Piloting a Supplemental Assessment Tool with Younger Residents of Long-Term Care
Bibliographic record
Abstract
Background: Young adults living with disabilities may sometimes end up in long-term care facilities which may not always meet their needs. Our project set out to pilot a supplemental assessment tool, a questionnaire to be used upon admission of younger adults into long-term care. We wanted the opinions of both staff and younger residents on what modifications may be needed in the implementation processes to ensure effectiveness of the tool. Methods: This project followed a qualitative design, implementing a previously designed supplemental assessment tool with five staff members and seven younger residents of two long-term care homes in Halifax, Nova Scotia. Residents completed the questionnaire with members of staff involved in admissions. Each group participated in follow-up interviews regarding their thoughts on implementation of the tool. Responses were analyzed using the constructs of the Consolidated Framework in Implementation Research following direct content analysis methods. Results: Feedback from residents and staff suggested that the tool could not be used as a one-size-fits-all solution but that flexibility in the format, content, and structure of the tool would be beneficial to ensure its utility in a variety of settings. Issues raised by staff and residents included, but were not limited to, accessibility of the intervention, the availability of resources, the format of the intervention and topics covered within it, and ensuring that processes for implementation are clearly defined. Conclusions: Both staff and residents approved of the tool for use in the admissions process and agreed that it would enhance the admissions practices already in place.
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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 | 0.023 | 0.031 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".