Tri‐focal Model of Care Implementation: Perspectives of Residents and Family
Bibliographic record
Abstract
PURPOSE: To explore residents' and family members' perceptions of partnership-centered long-term care (LTC) associated with implementation of the Tri-focal Model of Care. The Model promotes partnership-centered care, evidence-based practice, and a positive environment. Its implementation is supported by a specifically designed education program. METHODS: The Model was implemented over approximately 12 months in seven LTC facilities in Victoria, Australia. A qualitative exploratory-descriptive approach was used. Data were collected using individual and focus group interviews with residents and family members prior to and following implementation of the Model. Data were analyzed thematically. FINDINGS: Prior to implementation of the Model, residents described experiencing a sense of disempowerment, and emphasized the importance of communication, engagement, and being a partner in the staff-resident care relationship. Following implementation, residents reported experiencing improved partnership approaches to care, although there were factors that impacted on having a good experience. Family members described a desire to remain involved in the resident's life by establishing good communication and rapport with staff. They acknowledged this was important for partnership-centered care. Following implementation, they described experiencing a partnership with staff, giving them confidence to assist staff and be included in decisions about the resident. CONCLUSIONS: The Tri-focal Model of Care can enable residents, family members, and staff to be partners in resident care in LTC settings. CLINICAL RELEVANCE: With an ageing population, an increasing demand for complex, individualized LTC exists. Delivery of high-quality LTC requires a strategy to implement a partnership-centered approach, involving residents, family members, and staff.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.012 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.005 | 0.004 |
| Scholarly communication | 0.002 | 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".