A Multi-population Analysis of a Self-care Scale for Menstrual Pain;

Eriko YAMAMOTO
2020 Asian Journal of Human Services  
The purpose of this study was to verify the cross-validity of the "self-care scale for dysmenorrhea in young females" that we developed, to clarify the causal relationship between snacking and each of the factors with menstrual pain from the results of a multiple regression analysis of the related factors survey in the previous study (Yamamoto, 2019) . The study participants were 1,000 young females who had menstrual pain and participated in this study, and 300 young females who had menstrual
more » ... in and participated in the related factors survey. Assuming that the two participant populations had the same factor structure, we performed a simultaneous multi-population analysis. Based on the multiple regression analysis of the previous study (Yamamoto, 2019), we set up a hypothesis for the causal relationship between snacking and each scale factor with menstrual pain, and then clarified the relationship using a path analysis. The results of our multi-population analysis revealed that the factor structure of the main survey and the related factors survey were equivalent, and that the self-care scale for menstrual pain could accurately measure six structural concepts even in different populations. When they ate more snacks, the 1st factor "perception of self-efficacy" decreased, which led to the 5th factor "expected level of burden needed to improve menstrual pain". It also led to the 4th factor "self-care using medicine". The more menstrual pain they had, the less of the 4th factor "self-care using medicine" they performed. It was demonstrated that the self-care scale for menstrual pain had cross-validity. The relationship between snacking and each factor with menstrual pain became clear. menstrual pain, self-care scale, multi-population analysis, snacking, causal relationship yamamoto.eriko@twmu.ac.jp(Eriko YAMAMOTO; Japan) Asian J Human Services, 2020, 18:18-32.
doi:10.14391/ajhs.18.18 fatcat:yskr745y3zdh5d22l4ipabvye4