The purpose of the current study was to investigate how post-surgery multifaceted body image predicts negative affect (NA) 6 months post-surgery among women undergoing mastectomy. In total, 310 Chinese women undergoing mastectomy were recruited from a hospital in the Hunan province between 2012 and 2013. Upon enrollment (T1), all women were administered the Chinese version of Body Image after Breast Cancer Questionnaire (BIBCQ) (BIBCQ-C), NA subscale of Positive and Negative Affect Schedule (PANAS), Multidimensional Scale of Perceived Social Support (MSPSS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD). Two weeks later, BIBCQ-C was re-administered. Six months later (T2), the NA subscale was administered again. We first evaluated the psychometric properties of BIBCQ-C, and then investigated the long-term impact of different aspects of body image on NA using forced entry hierarchical regression analyses. The BIBCQ-C scores demonstrated acceptable internal consistency (all Cronbach’s α > 0.70) and test–retest reliability (all ICC > 0.86). Confirmatory factor analysis supported the six-factor model (CFI = 0.93, TLI = 0.94, RMSEA = 0.04). Regression analysis showed that two dimensions of body image, vulnerability (β = 0.217) and body concern (β = 0.119) at T1, significantly predict NA at T2 (all p < 0.05). BIBCQ-C was a good instrument for measuring multifaceted body image. Improvement of vulnerability and body concern, two aspects of body image, may reduce post-surgery NA among Chinese women undergoing mastectomy.
Archives of Women's Mental Health – Springer Journals
Published: May 27, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera