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基于互联网的抑郁症干预项目的依从性预测因素。

Adherence predictors in an Internet-based Intervention program for depression.

机构信息

a IUNICS-IDISBA , University of Balearic Islands , Palma de Mallorca , Spain.

b Primary Care Prevention and Health Promotion Research Network , RedIAPP , Madrid , Spain.

出版信息

Cogn Behav Ther. 2018 May;47(3):246-261. doi: 10.1080/16506073.2017.1366546. Epub 2017 Sep 5.

Abstract

Internet-delivered psychotherapy has been demonstrated to be effective in the treatment of depression. Nevertheless, the study of the adherence in this type of the treatment reported divergent results. The main objective of this study is to analyze predictors of adherence in a primary care Internet-based intervention for depression in Spain. A multi-center, three arm, parallel, randomized controlled trial was conducted with 194 depressive patients, who were allocated in self-guided or supported-guided intervention. Sociodemographic and clinical characteristics were gathered using a case report form. The Mini international neuropsychiatric interview diagnoses major depression. Beck Depression Inventory was used to assess depression severity. The visual analogic scale assesses the respondent's self-rated health and Short Form Health Survey was used to measure the health-related quality of life. Age results a predictor variable for both intervention groups (with and without therapist support). Perceived health is a negative predictor of adherence for the self-guided intervention when change in depression severity was included in the model. Change in depression severity results a predictor of adherence in the support-guided intervention. Our findings demonstrate that in our sample, there are differences in sociodemographic and clinical variables between active and dropout participants and we provide adherence predictors in each intervention condition of this Internet-based program for depression (self-guided and support-guided). It is important to point that further research in this area is essential to improve tailored interventions and to know specific patients groups can benefit from these interventions.

摘要

互联网心理治疗已被证明在治疗抑郁症方面是有效的。然而,这种治疗方式的依从性研究结果却存在差异。本研究的主要目的是分析西班牙基于互联网的初级保健抑郁症干预措施中依从性的预测因素。这是一项多中心、三臂、平行、随机对照试验,共纳入 194 例抑郁患者,将他们随机分配到自我指导或支持指导干预组。使用病例报告表收集社会人口统计学和临床特征。采用迷你国际神经精神访谈诊断重性抑郁障碍。贝克抑郁量表用于评估抑郁严重程度。视觉模拟量表评估受访者的自我报告健康状况,健康简表用于测量与健康相关的生活质量。年龄是两个干预组(有和没有治疗师支持)的预测变量。当模型中包含抑郁严重程度的变化时,感知健康是自我指导干预的依从性的负预测因子。支持指导干预中,抑郁严重程度的变化是依从性的预测因子。我们的研究结果表明,在我们的样本中,活跃参与者和脱落参与者在社会人口统计学和临床变量方面存在差异,我们为每个基于互联网的抑郁症方案(自我指导和支持指导)的干预条件提供了依从性预测因素。需要指出的是,这一领域的进一步研究对于改进个体化干预措施以及了解哪些特定患者群体可以从这些干预措施中受益至关重要。

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