在马拉维的普通卫生保健工作者中混合学习的预期接受度:以技术接受模型为指导的定性分析
Tiwonge E Mbeya-Munkhondya1, Caroline J Meek2, Mtisunge Mphande3
1School of Nursing, Kamuzu University of Health Sciences, Lilongwe, Malawi.
JMIR formative research
|April 7, 2025
概括
混合学习可以提高马拉维卫生工作者的艾滋病毒检测能力. 接受的关键因素包括数字工具的感知实用性和易用性,需要设备访问和清晰的沟通.
科学领域:
- 公共卫生 公共卫生
- 健康 职业 教育 教育 专业
- 数字健康数字健康
背景情况:
- 艾滋病毒指数病例测试 (ICT) 对于识别艾滋病毒感染者及其接触者至关重要.
- 马拉维ICT实施的挑战源于医疗保健工作者 (HCW) 咨询能力有限.
- 传统的面对面培训在后勤上复杂且昂贵,需要采用替代方法.
研究的目的:
- 探索影响卫生保健工作者 (HCWs) 预期接受混合学习方法的因素,以提高艾滋病毒指数病例测试 (ICT) 能力.
- 应用技术接受模型 (TAM) 来理解HCW对混合学习的看法.
主要方法:
- 进行了一项定性形成性研究,对马拉维的HCW进行了26次深入采访.
- 参与者参与了Machinga和Balaka地区14个设施的ICT计划.
- 使用TAM进行的主题分析指导了影响感知有用性和易用性的因素的分组.
主要成果:
- 感知到的有用性受到自我引导数字学习的强化吸引力和对技能应用的面对面实践的需求的影响.
- 感知到的易用性受到了数字技术导向,设备可访问性,时间表的清晰沟通,后勤支持和激励金钱补偿的需求的影响.
结论:
- 一个分散的混合学习模式显示了在马拉维的非专业医疗保健工作者中增强ICT知识和技能的潜力.
- 解决数字素养,设备访问,通信和激励等外部因素对于成功实施至关重要.
- 未来的步骤包括将发现整合到混合学习包中,以便在集群随机对照试验中进行评估.
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