Trait resilience moderates the longitudinal linkage between adolescent posttraumatic stress disorder symptoms and posttraumatic growth

Abstract

The current study examined the longitudinal association between posttraumatic stress disorder (PTSD) symptoms and posttraumatic growth (PTG) as well as the moderating role of trait resilience in that association. Participants completed measures of PTSD symptoms, PTG, and trait resilience at 12, 18, and 24 months after the Wenchuan earthquake. Results showed that after adjusting PTG at wave 1, PTSD symptoms at wave 1 were positively and significantly related to PTG at wave 2 for low-resilience individuals, but not for individuals with the other two levels (middle and high) of trait resilience. After adjusting PTSD symptoms at wave 1, PTG at wave 1 was positively and significantly related to PTSD symptoms at wave 2 for middle-resilience individuals, but not for individuals with the other two levels (low and high) of trait resilience. No other cross-lagged correlations were significant. Implications of the results for psychological service providers are discussed.

Keywords

adolescents PTG PTSD symptoms the Wenchuan earthquake trait resilience

The 2008 Wenchuan earthquake was one of the most devastating natural disasters in Chinese history, resulting in approximately 69,277 deaths and countless others injured or displaced. After the Wenchuan earthquake, children and adolescents at school had to cope with considerable changes, including damaged buildings, site sharing with students from other schools or even school mergers, and burned out teachers. Such changes could have rendered them particularly vulnerable to stress-related outcomes. PTSD is a commonly noted psychological reaction in the aftermath of disasters, characterized by the re-experience of a traumatic event, numbing/avoidance, and hyper-arousal (Ben-Zur & Almog, 2013; Bulut, Bulut, & Tayli, 2005; Goenjian et al., 1995; Groome & Soureti, 2004; Kessler, Chiu, Demler, & Walters, 2005; Ying, Wu, Lin, & Chen, 2013). For example, Fan, Zhang, Yang, Mo, and Liu (2011) reported that the prevalence rate of PTSD symptoms was 15.8% among 2,250 adolescent survivors (the mean age of 14.6 years, SD = 1.3) six months after the Wenchuan earthquake. Another study of 2,037 children (aged 9- to 17-years-old) exposed to the Athens earthquake found that the prevalence rates of likely PTSD cases among directly or indirectly exposed children were 35.7% and 20.1%, respectively (Giannopoulou et al., 2006).

Recently researchers have paid more attention to post-traumatic growth (PTG), which is defined as positive changes or personal growths as a result of the psychological struggle with highly challenging life circumstances (Tedeschi & Calhoun, 1996). These positive changes are often manifested in five main domains: A feeling of strength, becoming closer to family and friends, a greater appreciation of life, recognition of new possibilities, and spiritual development (Callhoun & Tedeschi, 2006; Tedeschi & Callhoun, 1996). The PTG-like changes have been found to exist in diverse youth samples globally including those experiencing natural disasters (Cryder, Kilmer, Tedeschi, & Calhoun, 2006; Kilmer & Gil-Rivas, 2010), traffic accidents (Salter & Stallard, 2004), and terror attacks (Laufer, Hamama-Raz, Levine, & Solomon, 2009; Little, Akin-Little, & Somerville, 2011).

Both PTSD and PTG are sequelae arising from traumatic events, but the relationship between them is unclear. So far, there are four models about this relationship. First, PTG is thought to coexist with PTSD symptoms in a positive manner (Alisic, van der Schoot, van Ginkel, & Kleber, 2008; Hafstad, Kilmer, & Gil-Rivas, 2011; Kilmer & Gil-Rivas, 2010; Laufer & Solomon, 2006). That is, high levels of distress trigger subsequent growth. Second, PTSD and PTG are considered as the opposite ends of the same continuum. More growth means less subsequent distress (Frazier, Conlon, & Glaser, 2001; Ickovics et al., 2006). For example, a longitudinal study of urban adolescent girls showed that PTG at the 12-month follow-up was associated with reductions in distress six months later (Ickovics et al., 2006). Third, PTSD and PTG are two separate and independent constructs (Cordova, Cunningham, Carlson, & Andrykowski, 2001; Linley & Joseph, 2004; Powell, Rosner, Butollo, Tedeschi, & Calhoun, 2003). One study found that the relationship between PTSD and PTG was not significant (Zoellner & Maercker, 2006). Finally, some researchers have proposed that the relation between PTSD and PTG is curvilinear (inverted-U), with adolescents suffering from moderate levels of PTSD showing the highest levels of PTG (Levine, Laufer, Hamama-Raz, Stein, & Solomon, 2008). In a recent meta-analysis, Shaespeare-Finch and Lurie-Beck (2014) concluded that there was a significant but weak relationship between PTSD symptoms and PTG, suggesting that many other factors might play a role in the relationship.

