Interventions to improve nurse–family communication in the emergency department: A scoping review
Bibliographic record
Abstract
AIM: To determine and describe what interventions exist to improve nurse-family communication during the waiting period of an emergency department visit. BACKGROUND: Communication between nurses and families is an area needing improvement. Good communication can improve patient outcomes, satisfaction with care and decrease patient and family anxiety. DESIGN: Scoping Review. METHODS: A scoping review was conducted following the Joanna Briggs Institution methodology: (1) identify the research question, (2) define the inclusion criteria, (3) use a search strategy to identify relevant studies using a three-step approach, (4) select studies using a team approach, (5) data extraction, (6) data analysis, and (7) presentation of results. DATA SOURCES: Medline, CINAHL, EMBASE, PsychInfo and grey literature were searched on 3 August 2022. RESULTS: The search yielded 1771 articles from the databases, of which 20 were included. An additional seven articles were included from the grey literature. Paediatric and adult interventions were found targeting staff and family of which the general recommendations were summarised into communication models. CONCLUSION: Future research should focus on evaluating the effectiveness of interventions using a standardised scale, understanding the specific needs of families, and exploring the communication models developed in this review. IMPLICATIONS FOR CLINICAL PRACTICE: Communication models for triage nurses and all emergency department nurses were developed. These may guide nurses to improve their communication which will contribute to improving family satisfaction. REPORTING METHOD: PRISMA-ScR. TRIAL AND PROTOCOL REGISTRATION: Protocol has been registered with the Open Science Framework, registration number 10.17605/OSF.IO/ETSYB. PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.
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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 | 0.034 | 0.115 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.007 | 0.008 |
| Bibliometrics | 0.019 | 0.016 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 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".