Needs, preferences and decision-making regarding long-term residential care: South Asian older adults' and family caregivers' perspectives
Bibliographic record
Abstract
The aging Canadian population is becoming increasingly ethno-culturally diverse primarily due to immigration. This, together with research indicating increased likelihood of long-term residential care (LTRC) use at older ages and challenges in providing these services, prompt important questions about whether LTRC services are prepared to provide culturally responsive and competent care to immigrant and ethno-cultural minority older adults (EMOA). This ethnographic study, informed by a critical theoretical perspective, explored these questions from the perspectives of South Asian older adults (SAOAs) and their family caregivers (FCGs). In-depth interviews with 18 SAOAs in LTRC, assisted living and those at home, their FCGs, and seven key informants from LTRC and the South Asian (SA) community (n=43) were undertaken. These interviews, in addition to 220 hours of participant observation in two LTRC facilities, provided information regarding the needs, preferences, experiences and situation of SAOAs in LTRC as well as how SA families make decisions regarding the use of such services. A select review of provincial policy, residential care regulation, health authority and facility documents, exposed taken-for-granted assumptions in how care and services are provided and the sociopolitical context of LTRC provision. Study findings suggest that LTRC services are challenged to meet the needs of immigrant and EMOA and reflect unequal and inequitable care, illuminated by the differential impact of macro-policies and resource-constrained LTRC environments on SAOAs and their families and on the ability of existing LTRC services to provide person-centred care. This inequity in service provision has implications for immigrant and EMOA and their family members in light of findings that the decision to move to LTRC is essentially a (non) decision influenced by a range of social structural factors that interact to necessitate the move to LTRC. Study findings revealed the salience of socio-economic status and economic resources in particular, in the (non) decision for LTRC placement. The findings from this study along with demographic shifts in the aging Canadian population call for LTRC service providers and policy makers to actively prepare for increasing ethno-culturally diverse resident populations and point to the need for equity informed approaches to the care of older adults.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| 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".