Journal List > J Korean Acad Nurs > v.46(3) > 1003161

TOOLS
Yang and Kim: The Structural Equation Model on Resilience of Breast Cancer Patients Receiving Chemotherapy
Original Article

Journal of Korean Academy of Nursing 2016; 46(3): 327-337.

Published online: 30 June 2016

DOI: https://doi.org/10.4040/jkan.2016.46.3.327

The Structural Equation Model on Resilience of Breast Cancer Patients Receiving Chemotherapy

Jeong Ha Yang1, Ok Soo Kim2

1Division of Nursing Science, JEI University, Incheon, Korea.

2Division of Nursing Science, College of Health Sciences, Ewha Womans University, Seoul, Korea.

Address reprint requests to: Yang, Jeong Ha. JEI University, 178, Jaeneung-ro, Dong-gu, Incheon 22573, Korea. Tel: +82-32-890-7322, Fax: +82-32-890-7199, mint2243@hotmail.com

Received 10 September 2015       Revised 21 December 2015       Accepted 11 January 2016

© 2016 Korean Society of Nursing Science

(open-access):

This is an Open Access article distributed under the terms of the Creative Commons Attribution NoDerivs License. (http://creativecommons.org/licenses/by-nd/4.0/) If the original work is properly cited and retained without any modification or reproduction, it can be used and re-distributed in any format and medium.

Abstract

Purpose

The purpose of this study was to construct and test a structural equation model on resilience of breast cancer patients receiving chemotherapy.

Methods

Participants were 204 patients with breast cancer who received chemotherapy treatment. They participated in a structured interview, which included social support, depression, symptom experience, self-efficacy, hope, resilience, and infection prevention behaviors. Data were analyzed using SPSS/WIN 20.0 and AMOS 18.0.

Results

Lower depression (γ=-.33, p=.020) and symptom experience (γ=-.31, p=.012) and higher self-efficacy (γ=.32, p=.005) and hope (γ=.48, p=.016) were influenced by higher social support. Greater resilience was influenced by lower symptom experience (β=-.18, p=.016), higher self-efficacy (β=.49, p=.023), and higher hope (β=.46, p=.012), and these predictors explained 66.7% of variance in resilience. Greater resilience (β=.54, p=.009) made an impact on greater infection prevention behaviors. Resilience mediated the relations of symptom experience (β=-.10 p=.013), self-efficacy (β=.27, p=.006) and hope (β=.25, p=.009) with infection prevention behaviors. These predictors explained 24.9% of variance in infection prevention behaviors.

Conclusion

The findings of the study suggest that breast cancer patientsw ith greater resilience who are receiving chemotherapy participate in increased infection prevention behaviors. Further research should be conducted to seek intervention strategies that improve breast cancer patients' resilience.

Keywords: Psychological resilience, Breast neoplasms, Chemotherapy adjuvant, Infection control, Social support

Figures and Tables

Figure 1

Conceptual framework based on ARM (Adolescent Resilience Model).

jkan-46-327-g001
Figure 2

Path diagram for the hypothetical model.

jkan-46-327-g002
Table 1

Descriptive Statistics of the Measured Variables (N=204)

jkan-46-327-i001
Table 2

Correlation among the Measured Variables (N=204)

jkan-46-327-i002
Table 3

Direct Effect, Indirect Effect and Total Effect in the Model (N=204)

jkan-46-327-i003

*SMC=Squared multiple correlation.

Notes

This manuscript is based on a part of the first author's doctoral dissertation from Ewha Womans University

CONFLICTS OF INTEREST The authors declared no conflict of interest.

