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A biopsychosocial model of resilience for breast cancer: A preliminary study in mainland China
European Journal of Oncology Nursing 36 (2018) 95–102
Contents lists available at ScienceDirect
European Journal of Oncology Nursing journal homepage: www.elsevier.com/locate/ejon
A biopsychosocial model of resilience for breast cancer: A preliminary study in mainland China
T
Zeng Jie Yea,∗, Chao Hua Pengb, Hao Wei Zhangc, Mu Zi Lianga,∗∗, Jing Jing Zhaod, Zhe Sune, Guang Yun Huf, Yuan Liang Yug a
Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China School of Nursing, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China c Harbin Medical University-Daqing, Daqing, Heilongjiang Province, 163319, China d Department of Nursing, Chongqing Medical and Pharmaceutical College, Chongqing, Sichuan Province, 401331, China e The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510405, China f Guangdong Second Provincial Traditional Chinese Medicine Hospital, Guangzhou, Guangdong Province, 510095, China g South China University of Technology, Guangzhou, Guangdong Province, 510641, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Breast cancer Oncology Resilience model SEM RM-BC Biopsychosocial adjustment Mainland China
Purpose: Patients diagnosed with breast cancer exhibited critical biopsychosocial functions following surgery or adjuvant treatment; therefore, it is important that they exhibit resilience. A Resilience Model for Breast Cancer (RM-BC) was developed using Chinese breast cancer patients to increase our understanding of how resilience outcomes are positively and negatively affected by protective and risk factors, respectively. Methods: Chinese women with breast cancer completed the questionnaires within 1 week of beginning treatment. Exploratory Structural Equation Modeling was used to evaluate the RM-BC using a sample size of 342 patients. Results: RM-BC suggested satisfactory goodness-of-fit indices and 67 percents of variance for resilience was explained. The Fit Indices for the measurement model were as follows: CFI = 0.909, GFI = 0.911, IFI = 0.897, NFI = 0.922, PNFI = 0.896, PCFI = 0.884, and RMSEA = 0.031. Three risk factors — emotional distress, physical distress, and intrusive thoughts — and four protective factors — self-efficacy, social support, couragerelated strategy, and hope — were recognized. Conclusion: The resilience model allows for a better understanding of Chinese breast cancer patients' resilience integration while undergoing treatment and provides an effective structure for the development of resiliencefocused interventions that are grounded in their experiences. A randomized trial has provided evidences of feasibility in Chinese women with breast cancer and the resilience model could be used as a useful framework for more resilience intervention in the future.
1. Introduction Breast cancer is the leading cause of cancer-related deaths in women and accounts for 10% of new malignancies annually worldwide (Torre et al., 2015). In Mainland China, about 210,000 women with breast cancer will be confirmed in 2018 and China will have 2.5 million breast cancer survivors by 2021 (Zhang et al., 2012). In the transition period, patients suffered a lot from biopsychosocial burdens induced by breast cancer and were required to learn self-care skills to combat the disease (Stanton et al., 2005). Despite the substantial amount of stress, the patients' psychosocial and physical reactions to this traumatic event
∗
vary depending on multiple factors (Allen et al., 2009; Andersen et al., 2008); and some protective factors can help patients adjusts themselves to this traumatic event, for example, by increasing their resilience levels, which is typically defined as the capacity to “bounce back” (or reduced negative responses) after encountering a traumatic event (Haglund et al., 2007). Whether resilience should be defined as a dynamic “state” variable or a stable “trait” variable is debated (Bonanno, 2012; Prince-Embury, 2013). Generally, it is suggested that anyone has a different baseline of resilience but can be enhanced through interventions. Resilience has been found in several western studies to be indicators of positive biopsychosocial functions and provides
Corresponding author. Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. Corresponding author. Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. E-mail addresses: [email protected] (Z.J. Ye), [email protected] (M.Z. Liang).
∗∗
https://doi.org/10.1016/j.ejon.2018.08.001 Received 16 October 2017; Received in revised form 1 August 2018; Accepted 3 August 2018 1462-3889/ © 2018 Elsevier Ltd. All rights reserved.
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researchers with insights about how breast cancer survivors can resist negative biopsychosocial responses and achieve optimal transition during the treatment and subsequent survivorship[Allen et al., 2009; Andersen et al., 2008; Haglund et al., 2007; Luthar and Cicchetti, 2000].
interacted and were added as outcome variables. This study was designed to examine the influencing factors of resilience among Chinese patients with breast cancer and to test the relationship of these factors in the RM-BC model. The information about risk and protective factors of RM-BC was detailed below.
2. Literature review
2.2.1. Emotional distress (anxiety, depression and illness uncertainty, risk factors) Anxiety and depression have been shown to have associations with elevated levels of stress and poor positive outcomes following a cancer diagnosis (Haglund et al., 2007; Steinhardt and Dolbier, 2008). Illness uncertainty is one of the most important psychological stressors when people are affected by life-threatening illnesses and patients with breast cancer experience higher levels of illness uncertainty compared with other cancer patients (Miller, 2012). They urgently want to know what they will suffer from the treatment and whether they will survive from the cancer disease (Miller, 2012). Anxiety, depression and illness uncertainty were three significant indicators to lower levels of resilience among patients with breast cancer in previous study (Ye et al., 2016a,b,c, 2017d,e).
2.1. A model of resilience Resilience is defined as the ability to display stable or optimal physical and psychosocial function when faced with significant adversity or traumatic events, such as a cancer diagnosis (Rutter, 1985). Resilience is characterized based on the protective factors (e.g., social resources, etc.) and risk factors (e.g., emotional distress, etc.) according to Kumpfer's resilience theory(Appendix, Fig. S1, Kumpfer, 1999). Positive factors and risk factors interact according to the empirical research, and protective resources are largely decreased if the subjects are exposed to long-term risk factors (Kumpfer, 1999; Craig, 2012). Thus, enhancing the protective factors and decreasing the risk factors of resilience could be an important intervention in breast cancer rehabilitation. Although the individualized process of adjustment to traumatic event was specifically described in the Kumpfer's framework, breast cancer has not been specifically described in the framework (Craig, 2012; Ye et al., 2017). All this suggests that a biopsychosocial resilience model for breast cancer (RM-BC) based on Kumpfer's theory can facilitate understandability of the adjustment process in breast cancer survivors.
2.2.2. Physical distress (fatigue, pain, nausea, risk factor) More than 60% of patients with breast cancer were reported to have different levels of fatigue, which affects their health-related quality of life (Loprinzi et al., 2008). Pain is another common burdensome symptom; even 9.4 years following the diagnosis, 46% breast cancer survivors reported at least some pain (Jensen et al., 2010). Nausea and vomiting is common during the chemotherapy treatment for breast cancer and cause elevated levels both of physical and psychological distress, resulting in a lower level of QOL (Yates et al., 2005; Allen et al., 2009). Fatigue, pain, nausea will affect patients' resilience by increasing the level of emotional distress (i.e., depression and anxiety), which has been confirmed in patients with different cancer types (Stanton et al., 2005; Allen et al., 2009; Ye et al., 2016a,b,c, 2017d,e; Matsuoka et al., 2002).
