The Black identity, hair product use, and breast cancer scale
Autoři:
Dede Teteh aff001; Marissa Ericson aff002; Sabine Monice aff003; Lenna Dawkins-Moultin aff001; Nasim Bahadorani aff004; Phyllis Clark aff005; Eudora Mitchell aff006; Lindsey S. Treviño aff001; Adana Llanos aff007; Rick Kittles aff001; Susanne Montgomery aff003
Působiště autorů:
Department of Population Sciences, Division of Health Equities, City of Hope Comprehensive Cancer Center, Duarte, California, United States of America
aff001; Department of Psychology, University of Southern California, Los Angeles, California, United States of America
aff002; School of Behavioral Health, Loma Linda University, Loma Linda, California, United States of America
aff003; Department of Health Sciences, California State University-Northridge, Northridge, California, United States of America
aff004; Healthy Heritage Movement, Riverside, California, United States of America
aff005; Quinn Community Outreach Corporation, Moreno Valley, California, United States of America
aff006; Rutgers School of Public Health and Cancer Institute of New Jersey, Piscataway, New Jersey, United States of America
aff007
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
prolekare.web.journal.doi_sk:
https://doi.org/10.1371/journal.pone.0225305
Souhrn
Introduction
Across the African Diaspora, hair is synonymous with identity. As such, Black women use a variety of hair products, which often contain more endocrine-disrupting chemicals than products used by women of other races. An emerging body of research is linking chemicals in hair products to breast cancer, but there is no validated instrument that measures constructs related to hair, identity, and breast health. The objective of this study was to develop and validate the Black Identity, Hair Product Use, and Breast Cancer Scale (BHBS) in a diverse sample of Black women to measure the social and cultural constructs associated with Black women’s hair product use and perceived breast cancer risk.
Methods
Participants completed a 27-item scale that queried perceptions of identity, hair products, and breast cancer risk. Principal Component Analyses (PCA) were conducted to establish the underlying component structures, and confirmatory factor analysis (CFA) was used to determine model fit.
Results
Participants (n = 185) were African American (73%), African, and Caribbean Black women (27%) aged 29 to 64. PCA yielded two components that accounted for 61% of total variance. Five items measuring sociocultural perspectives about hair and identity loaded on subscale 1 and accounted for 32% of total variance (α = 0.82; 95% CI = 0.77–0.86). Six items assessing perceived breast cancer risk related to hair product use loaded on subscale 2 and accounted for 29% of total variance (α = 0.82 (95% CI = 0.74–0.86). CFA confirmed the two-component structure (Root Mean Square Error of Approximation = 0.03; Comparative Fit Index = 0.91; Tucker Lewis Index = 0.88).
Conclusions
The BHBS is a valid measure of social and cultural constructs associated with Black women’s hair product use and perceived breast cancer risk. This scale is useful for studies that assess cultural norms in the context of breast cancer risk for Black women.
Klíčová slova:
Principal component analysis – Women's health – Behavior – Cancer detection and diagnosis – Culture – Breast cancer – African American people – Relaxation (psychology)
Zdroje
1. Centers for Disease Control and Prevention. Breast Cancer Statistics 2018. Available from: https://www.cdc.gov/cancer/breast/statistics/index.htm.
2. Corrarino JE. Barriers to mammography use for Black women. The Journal for Nurse Practitioners. 2015;11(8):790–6.
3. Centers for Disease Control and Prevention. Breast cancer rates among Black women and White women 2016. Available from: https://www.cdc.gov/cancer/dcpc/research/articles/breast_cancer_rates_women.htm.
4. DeSantis CE, Fedewa SA, Goding Sauer A, Kramer JL, Smith RA, Jemal A. Breast cancer statistics, 2015: Convergence of incidence rates between black and white women. CA: a cancer journal for clinicians. 2016;66(1):31–42.