References

1. Jung KW, Won YJ, Kong HJ, Oh CM, Cho H, Lee DH, et al. Cancer statistics in Korea: Incidence, mortality, survival., and prevalence in 2012. Cancer Res Treat. 2015; 47(2):127–141. DOI: 10.4143/crt.2015.060.
2. Schelenz S, Giles D, Abdallah S. Epidemiology, management and economic impact of febrile neutropenia in oncology patients receiving routine care at a regional UK cancer centre. Ann Oncol. 2012; 23(7):1889–1893. DOI: 10.1093/annonc/mdr520.
3. Lee YR, Kwon IS. The relationship between infection prevention behaviors and barriers among cancer patients undergoing chemotherapy. J Korean Oncol Nurs. 2007; 7(2):150–161.
4. Waugh CE, Fredrickson BL, Taylor SF. Adapting to life's slings and arrows: Individual differences in resilience when recovering from an anticipated threat. J Res Pers. 2008; 42(4):1031–1046. DOI: 10.1016/j.jrp.2008.02.005.
5. Nizamli F, Anoosheh M, Mohammadi E. Experiences of Syrian women with breast cancer regarding chemotherapy: A qualitative study. Nurs Health Sci. 2011; 13(4):481–487. DOI: 10.1111/j.1442-2018.2011.00644.x.
6. Kwak SY, Byeon YS. Factors influencing resilience of patients with hematologic malignancy. Korean J Adult Nurs. 2013; 25(1):95–104. DOI: 10.7475/kjan.2013.25.1.95.
7. Choi KS, Park JA, Lee J. The effect of symptom experience and resilience on quality of life in patients with colorectal cancers. Asian Oncol Nurs. 2012; 12(1):61–68. DOI: 10.5388/aon.2012.12.1.61.
8. Strauss B, Brix C, Fischer S, Leppert K, Füller J, Roehrig B, et al. The influence of resilience on fatigue in cancer patients undergoing radiation therapy (RT). J Cancer Res Clin Oncol. 2007; 133(8):511–518. DOI: 10.1007/s00432-007-0195-z.
9. Li Y, Cao F, Cao D, Wang Q, Cui N. Predictors of posttraumatic growth among parents of children undergoing inpatient corrective surgery for congenital disease. J Pediatr Surg. 2012; 47(11):2011–2021. DOI: 10.1016/j.jpedsurg.2012.07.005.
10. Lee EK. A study on factors affecting cancer patients. J Korean Acad Soc Nurs Educ. 2007; 13(1):52–58.
11. Ho SM, Ho JW, Bonanno GA, Chu AT, Chan EM. Hopefulness predicts resilience after hereditary colorectal cancer genetic testing: A prospective outcome trajectories study. BMC Cancer. 2010; 10:279. DOI: 10.1186/1471-2407-10-279.
12. Burton NW, Pakenham KI, Brown WJ. Evaluating the effectiveness of psychosocial resilience training for heart health, and the added value of promoting physical activity: A cluster randomized trial of the READY program. BMC Public Health. 2009; 9:427. DOI: 10.1186/1471-2458-9-427.
13. Perfect MM, Jaramillo E. Relations between resiliency, diabetes-related quality of life, and disease markers to school-related outcomes in adolescents with diabetes. Sch Psychol Q. 2012; 27(1):29–40. DOI: 10.1037/a0027984.
14. Lee EK, Ryu EJ, Kim KH. Structual equation modeling on adjustment of cancer patients receiving chemotherapy. J Korean Oncol Nurs. 2011; 11(2):101–107. DOI: 10.5388/jkon.2011.11.2.101.
15. Haase JE. The adolescent resilience model as a guide to interventions. J Pediatr Oncol Nurs. 2004; 21(5):289–299. DOI: 10.1177/1043454204267922.
16. Popoola AO, Adewuya AO. Prevalence and correlates of depressive disorders in outpatients with breast cancer in Lagos, Nigeria. Psychooncology. 2012; 21(6):675–679. DOI: 10.1002/pon.1968.
17. Bellury L, Pett MA, Ellington L, Beck SL, Clark JC, Stein KD. The effect of aging and cancer on the symptom experience and physical function of elderly breast cancer survivors. Cancer. 2012; 118(24):6171–6178. DOI: 10.1002/cncr.27656.
18. DiSipio T, Hayes S, Newman B, Janda M. What determines the health-related quality of life among regional and rural breast cancer survivors? Aust N Z J Public Health. 2009; 33(6):534–539. DOI: 10.1111/j.1753-6405.2009.00449.x.
19. Zhang J, Gao W, Wang P, Wu ZH. Relationships among hope, coping style and social support for breast cancer patients. Chin Med J (Engl). 2010; 123(17):2331–2335.
20. Hoelter JW. The analysis of covariance structures: Goodness-of-fit indices. Sociol Methods Res. 1983; 11(3):325–344. DOI: 10.1177/0049124183011003003.
21. Distefano M, Riccardi S, Capelli G, Costantini B, Petrillo M, Ricci C, et al. Quality of life and psychological distress in locally advanced cervical cancer patients administered pre-operative chemoradiotherapy. Gynecol Oncol. 2008; 111(1):144–150. DOI: 10.1016/j.ygyno.2008.06.034.
22. Zimet GD, Dahlem NW, Zimet SG, Farley GK. The multidimensional scale of perceived social support. J Pers Assess. 1988; 52(1):30–41. DOI: 10.1207/s15327752jpa5201_2.
23. Hahn HM, Yum TH, Shin YW, Kim KH, Yoon DJ, Chung KJ. A standardization study of Beck Depression Inventory in Korea. J Korean Neuropsychiatr Assoc. 1986; 25(3):487–500.
24. Fu MR, McDaniel RW, Rhodes VA. Measuring symptom occurrence and symptom distress: Development of the symptom experience index. J Adv Nurs. 2007; 59(6):623–634. DOI: 10.1111/j.1365-2648.2007.04335.x.
25. Chen G, Gully SM, Eden D. Validation of a new general self-efficacy scale. Organ Res Methods. 2001; 4(1):62–83. DOI: 10.1177/109442810141004.
26. Miller JF, Powers MJ. Development of an instrument to measure hope. Nurs Res. 1988; 37(1):6–10.
27. Campbell-Sills L, Stein MB. Psychometric analysis and refinement of the Connor-Davidson Resilience Scale (CD-RISC): Validation of a 10-item measure of resilience. J Trauma Stress. 2007; 20(6):1019–1028. DOI: 10.1002/jts.20271.
28. Centers for Disease Control and Prevention. Preventing infections in cancer patients [Internet]. Atlanta, GA: Author;2012. cited 2013 October 28. Available from: http://www.cdc.gov/cancer/preventinfections/.
29. Hair JF, Black WC, Babin BJ, Anderson RE. Multivariate data analysis. 7th ed. Upper Saddle River, NJ: Pearson Prentice Hall;2010.
30. Rud OP. Data mining cookbook: Modeling data for marketing, risk, and customer relationship management. New York, NY: John Wiley & Sons, Inc;2001.
TOOLS
Similar articles