评估基于网络的干预措施的使用:荷兰性健康干预措施的一个例子
Gido Metz1, Hanneke Roosjen2, Wessel Zweers2
1Department of Health Promotion, Maastricht University/CAPHRI, The Netherlands.
Health promotion international
|August 19, 2023
概括
本研究引入了非循环行为变化图 (ABCDs),以可视化基于网络的干预措施的预期使用. 将ABCD与网络分析 (Matomo) 结合起来,可以揭示实际的用户参与,并为干预改进提供信息.
科学领域:
- 数字健康数字健康
- 行为科学 行为科学
- 公共卫生干预 公共卫生干预
背景情况:
- 基于网络的干预措施正在增加,突出显示需要有效的参与度测量.
- 当前的网络分析监控使用情况,但缺乏开发人员预期的行为改变途径的背景.
- 描述不良的干预措施会导致评估不那么有意义.
研究的目的:
- 通过比较预期与实际使用,提出和展示一种评估基于网络的干预参与的方法.
- 突出非循环行为变化图 (ABCD) 的价值,以可视化干预设计和行为变化原则.
主要方法:
- 开发和应用非循环行为变化图 (ABCDs) 以可视化克拉米迪亚预防网页的预期使用.
- 使用Matomo网络分析来跟踪实际使用和用户参与干预.
- 将预期使用路径与实际用户行为数据进行比较.
主要成果:
- 克拉米迪亚预防页面在2020年有104,557次浏览.
- 在35,347次转移中,只有14%的转移从页面到STI测试页面.
- 观察到高反弹率 (79%) 和退出率 (69%),表明对预期结果的参与度较低.
结论:
- 将ABCD用于可视化预期使用与Matomo用于实际使用分析相结合,可以更深入地了解基于Web的干预参与.
- 这种综合方法有助于识别设计与用户行为之间的差异,从而实现有针对性的改进.
- 该方法为评估和增强数字健康干预提供了有价值的框架.
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