Impact of the applied simulated and integrated learning approach on nursing assistants’ knowledge and confidence caring for frail seniors in nursing homes
Bibliographic record
Abstract
Increasing importance is being placed on optimizing the role of Nursing Aides (NAs) in improving quality of care for nursing home (NH) residents. One approach to do so is to have NAs participate in assessments embedded within the Minimum Data Set (MDS). This pilot study aimed to design and evaluate the Applied Simulated and Integrated Learning Approach (ASILA) program, a novel innovative training program for NAs employed in NHs to enhance their ability to assess residents within an inter-professional framework. A mixed quantitative and qualitative repeated measures design was used to assess changes in NAs’ knowledge and perception of assessments and resident clinical outcomes. Additionally, focus groups were conducted with NAs upon completion of the ASILA program. A total of 23 NAs and nurses in NHs in two Canadian provinces participated. The ASILA pilot program consisted of three selected modules; each module including an evidence-informed case-scenario, assessments, the use of appropriate MDS tools and documentation, care planing and reporting systems. ASILA was delivered over the course of two days per home. The primary outcome measure focused on the impact of ASILA on NA knowledge and confidence in assessing residents and understanding the relevance and use of elements if the MDS tools. Secondary outcomes included NAs' satisfaction with ASILA and the impact of ASILA on resident clinical outcomes. Data were collected one week prior, immediately after, and three months after the ASILA program. Following ASILA, NAs reported increased knowledge test scores and confidence in assessing residents by using MDS tools, although this did not reach significance after multiple testing (p = 0.0256 and p = 0.1541 respectively). NAs reported more confidence in providing care to residents (77.8%) and felt that the care provided was more resident-centered (83.3%) than before the ASILA program. There were no significant trends in improved resident outcomes following ASILA. Pilot findings indicate that the ASILA program could be a successful approach to support NAs to enhance their ability to assess residents in an inter-professional framework.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".