To What Extent are Alberta Nursing Homes and Supportive Living Facilities Integrated with Their Community? A Sequential Quantitative- Qualitative Study
Bibliographic record
Abstract
Background: Nursing homes and supportive living facilities (continuing care homes [CCH]) are often regarded as separate from their communities. Although occasional studies highlight volunteering or intergenerational activities, there is little systematic evaluation of the existence of activities in CCH that may promote community integration. Methods: Study Design: The study utilized a sequential quantitative-qualitative approach: cross-sectional survey followed by semi-structured interviews. Setting: All registered long-term care (nursing home) and supportive living facilities (Levels 3, 4, and 4 Dementia) within Alberta. Subjects: The survey and interviews were conducted with directors of care. The survey was distributed to 334 facilities. Data saturation in the interviews was reached with seven participants. Results: 140 responses were received; 116 were analyzable (34.7% response rate). The range of activities varied widely. Prior to Covid-19, the most common were spiritual activities entering CCH (96.5%) and volunteers entering CCH (93.0%); CCH rarely had activities such as child daycare (5.2%). 12.9% of spiritual activities entering CCH had not been restarted following the pandemic, but homes were planning to restart this activity (16) or start it as a new activity (1). There was no statistically significant relationship between any activity and facility owner-operator model, size, type, or geography (urban/rural) at any survey time category. Four themes emerged from the interviews: resident quality of life and well-being, home's capacity and openness, sources of support, and planning and programming for implementation. Conclusions: This study addresses a knowledge gap regarding community integration in CCH and provides insight on the types of community-integrated activities occurring in Alberta's CCH.
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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 | 0.008 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".