Sample/Participants
Participants were enrolled from six hospitals in Guangdong and Heilongjiang Provinces between June 2015 and December 2018; each had a confirmed diagnosis of cancer based on biopsy and medical imaging. All participants had to fulfill the same inclusion/exclusion criteria, which were detailed as follows, inclusion: (1) aged 18–65 years, (2) had the ability to communicate in Mandarin or Cantonese fluently, and (3) receiving active treatment; exclusion: (1) misdiagnosed with cancer, (2) cannot communicate in Mandarin or Cantonese fluently, and (3) unwilling to participate in the study. Patients were all derived from a big project named as Be Resilient to Cancer. Informed consent was obtained, and the Human Research Ethics Committee approved the present study (registration number: 2016KYTD08).
Data collection
This prospective study was conducted between June 2015 and December 2018. RS-SCs, EORTC QLQ-C30, CD-RISC, and HADS were administered to 765 patients at baseline (T0), whereas ALI was conducted in 275 patients treated in the six hospitals. 3 months later (T1), the same instruments were administered again.
Measures
RS-SC
The original RS-SC is a 25-item resilience instrument specific to cancer (RS-SC-25) that has the five domains of generic element, benefit finding, support and coping, hope for the future, and meaning for existence [6]. A 10-item RS-SC (RS-SC-10) was developed later by MIRT analysis [9]. The two scales are both rated based on a five-point Likert scale, with higher scores indicating higher resilience levels. Scores for RS-SC-25 range from 25 to 125, and for RS-SC-10, from 10 to 50. The Cronbach’s α and test-retest reliability of RS-SC-25 are 0.83 and 0.87, respectively[6, 9]. The Cronbach’s α of RS-SC-10 is 0.86. RS-SC-25 and RS-SC-10 are attached in the Appendix (Tables S1 and S2).
EORTC QLQ-C30
EORTC QLQ-C30 is a 30-item quality of life (QoL) instrument specific to cancer, including five functional dimensions, three symptom dimensions, a global health status, some additional symptom items reported by patients with cancer, and perceived financial impact of cancer [15]. The raw score of each dimension can be converted to a score ranging from 0 to 100 according to the manual, with higher scores indicating better functional ability or increased distress in the symptom items [16]. In addition, Item 30 measuring the global health status was used as an anchor in this study (raw score ranging from 1 to 7). The Cronbach’s α of the Chinese version of EORTC QLQ-C30 ranges from 0.78 to 0.93 in different dimensions.
CD-RISC
The Chinese version of CD-RISC is a 25-item generic resilience instrument with the three dimensions of tenacity, strength, and optimism [17]. Additional two short non-dimensional versions of CD-RISC (2- and 10-item, named CD-RISC-2 and CD-RISC-10, respectively) were developed later. These three scales are all rated based on a five-point Likert scale with higher scores indicating higher resilience levels (ranging from 0–8, 0–40, 0-100, respectively). CD-RISC-10 was used as an anchor in this study. Cronbach’s αs of 0.83, 0.79, and 0.85 are identified for CD-RISC-25, CD-RISC-2, and CD-RISC-10, respectively [18–19].
HADS
The Chinese version of HADS is a 14-item emotional distress-screening tool with seven items for anxiety and seven items for depression [20]. The instrument is scored on a five-point scale with higher scores indicating worse emotional functions (ranging from 0–56). HADS was used as an anchor in this study. The Cronbach’s α of HADS is 0.91.
ALI
ALI is a validated composite index measuring 14 indicators from different physiological systems, such as the functions of the sympathetic nervous system, parasympathetic nervous system, and hypothalamic pituitary adrenal. ALI scores range from 0 to 14, with higher scores indicating higher allostatic load. Similar approaches to conceptualize physical allostatic load have been applied [21–23]. The Cronbach’s α of ALI has not been evaluated.
Data analysis
First, at T0, Pearson’s r correlation coefficients were used to measure the correlations between RS-SCs (RS-SC-25 and RS-SC-10) and anchors in patients with different cancer diagnoses [24–25]. Fisher’s z-transformation was applied to approximate the variance-stabilizing transformation for Pearson’s r correlation coefficients when RS-SCs and anchors followed a bivariate normal distribution, and determine the 95% confidence intervals (CIs) for the Pearson’s r correlation coefficients [26–27]. r < 0.3, 0.3 ≤ r ≤ 0.5, r > 0.5 were defined as weak, moderate and strong coefficients, respectively.
Second, from T0 to T1, Pearson’s r correlation coefficients (95%CI) were performed again to estimate the correlations between change in RS-SCs and change in anchors, in order to select suitable anchors. The correlation coefficients should be more than 0.30, as recommended [11].
Third, from T0 to T1, linear regression (95%CI, within-group) were calculated to compare changes in RS-SCs against different anchors. As for linear regression, change in RS-SC score (independent variable) was anchored against change in EORTC QLQ-C30, CD-RISC, and HADS score (dependent variables), respectively. In addition, Cohen effect size (ES) was also calculated [28]. ES < 0.3, 0.3 ≤ ES ≤ 0.8, ES > 0.8 were defined as small, medium, and large effect. For the distribution-based estimation (within-group) of MCIDs, we calculated the 20% (0.2 SD), 30% (0.3 SD), and 50% (0.5 SD) SD [29]; standard error of measurement (SEM) [30]; and minimal detectable change (MDC) for the 90%CI (MDC90) and 95%CI (MDC95) [10].
At last, from T0 to T1, receiver operating characteristic curves (ROCs, within-subject) analysis were performed. Changes in the cut-off of RS-SCs that best discriminated between patients who increased or decreased their resilience levels by the established MCIDs in the EORTC QLQ-C30 (1-point change in global health status, QoL-GHS)[31], CD-RISC-10 (3-point change) [32], and HADS (1.5-point change for anxiety and depression each) were defined as showing MCID [33]. The area under curve (AUC) and Youden index were adapted with equal weighting given to sensitivity and specificity [34]. P < 0.05 was recognized as statistically significant for all the data analysis. All data analyses were performed using SPSS 21 (IBM, USA).