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<p>Individual differences modulate our thoughts and emotional experiences, yet how thought and emotion interact in daily life remains largely unclear. We leverage alexithymia, a trait reflecting atypical emotional awareness, to reveal these interactions in naturalistic settings. Using multi-dimensional experience sampling via smartphones, we captured moment-to-moment thought patterns and concurrent affective states (valence, arousal, stress) in people’s daily life (<i>N</i>  =  190 undergraduate students, age range = 18 to 36, 159 females). Using Principal Component Analysis and Linear Mixed Models, we identified four thought dimensions that relate differently to these affective states: future-self orientation, intrusive distraction, sensory engagement, and task-focus. Alexithymia modulated these relationships. High overall alexithymia predicted fewer future-self-oriented thoughts and greater variability in sensory engagement across affective and social contexts, while difficulty identifying feelings selectively reduced future-self orientation during intense sadness, and externally oriented thinking rendered thought patterns less sensitive to affective context. By mapping affective experiences onto thought dimensions, these findings uncover cognitive pathways that connect to emotional well-being, providing a scalable framework for understanding variability in human affective experience.</p>

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Individual differences in alexithymia modulate cognition-emotion interactions in daily life ongoing experiences

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年3月10日

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  • Anqi Lei,
  • Md Faysal,
  • Louis Chitiz,
  • Raven Wallace,
  • Samyogita Hardikar,
  • Brontë McKeown,
  • Jonathan Smallwood,
  • Elizabeth Jefferies,
  • Robert Leech,
  • Nerissa Ho

摘要

Individual differences modulate our thoughts and emotional experiences, yet how thought and emotion interact in daily life remains largely unclear. We leverage alexithymia, a trait reflecting atypical emotional awareness, to reveal these interactions in naturalistic settings. Using multi-dimensional experience sampling via smartphones, we captured moment-to-moment thought patterns and concurrent affective states (valence, arousal, stress) in people’s daily life (N  =  190 undergraduate students, age range = 18 to 36, 159 females). Using Principal Component Analysis and Linear Mixed Models, we identified four thought dimensions that relate differently to these affective states: future-self orientation, intrusive distraction, sensory engagement, and task-focus. Alexithymia modulated these relationships. High overall alexithymia predicted fewer future-self-oriented thoughts and greater variability in sensory engagement across affective and social contexts, while difficulty identifying feelings selectively reduced future-self orientation during intense sadness, and externally oriented thinking rendered thought patterns less sensitive to affective context. By mapping affective experiences onto thought dimensions, these findings uncover cognitive pathways that connect to emotional well-being, providing a scalable framework for understanding variability in human affective experience.