An Assessment of Institutional Relocation: Qualitative Perceptions and Resident Outcomes
Bibliographic record
Abstract
Relocation among older adults, either from their home to a long term care (LTC) facility or between facilities, has been studied since the early 1960s. The earliest studies focused on resident mortality while more recent papers have included other outcomes such as functional ability, depression, behavioral symptoms and general health and well-being.\nCastle reviewed 78 studies measuring the impact of relocation. The vast majority of studies found no significant positive or negative effects of relocation. However, these studies were limited by sample size, equivocal time frames for outcome measurements and the lack of control groups.(1). Although the topic has clear relevance to Canadian LTC and complex continuing care (CCC) facilities, the Canadian literature is sparse.(2-4)\nSt. Joseph’s Hospital and Home has been providing care for the people of Guelph since 1861. Planning began for a new building in 1994 and at that time, the decision was made to change the focus of the services provided. The acute care portion of the staff and services were divested in 2001 to the Guelph General Hospital. In October 2002, residents, staff and volunteers moved into the new facility located on the existing property. The new 254-bed facility, known as St. Joseph’s Health Centre (SJHC), includes LTC, complex continuing care and rehabilitation inpatient services as well as several outpatient programs.\nThe current study attempted to broaden the understanding of relocation from the perspectives of residents, families and staff at SJHC. Several characteristics of this project made it unique. For example, it took place within a Canadian context, used both qualitative and quantitative data collection methods, included families and staff and included questions to elicit a set of recommendations for other facilities preparing for a similar move.
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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 | 0.011 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".