QUALITY OF LIFE IN RESIDENTIAL LONG-TERM CARE: CHINESE-SPEAKING IMMIGRANTS IN BRITISH COLUMBIA
Bibliographic record
Abstract
Objectives: The care provided by a majority of ‘mainstream’ Residential Long-Term Care (RLTC) facilities is incompatible with the needs of immigrant older adults. In British Columbia (BC), Canada, Chinese-origin older adults are a substantial and growing minority and research indicates that RLTC facilities not targeted at this population need direction to assist them in providing culturally competent care. Accordingly, our study seeks to identify which features of RLTC have the greatest impact on the quality of life of this subpopulation. Methods: A qualitative pilot study conducted in BC included 9 in-depth one-to-one interviews in two RLTC facilities with Chinese-origin residents and 11 family members who regularly visit such residents. We captured perspectives on residents’ quality of life (QoL) using an adapted version of an interview protocol established as trustworthy among diverse older adults in the U.K. This framework, developed by the National Centre for Social Research, understands the QoL of older adults to be contingent on their capability to pursue five conceptual attributes: attachment, role, enjoyment, security and control. Results: Participants perceived that the capability of residents to pursue the following dimensions of QoL was influenced by the organizational, social and/or physical features of the facilities in which they resided: Attachment (especially connection to the outside world), Control (especially decision-making), Enjoyment and Safety/Security. Conclusions: Findings concerning both positive and negative influences on older immigrant QoL that the facility can modify will provide direction and highlight priorities for RLTC administrators and policy makers.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".