Killen J D, Fortmann S P, Kraemer H C, Varady A N, Davis L, Newman B
Center for Research in Disease Prevention, Stanford University School of Medicine, California 94304, USA.
J Consult Clin Psychol. 1996 Oct;64(5):1060-7. doi: 10.1037//0022-006x.64.5.1060.
Signal detection methods were used to develop an algorithm useful in distinguishing those at risk for late relapse from those likely to maintain abstinence. Four subgroups with 24-month survival (nonrelapse) rates ranging from 79% to 33% were identified. Among participants whose depression symptoms decreased from baseline to the end of treatment, lower levels of nicotine dependence were associated with less relapse at the 24-month follow-up (odds ratio = 2.77; 95% confidence interval: 1.36-5.62). Among participants whose depression symptoms increased from baseline to the end of treatment, greater weight gain was associated with less relapse at follow-up (odds ratio = 2.90; 95% confidence interval: 1.41-5.96). This study suggested that it may become possible to use both baseline and treatment information to "titrate" interventions.
信号检测方法被用于开发一种算法，该算法有助于区分有晚期复发风险的人群与可能保持戒断状态的人群。识别出了四个亚组，其24个月生存率（无复发）从79%到33%不等。在抑郁症状从基线水平下降至治疗结束的参与者中，较低水平的尼古丁依赖与24个月随访时较低的复发率相关（优势比 = 2.77；95%置信区间：1.36 - 5.62）。在抑郁症状从基线水平上升至治疗结束的参与者中，更大的体重增加与随访时较低的复发率相关（优势比 = 2.90；95%置信区间：1.41 - 5.96）。这项研究表明，利用基线信息和治疗信息来“调整”干预措施或许将成为可能。
