Daily Process Design Applied to Cognitive Therapy

描述(申请人提供)：该项目是首次应用压力和应对的日常过程测量，以及具体的情绪调节指数，来研究抑郁症的认知治疗(CT)。日常压力和应对措施将通过交互式语音应答(IVR)程序进行管理，具体指数将使用分层线性建模(HLM)计算。具体地说，影响调节的具体指数将在CT开始时(时间1)计算，并在六次治疗后再次计算(时间2)。我们将评估时间1指数作为预测CT结果(抑郁减轻)的有效性，以及时间2指数作为CT效果的度量的有效性。研究假设，具有较好日常负性情绪调节初始能力的抑郁个体在CT检查中的症状减轻程度高于初始负性情绪调节能力较差的个体。预测在CT治疗过程中，患者调节日常负性情绪的能力将得到提高。如果成功，我们的项目将展示基于IVR的日常过程方法和基于HLM的日常情感调节的具体指数对于心理治疗结果研究的价值。

DESCRIPTION (provided by applicant): The proposed project represents the first application of daily process measures of stress and coping, and idiographic indices of affect regulation, to research on cognitive therapy (CT) for depression. The daily stress and coping measures will be administered by an interactive voice response (IVR) procedure, and the idiographic indices will be computed using hierarchical linear modeling (HLM). Specifically, idiographic indices of affect regulation will be computed at the beginning of CT (Time 1), and again six sessions later (Time 2). We will evaluate the utility of the Time 1 indices as predictors of CT outcome (depression-reduction), and the utility of the Time 2 indices as measures of the effects of CT. It is hypothesized that depressed individuals with better initial ability to regulate daily negative affect will show more symptom reduction in CT than individuals with worse initial ability to regulate daily negative affect. It is also predicted that patients' ability to regulate daily negative affect will-improve during the course of CT. If successful, our project will demonstrate the value of an IVR-based daily process methodology, and HLM-based idiographic indices of daily affect regulation, for research on psychotherapy outcome.