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

随机对照试验（rct）是确定患者是否受益于新疗法的最佳方法。在这些试验中，患者被随机分配到新的、积极的治疗，或安慰剂或现有的治疗。在试验结束时对两组进行比较。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，他们的统计分析存在问题。中途退出在试验中很常见。参与者可能会退出，因为他们感觉没有从治疗中受益，不喜欢副作用，甚至因为他们恢复得很快。因此，在试验结束时比较剩余的组可能会引入严重的偏倚。意向治疗原则（ITT）已被广泛采用，该原则规定，所有进入试验的患者的结果应在试验结束时进行比较。为了实现这一点，对于退出试验的参与者，最后一次可用的观察结果通常被“结转”到试验结束。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。该项目将研究在两种常见精神疾病：抑郁症和焦虑症的试验中，辍学者的治疗方式。该项目还将进行模拟研究，以调查在参与者退出时，哪些现代数据分析方法能产生最准确的结果，以及试验设计的变化如何提高准确性。这个项目很重要，因为它将使研究人员能够在未来改进试验的实施。从随机对照试验中得出的错误结论将使那些患有疾病的人受到无效治疗的谴责，并导致过早放弃可能有用的干预措施，这些干预措施被错误地声称缺乏疗效。

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.