Cancer-related cognitive impairment in breast cancer survivors: An examination of conceptual and statistical cognitive domains using principal component analysis
There is a great deal of variability in the composition of neuropsychological test batteries used in the assessment of cancerrelated cognitive impairment (CRCI). Not only the development of a gold standard approach for CRCI assessment would allow for easier identification of women suffering from CRCI but it would also promote optimal care for survivors. As a first step towards the development of a valid and reliable unified test battery, the objective of this study was to verify whether the theoretical domains commonly used in CRCI assessment are statistically supported, before and after breast cancer treatment. Principal component analyses (PCA) were performed on the results from 23 neuropsychological tests grouped into eight conceptual domains. For baseline data, the Kaiser-Meyer-Olkin was .82 and Bartlett’s χ2(253, N=95) = 949.48, P<0.001. A five-component solution explained 60.94% of the common variance. For the post-treatment data, the Kaiser-Meyer-Olkin was .83 and Bartlett’s χ2(253, N=95) = 1007.21, P<0.001 and a five component solution explained 62.03% of the common variance. Although a visual comparison of the theoretical model with those determined via PCA indicated important overlap between conceptual domains and statistical components, significant dissimilarities were also observed.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2018 Maude Lambert, Lea Ann Ouimet, Cynthia Wan, Angela Stewart, Barbara Collins, Irene Vitoroulis, Catherine Bielajew
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.