The role of pain sensitivity, pain catastrophizing level and personality traits in influencing the pre-hospital delay of acute myocardial infarction patients

Abstract

Background: The pre-hospital delay of acute myocardial infarction (AMI) patients is common around the world. The long pre-hospital delay threatens both mortality and morbidity. To address the challenge of shortening this pre-hospital delay, identifying the factors related to AMI patients’ pre-hospital delay is of significant importance.

Objective: This thesis aims to identify the risk factors related to the pre-hospital delay of Chinese AMI patients, especially three possible factors at the individual level: pain sensitivity, pain catastrophizing level and personality traits. Pain sensitivity is the minimum amount of pain recognized by an individual; pain catastrophizing refers to a negative magnification of pain stimulus; and personality traits mean the consistent and long-lasting tendency in behaviours. Methods: A comprehensive systematic review of relevant studies was completed to identify existing knowledge of risk factors of AMI patients’ pre-hospital delay in China and to inform the risk factors to be investigated in this thesis. Then, a tool- the Pain Sensitivity Questionnaire (PSQ) was translated and validated into Mandarin Chinese (PSQ-C) to measure one of the potential risk factors: pain sensitivity. Standard cross-cultural adaptation steps were followed. The psychometric properties of the PSQ-C were assessed using a cross-sectional study design. An electrical experimental pain test was used to assess the concurrent validity. Finally, a cross-sectional survey study on Chinese AMI patients was conducted in Changsha city, China. A structured face-to-face questionnaire was administered. Alongside the PSQ-C, a Pain Catastrophizing Scale and Eysenck Personality Questionnaire were used to measure the pain catastrophizing level and personality traits, respectively. Pre-hospital delay was defined as more than 90 minutes between the onset of symptoms and arrival at an adequately equipped hospital. Logistic regression was used to identify the predictors to AMI patients’ pre-hospital delay. Results: The systematic review identified the common risk factors of AMI patients’ pre-hospital delay in China, including socio-demographic factors (e.g. unemployment and living alone), clinical characteristics (e.g. onset during the night and lack of pain), actions taken (e.g. self-medication and informally consulting a doctor) and psychological factors (e.g. wait-and-see and passive attitude). A knowledge gap in terms of the influence of pain sensitivity, pain catastrophizing level and personality traits was revealed in the systematic review. In the cultural adaptation of the PSQ-C, three of the 17 PSQ items were revised according to the knowledge and understanding by Chinese people. It was validated in a convenience sample of 182 Chinese people aged 39.9±14.6. The Cronbach’s alpha coefficients of the PSQ-C-total, PSQ-C-moderate, and PSQ-C-minor were 0.90, 0.86 and 0.81, respectively. The test-retest reliability, content validity, and construct validity of the PSQ-C were demonstrated. The PSQ-C showed reasonably good psychometric properties, similar to the English and German versions. Of the 329 patients interviewed in the Chinese AMI patients survey, over half (55%) were admitted to hospital more than 90 minutes after the onset of symptoms. Multiple logistic regression with forward selection procedure demonstrated that among pain sensitivity, pain catastrophizing level and personality traits, only the personality trait of psychoticism was significantly associated with pre-hospital delay (OR: 0.34, 95% CI: 0.20-0.56), in the presence of other predictors. Conclusion: The PSQ-C is a reliable and useful instrument to assess pain sensitivity levels in the Chinese population. The new predictor, namely the psychotic personality trait, to AMI patients’ pre-hospital delay indicates the need to have tailored public education about proper health seeking behaviour for this group of the population.