Tobacco Approach Avoidance Training for Smoking Cessation in Adolescent Smokers-Study 1
试验速览
- 阶段
- 2 期
- 状态
- 已完成
- 入组人数
- 40
- 试验地点
- 2
- 主要终点
- automatic approach tendencies towards smoking-related stimuli
研究概览
简要总结
This is a two part study. Study 1 will compare Approach Avoidance Training (AAT) responses in smokers and nonsmokers in order to confirm that adolescent smokers experience cognitive bias towards tobacco-related stimuli.
研究设计
- 研究类型
- Interventional
- 分配方式
- Na
- 干预模型
- Single Group
- 主要目的
- Treatment
- 盲法
- Single (Care Provider)
入排标准
- 年龄范围
- 13 Years 至 18 Years（Child, Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Between ages 13-18 years
- •Able to read and write in English.
- •Smokers: Smoking 5 or more cigarettes daily for at least 6 months; Baseline urine cotinine levels > 500 ng/ml
- •Nonsmokers: Never smokers; Baseline urine cotinine levels < 50 ng/ml
排除标准
- •Current criteria for dependence on another psychoactive substance
- •Current diagnosis of psychosis, major depression or panic disorder
- •Regular use of any psychoactive drugs including anxiolytics and antidepressants unless the medication has been taken consistently for 2 months, is currently being monitored by a physician, and the condition for which the medication is taken is considered to be stable
- •Pregnant or lactating girls, based on self report.
结局指标
主要结局
automatic approach tendencies towards smoking-related stimuli
时间窗: at end of AAT at Day 29
For all AAT comparisons, the investigators will compare median scores (to minimize influence of outliers) for cigarette approach and cigarette avoid RTs. The difference between these values gives the smoking AAT-scores, which the investigators expect to not differ from zero in the non-smokers (or to show mild avoidance), while it is expected that smokers will be faster to approach than to avoid cigarettes. ANOVA models will be used to compare scores in smokers vs. nonsmokers. Regression analyses will be used to explore the relationships between impulsivity-related measures and AAT responses.
次要结局
未报告次要终点
研究者
Suchitra Krishnan-Sarin
Associate Professor
Yale University