2.2. Preliminary hypothesis for RM-BC In this model, we proposed that four strength-based protective variables provide buffers for patients' resilience levels and decrease the effect of all types of risk factors on resilience. Patients who experience severe symptoms of physical or psychological distress (risk factors) and have low levels of external or internal strength (protective factors) will display lower levels of resilience, which is presented in Fig. 1. Four strength-based protective variables (social support, courage-related strategy, hope for the future and self-efficacy) are believed to directly contribute to resilience and, as potential mediators, will serve as buffers to resilience against the effect of three risk factors (emotional distress, physical distress, and intrusive thoughts). Resilience and transcendence
2.2.3. Social support (protective factor) A strong support system can help patients overcome difficulties in challenging situations and is a robust buffering factor between stressors and psychosocial symptoms, which has been proven in previous studies (Allen et al., 2009; Yates et al., 2005). Social support is also an important resource to resilience integration and was found to be positively
Fig. 1. Hypothesized model of resilience in Chinese breast cancer survivors (RM-BC). 96
The degree of anxiety, depression and illness uncertainty that is perceived by the patients during treatment
The degree of pain, nausea and fatigue that is perceived by the patients during treatment The degree to which patients have been distressed or bothered by intrusive thoughts during the treatment for cancer The degree to which the patients experience sufficient emotional and instrumental support throughout the cancer treatment. The degree to which the patients experience a motivated state to reach their desired goals The degree to which the patients use direct, optimistic, and supportive coping strategies to manage the cancer experience The degree to which the patients' beliefs about confidence in their personal ability to cope with a variety of problems in the process of treatment. The ability of identifying resources to resist negative psychological responses when encountering a potentially traumatic circumstance The ability of developing strength to gain a sense of selftranscendence
Emotional Distress (Risk)
Physical Distress (Risk)
97
Transcendence (outcome)
Resilience (outcome)
Self-efficacy (Protective)
Hope for the Future (Protective) Courage-related strategy (Protective)
Social Support (Protective)
Intrusive Thoughts (Risk)
Definitions
Latent Variables
Chinese version of Self-transcendence Scale (CSTS, Zhang et al., 2014)
15
10
10-item Connor-Davidson Resilience Scale (CDRISC-10, Ye et al., 2017)
One dimension
One dimension.
One dimension
Direct, optimistic, and supportive dimensions
24
10
Will level and Ways level
One dimension
88
3
8
Pain level, nausea level and fatigue level One dimension
Anxiety level, depression level and illness uncertainty level
19
6
Dimensions
No. of Items
The Chinese version of General Self-efficacy Scale (GSE,Wang et al., 2001)
The Chinese version of the 8-item Hope Scale (HS, Wang, 2010) The Jalowiec Coping Scale- Revised (JCS-R, Wang, 1999)
Social Support Scale by Seeman & Berkman (SSS, Ye et al., 2010)
Chinese Hospital Anxiety and Depression Scale (HADS, Leung et al., 1993), 5-item Illness Uncertainty Scale for Patients (IUSP, Ye et al., 2014) QLQ-C30 core questionnaire of EORTC (Jiang et al., 2005) The Revised Impact of Event Scale (IES-R,Ye and Liang, 2013)
Instruments
Table 1 Summary of psychometric properties of measurements derived from the resilience model for breast cancer (RM-BC).
4-point Likert scale
5-point Likert scale
4-point Likert scale
4-point Likert scale
4-point Likert scale
4-point Likert scale
5-point Likert scale
0.92
0.88
0.81
0.79
0.87
0.92
0.83
0.79
15–60
0–40
10–40
0–72
8–32
3–12
0–32
0–100
5–67
0.86 for HADS; 0.89 for IUSP 4-point Likert for HADS, 5-point Likert for IUSP 4-point Likert scale
Score Range
α
No. of Points on the Likert Scale
Z.J. Ye et al.
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3.2. Instruments for RM-BC
linked to resilience and quality of life in previous study (Ye et al., 2016a,b,c, 2017d,e). However, we should be cautious because such effects only occur when the recipient regards the support provided as adequate and helpful (Rutter, 1985).
The psychometrics of scales used in this study are presented in Table 1. Each scale was validated in previous researches and showed good internal reliability and cronbach’ s coefficients in this study were also included.
2.2.4. Intrusive thoughts (risk factor) Intrusive thoughts are unwanted and common during the cancer treatment and mainly include recurring images of painful cancer treatment or fears of recurrence according to cancer survivors' reports (Matsuoka et al., 2002). In addition, breast cancer survivors are reported to have higher levels of intrusive thoughts relative to other cancer patient groups(Matsuoka et al., 2002). Intrusive thoughts may be particularly relevant for some physical symptoms because these disruptive thoughts can disturb sleep and increase sensitivity to physical sensations. Intrusive thoughts are chronic risk factors and are negatively correlated to resilience (Dooley et al., 2017; Ye et al., 2016).
3.3. Data analysis SEM (Structural Equation Modeling) was performed using the AMOS 21.0. The covariance matrix of relevant variables was evaluated by maximum likelihood estimation. Research with a sample of more than ten times the number of variables included in a SEM is recommended, and thus we had a sufficient sample size to conduct the SEM (Bentler, 1990). When all parameters appeared in order and no special problems were reported during the optimization process, the X2 test and some fit indexes such as Comparative Fit Index (CFI), Goodness Fit Index (GFI), Parsimony Normed Fit Index (PNFI), Root-Mean-Square Error of Approximation (RMSEA) were evaluated (Hu and Bentler, 1990).
2.2.5. Self-efficacy (protective factor) Self-efficacy is defined as one's belief and confidence to carry out a task and is a significant cognitive mediator of action (Bandura, 1997). It is believed that a lower level of self-efficacy is associated with higher levels of helplessness and depression (Williams and Schreier, 2004). In the treatment of breast cancer, patients suffered a lot from biopsychosocial burdens induced by breast cancer and were required to learn selfcare skills to combat the disease (Wu et al., 2016). Also, higher levels of self-efficacy was found to be significantly linked to resilience (Wu et al., 2016; Ye et al., 2016a,b,c, 2017d,e).
4. Results 4.1. Sample characteristics In total, 420 patients were recruited and 363 completed the booklet of scales. Subjects were not included due to lack of time or lack of willingness to participate. Due to missing or incomplete scales, 21 patients were also excluded and the response rate was 81.4%. The final data analyses were based on the remaining 342 patients. Patients with non-metastatic breast cancer (stage 0-II) was the majority in this study, constituting 81.6% (n = 279) of the whole participants. Other demographics and disease-related information are presented in Table 2.
2.2.6. Courage-related strategies (protective factor) Courage-related coping strategies is defined that patients use direct, optimistic, and supportive coping strategies to manage the cancer experience by addressing the problem and regulating the emotions (Hjemdal et al., 2006). Courage-related strategies are strongly associated with self-efficacy and represent an important indicator of resilience(Folkman and Moskowitz, 2004; Ye et al., 2016; Chen and Miller, 2012). It is believed that enduring suffering from cancer using couragerelated strategies and maintaining optimism for the future can allow for successful adjustment and resilience integration (Updegraff et al., 2008).
