Data-Driven Implications for Translating Evidence-Based Psychotherapies into Technology-Delivered Interventions.
Data-Driven Implications for Translating Evidence-Based Psychotherapies into Technology-Delivered Interventions.
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DOI：
10.1145/3421937.3421975
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发表时间：
2020-05
期刊：
影响因子：
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通讯作者：
Althoff T
中科院分区：
文献类型：
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作者：
Schroeder J;Suh J;Wilks C;Czerwinski M;Munson SA;Fogarty J;Althoff T
移动的心理健康干预措施有可能减少心理治疗的障碍并增加参与。然而，目前大多数工具都不符合循证原则。在本文中，我们描述了将循证干预措施转化为移动的应用程序的数据驱动设计含义。为了开发这些设计的影响，我们分析了一个为期一个月的实地研究的数据，该研究是一个旨在支持辩证行为疗法的应用程序，这是一种心理疗法，旨在教授具体的应对技能，以帮助人们更好地管理他们的心理健康。我们调查了特定的技能在减少痛苦或情绪强度方面是否更有效。我们还描述了个体的疾病、特征和偏好如何与技能有效性相关，以及技能水平的提高如何与抑郁症状的研究范围内的变化相关。然后，我们开发了一个模型来预测技能有效性。基于我们的研究结果，我们提出了设计的影响，强调考虑不同的环境，情感和个人背景的重要性。最后，我们讨论了移动的应用程序未来有希望更好地支持循证心理治疗的机会，包括使用机器学习算法来开发个性化和上下文感知的技能建议。
Mobile mental health interventions have the potential to reduce barriers and increase engagement in psychotherapy. However, most current tools fail to meet evidence-based principles. In this paper, we describe data-driven design implications for translating evidence-based interventions into mobile apps. To develop these design implications, we analyzed data from a month-long field study of an app designed to support dialectical behavioral therapy, a psychotherapy that aims to teach concrete coping skills to help people better manage their mental health. We investigated whether particular skills are more or less effective in reducing distress or emotional intensity. We also characterized how an individual’s disorders, characteristics, and preferences may correlate with skill effectiveness, as well as how skill-level improvements correlate with study-wide changes in depressive symptoms. We then developed a model to predict skill effectiveness. Based on our findings, we present design implications that emphasize the importance of considering different environmental, emotional, and personal contexts. Finally, we discuss promising future opportunities for mobile apps to better support evidence-based psychotherapies, including using machine learning algorithms to develop personalized and context-aware skill recommendations.