Abstract
This study aims to adapt positive self-talk for mobile devices by evaluating content suitability for diverse negative emotional states. To this end, we focus on four different negative emotions: anger, sadness, shame, and anxiety. Based on Regulatory Focus Theory, we categorized eight types of self-talk messages as either promotion- or prevention-focused. The latter are designed to guide individuals away from negative outcomes by emphasizing the assurance of safety and comfort amid adverse emotional states. In contrast, promotion-focused messages aim to lead individuals toward positive outcomes, highlighting hopes, accomplishments, and advancements. We then examined how users’ preferences for certain messaging types vary depending on their specific emotional states. To explore and categorize mobile-based self-talk, we conducted two distinct surveys. In Study 1, participants were exposed to vignettes designed to induce four types of moods (i.e., anger, anxiety, sadness, and shame). In Study 2, participants encountered a single vignette (e.g., anger) that corresponded to their most recently experienced negative emotion. The results indicate that messages preference is influenced by the individual’s mood. Both Study 1 and 2 confirm a preference for prevention-focused messages among individuals experiencing anger or anxiety. In contrast, promotion-focused messages were preferred by people who feeling sadness and shame. This study offers crucial insights for developing mHealth and emotional regulation applications. Moreover, this paper strongly underscores the need to customize self-talk messages to users’ specific negative emotions to enhance the efficacy of emotional regulation through mobile technology.
Original language | English |
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Pages (from-to) | 15971-15982 |
Number of pages | 12 |
Journal | Current Psychology |
Volume | 43 |
Issue number | 17 |
DOIs | |
State | Published - May 2024 |
Bibliographical note
Publisher Copyright:© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. corrected publication 2024.
Keywords
- Digital emotion regulation
- Emotion regulation
- Mobile health
- Mood
- Self-talk