Day to day worry about interference from chronic pain:an ecological momentary assessment study

Introduction. Chronic pain disrupts daily activities directly and through anticipatory avoidance. From a Bayesian brain perspective, individuals should update predictions about pain interference based on the outcomes of prior predictions. Yet in chronic pain, worry about pain interference often persists even when actual interference is less than expected. Most studies treat worry as a stable trait, here we sampled it repeatedly to capture its day-to-day variability. We examined (1) how accurately morning worry about pain interference predicted evening reports of interference, and (2) whether participants adjusted their pain interference worry based on previous-day prediction errors. Methods. Eighteen adults with chronic pain completed ecological momentary assessments four times daily for 28 days (morning, evening, and two random daytime prompts), rating pain, mood, and stress at each prompt, and worry about pain interference each morning. We used lagged-level mixed-effects models and Monte Carlo simulations to test error-driven learning. Results. Morning worry moderately predicted evening interference (b=0.39, p<.001; model R²=0.27). Yesterday's prediction errors showed a marginal negative association with worry (b=-0.08, p=.064). The stability of day-to-day worry (b=0.28, p<.001) and recent stress (b=0.19, p=.008) were each approximately twice as large as the learning coefficient. Discussion. In this exploratory naturalistic study, day-to-day adjustments of pain interference worry appeared to be overwhelmed by affective state rather than driven by prediction error. The prediction-error estimate is consistent with a small rather than null effect, warranting confirmation in a larger sample. This may help explain why pain interference worry persists despite disconfirmatory experience.