4.2. Descriptive statistics on measurements for RM-BC Patients showed varied biopsychosocial functions as depicted in Table 3. Bivariate correlations among the major variables were conducted first in order to evaluate the strength of the correlations and a correlation matrix is presented in Table 4. The unstandardized and standardized estimates, critical ratio, standard errors and significance for the construct in the final model are presented in Table 5. The Fit Indices for the measurement model were as follows: CFI = 0.909, GFI = 0.911, IFI = 0.897, NFI = 0.922, PNFI = 0.896, PCFI = 0.884, and RMSEA = 0.031. However, the pathway from social support to resilience was removed due to the low load on its construct (P > .05). In the final structural model depicted in Fig. 2, sixty-seven percent of the variance in resilience and fifty-four percent of the variance in transcendence were directly accounted for by 4 protective variables (buffering effect). For these buffers, forty-eight percent of the variance in courage-related strategies is directly accounted for by intrusive thoughts, social support, and self-efficacy; courage-related strategy is strongly associated with resilience (β = 0.44, P < .001) and transcendence (β = 0.38, P < .001). Fifty-one percent of the variance in Self-efficacy is directly accounted for by emotional distress, physical distress, intrusive thoughts and social support and is associated with resilience (β = 0.57, P < .001) and transcendence (β = 0.37, P < .001). Fifty-three percent of the variance in Hope for the future is directly accounted for by emotional distress, physical distress, self-efficacy and courage-related strategy and is associated with resilience (β = 0.39, P < .001) and transcendence (β = 0.46, P < .001). For intrusive thoughts, as an intermediate variable, forty-nine percent of the variance is directly accounted for by physical distress, social support, and emotional distress, and is associated with courage-related strategy (β = −0.47, P < .001) and self-efficacy (β = −0.33, P < .001). Physical distress, social support, and emotional distress
2.2.7. Hope for the future (protective factor) Maintaining hope for the future gives patients strong feelings of security and benevolence in the world when confronted by life-threatening disease and has been proven to have associations with better clinical outcomes in the previous study (Roy et al., 2010). People with higher levels of hope and having a greater sense of purpose are found to indicate a decreased risk of mortality of all types (Boyle et al., 2009). Also, a higher level of hope is proved to indicate a higher level of resilience (Wu et al., 2016; Ye et al., 2016a,b,c, 2017d,e). 3. Methods 3.1. Participants Patients were recruited from 4 hospitals in Guangdong Province from September 2013 to December 2015. The patients were hospitalized for surgery or adjuvant treatments. Patients should meet the inclusion criteria: (1) Female; (2) diagnosed with breast cancer (0-IV); (3) 18–65 years; (4)fluent communications in Mandarin or Cantonese. Patients were excluded if they met the exclusion criteria: (1) male, (2) insufficient knowledge to complete the booklet of scales, and (3) unwilling to be enrolled into the program. On average, it took patients about 40–55 min to complete the booklet of scales. This study was approved by the ethics committees of the hospitals(No: 2016KYTD08) and written or oral informed consent was acquired before the survey. 98
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Table 2 Demographics and clinical information of the participants. Demographics
No.
Age < =30 > 30 and ≤ 45 > 45 Race Han Other Education High school or lower Undergraduate or higher Income (monthly) < =¥5000 > ¥5000 and < =¥10,000 > ¥10,000 Relationship Single Married Divorced or widowed Religious affiliation Yes No Employment Part/full time Unemployed Insurance Business insurance Rural cooperative insurance none Residence Rural City
%
64 133 145
18.7 38.9 42.4
327 15
95.6 4.4
184 158
53.8 46.2
154 126
45.1 36.8
62
18.1
24 268 50
7.0 78.4 14.6
35 307
10.2 89.8
277 65
81.0 19.0
31 294
9.1 86.0
17
4.9
116 226
33.9 66.1
Table 4 Intercorrelation matrix of the study variables (N = 342).
Clinical Information
No.
Tumor size (mm) < =10 73 > 10 and ≤ 30 205 > 30 64 First diagnosis Yes 237 No 105 Lymph node status Positive 212 Negative 130 Duration of treatment (year) < =1 167 > 1 and ≤ 5 130 >5 Degree of malignancy 0 I II III IV Receptor status Estrogen positive Estrogen native Treatment Mastectomy only Lumpectomy only Mastectomy and chemotherapy Lumpectomy and chemotherapy Had radiation Yes No
%
69.3 30.7 62.0 38.0 b
48.8 38.0 13.2
57 123 99 38 25
16.7 36.0 28.9 11.1 7.3
238 104
69.6 30.4
50 146 58
14.6 42.7 17.0
88
25.7
229 113
66.9 33.1
Subscale Mean
SD
Emotional Distress (Risk) Anxiety 7.51 3.45 2–17 Depression 9.68 2.87 5–19 Illness Uncertainty 14.08 5.89 9–24 Physical Distress (Risk) Pain 62.34 17.81 0–100 Fatigue 51.27 15.38 10–100 Nausea 46.37 19.23 0–100 Intrusive Thoughts 9.23 5.47 4–27 (Risk) Social Support 8.86 2.44 4–12 (Protective) Hope for the Future 19.04 7.68 8–27 (Protective) Courage-related strategies (Protective) Direct Coping 14.37 6.86 5–26 Optimistic Coping 17.22 8.84 6–25 Supportive Coping 8.65 4.01 2–14 Self-efficacy 26.02 9.98 12–39 (Protective) Resilience 18.96 7.89 7–38 (outcome) Transcendence 29.76 14.35 17–49 (outcome)
Scale range
Score range
Item range
0–21 0–21 5–25
0–3 0–3 1–5
0–3 0–3 1–5
0–100 0–100 0–100 0–32
1–4 1–4 1–4 0–4
1–4 1–4 1–4 0–4
3–12
0–4
0–4
8–32
1–4
1–4
0–30 0–27 0–15 10–40
0–3 0–3 0–3 1–4
0–3 0–3 0–3 1–4
0–40
0–4
0–4
15–60
1–5
1–5
–
.52 –
3 a
4 a
.37 .41a –
-.13 -.18b .09 –
5
6 a
-.28 -.25b -.37a .11 –
7 a
-.41 -.38a -.58a .32a .39a –
8 a
9 a
-.44 -.36a -.39a .42a .31a .51a
-.61 -.53a -.43a .25b .46a .67a
-.38a -.32a -.19b .49a .34a .55a
–
.72a –
.46a .42a –
p < .05,a p < .01.
A biopsychosocial model of resilience (RM-BC) was proposed and tested among Chinese women with breast cancer. Four protective variables — social support, courage-related strategy, self-efficacy, and hope for the future — directly and significantly accounted for levels of resilience and transcendence, while three risk variables affected resilience and transcendence in an indirect way by affecting these protective variables. These resilience-related themes were confirmed in our mentees from BRBC program (Be Resilient to Breast Cancer), which is designed based on RM-BC (Ye et al., 2016c, 2017e). Just as one stated, “Since the diagnosis and surgery, I always felt inferior to others …. But now, I find that others (mentors) like me could live so well … So can I.” Thus, buffering effect of social support against disease-related stigma and intrusive thoughts could be primarily confirmed based on these qualitative data. Another mentee said, “The program taught me much than I expected. Now I can recognize and manage my emotions, cherish my life with my husband and child, and the meaning of life is different.” Therefore, the importance of patients' self-efficacy through knowledge learning (taught by mentors and teachers from BRBC) and hope were also emphasized to help patients normalize the experience of diagnosis and treatment of breast cancer and finally enhance their resilience levels. To our surprise, the pathway from social support to resilience was removed according to statistical standards, though the pathway from social support to transcendence was retained, which is not consistent with previous studies (McCabe and O’Connor, 2011). One explanation may be the different social support instruments used among different researches, with this study assessing the sufficiency of the received emotional and instrumental support compared to studies conducted by a generic social support instrument (Richardon, 2002). In addition, due to the complex nature of cancer and the following treatment, support from the medical staff will be very important to the patients, which should warrant more studies in the future to evaluate the differential contribution of social support provided by the medical staff or families and friends. In total, RM-BC provides valuable information about influencing factors of resilience in patients with breast cancer and lays a good foundation for resilience instruments development(i.e., Resilience Scale Specific to Cancer, RS-SC) and resilience-related intervention in the future (Ye et al., 2015; Ye et al., 2016a,b,c, 2017a,b,c,d,e, 2018a,b). However, most variables from RM-BC are measured by psychosocial instruments and will be affected by cultural background. Thus, we suggest that future studies incorporate more clinician-based ratings of variables such as allostatic load index (ALI) into the resilience model (Qiu et al., 2017; Kinnunen et al., 2005), which has been proved to have strong associations with resilience, quality of life and survival among patients with breast cancer (Ye et al., 2016c, 2017e, 2018a,b), and can also improve the generality of RM-BC among patients with different cultures.
Item Score range
1. 2. 3. 4. 5. 6.
