Modeling Complexity of EMA Data: Time-Varying Lagged Effects of Negative Affect on Smoking Urges for Subgroups of Nicotine Addiction
Modeling Complexity of EMA Data: Time-Varying Lagged Effects of Negative Affect on Smoking Urges for Subgroups of Nicotine Addiction
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DOI：
10.1093/ntr/ntt109
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发表时间：
2014-05-01
影响因子：
4.7
通讯作者：
Li, Runze
中科院分区：
文献类型：
--
作者：
Shiyko, Mariya;Naab, Pamela;Li, Runze
生态瞬时评估（EMA）越来越多地用于吸烟行为的研究。通过EMA，检查滞后关系对于建立事件的时间顺序和识别风险因素的类型和时间特别有用。时变效应模型（TVEM）处理EMA数据的挑战，并解决了独特的问题的时变effects.Generalized TVEM适用于EMA数据从戒烟研究调查随时间变化的滞后效应的负面影响高吸烟欲望。参与者包括224名吸烟者，吸烟史为23.1年（SD 9.8）每天吸烟27.3支（SD 10.7），在尝试戒烟后和戒烟前提供了11，394个EMA。发现负面情绪的影响随时间滞后而变化，具有更强的直接影响：较低尼古丁依赖组（早晨第一支烟的时间> 5分钟，57.6%）的估计比值比（OR）为2.7，较高尼古丁依赖组（5分钟）的OR为2.4。这种影响的程度持续到7小时，但随着时间的推移而下降。这项分析证实了负面影响作为吸烟冲动的前兆的重要性，同时表明这种影响的程度随着时间的推移而变化。一个恒定的滞后效应的假设可能会偏见的关系的估计，并不能提供一个全面的前景的关系动态。
Ecological momentary assessments (EMA) are increasingly used in studies of smoking behavior. Through EMA, examination of lagged relationships is particularly useful for establishing a temporal order of events and for identifying types and timing of risk factors. The time-varying effect model (TVEM) handles EMA data challenges and addresses unique questions about the time-varying effects.Generalized TVEM was applied to EMA data from a smoking cessation study to investigate a time-varying lagged effect of negative affect on high smoking urges. Participants included 224 smokers with a smoking history of 23.1 years (SD 9.8) smoking 27.3 cigarettes per day (SD 10.7), which provided 11,394 EMAs following a quit attempt and prior to a smoking lapse.The effect of negative affect was found to vary as a function of a time lag, with stronger immediate effects: estimated odds ratio (OR) of 2.7 for the lower nicotine-dependence group (time to first morning cigarette > 5min, 57.6%) and OR of 2.4 for the higher nicotine-dependence group ( 5min). The magnitude of the effect persisted up to 7hr while decreasing over time.This analysis confirmed the importance of negative affect as a precursor of smoking urges while showing that the magnitude of the effect varies over time. An assumption of a constant lagged effect may bias estimates of the relationships and fail to provide a comprehensive outlook of the relational dynamics.