Poster Presentation
Water's Edge Ballroom (Hilton Waikoloa Village)
Friday, July 15, 2005
10:30 AM - 11:00 AM
Water's Edge Ballroom (Hilton Waikoloa Village)
Friday, July 15, 2005
4:00 PM - 4:30 PM
This presentation is part of : Poster Presentations II
Establishing an Array of Pain Intensity Descriptors by Cross Modality
Meyrick C.M. Chow, MA and Joanne Chung, PhD. School of Nursing, The Hong Kong Polytechnic University, Kowloon, Hong Kong
Learning Objective #1: Understand the cultural difference in use of pain descriptors
Learning Objective #2: Understand the method in development of a pain assessment scale

Introduction The team had conducted an exploratory study on the use of pain descriptors in local ethnic Chinese. The team further extrapolated the 10 pain descriptors which were: crucifying pain (µh¨ì¦º), crushing the heart and lungs (µhºRªÍµÆ), excruciating pain (¼@µh), unbearable pain (¤%iµÔ¨ü), indescribable pain (Ãø¥HµÎ®e), very painful (¤Q¤Àµh), painful (¦nµh), bearable pain (¥i¥HµÔ¨ü), quite painful (»áµh) and slight pain (·Lµh). With the addition of a 'no pain (¤£µh).' as a zero, the 10 descriptors were arranged in an ascending order by Q-sorting technique (Chung, Wong and Yang, 1999). The concurrent validity of tool was established (Chung, Wong and Yang, 2001). The reliability and validity were also established with the Visual Analogue Scale. The intra-class coefficient was 0.85 and a single factor with an eigenvalue greater than 1 was reported in the factor analysis (Liu, Chung and Wong, 2001).

Purpose It is to refine and improve the nature of the scale by cross-modality method.

Subject and sample size Three hundred healthy adults of Chinese ethnic origin in total will be recruited by stratified sampling (by age) from the community.

Method Cross-modality will be adopted in this study.

Data management Data collected included the demographic profile of the subjects and the data on similarity collected from the subject will be directly entered into a matrix sheet. Then, all the data will be entered into the SPSS for cluster analysis. Dentogram will be computed for their similarity.

Expected contribution This can provide the clinician a better way of assessing their clients' report of pain.