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Observational Study
. 2024 Nov 29:11:e50835.
doi: 10.2196/50835.

Understanding Morning Emotions by Analyzing Daily Wake-Up Alarm Usage: Longitudinal Observational Study

Affiliations
Observational Study

Understanding Morning Emotions by Analyzing Daily Wake-Up Alarm Usage: Longitudinal Observational Study

Kyue Taek Oh et al. JMIR Hum Factors. .

Abstract

Background: Morning emotions can significantly affect daily wellness. While many studies have analyzed daily survey responses to identify factors influencing morning emotions, these methods require additional time and effort from individuals for emotional monitoring.

Objective: This study aims to identify daily alarm usage patterns related to morning emotions.

Methods: We recruited 373 users of the Alarmy app (DelightRoom) in the United States and South Korea and surveyed their demographics and usual behaviors related to morning emotions. Participants described their morning emotions over a 2-week period, during which we collected daily alarm app logs. We used a generalized estimating equation (GEE) method to identify factors affecting morning emotions.

Results: The findings indicate that varied alarm usage is related to morning emotions. Alarm set time was positively associated with feelings of peacefulness and refreshment in the morning, while task-based alarms were related to nervousness. The time taken to deactivate the alarm after it rang was negatively correlated with happiness. In addition, usual behaviors and demographic factors were found to be related to morning emotions, consistent with previous studies.

Conclusions: The study reveals that daily alarm usage is related to morning emotions, suggesting that daily alarm logs can supplement survey methods to facilitate daily emotion monitoring.

Keywords: emotion monitoring; longitudinal observational study; morning context; morning emotion; wake-up alarm usage.

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Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
Results of generalized estimating equations analysis on positive emotions.
Figure 2
Figure 2
Results of generalized estimating equations analysis on negative emotions.

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