Nurses' Perceptions of the Reliability of an Automated Medication Dispensing System
Bibliographic record
Abstract
Automated medication dispensing systems (AMDS) technology is increasingly being implemented in health care facilities to reduce the risk of medication errors. However, the case study evidence of their effectiveness has so far been mixed. It has been suggested that the attitudes of nursing staff toward AMDS can be an important factor in influencing whether or not the technology will be successfully implemented. Nurses' attitudes toward AMDS were examined at Riverview Health Centre, a long-term care facility where the Meditrol automated dispensing system had been installed the previous year. It was found that nurses were generally distrustful of AMDS and skeptical that it had reduced medication errors. A number of technological, organizational, and social factors has been put forward to explain this distrust. In addition, the efforts of hospital administrators to raise nurses' confidence in the system's reliability were also delineated.
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How this classification was reachedexpand
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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".