A protocol for validation of the Handover Evaluation Scale in multicultural <scp>ICUs</scp>
Bibliographic record
Abstract
BACKGROUND: Effective handover communication by nurses is essential to ensuring care continuity, care quality and patient safety and minimizing the risk of adverse events. Notably, the increasing globalization of the nursing profession and the resulting rise of multicultural workplaces in health care can affect handover communication. However, no tools have yet been developed to evaluate the current practices and factors contributing to effective handover in multicultural care settings, even though such instruments are deemed necessary to identify communication challenges and opportunities for improvement. AIMS: This paper describes the protocol that will be used in a proposed study that aims to adapt and validate an existing instrument for measuring handover quality-namely the Handover Evaluation Scale. The proposed study will also examine the factors contributing to effective handovers in a multicultural critical care context using a sequential exploratory mixed-method and will involve a qualitative and a quantitative phase. STUDY DESIGN: The first phase will explore Saudi Arabian ICU nurses' perceptions of effective shift handovers and the factors influencing handover quality. Data will be collected by recruiting 20 nurses through purposive sampling for semi-structured interviews. Interpretive description will be used to analyse the data to identify items useful for modifying the tool. Next, the tool will be modified based on the qualitative findings. Lastly, a quantitative study will be conducted based on the results of the first phase to assess the instrument's reliability and content validity and determine its internal dimensional structure. RESULTS: This paper describes the study protocol that will be applied to adapt and validate an existing tool to measure the quality of handover in multicultural ICUs, using an exploratory sequential mixed-methods design. RELEVANCE TO CLINICAL PRACTICE: The protocol described in this paper provides a framework for an adaptation of the Handover Evaluation Scale to measure handover effectiveness and to identify current challenges and factors affecting handover effectiveness in the multicultural critical care context. This version of the scale can be applied in clinical practice to determine best practices for improving handover.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".