirect Nursing Activities in Three Home Care Settings in Italy: An Observational Time and Motion Study
Bibliographic record
Abstract
BACKGROUND: Home nursing care is increasing in Italy due to chronic disease expansion and population aging. This study aimed to describe the types of home nursing activities performed in two home care settings and estimate the time dedicated to them. METHODS: A cross-sectional observational time-and-motion study was conducted in three local health authorities in northern and central Italy. Time spent on activities was recorded as total and average time per nurse. Average care time was estimated using linear multilevel mixed effects models. RESULTS: Forty-four activities were recorded across 527 visits. A total of 300 nurses (81.33% female) reported 343 h of activities: 221 hs (64.29%) on direct care and 123 h (35.71%) on indirect activities. The most time-consuming direct activities were patient assessment (54 h), pressure ulcer dressing (27 h), vascular wound dressing (22 h), and bandage application (21 h). The longest indirect activities were managing nursing documentation (62 h) and traveling to patients' homes (48 h). CONCLUSION: Time nurses spent in this study on direct care outperformed the time allocated for indirect care. However, other important direct nursing activities were not performed, including family involvement in the care process and patient self-care education.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".