EXPLORING FAMILY INVOLVEMENT IN RESIDENT CARE CONFERENCES IN LONG-TERM RESIDENTIAL CARE
Bibliographic record
Abstract
Current long-term residential care (LTRC) policy emphasizes the need for collaborative, team-based care planning that actively involves families and/or residents. Resident care conferences are one of the more common ways in which care providers, families and/or residents come together to discuss and coordinate resident care needs and evaluate care goals. To date, research in this area has focused on evaluating conference outcomes (e.g., improved end-of-life care); far less is known about the care conference process such as how care is negotiated and how care decisions are made. Drawing on data from a critical ethnography examining the negotiation of care work among families and staff in three LTRC facilities in British Columbia, Canada, this presentation explores the process, structure and content of care conferences. Thirty-seven care conferences were observed and informal conversations held with families and staff following the conference. Additional information came from interview data from the larger study (n=37 family, 35 care staff). Grounded in critical theory, thematic analyses identified two key themes, Following Script and Devaluing Knowledge. Following Script reveals how the conference agenda and ensuing discussion was a tightly-controlled, homogenized process, in which opportunity for meaningful input from families was severely curtailed. Devaluing Knowledge outlines how adherence to script and clinical ways of knowing subjugated family members’ knowledge of residents’ needs and care goals, again limiting family contributions. A series of practice recommendations outline how to engage and empower families as active participants in care conference decision-making and planning.
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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 | 0.015 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.014 | 0.007 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.003 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".