2
5. Discussion
Table 3 Descriptive statistics for the outcome measures (N = 342). Variables
1
Emotional Distress Physical Distress Intrusive Thoughts Social Support Hope for the Future Courage-related strategies 7. Self-efficacy 8. Resilience 9. Transcendence
21.3 59.9 18.8
45
Variables
were three independent indicators in the RM-BC and increased or decreased the levels of resilience and transcendence by affecting four intermediate variables (courage-related strategy, intrusive thoughts, self-efficacy, and hope for the future). 99
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Table 5 Maximum likelihood estimates of the respecified model. Pathway Emotional Distress Emotional Distress Emotional Distress Physical Distress Physical Distress Physical Distress Intrusive Thoughts Intrusive Thoughts Self-efficacy Self-efficacy Self-efficacy Self-efficacy Hope for the Future Hope for the Future Social Support Social Support Social Support Social Support Courage-related strategy Courage-related strategy Courage-related strategy
→Intrusive Thoughts →Self-efficacy →Hope for the Future →Intrusive Thoughts →Self-efficacy →Hope for the Future →Self-efficacy →Courage-related strategy →Courage-related strategy →Transcendence →Hope for the Future →Resilience →Transcendence →Resilience →Intrusive Thoughts →Self-efficacy →Courage-related strategy →Transcendence →Hope for the Future →Transcendence →Resilience
Non-standardized Coefficients
Standardized Coefficients
Standard Errors
Critical Ratio
0.41 −0.47 −0.36 0.62 −0.46 −0.51 −0.62 −0.39 0.71 0.54 0.43 0.45 0.24 0.35 −0.46 0.16 0.09 0.12 0.59 0.46 0.42
0.52 −0.36 −0.34 0.43 −0.38 −0.25 −0.33 −0.47 0.44 0.37 0.38 0.57 0.46 0.39 −0.19 0.35 0.26 0.23 0.45 0.38 0.44
0.23 0.11 0.16 0.07 0.09 0.39 0.04 0.13 0.09 0.20 0.05 0.06 0.17 0.44 0.27 0.32 0.04 0.06 0.18 0.22 0.13
7.66 −5.47 −4.72 6.86 −4.74 −1.96 −5.02 −7.25 6.41 4.51 3.88 8.34 6.48 5.67 −1.74 5.22 3.11 2.03 7.23 5.33 7.62
5.1. Implications for clinical practice
5.2. Limitations
Based on RM-BC, BRBC could significantly improve the positive factors (e.g. social support, hope, etc) and reduce the illness-related factors (e.g. anxiety, depression, etc) of resilience during the cancer treatment though it could not prolong the lifespan of patients with metastatic breast cancer at 5-year follow-up (Ye et al., 2016c, 2017e).This successful program provided evidences of the feasibility of RM-BC in Chinese women with breast cancer and could be used as a useful framework for more resilience-specific intervention in the future. Also, RM-BC might be feasible in the western countries because the proposed variables are all developed there and more cross-cultural research should be warranted. Although this article has provided preliminary findings on the development of RM-BC in Chinese patients with breast cancer, further qualitative and quantitative work is needed to verify the relationships between resilience and its influencing factors and better determine methods of promoting resilience in the Chinese patients with breast cancer.
This article also has some limitations. First, no causal relationships could be found because of the cross-sectional design, and more longitudinal studies examining the trajectories of resilience are warranted due to the dynamic nature of resilience across time. Second, we should be cautious that 57 participants declined to participate in this study for various reasons, and it may lead to biased results because patients with lower levels of biopsychosocial burdens were more able to participate in the survey. Third, this study does not investigate psychosocial variables such as defensive coping strategies, family environment, personalities, etc., due to the limitation of excessive scales. Future studies can focus on these dimensions to improve the fitness of the resilience model.
6. Conclusion In summary, this article provides empirical and clinical evidence for Fig. 2. The final framework of the resilience model for patients with breast cancer (RM-BC). Emotional Distress, Physical Distress and Social Support are three independent variables affecting the outcome variables of Transcendence and Resilience by adjusting four moderating variables of Self-efficacy, Courage-related strategy, Intrusive Thoughts and Hope for the Future.
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the nature and process of resilience following a breast cancer diagnosis and, to our knowledge, is the first study to evaluate resilience and its influencing factors using SEM. The feasibility of RM-BC in Chinese patients with breast cancer has been confirmed but more researches about its application in patients with different cultures should be warranted.
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Effect of a multidiscipline mentor-based program, Be Resilient to Breast Cancer (BRBC), on female breast cancer survivors in mainland China-A randomized, controlled, theoretically-derived intervention trial. Breast Canc. Res. Treat. 158, 509–522. Ye, Z.J., Qiu, H.Z., Li, P.F., Chen, P., Liang, M.Z., Liu, M.L., Yu, Y.L., Wang, S.N., Quan, X.M., 2017a. Validation and application of the Chinese version of the 10-item Connor-Davidson Resilience Scale (CD-RISC-10) among parents of children with cancer diagnosis. Eur. J. Oncol. Nurs. 27, 36–44. Ye, Z.J., Liu, M.L., Zhang, Z., Liao, K.L., Peng, C.F., Huang, H., Yu, Y.L., Qiu, H.Z., 2017b. Psychometric properties of the Chinese version of the Parent Perception of Uncertainty Scale (PPUS) among parents of children with cancer diagnosis. Int. J. Nurs. Sci. 4, 278–284. Ye, Z.J., Qiu, H.Z., Li, P.F., Liang, M.Z., Wang, S.N., Quan, X.M., 2017c. Resilience model for parents of children with cancer in mainland China-An exploratory study. Eur. J. 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Funding This research was funded by grants from Research Fund for Talented Scholars of Guangzhou University of Chinese Medicine (A1AFD018) and Innovative Project of Guangzhou University of Chinese Medicine (2016KYTD08). Conflicts of interest The authors have no conflicts of interest to disclose. Acknowledgment The authors gratefully appreciated the assistance and data provided by the patients participating in this study. Appendix A. Supplementary data Supplementary data related to this article can be found at https:// doi.org/10.1016/j.ejon.2018.08.001. References Allen, J.D., Savadatti, S., Levy, A.G., 2009. The transition from breast cancer ‘patient’ to ‘survivor’. Psycho Oncol. 18, 71–78. Andersen, B.L., Yang, H.C., Farrar, W.B., 2008. Psychologic intervention improves survival for breast cancer patients. Cancer 113, 3450–3458. Bandura, A., 1997. Self-efficacy: the Exercise of Control. WH, Freeman, New York, NY. Bentler, P.M., 1990. Comparative fit indexes in structural models. Psychol. Bull. 107, 238–246. Bonanno, G.A., 2012. Uses and abuses of the resilience construct: loss, trauma, and health-related adversities. Soc. Sci. Med. 74, 753–756. Boyle, P.A., Barnes, L.L., Buchman, A.S., Bennett, D.A., 2009. Purpose in life is associated with mortality among community-dwelling older persons. Psychosom. Med. 71, 574–579. Chen, E., Miller, G.E., 2012. “Shift-and-persist” strategies: why being low in socioeconomic status isn't always bad for health. Perspect. Psychol. Sci. 7, 135–158. Craig, A., 2012. Resilience in people with physical disabilities. In: Kennedy, P. (Ed.), Oxford Handbook of Rehabilitation Psychology. Oxford University Press, Oxford. Dooley, L.N., Slavich, G.M., Moreno, P.I., Bower, J.E., 2017. Strength through adversity: moderate lifetime stress exposure is associated with psychological resilience in breast cancer survivors. Stress Health. https://doi.org/10.1002/smi.2739. Folkman, S., Moskowitz, J.T., 2004. Coping: pitfalls and promise. Annu. Rev. Psychol. 55, 745–774. Haglund, M.E.M., Nestadt, P.S., Cooper, N.S., Southwick, S.M., Charney, D.S., 2007. Psychobiological mechanisms of resilience: relevance to prevention and treatment of stress-related psychopathology. Dev. Psychopathol. 