Exploring Variance in Users’ Moods across Times, Seasons, and Activities: A Longitudinal Analysis

The goal of this research is to evaluate the relationship between moods and activities based on data collected in everyday life. To achieve our goal, we conducted a longitudinal analysis of mobile app usage data. We used a random sample of 132 users on the Version II of a mental health app called Feeling Moodie. All considered participants used the app between September 16th to December 13th, 2021. The app allowed users to log their moods and activities at their convenience. A chi-square analysis showed that there is a strong significant relationship between mood and activities. Furthermore, an exploratory analysis using descriptive statistics seems to show that the start of a specific activity (e.g., back to school/work) can be daunting and provoke an increase in mood levels (e.g., increase the level of “sadness”), but can stabilize after a certain period when the activity is more accustomed to everyday life. This research is the first building block for designing a user-centered mental health mobile app. The results obtained in this work will be used to inform the design of the next version of the Feeling Moodie app and can inform designers on how to improve the implementation of adaptive apps. The paper contributes to a better understanding of the relationship between moods and daily life activities and sheds light on the emotional and technological implications for personalizing and improving the quality of mHealth apps.

这项研究的目的是根据日常生活中收集的数据评估情绪和活动之间的关系。为了实现我们的目标，我们对移动应用程序的使用数据进行了纵向分析。我们从一款名为“Feeling Moodie”的心理健康应用程序第二版中随机抽取了132名用户作为样本。所有被考虑的参与者在2021年9月16日至12月13日期间使用了该应用程序。该应用程序允许用户在方便的时候记录自己的情绪和活动。卡方分析表明，情绪和活动之间存在着很强的显著关系。此外，使用描述性统计进行的探索性分析似乎表明，一项特定活动的开始（例如，返校/上班）可能会令人望而却步，并导致情绪水平升高（例如，增加“悲伤”的程度），但当这项活动更适应日常生活后，在一段时间后情绪会稳定下来。这项研究是设计以用户为中心的心理健康移动应用程序的第一块基石。这项工作中获得的结果将用于为“Feeling Moodie”应用程序的下一版本设计提供信息，并可以告知设计师如何改进自适应应用程序的实施。这篇论文有助于更好地理解情绪和日常生活活动之间的关系，并阐明了个性化和提高移动健康应用程序质量在情感和技术方面的影响。