Validity of the Medication Safety Self‐Assessment for Long‐Term Care tool in Australian long‐term care: a RAND appropriateness method study
Bibliographic record
Abstract
AIMS: The validity of using the Canadian Medication Safety Self-Assessment for Long-Term Care (MSSA-LTC) tool in the international context is unknown. This study aims to determine the face and content validity of the Canadian MSSA-LTC tool for assessing medication safety-related processes in the Australian long-term care (LTC) setting. METHODS: A modified two-round RAND/UCLA Appropriateness Method was used to assess the face and content validity of the 129 items in the Canadian MSSA-LTC tool for use in the Australian LTC setting. An expert panel of health professionals with expertise in medication management in the Australian LTC setting rated each item separately for relevance to the Australian LTC context (face validity) and importance for medication safety (content validity). Items, where there was panel agreement that the item was definitely or potentially relevant for the Australian context/important for medication safety, were considered valid for the relevant attribute. RESULTS: Nine expert panel members participated in the study. The expert panel rated 118 (91.5%) of the 129 items of the MSSA-LTC tool as acceptable relevant for the Australian LTC setting and, therefore, having face validity and all items (100%) as important for medication safety, thus having good content validity. The expert panel members were unable to agree about the relevance of nine items for use in the Australian LTC context and considered two items as not relevant for the Australian LTC context. CONCLUSIONS: The Canadian MSSA-LTC tool appears valid for measuring medication safety-related processes in Australian LTC with good face and content validity.
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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 | 0.011 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".