Gaming the Pain Away? The Relationship Between Flow Experience and Chronic Pain
Abstract
Empirical research into psychological strategies for chronic pain remains notably scarce to date. While cognitive-behavioral and attentional strategies such as distraction are well-established in pain management, their efficacy is often temporary and limited. This highlights the need for alternative psychological mechanisms that allow for more sustained modulation of pain. One promising yet under-researched approach to pain modulation lies in the experience of flow – a state of deep, effortless attention, optimal challenge, and intrinsic enjoyment (Csikszentmihalyi, 1990; Peifer & Engeser, 2021). Given an optimal demand-skill balance, flow experience may modulate both the sensory and affective components of pain through maximal cognitive resource allocation and optimal psychophysiological arousal, beyond mere distraction. The present study examines the effect of experimentally induced flow on pain experience in adults with chronic pain. As controlled, experimental mixed-design with a planned minimum sample size of N = 48, the online study employs a computer-based task (Tetris) to manipulate flow. Task demands are systematically manipulated across the three conditions: Boredom, Fit and Overload. Pain experience (NRS-11) is measured at three time points pre-, during-, and post-task, and Flow intensity (FIS), Flow frequency (FFS) and clinical covariates are recorded. It is hypothesized that the Fit condition will successfully induce Flow, leading to a significantly greater reduction in both pain intensity and unpleasantness compared to the Misfit conditions. These findings may highlight the therapeutic potential of flow-inducing tasks and game-based interventions for chronic pain management. This study is conducted as part of a research internship within the Master’s program Psychology Cognitive Systems at the University of Lübeck, Work and Health Lab, Institute of Psychology.
Publication details
- Journal / source
- Open Science Framework
- Publication date
- 1 January 2026