检测即将发生的吸烟失效风险:前失效风险算法与参与者的回顾性自我报告
Jeremy S Langford1, Emily T Hébert2, Darla E Kendzor2
1TSET Health Promotion Research Center, Stephenson Cancer Center, University of Oklahoma Health Sciences, Oklahoma City, OK, USA.
Drug and alcohol dependence
|September 17, 2025
概括
使用智能手机数据的算法可以比个人意识到的更早地检测出吸烟失效风险. 这一发现有助于开发实时干预措施,以改善弱势成年人的戒烟成功.
科学领域:
- 行为科学 行为科学
- 数字健康数字健康
- 公共卫生 公共卫生
背景情况:
- 在社会经济上处于劣势的成年人中,戒烟率较低.
- 早期发现吸烟失效风险对于干预至关重要.
- 基于智能手机的干预为这一群体提供了一个有希望的途径.
研究的目的:
- 为了比较两种基于智能手机的戒烟干预措施的疗效.
- 评估算法检测吸烟失效风险的能力.
- 将算法检测到的风险与参与者对风险的自我意识进行比较.
主要方法:
- 利用来自随机对照试验的数据.
- 雇佣每日生态瞬间评估 (EMA) 来追踪失效风险.
- 参与者在识别失效冲动或失效后自主发起EMA.
- 分析了参与者报告的风险意识和失败后应对策略.
主要成果:
- 一个算法在68.93%的失误中检测到高的吸烟失误风险.
- 在70.06%的失败中,参与者自我报告了对增加风险的认识,但在两个小时前,只有30%的失败预计会发生.
- 该算法比参与者自我报告的意识 (AOR=3.34) 早识别了高风险.
结论:
- 根据EMA的信息算法显示,早期检测吸烟失效风险具有潜力.
- 这种早期检测可以在参与者识别之前进行,从而使及时干预成为可能.
- 这些发现支持为社会经济弱势的成年人开发实时戒烟工具.
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