AI 中文总结
针对数字健康干预中习惯行为干预时间难确定的问题，提出在线决策框架，能随个体行为模式变化调整干预时间，以口腔健康干预试验为例评估，发现自适应干预时间可提高覆盖率，该框架已用于相关随机对照试验。
AI 中文摘要
旨在改善习惯行为的数字健康干预面临的核心挑战是决定何时提供干预提示。对于刷牙或进食等日常习惯，人们往往在一天中的特定时间行动，但时间并不固定且会随日常活动演变。预先选定并在研究中保持不变的干预时间可能会与行为逐渐脱节。本文提出在线决策框架，随个体行为模式变化持续调整干预时间，将其融入决定何时及是否进行干预的顺序过程。以口腔健康干预试验数据为案例研究，用观察数据和模拟设置评估不同干预时间策略与刷牙事件时间的契合度，采用基于覆盖率的指标衡量性能。结果表明，自适应干预时间比基于用户输入的固定干预时间能持续提高覆盖率，该框架已应用于正在进行的数字口腔健康干预随机对照试验，初步结果支持先前评估。
英文摘要
A central challenge for digital health interventions aimed at improving habitual behaviors is deciding when to deliver an intervention prompt. For many daily habits, such as tooth brushing or eating, individuals tend to act around a usual time of day, but this timing is not fixed and can shift as routines evolve. When intervention timing is selected in advance and held constant throughout a study, it can gradually become misaligned with behavior, causing interventions to potentially arrive after the behavior has already occurred or too early to be effective. In this work, we address this habitual timing misalignment in digital health interventions by proposing an online decision-making framework that continuously adapts intervention timing as individual behavior patterns change. Rather than treating intervention timing as a static design choice, our framework adapts it over time and integrates it into a sequential process that determines both when and whether to deliver an intervention. Using data from a deployed oral health intervention trial as a case study, we evaluate our approach using both observed data and simulated settings to assess how well different intervention timing strategies align with the timing of brushing events. Across these evaluations, we measure performance using a coverage-based metric that captures whether an intervention is delivered sufficiently close to a subsequent brushing event. We find that adaptive intervention timing consistently improves coverage compared to fixed intervention times based on user-provided input. The proposed framework is currently deployed in an ongoing randomized controlled trial of a digital oral health intervention, with preliminary results that are consistent with and further support our prior evaluations.
Comments28 pages, 2 figures
