CLIENTS’ AND CAREGIVERS’ EXPERIENCES OF A COMMUNITY-BASED SUPPORT SERVICE PROGRAM “BETTER AT HOME”
Bibliographic record
Abstract
This qualitative study explored older adult clients’ and family caregivers’ experiences of the Better at Home (B@H) program, a non-medical home support service program to foster older adults’ independent living in their homes in British Columbia, Canada. Forty clients (age 60+) of the program and 14 informal caregivers were recruited in Metro Vancouver and North Okanagan who participated in semi-structured interviews (April 2016 - May 2017). The interviews with clients elicited their experiences of B@H regarding its impact on their levels of health, independence and community participation. The interviews with family caregivers explored their perceptions of how B@H influenced the older adult clients as well as themselves regarding functioning and social engagement. Using a thematic analysis approach, we analyzed clients’ and caregivers’ interviews separately and compared the findings between the two groups. The findings revealed: 1) clients’ levels of satisfaction with B@H (e.g., accessibility, affordability, quality of services); 2) clients’ and caregivers’ perceptions of the impact of B@H on clients’ physical and mental health (e.g., saving personal energy, reduced stress) and social participation; 3) the impact of B@H on caregivers’ health (e.g., decreased pressure) and social engagement (e.g., time to pursue their own goals); and 4) suggestions to enhance and advance B@H in supporting older adults’ independent living in their homes and communities. The findings indicate that while both clients’ and caregivers’ experiences of B@H were generally positive, there is a diversity of client needs. Implications for the program will be discussed.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".