大学学生对使用基于症状的算法来增强自动售货机 (OTC) 药物使用的看法
Lucas Nicolau1, Jeffrey Bratberg1, Katherine Houlihan1
1URI College of Pharmacy, Kingston, Rhode Island.
Rhode Island medical journal (2013)
|January 27, 2026
概括
大学生更喜欢使用在线症状检查器而不是健康自动售货机来做出非处方 (OTC) 药物决定. 基于症状的算法可以改善他们与OTC产品选择的经验.
科学领域:
- 数字健康数字健康
- 消费者健康信息学
- 药房实践 在药房实践.
背景情况:
- 症状检查器有助于临床决策,包括非处方药 (OTC) 产品选择.
- 提供OTC药物的健康和健康自动售货机 (HWVM) 在大学校园中很普遍.
- 目前的系统缺乏自我评估工具和HWVM之间的集成,用于OTC选择.
研究的目的:
- 评估大学生对症状检查算法的偏好.
- 为了比较基于kiosk的与与HWVM相关的症状检查器的在线访问.
主要方法:
- 在2025年春天,对303名独特的大学生进行了一项调查.
- 收集的数据包括人口统计,HWVM使用情况以及症状算法的感知好处.
- 通过使用QualtricsTM收集了回复.
主要成果:
- 只有17%的学生报告使用HWVM.
- 64%的学生更喜欢在新的健康问题上咨询一个人,而30%更喜欢在线资源.
- 75%的人认为症状算法可以增强HWVM体验,78%的人更喜欢移动访问而不是收纳台 (57%).
结论:
- 尽管HWVM使用率很低,并且更喜欢人类咨询,但学生对OTC选择的症状算法很容易接受.
- 需要进一步的研究来验证算法,分析库存趋势和评估用户满意度.
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