Arousal and attentional processes in the relationship between pain and time perception: Evidence from a systematic...

Distortions in time perception under pain have been widely reported, yet the mechanisms underlying these effects remain unclear. The Attentional Gate Model and prior empirical research indicate that attention and arousal are associated with pain and time perception, yet their roles remain unexamined in a unified framework. The study aimed to investigate the mediating roles of arousal, attention control, and attention bias in the relationship between pain and time perception. A systematic search of China National Knowledge Infrastructure, Wanfang, Web of Science, and PubMed identified studies reporting associations among pain, arousal, attention control, attention bias, and time perception. A two-stage meta-analytic structural equation modeling approach was used to test mediation, with multilevel meta-regression analyses examining moderation by age, gender, pain type, and target duration. A total of 154 articles (176 independent studies) were included. Pain was positively correlated with time perception, arousal, and attention bias. Both arousal and attention bias were positively correlated with time perception, while arousal was negatively correlated with attention control and attention bias. Mediation analysis showed that only arousal had a significant mediating effect. Moderation analysis indicated that age, gender, and target duration significantly moderated the relationships between attentional processes and time perception, with age additionally moderating the relationship between attention control and attention bias. Overall, arousal showed a mediating role between pain and time perception, while attentional effects are context-dependent. This study extends the Attentional Gate Model to pain and clarifies the roles of arousal and attentional mechanisms in temporal experience under pain. OPEN PRACTICES STATEMENT: This study was preregistered on the Open Science Framework ( https://osf.io/suzhn/ ). The data and code are publicly available online ( https://osf.io/3ucvb/ ).