Abstract
Deviant eating behavior such as skipping meals and consuming unhealthy meals has a significant association with mental well-being in college students. However, there is more to what an individual eats. While eating patterns form a critical component of their mental well-being, insights and assessments related to the interplay of eating patterns and mental well-being remain under-explored in theory and practice. To bridge this gap, we use an existing real-time eating detection system that captures context during meals to examine how college students' eating context associates with their mental well-being, particularly their affect, anxiety, depression, and stress. Our findings suggest that students' irregularity or skipping meals negatively correlates with their mental well-being, whereas eating with family and friends positively correlates with improved mental well-being. We discuss the implications of our study in designing dietary intervention technologies and guiding student-centric well-being technologies.
Original language | English (US) |
---|---|
Article number | 3533390 |
Journal | ACM Transactions on Computing for Healthcare |
Volume | 3 |
Issue number | 4 |
DOIs | |
State | Published - Nov 3 2022 |
Externally published | Yes |
Keywords
- affective computing
- anxiety
- college students
- depression
- Eating behavior
- eating context
- eating detection
- mental health
- stress
- wearable
ASJC Scopus subject areas
- Software
- Medicine (miscellaneous)
- Information Systems
- Biomedical Engineering
- Computer Science Applications
- Health Informatics
- Health Information Management