19, 889–920. Hjemdal, O., Friborg, O., Stiles, T.C., Rosenvinge, J.H., Martinussen, M., 2006. Resilience predicting psychiatric symptoms: a prospective study of protective factors and their role in adjustment to stressful life events. Clin. Psychol. Psychother. 13, 194–201. Hu, L.T., Bentler, P.M., 1990. Cutoff criteria for fit indexes in covariance structure analysis: conventional criteria versus new alternatives. Struct. Equ. Model. 6, 1–55. Jensen, M.P., Chang, H.Y., Lai, Y.H., Syrjala, K.L., Fann, J.R., Gralow, J.R., 2010. Pain in long-term breast cancer survivors: frequency, severity, and impact. Pain Med. 11, 1099–1106. Jiang, B.F., Liu, X.C., Cui, Y.C., Xu, T., Xu, M., Wang, J.L., Du, J., 2005. Validation of Chinese version of EORTC QLQ-C30 in patients with cancer. Chin. J. Clin. Psychol. 1, 31–36. Kinnunen, M.L., Kokkonen, M., Kaprio, J., Pulkkinen, L., 2005. The associations of emotion regulation and dysregulation with the metabolic syndrome factor. J. Psychosom. Res. 58, 513–521. Kumpfer, K.L., 1999. Factors and Processes Contributing to Resilience: the Resilience Framework. Kluwer Academic/Plenum Publishers, New York. Leung, C.M., Ho, S., Kan, C.S., 1993. Evaluation of the Chinese version of the hospital anxiety and depression scale. A cross-cultural perspective. Int. J. Psychosom. 40, 29–34. Loprinzi, C.L., Wolf, S.L., Barton, D.L., Laack, N.N.I., 2008. Symptom management in premenopausal patients with breast cancer. Lancet Oncol. 9, 993–1001. Luthar, S.S., Cicchetti, D., 2000. The construct of resilience: implications for interventions
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cancer: an item response theory analysis. Qual. Life Res. 27, 1635–1645. Zhang, M.L., Huang, Z.Z., Zheng, Y., 2012. The Chinese breast cancer incidence and mortality rates in 2008 and predictions for the future. Chin. J. Epidemiol. 33, 1049–1051. Zhang, J., Sun, J.P., Zhang, L., Wu, X.J., Chen, Y., Tian, R., 2014. Validation of Chinese version of Self-transcendence Scale in old patients with cancer. Chin J Gerontol 34, 1910–1911.
Zhao, J.J., 2017e. Effect of a mentor-based, supportive-expressive program, Be Resilient to Breast Cancer, on survival in metastatic breast cancer: a randomised, controlled intervention trial. Br. J. Canc. 117, 1486–1494. Ye, Z.J., Liang, M.Z., Li, P.F., Sun, Z., Chen, P., Hu, G.Y., Yu, Y.L., Wang, S.N., Qiu, H.Z., 2018a. New resilience instrument for patients with cancer. Qual. Life Res. 27, 355–365. Ye, Z.J., Liang, M.Z., Zhang, H.W., Li, P.F., Ouyang, X.R., Yu, Y.L., Liu, M.L., Qiu, H.Z., 2018b. Psychometric properties of the Chinese version of resilience scale specific to
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Contents lists available at ScienceDirect
European Journal of Oncology Nursing journal homepage: www.elsevier.com/locate/ejon
A biopsychosocial model of resilience for breast cancer: A preliminary study in mainland China
T
Zeng Jie Yea,∗, Chao Hua Pengb, Hao Wei Zhangc, Mu Zi Lianga,∗∗, Jing Jing Zhaod, Zhe Sune, Guang Yun Huf, Yuan Liang Yug a
Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China School of Nursing, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China c Harbin Medical University-Daqing, Daqing, Heilongjiang Province, 163319, China d Department of Nursing, Chongqing Medical and Pharmaceutical College, Chongqing, Sichuan Province, 401331, China e The First Affiliated Hospital, Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510405, China f Guangdong Second Provincial Traditional Chinese Medicine Hospital, Guangzhou, Guangdong Province, 510095, China g South China University of Technology, Guangzhou, Guangdong Province, 510641, China b
A R T I C LE I N FO
A B S T R A C T
Keywords: Breast cancer Oncology Resilience model SEM RM-BC Biopsychosocial adjustment Mainland China
Purpose: Patients diagnosed with breast cancer exhibited critical biopsychosocial functions following surgery or adjuvant treatment; therefore, it is important that they exhibit resilience. A Resilience Model for Breast Cancer (RM-BC) was developed using Chinese breast cancer patients to increase our understanding of how resilience outcomes are positively and negatively affected by protective and risk factors, respectively. Methods: Chinese women with breast cancer completed the questionnaires within 1 week of beginning treatment. Exploratory Structural Equation Modeling was used to evaluate the RM-BC using a sample size of 342 patients. Results: RM-BC suggested satisfactory goodness-of-fit indices and 67 percents of variance for resilience was explained. The Fit Indices for the measurement model were as follows: CFI = 0.909, GFI = 0.911, IFI = 0.897, NFI = 0.922, PNFI = 0.896, PCFI = 0.884, and RMSEA = 0.031. Three risk factors — emotional distress, physical distress, and intrusive thoughts — and four protective factors — self-efficacy, social support, couragerelated strategy, and hope — were recognized. Conclusion: The resilience model allows for a better understanding of Chinese breast cancer patients' resilience integration while undergoing treatment and provides an effective structure for the development of resiliencefocused interventions that are grounded in their experiences. A randomized trial has provided evidences of feasibility in Chinese women with breast cancer and the resilience model could be used as a useful framework for more resilience intervention in the future.
1. Introduction Breast cancer is the leading cause of cancer-related deaths in women and accounts for 10% of new malignancies annually worldwide (Torre et al., 2015). In Mainland China, about 210,000 women with breast cancer will be confirmed in 2018 and China will have 2.5 million breast cancer survivors by 2021 (Zhang et al., 2012). In the transition period, patients suffered a lot from biopsychosocial burdens induced by breast cancer and were required to learn self-care skills to combat the disease (Stanton et al., 2005). Despite the substantial amount of stress, the patients' psychosocial and physical reactions to this traumatic event
∗
vary depending on multiple factors (Allen et al., 2009; Andersen et al., 2008); and some protective factors can help patients adjusts themselves to this traumatic event, for example, by increasing their resilience levels, which is typically defined as the capacity to “bounce back” (or reduced negative responses) after encountering a traumatic event (Haglund et al., 2007). Whether resilience should be defined as a dynamic “state” variable or a stable “trait” variable is debated (Bonanno, 2012; Prince-Embury, 2013). Generally, it is suggested that anyone has a different baseline of resilience but can be enhanced through interventions. Resilience has been found in several western studies to be indicators of positive biopsychosocial functions and provides
Corresponding author. Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. Corresponding author. Guangzhou University of Chinese Medicine, Guangzhou, Guangdong Province, 510006, China. E-mail addresses: [email protected] (Z.J. Ye), [email protected] (M.Z. Liang).
∗∗
https://doi.org/10.1016/j.ejon.2018.08.001 Received 16 October 2017; Received in revised form 1 August 2018; Accepted 3 August 2018 1462-3889/ © 2018 Elsevier Ltd. All rights reserved.
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researchers with insights about how breast cancer survivors can resist negative biopsychosocial responses and achieve optimal transition during the treatment and subsequent survivorship[Allen et al., 2009; Andersen et al., 2008; Haglund et al., 2007; Luthar and Cicchetti, 2000].
interacted and were added as outcome variables. This study was designed to examine the influencing factors of resilience among Chinese patients with breast cancer and to test the relationship of these factors in the RM-BC model. The information about risk and protective factors of RM-BC was detailed below.
