Relationship-Centered Care for Older Adults in Long-Term Care Homes: A Scoping Review
Bibliographic record
Abstract
This scoping review, following Levac et al.'s methodology, examines the implementation and impact of relationship-centered care (RCC) in long-term care (LTC) settings for older adults. Peer-reviewed articles from AgeLine, CINAHL Complete, MEDLINE, PsycINFO, and Web of Science were included if published after 2000, involved older adults in LTC homes, focused on RCC, and conducted in Australia, Europe, New Zealand, or North America. Key findings were organized using inductive content analysis, and 41 empirical studies with qualitative, quantitative, and mixed-methods designs were included. Three categories emerged: (1) Core Practices of RCC-relationship building and reciprocal exchange; (2) Transformative Impacts of RCC-improved care quality and collaboration; and (3) Pathways and Roadblocks to RCC-individual and organizational factors. By understanding the key elements, facilitators, and barriers of RCC, policymakers and practitioners can develop targeted strategies to improve care experiences and outcomes for residents, families, staff, and all others involved in LTC.
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 | 0.010 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.013 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".