The knowledge, attitudes, and practices of arteriovenous access assessment among hemodialysis nurses: A multicenter cross‐sectional survey
Bibliographic record
Abstract
INTRODUCTION: Hemodialysis nurses' cannulation technique, monitoring, and management methods can affect patients' vascular access longevity. An arteriovenous access assessment comprises a medical history and vascular assessment through physical examination and surveillance. However, further exploration is needed to fully understand hemodialysis nurses' knowledge, attitudes, and practices (KAP) in this area. METHODS: Between June and July 2023, we recruited hemodialysis nurses from 21 cities in Guangdong Province using a convenience sampling method. Four questionnaires-the General Data Questionnaire, the KAP Scale of Arteriovenous Access Assessment among Hemodialysis Nurses, the Utrecht Work Engagement Scale, and the NASA Task Load Index-were utilized for data collection through the Questionnaire Star platform. FINDINGS: Of the 530 hemodialysis nurses participating in the study, 458 (86.4%) had a valid response. The participants demonstrated moderate knowledge and practice levels regarding arteriovenous access assessment and exhibited positive attitudes. We identified several factors related to arteriovenous access assessment that predict KAP in hemodialysis nurses. These factors included years of experience as a hemodialysis nurse, whether a nurse's knowledge of physical examination was sufficient to meet clinical needs, whether a nurse had received training in performing physical examination, whether a nurse's department regularly checked the quality of physical examination, and nurses' levels of work engagement and mental workload. All factors explained 32.4% of the variance in participants' KAP regarding arteriovenous access assessment. DISCUSSION: Improving hemodialysis nurses' assessment of arteriovenous access is crucial to ensure optimal patient care. Dialysis center managers and educators should prioritize understanding hemodialysis nurses' KAP of arteriovenous access assessment and any factors influencing these areas.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".