Evaluation and Improvement of the Implementation of the Intention to Treat Model in Controlled Trials of Psychotherapies

随机对照试验（RCT）是确定患者是否从新治疗中获益的最佳方法。在这些试验中，患者被随机分配到新的活性治疗，或安慰剂或现有治疗。在试验结束时比较各组。随机对照试验可以用于心理治疗和教育项目，也可以用于新药和其他医疗程序。随机对照试验的一个主要问题是当一些参与者在试验结束前退出时的统计分析。脱落在试验中很常见。参与者可能会退出，因为他们觉得没有从治疗中获益，不喜欢副作用，甚至因为他们恢复得很快。因此，比较试验结束时剩余的组可能会引入严重偏倚。广泛采用的意向治疗（ITT）原则规定，应在试验结束时对所有进入试验的患者的结局进行比较。为了实现这一点，退出研究的受试者的最后一次可用观察结果通常“结转”至试验结束。虽然目前被认为是保守的，但有证据表明，这种方法并不总是最佳的。这个项目将研究在两种常见的精神疾病：抑郁症和焦虑症的试验中辍学的治疗方法。该项目还将进行模拟研究，以调查当参与者退出时，一些现代数据分析方法中的哪一种产生最准确的结果，以及试验设计的变化如何提高准确性。该项目很重要，因为它将使研究人员能够在未来改进试验的进行。从随机对照试验中得出的错误结论会使那些患有疾病的人接受无效的治疗，并导致过早放弃那些被错误地声称缺乏疗效的潜在有用的干预措施。

Randomized controlled trials (RCTs) are the best way to determine whether patients benefit from a new treatment. In these trials patients are randomly assigned to the new, active treatment, or to a placebo or existing treatment. The groups are compared at the end of the trial. RCTs may be mounted for psychotherapy and educational programs as well as for new drugs and other medical procedures. A major problem for RCTs concerns their statistical analysis when some participants drop out before the end of the trial. Dropout is common in trials. Participants may drop out because they feel no benefit from the treatment, dislike side effects, or even because they have recovered quickly. Thus, to compare the groups remaining at the end of trial may introduce serious bias. The Intention to Treat (ITT) principle which has been widely adopted states that outcomes from all patients who enter a trial should be compared at its end. To achieve this, the last available observation for a participant who withdraws is often 'carried forward' to the end of the trial. While currently believed to be conservative, there is evidence that this approach is not always optimal. This project will examine the way in which dropout is treated in trials of two common psychiatric conditions: depression and anxiety disorders. The project will also undertake simulation research to investigate which of a number of modern methods of data analysis yield the most accurate results when participants drop out, and how changes in the design of trials might improve accuracy. The project is important because it will enable researchers to improve the conduct of trials in the future. Erroneous conclusions drawn from RCTs stand to condemn those suffering from disorders to ineffective treatment and to lead to the premature abandonment of potentially useful interventions which are falsely claimed to lack efficacy.