2. Literature review
2.2.1. Emotional distress (anxiety, depression and illness uncertainty, risk factors) Anxiety and depression have been shown to have associations with elevated levels of stress and poor positive outcomes following a cancer diagnosis (Haglund et al., 2007; Steinhardt and Dolbier, 2008). Illness uncertainty is one of the most important psychological stressors when people are affected by life-threatening illnesses and patients with breast cancer experience higher levels of illness uncertainty compared with other cancer patients (Miller, 2012). They urgently want to know what they will suffer from the treatment and whether they will survive from the cancer disease (Miller, 2012). Anxiety, depression and illness uncertainty were three significant indicators to lower levels of resilience among patients with breast cancer in previous study (Ye et al., 2016a,b,c, 2017d,e).
2.1. A model of resilience Resilience is defined as the ability to display stable or optimal physical and psychosocial function when faced with significant adversity or traumatic events, such as a cancer diagnosis (Rutter, 1985). Resilience is characterized based on the protective factors (e.g., social resources, etc.) and risk factors (e.g., emotional distress, etc.) according to Kumpfer's resilience theory(Appendix, Fig. S1, Kumpfer, 1999). Positive factors and risk factors interact according to the empirical research, and protective resources are largely decreased if the subjects are exposed to long-term risk factors (Kumpfer, 1999; Craig, 2012). Thus, enhancing the protective factors and decreasing the risk factors of resilience could be an important intervention in breast cancer rehabilitation. Although the individualized process of adjustment to traumatic event was specifically described in the Kumpfer's framework, breast cancer has not been specifically described in the framework (Craig, 2012; Ye et al., 2017). All this suggests that a biopsychosocial resilience model for breast cancer (RM-BC) based on Kumpfer's theory can facilitate understandability of the adjustment process in breast cancer survivors.
2.2.2. Physical distress (fatigue, pain, nausea, risk factor) More than 60% of patients with breast cancer were reported to have different levels of fatigue, which affects their health-related quality of life (Loprinzi et al., 2008). Pain is another common burdensome symptom; even 9.4 years following the diagnosis, 46% breast cancer survivors reported at least some pain (Jensen et al., 2010). Nausea and vomiting is common during the chemotherapy treatment for breast cancer and cause elevated levels both of physical and psychological distress, resulting in a lower level of QOL (Yates et al., 2005; Allen et al., 2009). Fatigue, pain, nausea will affect patients' resilience by increasing the level of emotional distress (i.e., depression and anxiety), which has been confirmed in patients with different cancer types (Stanton et al., 2005; Allen et al., 2009; Ye et al., 2016a,b,c, 2017d,e; Matsuoka et al., 2002).
2.2. Preliminary hypothesis for RM-BC In this model, we proposed that four strength-based protective variables provide buffers for patients' resilience levels and decrease the effect of all types of risk factors on resilience. Patients who experience severe symptoms of physical or psychological distress (risk factors) and have low levels of external or internal strength (protective factors) will display lower levels of resilience, which is presented in Fig. 1. Four strength-based protective variables (social support, courage-related strategy, hope for the future and self-efficacy) are believed to directly contribute to resilience and, as potential mediators, will serve as buffers to resilience against the effect of three risk factors (emotional distress, physical distress, and intrusive thoughts). Resilience and transcendence
2.2.3. Social support (protective factor) A strong support system can help patients overcome difficulties in challenging situations and is a robust buffering factor between stressors and psychosocial symptoms, which has been proven in previous studies (Allen et al., 2009; Yates et al., 2005). Social support is also an important resource to resilience integration and was found to be positively
Fig. 1. Hypothesized model of resilience in Chinese breast cancer survivors (RM-BC). 96
The degree of anxiety, depression and illness uncertainty that is perceived by the patients during treatment
The degree of pain, nausea and fatigue that is perceived by the patients during treatment The degree to which patients have been distressed or bothered by intrusive thoughts during the treatment for cancer The degree to which the patients experience sufficient emotional and instrumental support throughout the cancer treatment. The degree to which the patients experience a motivated state to reach their desired goals The degree to which the patients use direct, optimistic, and supportive coping strategies to manage the cancer experience The degree to which the patients' beliefs about confidence in their personal ability to cope with a variety of problems in the process of treatment. The ability of identifying resources to resist negative psychological responses when encountering a potentially traumatic circumstance The ability of developing strength to gain a sense of selftranscendence
Emotional Distress (Risk)
Physical Distress (Risk)
97
Transcendence (outcome)
Resilience (outcome)
Self-efficacy (Protective)
Hope for the Future (Protective) Courage-related strategy (Protective)
Social Support (Protective)
Intrusive Thoughts (Risk)
Definitions
Latent Variables
Chinese version of Self-transcendence Scale (CSTS, Zhang et al., 2014)
15
10
10-item Connor-Davidson Resilience Scale (CDRISC-10, Ye et al., 2017)
One dimension
One dimension.
One dimension
Direct, optimistic, and supportive dimensions
24
10
Will level and Ways level
One dimension
88
3
8
Pain level, nausea level and fatigue level One dimension
Anxiety level, depression level and illness uncertainty level
19
6
Dimensions
No. of Items
The Chinese version of General Self-efficacy Scale (GSE,Wang et al., 2001)
The Chinese version of the 8-item Hope Scale (HS, Wang, 2010) The Jalowiec Coping Scale- Revised (JCS-R, Wang, 1999)
Social Support Scale by Seeman & Berkman (SSS, Ye et al., 2010)
Chinese Hospital Anxiety and Depression Scale (HADS, Leung et al., 1993), 5-item Illness Uncertainty Scale for Patients (IUSP, Ye et al., 2014) QLQ-C30 core questionnaire of EORTC (Jiang et al., 2005) The Revised Impact of Event Scale (IES-R,Ye and Liang, 2013)
Instruments
Table 1 Summary of psychometric properties of measurements derived from the resilience model for breast cancer (RM-BC).
4-point Likert scale
5-point Likert scale
4-point Likert scale
4-point Likert scale
4-point Likert scale
4-point Likert scale
5-point Likert scale
0.92
0.88
0.81
0.79
0.87
0.92
0.83
0.79
15–60
0–40
10–40
0–72
8–32
3–12
0–32
0–100
5–67
0.86 for HADS; 0.89 for IUSP 4-point Likert for HADS, 5-point Likert for IUSP 4-point Likert scale
Score Range
α
No. of Points on the Likert Scale
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3.2. Instruments for RM-BC
linked to resilience and quality of life in previous study (Ye et al., 2016a,b,c, 2017d,e). However, we should be cautious because such effects only occur when the recipient regards the support provided as adequate and helpful (Rutter, 1985).
The psychometrics of scales used in this study are presented in Table 1. Each scale was validated in previous researches and showed good internal reliability and cronbach’ s coefficients in this study were also included.
2.2.4. Intrusive thoughts (risk factor) Intrusive thoughts are unwanted and common during the cancer treatment and mainly include recurring images of painful cancer treatment or fears of recurrence according to cancer survivors' reports (Matsuoka et al., 2002). In addition, breast cancer survivors are reported to have higher levels of intrusive thoughts relative to other cancer patient groups(Matsuoka et al., 2002). Intrusive thoughts may be particularly relevant for some physical symptoms because these disruptive thoughts can disturb sleep and increase sensitivity to physical sensations. Intrusive thoughts are chronic risk factors and are negatively correlated to resilience (Dooley et al., 2017; Ye et al., 2016).
