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用于抑郁症的认知行为疗法应用程序的用户体验:应用程序功能与用户评论分析

User Experience of Cognitive Behavioral Therapy Apps for Depression: An Analysis of App Functionality and User Reviews.

作者信息

Stawarz Katarzyna, Preist Chris, Tallon Debbie, Wiles Nicola, Coyle David

机构信息

Bristol Interaction Group, Faculty of Engineering, University of Bristol, Bristol, United Kingdom.

Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.

出版信息

J Med Internet Res. 2018 Jun 6;20(6):e10120. doi: 10.2196/10120.

DOI:10.2196/10120
PMID:29875087
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6010839/
Abstract

BACKGROUND

Hundreds of mental health apps are available to the general public. With increasing pressures on health care systems, they offer a potential way for people to support their mental health and well-being. However, although many are highly rated by users, few are evidence-based. Equally, our understanding of what makes apps engaging and valuable to users is limited.

OBJECTIVE

The aim of this paper was to analyze functionality and user opinions of mobile apps purporting to support cognitive behavioral therapy for depression and to explore key factors that have an impact on user experience and support engagement.

METHODS

We systematically identified apps described as being based on cognitive behavioral therapy for depression. We then conducted 2 studies. In the first, we analyzed the therapeutic functionality of apps. This corroborated existing work on apps' fidelity to cognitive behavioral therapy theory, but we also extended prior work by examining features designed to support user engagement. Engagement features found in cognitive behavioral therapy apps for depression were compared with those found in a larger group of apps that support mental well-being in a more general sense. Our second study involved a more detailed examination of user experience, through a thematic analysis of publicly available user reviews of cognitive behavioral therapy apps for depression.

RESULTS

We identified 31 apps that purport to be based on cognitive behavioral therapy for depression. Functionality analysis (study 1) showed that they offered an eclectic mix of features, including many not based on cognitive behavioral therapy practice. Cognitive behavioral therapy apps used less varied engagement features compared with 253 other mental well-being apps. The analysis of 1287 user reviews of cognitive behavioral therapy apps for depression (study 2) showed that apps are used in a wide range of contexts, both replacing and augmenting therapy, and allowing users to play an active role in supporting their mental health and well-being. Users, including health professionals, valued and used apps that incorporated both core cognitive behavioral therapy and non-cognitive behavioral therapy elements, but concerns were also expressed regarding the unsupervised use of apps. Positivity was seen as important to engagement, for example, in the context of automatic thoughts, users expressed a preference to capture not just negative but also positive ones. Privacy, security, and trust were crucial to the user experience.

CONCLUSIONS

Cognitive behavioral therapy apps for depression need to improve with respect to incorporating evidence-based cognitive behavioral therapy elements. Equally, a positive user experience is dependent on other design factors, including consideration of varying contexts of use. App designers should be able to clearly identify the therapeutic basis of their apps, but they should also draw on evidence-based strategies to support a positive and engaging user experience. The most effective apps are likely to strike a balance between evidence-based cognitive behavioral therapy strategies and evidence-based design strategies, including the possibility of eclectic therapeutic techniques.

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd77/6010839/131c1b5d4ecd/jmir_v20i6e10120_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd77/6010839/131c1b5d4ecd/jmir_v20i6e10120_fig1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd77/6010839/131c1b5d4ecd/jmir_v20i6e10120_fig1.jpg
摘要

背景

普通大众可以使用数百种心理健康应用程序。随着医疗保健系统压力的不断增加,这些应用程序为人们提供了一种支持自身心理健康和幸福的潜在方式。然而,尽管许多应用程序受到用户的高度评价,但很少有基于证据的。同样,我们对使应用程序对用户具有吸引力和价值的因素的理解也很有限。

目的

本文旨在分析声称支持抑郁症认知行为疗法的移动应用程序的功能和用户意见,并探讨影响用户体验和支持参与度的关键因素。

方法

我们系统地识别了被描述为基于抑郁症认知行为疗法的应用程序。然后我们进行了两项研究。在第一项研究中,我们分析了应用程序的治疗功能。这证实了现有关于应用程序对认知行为疗法理论的忠诚度的研究,但我们也通过检查旨在支持用户参与度的功能扩展了先前的研究。将抑郁症认知行为疗法应用程序中发现的参与功能与更广泛意义上支持心理健康的大量应用程序中发现的功能进行了比较。我们的第二项研究通过对抑郁症认知行为疗法应用程序的公开用户评论进行主题分析,对用户体验进行了更详细的检查。

结果

我们识别出31个声称基于抑郁症认知行为疗法的应用程序。功能分析(研究1)表明,它们提供了各种功能的混合,包括许多并非基于认知行为疗法实践的功能。与253个其他心理健康应用程序相比,抑郁症认知行为疗法应用程序使用的参与功能种类较少。对1287条抑郁症认知行为疗法应用程序的用户评论的分析(研究2)表明,这些应用程序在广泛的背景下被使用,既可以替代治疗,也可以增强治疗效果,并允许用户在支持自身心理健康和幸福方面发挥积极作用。包括健康专业人员在内的用户重视并使用了结合了核心认知行为疗法和非认知行为疗法元素的应用程序,但也有人对应用程序的无监督使用表示担忧。积极性被视为对参与度很重要,例如,在自动思维的背景下,用户表示不仅倾向于捕捉消极的思维,也倾向于捕捉积极的思维。隐私、安全和信任对用户体验至关重要。

结论

抑郁症认知行为疗法应用程序需要在纳入基于证据的认知行为疗法元素方面加以改进。同样,积极的用户体验取决于其他设计因素,包括考虑不同的使用背景。应用程序设计师应该能够清楚地识别其应用程序的治疗基础,但他们也应该借鉴基于证据的策略来支持积极且吸引人的用户体验。最有效的应用程序可能需要在基于证据的认知行为疗法策略和基于证据的设计策略之间取得平衡,包括采用折衷的治疗技术的可能性。

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