Department of Mathematics and Statistics, University of Missouri-Kansas City, 5100 Rockhill Road, Kansas City, MO, 64110-2499, USA.
School of Medicine, Creighton University, 2500 California Plaza, Omaha, NE, 68178, USA.
BMC Med Res Methodol. 2018 Jun 13;18(1):52. doi: 10.1186/s12874-018-0511-0.
Motivational Interviewing (MI), Brief Advice (BA) and Health Education (HE) are established smoking cessation induction methods for smokers with low desire to quit. Although randomized controlled trials (RCT's) have been frequently used to assess these interventions the temporal efficacy and effectiveness of these interventions have been poorly elaborated. The present work endeavors to fill the gap by considering the full range of possible motivational outcomes for all of the participants.
As a two-step process, Markov Chain (MC) and Ordinary Differential Equation (ODE) models were successively employed to examine the temporal efficacy and effectiveness of these interventions by computing the gradual movements of participants from an initial stage of unmotivated smoker to stages of increased motivation to quit and cessation. Specifically, in our re-analysis of data from the RCT we examined the proportion of participants in 4 stages of readiness to quit (unmotivated, undecided, motivated, former smokers) over 6 months, across treatment groups [MI (n = 87), BA (n = 43) and HE (n = 91)].
Although HE had greater efficacy compared to MI and BA (i.e., the highest smoking cessation rates), it had lower effectiveness at certain time points. This was due to the fact that HE had the greatest proportion of motivated smokers who quit smoking but simultaneously a large proportion of the motivated smokers became unmotivated to quit. The effectiveness of HE dropped substantially in weeks 3-12 and remained below the effectiveness of BA from week 12 onward. The 2-year ODE model projections show that the prevalence of motivated smokers in HE group may fall below 5%. The prevalence of HE former smokers can reach an equilibrium of 26%, where the prevalence of both BA and MI former smokers exceeds this equilibrium.
The methodology proposed in this paper strongly benefits from the capabilities of both MC and ODE modeling approaches, in the event of low observations over the time. Particularly, the temporal population sizes are first estimated by the MC model. Then they are used to parametrize the ODE model and predict future values. The methodology enabes us to determine and compare the temporal efficacy and effectiveness of smoking cessation interventions, yielding predictive and analytic insights related to temporal characteristics and capabilities of these interventions during the study period and beyond.
Testing Counseling Styles to Motivate Smokers to Quit, NCT01188018 , (July 4, 2012). This study is registered at www.clinicaltrials.gov NCT01188018.
动机访谈(MI)、简短建议(BA)和健康教育(HE)是针对低戒烟意愿吸烟者的既定戒烟诱导方法。尽管随机对照试验(RCT)经常被用于评估这些干预措施,但这些干预措施的时间疗效和效果仍未得到充分阐述。本研究通过考虑所有参与者可能的动机结果的全部范围来弥补这一空白。
作为两步法,我们先后使用马尔可夫链(MC)和常微分方程(ODE)模型,通过计算参与者从初始无动机吸烟者阶段逐渐向增加戒烟动机和戒烟阶段的过程,来检查这些干预措施的时间疗效和效果。具体来说,在对 RCT 数据的重新分析中,我们在 6 个月内检查了治疗组中处于戒烟准备的 4 个阶段(无动机、未决定、有动机、前吸烟者)的参与者比例[MI(n=87)、BA(n=43)和 HE(n=91)]。
尽管 HE 与 MI 和 BA 相比具有更高的疗效(即,更高的戒烟率),但在某些时间点的效果较低。这是因为 HE 有最大比例的有动机吸烟者戒烟,但同时也有很大比例的有动机吸烟者变得没有戒烟动机。HE 的效果在第 3-12 周大幅下降,并在第 12 周后一直低于 BA 的效果。2 年 ODE 模型预测显示,HE 组中活跃吸烟者的比例可能会降至 5%以下。HE 前吸烟者的比例可以达到 26%的平衡,而 BA 和 MI 前吸烟者的比例都超过了这个平衡。
本文提出的方法从 MC 和 ODE 建模方法的能力中受益良多,特别是在时间上观测值较低的情况下。特别是,MC 模型首先估计时间上的人口规模。然后,它们被用来参数化 ODE 模型并预测未来的值。该方法使我们能够确定和比较戒烟干预措施的时间疗效和效果,从而提供与研究期间和之后这些干预措施的时间特征和能力相关的预测和分析见解。
测试咨询风格以激励吸烟者戒烟,NCT01188018,(2012 年 7 月 4 日)。本研究在 www.clinicaltrials.gov 注册,NCT01188018。