Staff-Family Communication Methods in Long-Term Care Homes: An Integrative Review
Bibliographic record
Abstract
Context: Communication methods have been trialled to promote staff-family relations and facilitate person-centred care for residents living in long-term care homes. A review and synthesis of the common methods will inform the development of staff-family communication methods, policy and best practice guidelines. Objectives: 1) synthesise and summarise common communication methods, and types(s) of delivery, used for staff-family communication in long-term care homes; and 2) identify any challenges that impacted the implementation of the communication method(s). Methods: An integrative review was employed to incorporate papers with diverse research designs. It involved a comprehensive database and grey literature search, and study selection based on inclusion criteria. Data from included studies were extracted, coded and categorised by common communication method, delivery type(s) and challenges; studies were assessed for quality. Findings: A total of 3,183 potential papers were retrieved from seven international databases. Twenty-four original papers from six countries meeting inclusion criteria were reviewed and assessed for quality (M = 30; SD = 3.8). Common communication methods (structured education, meetings and takeaway resources) and challenges to implementation (confusion, misunderstanding and disagreement; lack of time; and technological difficulties) were identified and summarised. Limitations: The exclusion of papers published more than 20 years ago, geographical concentration of studies in high-income countries, and absence of stakeholder consultation may limit the generalisability and depth of the findings. Implications: Staff professional development and education, technology training and support, and accessibility of information in pamphlets and resources for family are crucial for facilitating staff-family communication in long-term care homes.
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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 | 0.029 | 0.081 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.011 | 0.011 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.002 | 0.003 |
| 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".