Exploring the spatiotemporal stress patterns of commuting in large Cities: Using wearable device data

Area of Science:

• Environmental Psychology
• Urban Planning
• Transportation Science

Background:

• Urban commuting is a major source of stress, influenced by various contextual factors.
• Understanding the spatiotemporal dynamics of commuting stress is crucial for urban well-being.

Purpose of the Study:

• To investigate the spatiotemporal characteristics of commuting stress in Beijing using wearable device data and GPS tracking.
• To identify distinct commuting stress patterns and their contributing factors.

Main Methods:

• Time-series stress data from wearable devices and GPS tracking were collected.
• K-means clustering identified four distinct stress patterns.
• Statistical analyses (ANOVA, chi-square, logistic regression) examined stress pattern features and contributing factors.

Main Results:

• High-stress commuting is characterized by intense alarm phases, elevated stress peaks, and extended recovery periods, potentially leading to mental exhaustion.
• Long-distance commutes from suburbs to urban centers and crowded transit environments (subways, e-bicycles) are strongly associated with increased stress.
• Commute duration alone did not consistently correlate with higher stress levels.

Conclusions:

• Urban planning should prioritize enhancing public transportation and non-motorized vehicle environments during peak hours.
• Addressing transportation equity for low-income groups undertaking long commutes is essential for mitigating stress.
• Targeted interventions can improve urban residents' quality of life by reducing daily commuting stress.