将一种解释偏差智能手机应用程序干预措施付诸实践：病例系列
Operationalizing Engagement With an Interpretation Bias Smartphone App Intervention: Case Series.
作者信息
Ramadurai Ramya, Beckham Erin, McHugh R Kathryn, Björgvinsson Thröstur, Beard Courtney
机构信息
Department of Psychology, American University, Washington, DC, United States.
Cognition and Affect Research and Education Lab, McLean Hospital, Belmont, MA, United States.
出版信息
JMIR Ment Health. 2022 Aug 17;9(8):e33545. doi: 10.2196/33545.
BACKGROUND
Engagement with mental health smartphone apps is an understudied but critical construct to understand in the pursuit of improved efficacy.
OBJECTIVE
This study aimed to examine engagement as a multidimensional construct for a novel app called HabitWorks. HabitWorks delivers a personalized interpretation bias intervention and includes various strategies to enhance engagement such as human support, personalization, and self-monitoring.
METHODS
We examined app use in a pilot study (n=31) and identified 5 patterns of behavioral engagement: consistently low, drop-off, adherent, high diary, and superuser.
RESULTS
We present a series of cases (5/31, 16%) from this trial to illustrate the patterns of behavioral engagement and cognitive and affective engagement for each case. With rich participant-level data, we emphasize the diverse engagement patterns and the necessity of studying engagement as a heterogeneous and multifaceted construct.
CONCLUSIONS
Our thorough idiographic exploration of engagement with HabitWorks provides an example of how to operationalize engagement for other mental health apps.
背景
在追求提高疗效的过程中，使用心理健康智能手机应用程序是一个研究不足但至关重要的概念。
目的
本研究旨在将参与度作为一种多维概念，用于一款名为HabitWorks的新型应用程序。HabitWorks提供个性化的解释偏差干预，并包括各种提高参与度的策略，如人工支持、个性化和自我监测。
方法
我们在一项试点研究（n=31）中检查了应用程序的使用情况，并确定了5种行为参与模式：持续低参与度、中途退出、坚持使用、高记录频率和超级用户。
结果
我们展示了该试验中的一系列案例（5/31，16%），以说明每个案例的行为参与、认知和情感参与模式。通过丰富的参与者层面数据，我们强调了多样化的参与模式以及将参与度作为一个异质且多方面概念进行研究的必要性。
结论
我们对使用HabitWorks的参与度进行的全面个案研究，为如何将参与度应用于其他心理健康应用程序提供了一个示例。
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