通过SIMBA:一种混合方法研究,为世界各地的医疗保健专业人员提供学习基础
Kashish Malhotra1,2, Anisah Ali3, Vina Soran3
1Department of Medicine, Dayanand Medical College and Hospital, Ludhiana, India.
通过即时通讯-伯明翰提前 (SIMBA) 模拟为全球医疗保健专业人员提供同等的专业发展. 这种虚拟培训模型展示了可扩展,标准化的全球健康教育的潜力,特别有利于低收入/中等收入国家.
科学领域:
- 医学教育 医学教育
- 全球健康 全球健康
- 数字健康数字健康
背景情况:
- 医疗保健专业人员的发展对于高质量的患者护理至关重要.
- 传统的培训方法可能在可访问性和可扩展性方面存在局限性,特别是在资源有限的环境中.
- 数字健康干预提供了持续学习的创新解决方案.
研究的目的:
- 通过即时通讯-伯明翰先进 (SIMBA) 模拟在低收入/中等收入国家 (LMIC) 和高收入国家 (HIC) 的接受度,优势和局限性进行比较.
- 评估SIMBA对医疗保健专业人员职业发展和学习成果的影响.
- 评估SIMBA模型的全球可扩展性潜力.
主要方法:
- 一项涉及462名医疗保健专业人员的横截面研究 (29.7%来自LMIC,71.3%来自HIC).
- 通过WhatsApp进行了16次在线SIMBA会议,以解决匿名的临床场景.
- 使用了柯克帕特里克的培训评估模型,比较了会议前后的调查数据,并进行了内容分析.
主要成果:
- 在LMIC和HIC参与者之间,在应用到实践,参与或总体会议质量方面没有发现显著差异.
- HIC参与者在患者管理方面表现出更高的知识 (86.5%对77.4%),而LMIC参与者在专业性方面表现出更大的改善 (41.6%对31.1%).
- 两组之间在不同领域的临床能力得分改善方面没有发现显著差异.
结论:
- 辛巴为LMIC和HIC的医疗保健专业人员提供同等的教学经验和自我报告的临床能力改进.
- SIMBA的虚拟性质确保了全球健康教育的国际可访问性和可扩展性.
- SIMBA模型有可能指导未来的标准化全球健康教育政策制定,特别是在LMICs.
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