3.3. Data analysis SEM (Structural Equation Modeling) was performed using the AMOS 21.0. The covariance matrix of relevant variables was evaluated by maximum likelihood estimation. Research with a sample of more than ten times the number of variables included in a SEM is recommended, and thus we had a sufficient sample size to conduct the SEM (Bentler, 1990). When all parameters appeared in order and no special problems were reported during the optimization process, the X2 test and some fit indexes such as Comparative Fit Index (CFI), Goodness Fit Index (GFI), Parsimony Normed Fit Index (PNFI), Root-Mean-Square Error of Approximation (RMSEA) were evaluated (Hu and Bentler, 1990).
2.2.5. Self-efficacy (protective factor) Self-efficacy is defined as one's belief and confidence to carry out a task and is a significant cognitive mediator of action (Bandura, 1997). It is believed that a lower level of self-efficacy is associated with higher levels of helplessness and depression (Williams and Schreier, 2004). In the treatment of breast cancer, patients suffered a lot from biopsychosocial burdens induced by breast cancer and were required to learn selfcare skills to combat the disease (Wu et al., 2016). Also, higher levels of self-efficacy was found to be significantly linked to resilience (Wu et al., 2016; Ye et al., 2016a,b,c, 2017d,e).
4. Results 4.1. Sample characteristics In total, 420 patients were recruited and 363 completed the booklet of scales. Subjects were not included due to lack of time or lack of willingness to participate. Due to missing or incomplete scales, 21 patients were also excluded and the response rate was 81.4%. The final data analyses were based on the remaining 342 patients. Patients with non-metastatic breast cancer (stage 0-II) was the majority in this study, constituting 81.6% (n = 279) of the whole participants. Other demographics and disease-related information are presented in Table 2.
2.2.6. Courage-related strategies (protective factor) Courage-related coping strategies is defined that patients use direct, optimistic, and supportive coping strategies to manage the cancer experience by addressing the problem and regulating the emotions (Hjemdal et al., 2006). Courage-related strategies are strongly associated with self-efficacy and represent an important indicator of resilience(Folkman and Moskowitz, 2004; Ye et al., 2016; Chen and Miller, 2012). It is believed that enduring suffering from cancer using couragerelated strategies and maintaining optimism for the future can allow for successful adjustment and resilience integration (Updegraff et al., 2008).
4.2. Descriptive statistics on measurements for RM-BC Patients showed varied biopsychosocial functions as depicted in Table 3. Bivariate correlations among the major variables were conducted first in order to evaluate the strength of the correlations and a correlation matrix is presented in Table 4. The unstandardized and standardized estimates, critical ratio, standard errors and significance for the construct in the final model are presented in Table 5. The Fit Indices for the measurement model were as follows: CFI = 0.909, GFI = 0.911, IFI = 0.897, NFI = 0.922, PNFI = 0.896, PCFI = 0.884, and RMSEA = 0.031. However, the pathway from social support to resilience was removed due to the low load on its construct (P > .05). In the final structural model depicted in Fig. 2, sixty-seven percent of the variance in resilience and fifty-four percent of the variance in transcendence were directly accounted for by 4 protective variables (buffering effect). For these buffers, forty-eight percent of the variance in courage-related strategies is directly accounted for by intrusive thoughts, social support, and self-efficacy; courage-related strategy is strongly associated with resilience (β = 0.44, P < .001) and transcendence (β = 0.38, P < .001). Fifty-one percent of the variance in Self-efficacy is directly accounted for by emotional distress, physical distress, intrusive thoughts and social support and is associated with resilience (β = 0.57, P < .001) and transcendence (β = 0.37, P < .001). Fifty-three percent of the variance in Hope for the future is directly accounted for by emotional distress, physical distress, self-efficacy and courage-related strategy and is associated with resilience (β = 0.39, P < .001) and transcendence (β = 0.46, P < .001). For intrusive thoughts, as an intermediate variable, forty-nine percent of the variance is directly accounted for by physical distress, social support, and emotional distress, and is associated with courage-related strategy (β = −0.47, P < .001) and self-efficacy (β = −0.33, P < .001). Physical distress, social support, and emotional distress
2.2.7. Hope for the future (protective factor) Maintaining hope for the future gives patients strong feelings of security and benevolence in the world when confronted by life-threatening disease and has been proven to have associations with better clinical outcomes in the previous study (Roy et al., 2010). People with higher levels of hope and having a greater sense of purpose are found to indicate a decreased risk of mortality of all types (Boyle et al., 2009). Also, a higher level of hope is proved to indicate a higher level of resilience (Wu et al., 2016; Ye et al., 2016a,b,c, 2017d,e). 3. Methods 3.1. Participants Patients were recruited from 4 hospitals in Guangdong Province from September 2013 to December 2015. The patients were hospitalized for surgery or adjuvant treatments. Patients should meet the inclusion criteria: (1) Female; (2) diagnosed with breast cancer (0-IV); (3) 18–65 years; (4)fluent communications in Mandarin or Cantonese. Patients were excluded if they met the exclusion criteria: (1) male, (2) insufficient knowledge to complete the booklet of scales, and (3) unwilling to be enrolled into the program. On average, it took patients about 40–55 min to complete the booklet of scales. This study was approved by the ethics committees of the hospitals(No: 2016KYTD08) and written or oral informed consent was acquired before the survey. 98
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Table 2 Demographics and clinical information of the participants. Demographics
No.
Age < =30 > 30 and ≤ 45 > 45 Race Han Other Education High school or lower Undergraduate or higher Income (monthly) < =¥5000 > ¥5000 and < =¥10,000 > ¥10,000 Relationship Single Married Divorced or widowed Religious affiliation Yes No Employment Part/full time Unemployed Insurance Business insurance Rural cooperative insurance none Residence Rural City
%
64 133 145
18.7 38.9 42.4
327 15
95.6 4.4
184 158
53.8 46.2
154 126
45.1 36.8
62
18.1
24 268 50
7.0 78.4 14.6
35 307
10.2 89.8
277 65
81.0 19.0
31 294
9.1 86.0
17
4.9
116 226
33.9 66.1
Table 4 Intercorrelation matrix of the study variables (N = 342).
Clinical Information
No.
Tumor size (mm) < =10 73 > 10 and ≤ 30 205 > 30 64 First diagnosis Yes 237 No 105 Lymph node status Positive 212 Negative 130 Duration of treatment (year) < =1 167 > 1 and ≤ 5 130 >5 Degree of malignancy 0 I II III IV Receptor status Estrogen positive Estrogen native Treatment Mastectomy only Lumpectomy only Mastectomy and chemotherapy Lumpectomy and chemotherapy Had radiation Yes No
%
69.3 30.7 62.0 38.0 b
48.8 38.0 13.2
57 123 99 38 25
16.7 36.0 28.9 11.1 7.3
238 104
69.6 30.4
50 146 58
14.6 42.7 17.0
88
25.7
229 113
66.9 33.1
Subscale Mean
SD
Emotional Distress (Risk) Anxiety 7.51 3.45 2–17 Depression 9.68 2.87 5–19 Illness Uncertainty 14.08 5.89 9–24 Physical Distress (Risk) Pain 62.34 17.81 0–100 Fatigue 51.27 15.38 10–100 Nausea 46.37 19.23 0–100 Intrusive Thoughts 9.23 5.47 4–27 (Risk) Social Support 8.86 2.44 4–12 (Protective) Hope for the Future 19.04 7.68 8–27 (Protective) Courage-related strategies (Protective) Direct Coping 14.37 6.86 5–26 Optimistic Coping 17.22 8.84 6–25 Supportive Coping 8.65 4.01 2–14 Self-efficacy 26.02 9.98 12–39 (Protective) Resilience 18.96 7.89 7–38 (outcome) Transcendence 29.76 14.35 17–49 (outcome)
Scale range
Score range
Item range
0–21 0–21 5–25
0–3 0–3 1–5
0–3 0–3 1–5
0–100 0–100 0–100 0–32
1–4 1–4 1–4 0–4
1–4 1–4 1–4 0–4
3–12
0–4
0–4
8–32
1–4
1–4
0–30 0–27 0–15 10–40
0–3 0–3 0–3 1–4
0–3 0–3 0–3 1–4
0–40
0–4
0–4
15–60
1–5
1–5
–
.52 –
3 a
4 a
.37 .41a –
-.13 -.18b .09 –
5
6 a
-.28 -.25b -.37a .11 –
7 a
-.41 -.38a -.58a .32a .39a –
8 a
9 a
-.44 -.36a -.39a .42a .31a .51a
-.61 -.53a -.43a .25b .46a .67a
-.38a -.32a -.19b .49a .34a .55a
–
.72a –
.46a .42a –
p < .05,a p < .01.
