Background It is well known that web-based interventions can be effective treatments for various conditions. Less is known about predictors, moderators, and mediators of outcome and especially interrelations between participant and interventions characteristics, process variables and outcomes in online interventions. Clinical trials often lack statistical power to detect variables that affect intervention effects and their interrelations. Within ICare, we can investigate the interrelation of potential predictor and process variables in a large sample. Method The ICare consortium postulated a model of interrelations between participant and intervention characteristics, process variables and outcomes in online interventions. We will assess general and disorder-specific interrelations between characteristics of the intervention, characteristics of the participants, adherence, working alliance, early response, and intervention outcomes in a sample of over 7500 participants from seven clinical trials evaluating 15 online interventions addressing a range of mental health conditions and disorders, using an individual participant data meta-analyses approach. Discussion/conclusion Existing research tends to support the efficacy of online mental health interventions, but the knowledge base regarding factors that affect intervention effects needs to be expanded. The overarching analyses using data from the ICare intervention trials will add considerably to the evidence.

中文翻译：

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在线干预中参与者和干预特征、过程变量和结果之间的相互关系：ICare 七项临床试验内部和之间的总体分析协议。

背景众所周知，基于网络的干预措施可以有效治疗各种病症。对于结果的预测因素、调节因素和中介因素，尤其是在线干预中参与者和干预特征、过程变量和结果之间的相互关系，人们知之甚少。临床试验通常缺乏统计能力来检测影响干预效果及其相互关系的变量。在 ICare 中，我们可以研究大样本中潜在预测变量和过程变量的相互关系。方法 ICare 联盟假设了一个在线干预中参与者和干预特征、过程变量和结果之间相互关系的模型。我们将评估干预措施特征、参与者特征、依从性、工作联盟、早期反应和干预结果之间的一般和特定疾病之间的相互关系，该样本来自七项临床试验，评估了 15 项在线干预措施，该样本由 7500 多名参与者组成。心理健康状况和疾病，使用个体参与者数据荟萃分析方法。讨论/结论现有研究倾向于支持在线心理健康干预措施的有效性，但有关影响干预效果的因素的知识库需要扩大。使用 ICare 干预试验数据进行的总体分析将大大增加证据。