5. Anders CK, Johnson R, Litton J, Phillips M, Bleyer A. Breast Cancer Before Age 40 Years. Seminars in oncology. 2009;36(3):237–49. doi: 10.1053/j.seminoncol.2009.03.001 PMC2894028. 19460581
6. Carey LA, Perou CM, Livasy CA, Dressler LG, Cowan D, Conway K, et al. Race, breast cancer subtypes, and survival in the Carolina Breast Cancer Study. Jama. 2006;295(21):2492–502. doi: 10.1001/jama.295.21.2492 16757721
7. Porter PL, Lund MJ, Lin MG, Yuan X, Liff JM, Flagg EW, et al. Racial differences in the expression of cell cycle–regulatory proteins in breast carcinoma: Study of young African American and white women in Atlanta, Georgia. Cancer. 2004;100(12):2533–42. doi: 10.1002/cncr.20279 15197793
8. Paxton RJ, Taylor WC, Chang S, Courneya KS, Jones LA. Lifestyle Behaviors of African American Breast Cancer Survivors: A Sisters Network, Inc. Study. PLoS ONE. 2013;8(4):e61854. doi: 10.1371/journal.pone.0061854 PMC3633932. 23626740
9. Stiel L, Adkins‐Jackson PB, Clark P, Mitchell E, Montgomery S. A review of hair product use on breast cancer risk in African American women. Cancer medicine. 2016;5(3):597–604. doi: 10.1002/cam4.613 26773423
10. Helm JS, Nishioka M, Brody JG, Rudel RA, Dodson RE. Measurement of endocrine disrupting and asthma-associated chemicals in hair products used by Black women. Environmental Research. 2018.
11. Llanos AAM, Rabkin A, Bandera EV, Zirpoli G, Gonzalez BD, Xing CY, et al. Hair product use and breast cancer risk among African American and White women. Carcinogenesis. 2017;38(9):883–92. doi: 10.1093/carcin/bgx060 28605409
12. Ambrosone CB, Abrams SM, Gorlewska-Roberts K, Kadlubar FF. Hair dye use, meat intake, and tobacco exposure and presence of carcinogen-DNA adducts in exfoliated breast ductal epithelial cells. Archives of biochemistry and biophysics. 2007;464(2):169–75. doi: 10.1016/j.abb.2007.05.018 17601487
13. Donovan M, Tiwary CM, Axelrod D, Sasco AJ, Jones L, Hajek R, et al. Personal care products that contain estrogens or xenoestrogens may increase breast cancer risk. Medical Hypotheses. 2007;68(4):756–66. doi: 10.1016/j.mehy.2006.09.039 17127015
14. Myers SL, Yang CZ, Bittner GD, Witt KL, Tice RR, Baird DD. Estrogenic and anti-estrogenic activity of off-the-shelf hair and skin care products. Journal of Exposure Science and Environmental Epidemiology. 2015;25(3):271. doi: 10.1038/jes.2014.32 24849798
15. Burnett CM, Goldenthal EI. Multigeneration reproduction and carcinogenicity studies in Sprague-Dawley rats exposed topically to oxidative hair-colouring formulations containing p-phenylenediamine and other aromatic amines. Food and chemical toxicology: an international journal published for the British Industrial Biological Research Association. 1988;26(5):467–74. doi: 10.1016/0278-6915(88)90059-2 3391471.
16. Evarts RP, Brown CA. 2,4-diaminoanisole sulfate: early effect on thyroid gland morphology and late effect on glandular tissue of Fischer 344 rats. Journal of the National Cancer Institute. 1980;65(1):197–204. 6930514.
17. Rojanapo W, Kupradinun P, Tepsuwan A, Chutimataewin S, Tanyakaset M. Carcinogenicity of an oxidation product of p-phenylenediamine. Carcinogenesis. 1986;7(12):1997–2002. doi: 10.1093/carcin/7.12.1997 3779896.
18. James-Todd T, Senie R, Terry MB. Racial/ethnic differences in hormonally-active hair product use: a plausible risk factor for health disparities. Journal of immigrant and minority health. 2012;14(3):506–11. doi: 10.1007/s10903-011-9482-5 21626298
19. Mintel. Natural hair movement drives sales of styling products in US Black hair care market 2015. Available from: http://www.mintel.com/press-centre/beauty-and-personal-care/natural-hair-movement-drives-sales-of-styling-products-in-us-black-haircare-market.
20. Teteh DK, Montgomery SB, Monice S, Stiel L, Clark PY, Mitchell E. My crown and glory: Community, identity, culture, and Black women’s concerns of hair product-related breast cancer risk. Cogent Arts & Humanities. 2017;4(1):1345297.
21. Thompson C. Black women, beauty, and hair as a matter of being. Women's Studies. 2009;38(8):831–56.
22. Johnson TA, Bankhead T. Hair it is: Examining the experiences of Black women with natural hair. Open Journal of Social Sciences. 2014;2(86–100).