A biopsychosocial model of resilience (RM-BC) was proposed and tested among Chinese women with breast cancer. Four protective variables — social support, courage-related strategy, self-efficacy, and hope for the future — directly and significantly accounted for levels of resilience and transcendence, while three risk variables affected resilience and transcendence in an indirect way by affecting these protective variables. These resilience-related themes were confirmed in our mentees from BRBC program (Be Resilient to Breast Cancer), which is designed based on RM-BC (Ye et al., 2016c, 2017e). Just as one stated, “Since the diagnosis and surgery, I always felt inferior to others …. But now, I find that others (mentors) like me could live so well … So can I.” Thus, buffering effect of social support against disease-related stigma and intrusive thoughts could be primarily confirmed based on these qualitative data. Another mentee said, “The program taught me much than I expected. Now I can recognize and manage my emotions, cherish my life with my husband and child, and the meaning of life is different.” Therefore, the importance of patients' self-efficacy through knowledge learning (taught by mentors and teachers from BRBC) and hope were also emphasized to help patients normalize the experience of diagnosis and treatment of breast cancer and finally enhance their resilience levels. To our surprise, the pathway from social support to resilience was removed according to statistical standards, though the pathway from social support to transcendence was retained, which is not consistent with previous studies (McCabe and O’Connor, 2011). One explanation may be the different social support instruments used among different researches, with this study assessing the sufficiency of the received emotional and instrumental support compared to studies conducted by a generic social support instrument (Richardon, 2002). In addition, due to the complex nature of cancer and the following treatment, support from the medical staff will be very important to the patients, which should warrant more studies in the future to evaluate the differential contribution of social support provided by the medical staff or families and friends. In total, RM-BC provides valuable information about influencing factors of resilience in patients with breast cancer and lays a good foundation for resilience instruments development(i.e., Resilience Scale Specific to Cancer, RS-SC) and resilience-related intervention in the future (Ye et al., 2015; Ye et al., 2016a,b,c, 2017a,b,c,d,e, 2018a,b). However, most variables from RM-BC are measured by psychosocial instruments and will be affected by cultural background. Thus, we suggest that future studies incorporate more clinician-based ratings of variables such as allostatic load index (ALI) into the resilience model (Qiu et al., 2017; Kinnunen et al., 2005), which has been proved to have strong associations with resilience, quality of life and survival among patients with breast cancer (Ye et al., 2016c, 2017e, 2018a,b), and can also improve the generality of RM-BC among patients with different cultures.
Item Score range
1. 2. 3. 4. 5. 6.
2
5. Discussion
Table 3 Descriptive statistics for the outcome measures (N = 342). Variables
1
Emotional Distress Physical Distress Intrusive Thoughts Social Support Hope for the Future Courage-related strategies 7. Self-efficacy 8. Resilience 9. Transcendence
21.3 59.9 18.8
45
Variables
were three independent indicators in the RM-BC and increased or decreased the levels of resilience and transcendence by affecting four intermediate variables (courage-related strategy, intrusive thoughts, self-efficacy, and hope for the future). 99
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Table 5 Maximum likelihood estimates of the respecified model. Pathway Emotional Distress Emotional Distress Emotional Distress Physical Distress Physical Distress Physical Distress Intrusive Thoughts Intrusive Thoughts Self-efficacy Self-efficacy Self-efficacy Self-efficacy Hope for the Future Hope for the Future Social Support Social Support Social Support Social Support Courage-related strategy Courage-related strategy Courage-related strategy
→Intrusive Thoughts →Self-efficacy →Hope for the Future →Intrusive Thoughts →Self-efficacy →Hope for the Future →Self-efficacy →Courage-related strategy →Courage-related strategy →Transcendence →Hope for the Future →Resilience →Transcendence →Resilience →Intrusive Thoughts →Self-efficacy →Courage-related strategy →Transcendence →Hope for the Future →Transcendence →Resilience
Non-standardized Coefficients
Standardized Coefficients
Standard Errors
Critical Ratio
0.41 −0.47 −0.36 0.62 −0.46 −0.51 −0.62 −0.39 0.71 0.54 0.43 0.45 0.24 0.35 −0.46 0.16 0.09 0.12 0.59 0.46 0.42
0.52 −0.36 −0.34 0.43 −0.38 −0.25 −0.33 −0.47 0.44 0.37 0.38 0.57 0.46 0.39 −0.19 0.35 0.26 0.23 0.45 0.38 0.44
0.23 0.11 0.16 0.07 0.09 0.39 0.04 0.13 0.09 0.20 0.05 0.06 0.17 0.44 0.27 0.32 0.04 0.06 0.18 0.22 0.13
7.66 −5.47 −4.72 6.86 −4.74 −1.96 −5.02 −7.25 6.41 4.51 3.88 8.34 6.48 5.67 −1.74 5.22 3.11 2.03 7.23 5.33 7.62
5.1. Implications for clinical practice
5.2. Limitations
Based on RM-BC, BRBC could significantly improve the positive factors (e.g. social support, hope, etc) and reduce the illness-related factors (e.g. anxiety, depression, etc) of resilience during the cancer treatment though it could not prolong the lifespan of patients with metastatic breast cancer at 5-year follow-up (Ye et al., 2016c, 2017e).This successful program provided evidences of the feasibility of RM-BC in Chinese women with breast cancer and could be used as a useful framework for more resilience-specific intervention in the future. Also, RM-BC might be feasible in the western countries because the proposed variables are all developed there and more cross-cultural research should be warranted. Although this article has provided preliminary findings on the development of RM-BC in Chinese patients with breast cancer, further qualitative and quantitative work is needed to verify the relationships between resilience and its influencing factors and better determine methods of promoting resilience in the Chinese patients with breast cancer.
This article also has some limitations. First, no causal relationships could be found because of the cross-sectional design, and more longitudinal studies examining the trajectories of resilience are warranted due to the dynamic nature of resilience across time. Second, we should be cautious that 57 participants declined to participate in this study for various reasons, and it may lead to biased results because patients with lower levels of biopsychosocial burdens were more able to participate in the survey. Third, this study does not investigate psychosocial variables such as defensive coping strategies, family environment, personalities, etc., due to the limitation of excessive scales. Future studies can focus on these dimensions to improve the fitness of the resilience model.
6. Conclusion In summary, this article provides empirical and clinical evidence for Fig. 2. The final framework of the resilience model for patients with breast cancer (RM-BC). Emotional Distress, Physical Distress and Social Support are three independent variables affecting the outcome variables of Transcendence and Resilience by adjusting four moderating variables of Self-efficacy, Courage-related strategy, Intrusive Thoughts and Hope for the Future.
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the nature and process of resilience following a breast cancer diagnosis and, to our knowledge, is the first study to evaluate resilience and its influencing factors using SEM. The feasibility of RM-BC in Chinese patients with breast cancer has been confirmed but more researches about its application in patients with different cultures should be warranted.
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