数字化医疗保健中的用户个人资料:活跃,潜在和拒绝 - - 一项采用隐性类分析的横截面研究
Anja Knöchelmann1, Karl Healy2, Thomas Frese3
1Institute of Medical Sociology, Interdisciplinary Center for Health Sciences, Medical Faculty of the Martin Luther University Halle-Wittenberg, Magdeburger Str. 8, Halle (Saale), 06112, Germany. anja.knoechelmann@medizin.uni-halle.de.
BMC health services research
|September 17, 2024
概括
数字化医疗保健的使用在不同类型的用户之间有很大的差异,具有不同的社会人口统计学概况. 了解这些差异对于公平获得数字健康创新至关重要.
科学领域:
- 数字健康数字健康
- 医疗保健服务研究 医疗保健服务研究
- 卫生社会学 卫生社会学
背景情况:
- 一般卫生应用程序在人口统计学中显示了多样化的使用情况,但对于数字化医疗保健来说,这一点还未得到充分研究.
- 在数字化医疗保健中理解用户模式和描述用户类型目前尚不清楚.
研究的目的:
- 识别和描述数字化医疗保健服务的用户类型.
- 调查影响这些用户类型的社会人口和态度因素.
主要方法:
- 隐性类别分析被用来根据数字化医疗保健服务使用情况来确定用户类型.
- 多项物流回归分析了每个用户类型的社会经济,人口统计和态度因素.
主要成果:
- 确定了三个用户类型:拒绝 (27.9%),潜在的 (53.8%) 和活跃的 (18.3%).
- 活跃用户就业率较低,受教育程度较低,怀疑程度较低;潜在用户年轻,受过高等教育,就业程度较低,怀疑程度较低;被拒绝者年龄较大,女性多,社会经济地位较高.
结论:
- 在数字化医疗保健用户类型中存在显著的社会人口和社会经济差异.
- 不是所有人口群体都能从医疗数字化中获得同等的好处.
- 需要采取干预措施,以改善所有人获得数字健康创新的机会.
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