23. Robinson-Flint J. Why Black women should watch the environmental impact of beauty products. Ebony. 2017.
24. Breast Cancer Prevention Partners. Right to know: Exposing toxic fragrance chemicals in beauty, personal care, and cleaning products. San Francisco, CA: 2018.
25. Vandiver BJ, Cross WE Jr, Worrell FC, Fhagen-Smith PE. Validating the Cross Racial Identity Scale. Journal of Counseling psychology. 2002;49(1):71.
26. Wallston BS, Wallston KA, Kaplan GD, Maides SA. Development and validation of the health locus of control (HLC) scale. Journal of consulting and clinical psychology. 1976;44(4):580. doi: 10.1037//0022-006x.44.4.580 939841
27. Weber EU, Blais AR, Betz NE. A domain‐specific risk‐attitude scale: Measuring risk perceptions and risk behaviors. Journal of behavioral decision making. 2002;15(4):263–90.
28. Creswell JW, Clark VL. Designing and conducting mixed methods research: Sage publications; 2017.
29. Calzo JP, Bogart LM, Francis E, Kornetsky SZ, Winkler SJ, Kaberry JM. Engaging Institutional Review Boards in developing a brief, community-responsive human subjects training for community partners. Progress in community health partnerships: Research, education, and action. 2016;10(3):471–7. doi: 10.1353/cpr.2016.0053 PMC5555620. 28230554
30. Teteh DK, Ericson M, Monice S, Dawkins-Moultin L, Bahadorani N, Clark P, et al. The Black identity, hair product use, and breast cancer scale: Qualitative questions 2014. Available from: dx.doi.org/10.17504/protocols.io.4a8gshw.
31. Provalis Research. Qualitative data analysis software n.d. Available from: https://provalisresearch.com/products/qualitative-data-analysis-software/.
32. Trusson D, Pilnick A. The role of hair loss in cancer identity: Perceptions of chemotherapy-induced alopecia among women treated for early-stage breast cancer or ductal carcinoma in situ. Cancer nursing. 2017;40(2):E9–E16. doi: 10.1097/NCC.0000000000000373 27070222
33. Strauss A, Corbin JM. Grounded theory in practice: Sage; 1997.
34. IBM. IBM Statistical Package for Social Sciences 2017.
35. Gorsuch RL. Factor analysis. 2nd ed. Hillsdale, NJ: Lawrence Erlbaum; 1983.
36. Osborne JW, Costello AB, Kellow JT. Best practices in exploratory factor analysis. Best practices in quantitative methods. 2008:86–99.
37. Cattell RB. The scree test for the number of factors. Multivariate behavioral research. 1966;1(2):245–76. doi: 10.1207/s15327906mbr0102_10 26828106
38. Kaiser HF. The application of electronic computers to factor analysis. Educational and psychological measurement. 1960;20(1):141–51.
39. Watkins MW. Exploratory factor analysis: A guide to best practice. Journal of Black Psychology. 2018;44(3):219–46.
40. Cronbach LJ. Coefficient alpha and the internal structure of tests. psychometrika. 1951;16(3):297–334.
41. Nunnally J, Bernstein I. Psychometric Theory McGraw-Hill New York Google Scholar. 1978.
42. Muthen L, Muthen B. Mplus User’s Guide. Los Angeles, CA: Muthen & Muthen, 2003.
43. MacCallum RC, Browne MW, Sugawara HM. Power analysis and determination of sample size for covariance structure modeling. Psychological methods. 1996;1(2):130.
44. Mulaik SA, James LR, Van Alstine J, Bennett N, Lind S, Stilwell CD. Evaluation of goodness-of-fit indices for structural equation models. Psychological bulletin. 1989;105(3):430.
45. Muthen B, Kaplan D. A comparison of some methodologies for the factor analysis of non‐normal Likert variables: A note on the size of the model. British Journal of Mathematical and Statistical Psychology. 1992;45(1):19–30.
46. Akaike H. Factor analysis and AIC. Selected Papers of Hirotugu Akaike: Springer; 1987. p. 371–86.
47. King LM. Development of authenticity in public health. The Health Behavioral Change Imperative: Springer; 2002. p. 91–111.
48. Proctor RN. The history of the discovery of the cigarette–lung cancer link: evidentiary traditions, corporate denial, global toll. Tobacco control. 2012;21(2):87–91. doi: 10.1136/tobaccocontrol-2011-050338 22345227
49. Fokkema M, Greiff S. How performing PCA and CFA on the same data equals trouble. Hogrefe Publishing; 2017.
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