使用高灵敏度热素算法对巴西急诊护士进行分选排除的证据有效性
Thábata Larissa Agostini Dos Santos1, Kátia Cilene Godinho Bertoncello1, Keyla Cristiane do Nascimento1
1Universidade Federal de Santa Catarina (UFSC). Programa de Pós-Graduação em Gestão do Cuidado em Enfermagem. Florianópolis, Santa Catarina, Brasil.
使用高灵敏度热素 (TRUST) 的选排除算法成功适应了巴西护士,证明了对心脏风险评估的有效性和理解性. 这确保了其适合在巴西临床使用.
科学领域:
- 心脏病学 心脏病学
- 护理研究 护理研究
- 医疗保健服务研究 医疗服务研究
背景情况:
- 心脏风险评估在紧急情况下至关重要.
- 使用高灵敏度热素 (TRUST) 算法的分类排除有助于评估患有胸痛的患者.
- 验证各种医疗保健背景的临床工具是必不可少的.
研究的目的:
- 为了证明TRUST算法对巴西护士心脏风险评估的有效性.
- 为了确保TRUST算法的跨文化适应性,TRUST算法符合巴西医疗保健标准.
- 评估适应的TRUST算法的可理解性和相关性,用于护理实践.
主要方法:
- 采用了六个阶段的跨文化适应过程,包括翻译,逆向翻译和专家委员会验证.
- 内容有效性使用内容有效性指数 (CVI) 进行评估,可靠性使用Cronbach的Alpha.
- 一项涉及31名护士的预测测试评估了算法在巴西环境中的清晰度和相关性.
主要成果:
- 经过调整的TRUST算法显示了高内容有效性 (CVI>0.90) 和良好的可靠性 (Cronbach的Alpha=0.80).
- 在预测中,护士们发现该算法清晰,相关且易于理解.
- 技术和文化调整成功地被整合到算法中.
结论:
- TRUST算法的跨文化适应是有效的,并且与原始版本相当.
- 调整的算法适用于巴西的急诊护士用于心脏风险评估.
- 这种经过验证的工具可以提高巴西急诊室心脏风险评估的准确性和效率.
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