Setting. Thoracic surgery department of a tertiary hospital. Background. Fear of pain (FOP) has been recognized as an influential moderator and determinant of the perception and disability of chronic pain. However, studies on FOP in postoperative acute pain are few and inconsistent. Objective. To explore whether FOP is related to pain intensity after thoracic surgery and provide a reference for FOP study in postoperative pain. Methods. From February to March 2022, 89 patients completed Chinese Version of Fear of Pain-9 Items (FOP-9), Chinese version of the Brief Pain Inventory (BPI, including least, worst, and average pain) and Simplified Chinese version of the Pain Catastrophizing Scale (PCS). Correlation analyses and mediation analyses were used for exploring the relationship between factors. Results. Mediation analyses showed that the total effects of FOP-9 on BPI all were significant (least pain: effect = 0.085, p = 0.013 , 95% CI = 0.019∼0.151; worst pain: effect = 0.116, p = 0.004 , 95% CI = 0.037∼0.196; average pain: effect = 0.102, p = 0.005 , 95% CI = 0.031∼0.174) indicating that FOP-9 was a predictor to BPI. The 95% bias-corrected bootstrap confidence interval of estimate of indirect effect between FOP-9 and least pain/average pain through PCS was −0.036∼0.024 and −0.003∼0.069 (all contain zero), which indicated that PCS is not a mediator between FOP-9 and least pain/average pain. However, the estimate of indirect effect between FOP-9 and worst pain through PCS were 0.048 (95% CI = 0.095∼0.088), and direct effect was not statistically significant (95% CI = −0.017∼0.153), indicating that PCS acted as a complete intermediary between FOP-9 and worst pain. FOP-9 and PCS showed significant positive prediction effect on worst pain. Conclusions. Both trait FOP and state FOP were associated with higher postoperative pain reports after thoracic surgery. Trait FOP influences postoperative pain through the mediating effect of state FOP.

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The image information change law with the change of scale parameter is first studied in terms of regarding ramp edge and step edge as measurement of image information. Then the paper proposes a kind of adaptive recursive algorithm of scale parameter with the module of visual characters. The information of the image is uniformly distributed among each layer in the algorithm. The method can avoid the problem of complicated computation or over-distortion because of losing too much key information. The experimental results show that the uniformly distributed information is more reasonable for human to perceive an image which will be useful for higher-level image processing technologies such as object recognition.