Jacquart Jolene, Papini Santiago, Davis Michelle L, Rosenfield David, Powers Mark B, Frierson Georita M, Hopkins Lindsey B, Baird Scarlett O, Marcus Bess H, Church Timothy S, Otto Michael W, Zvolensky Michael J, Smits Jasper A J
Department of Psychology and Institute for Mental Health Research, The University of Texas at Austin, SEA 4.208, 108 E. Dean Keeton Stop A8000, Austin, TX, 78712-1043, USA.
Department of Psychology and Institute for Mental Health Research, The University of Texas at Austin, SEA 4.208, 108 E. Dean Keeton Stop A8000, Austin, TX, 78712-1043, USA.
Drug Alcohol Depend. 2017 May 1;174:65-69. doi: 10.1016/j.drugalcdep.2017.01.007. Epub 2017 Mar 6.
While important for substance use outcomes, knowledge about treatment attendance patterns, and their relation with clinical outcomes is limited. We examined the association between attendance patterns and smoking outcomes in a randomized, controlled smoking cessation intervention trial.
In addition to standard smoking cessation treatment, participants were randomized to 15 weeks of an exercise intervention (n=72) or an education control condition (n=64). Latent class growth analysis (LCGA) tested whether intervention attendance would be better modeled as qualitatively distinct attendance patterns rather than as a single mean pattern. Multivariate generalized linear mixed modeling (GLMM) was used to evaluate associations between the attendance patterns and abstinence at the end of treatment and at 6-month follow-up.
The LCGA solution with three patterns characterized by high probability of attendance throughout (Completers, 46.3%), gradual decreasing probability of attendance (Titrators, 23.5%), and high probability of dropout within the first few weeks (Droppers, 30.1%) provided the best fit. The GLMM analysis indicated an interaction of attendance pattern by treatment condition, such that titration was associated with lower probability of quit success for those in the control condition. Probability of quit success was not significantly different between Titrators and Completers in the exercise condition.
These findings underscore the importance of examining how treatment efficacy may vary as a function of attendance patterns. Importantly, treatment discontinuation is not necessarily indicative of poorer abstinence outcome.
虽然了解治疗出勤模式及其与临床结果的关系对物质使用结果很重要，但相关知识有限。我们在一项随机对照戒烟干预试验中研究了出勤模式与吸烟结果之间的关联。
除了标准的戒烟治疗外，参与者被随机分为接受15周运动干预组（n = 72）或教育对照组（n = 64）。潜在类别增长分析（LCGA）测试干预出勤是否能更好地被建模为质上不同的出勤模式，而不是单一的平均模式。多变量广义线性混合模型（GLMM）用于评估出勤模式与治疗结束时和6个月随访时戒烟之间的关联。
具有三种模式的LCGA解决方案提供了最佳拟合，这三种模式的特点分别是全程高出勤概率（完成者，46.3%）、出勤概率逐渐降低（滴定者，23.5%）和在最初几周内高辍学概率（辍学者，30.1%）。GLMM分析表明出勤模式与治疗条件之间存在交互作用，即对于对照组中的人来说，滴定与戒烟成功概率较低相关。在运动条件下，滴定者和完成者之间的戒烟成功概率没有显著差异。
这些发现强调了研究治疗效果如何因出勤模式而异的重要性。重要的是，治疗中断不一定表明戒烟结果较差。
