Mobile Applications for Depression: Comparing Cognitive and Behavioral Approaches

描述(由申请人提供)：抑郁症在成本、发病率、痛苦和死亡率方面造成了非常高的社会负担。它是美国致残的首要原因，也是全世界的第四大致残原因。目前的治疗方法不足以应对这种普遍的健康问题。因此，应对这一精神健康流行病需要在干预策略上做出重大改变。越来越多的研究正在研究使用行为干预技术(BITS)，例如手机来提供行为和心理健康干预。通过移动电话提供干预措施提供了在护理系统和患者之间提供近乎持续的连接的可能性。然而，目前可用的抑郁症移动应用程序(App)缺乏关于其有效性的证据。应用商店目前提供的抑郁症应用程序是基于认知疗法(CT)干预设计的，一些带有行为激活(BA)，一些只有情绪监测，还有许多没有可识别的心理方法。即使是基于心理学理论，也没有证据表明，这些理论的翻译是为面对面的治疗而开发的，当通过应用程序传递时，对抑郁症患者也是如此。考虑到移动应用程序的快速发展性质，对每一款可用的应用程序进行研究永远不可能，也不会非常有用。拟议的研究计划采用了一种创新的方法来研究BITS导致抑郁症的原因，融合了心理学、工程学和设计学的原理，以检查移动应用程序提供的两个主要心理学原理-CT和BA。该项目将包括两个阶段。首先，将确定现有应用程序中最有用的元素，以创建两个应用程序，一个使用CT，另一个使用BA，针对抑郁症状。该可用性流程将使用清晰、模型驱动的方法来确定三个应用程序元素的最有用和最有用的特征：信息交付、工具和视觉反馈。在可用性测试和改进之后，这两款应用程序将进行一次小型的对比试验。次要目标将包括对应用程序的使用情况进行检查，定义为应用程序在移动设备上打开的次数。结果将提供可被抑郁症应用程序开发商广泛使用的信息，也可能对旨在治疗其他精神健康障碍的应用程序产生影响。

DESCRIPTION (provided by applicant): Depression imposes a very high societal burden in terms of cost, morbidity, suffering, and mortality. It is the leading cause of disability in the Unted States and the fourth leading cause worldwide. Current methods of treatment are insufficient to combat such a widespread health problem. Therefore, addressing this mental health epidemic requires significant changes in intervention strategies. A growing body of research is examining the use of behavioral intervention technologies (BITs), such as mobile phones to deliver behavioral and mental health interventions. The delivery of interventions via mobile phones offers the potential to provide a near continuous connection between a care system and the patient. However, currently available mobile applications (apps) for depression lack evidence regarding their efficacy. App stores currently offer apps for depression that are designed based on cognitive therapy (CT) interventions, some with behavioral activation (BA), some with mood monitoring only, and many with no discernable psychological approach. Even when based on psychological theory, there is no evidence that the translation of these theories, developed for face- to-face treatment, work the same way for people with depression when delivered through an app. Given the quickly evolving nature of mobile apps, conducting research on every available app will never be possible, nor very useful. The proposed research plan takes an innovative approach to investigating BITs for depression by incorporating principles from psychology, engineering, and design to examine two primary psychological principles, CT and BA, delivered by mobile apps. The project will include two stages. First, the most usable elements of existing apps will be identified to create two apps, one using CT and the other BA, targeting depressive symptoms. This usability process will use a clear, model-driven approach to identify the most usable and useful characteristics for three app elements: information delivery, tools, and visual feedback. Following usability testing and improvements, the two apps will be subjected to a small comparative trial. Secondary aims will include an examination of usage of the apps, defined as how many times the apps are opened on the mobile devices. Results will provide information that can be broadly used by developers of apps for depression and may also have implications for apps aimed at treating other mental health disorders.