Using Simulations to Integrate Technology into Health Care Aides' Workflow
Bibliographic record
Abstract
Health care aides (HCAs) are critical to home care, providing a range of services to people with chronic conditions, aging or are unable to care for themselves independently. The current HCA supply will not keep up with this increasing demand without fundamental changes in their work environment. One possible solution to some of the workflow challenges and workplace stress of HCAs is hand-held tablet technology. In order to introduce the use of tablets with HCAs, simulations were developed. Once an HCA was comfortable with the tablet, a simulated client was introduced. The HCA interacted with the simulated client and used the tablet applications to assist with providing care. After the simulations, the HCAs participated in a focus group. HCAs completed a survey before and after the tablet training and simulation to determine their perception and acceptance of the tablet. Future deployment and implementation of technologies in home care should be further evaluated for outcomes.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".