Resilience is another salutogenic outcome in the aftermath of a traumatic event. Although no universal definition of resilience has yet been established, resilience is frequently defined as positive adaptation in the face of adversity (Masten, 2011). Conceptually, an important debate focuses on whether resilience should be conceptualized as either a personality trait or a process (Fletcher & Sarkar, 2013; Windle, 2011). As a trait, resilience represents a constellation of personal characteristics (i.e., optimism, hardiness, strong self-esteem, and positive affects) that facilitate achievement of developmental tasks (Connor & Davidson, 2003). As a process, resilience is usually referred to as a dynamic process that encompasses both behavioral and psychological manifestation of positive adaptation despite adversity (Luthar, Cicchetti, & Becker, 2000). For the current research, resilience was measured with the Connor-Davidson Resilience Scale (Connor & Davidson, 2003), which includes personality traits such as tenacity, personal strength, and optimism.

These characteristics of resilience are assumed to help individuals to recover from the stressful situations and promote active engagement and meaningful action (Westphal & Bonanno, 2007). For example, Catalano, Chan, Wilson, Chiu, and Muller (2011) suggested that characteristics of resilience helped to attenuate depressive symptoms among adults (Mean = 46.30 years, SD = 13.01) with spinal cord injury living in the community. Additionally, Bensimon (2012) found that trait resilience was positively associated with PTG among college students (the mean years of 24.7, SD = 2.76) with varied exposure levels. In addition, although previous studies have found the moderating role of trait resilience in the association between PTSD symptoms and PTG, the conclusions are inconsistent. For example, some studies suggest that high-resilience individuals more likely evaluate a traumatic event in a positive manner, which will prompt them to perceive growth (Pietrzak, Johnson, Goldstein, Malley, & Southwick, 2009; Prati & Pietrantoni, 2009). Other research suggests that high-resilience individuals more likely emerge from trauma with less psychological wounds (Bonanno, Wortman, & Nesse, 2004). Thus, they have less chance of engaging in the meaning-making behaviors associated with growth because they tend not to struggle with the implications of the traumas (Levine, Laufer, Stein, Hamama-Raz, & Solomon, 2009; Westphal & Bonanno, 2007).

Based on the literature, the current study used cross-lagged structural equation modeling (SEM) with latent variables to examine the associations among PTSD symptoms, PTG, and trait resilience in adolescent survivors of the Wenchuan earthquake. The specific aims of the present study were a) to examine longitudinally the reciprocal relationship between PTSD symptoms and PTG, b) to determine whether trait resilience moderated the longitudinal association.

Method

Participants and procedure

Data were collected as part of a large-scale longitudinal study on psychological adjustment among child survivors following the Wenchuan earthquake (see Ying et al., 2013 for full details). In the current study, data consisted of 788 adolescent survivors (the mean age of 15.03 years, SD = 1.65 years; 54% female) who completed all three main measures at 12 months after the Wenchuan earthquake (wave 1): the Post-Traumatic Growth Inventory (PTGI; Tedeschi & Calhoun, 1996), the Child PTSD Symptom Scale (CPSS; Foe, Johnson, Feeny, & Treadwell, 2001), and the Connor and Davidson’s Resilience Scale (CDRS; Connor & Davidson, 2003). Of 788 participants, 566 and 329 participants completed the two follow-up assessments at 18 (wave 2) and 24 months (wave 3) following the Wenchuan earthquake, respectively. The reduction in sample was mainly due to school merges or relocations. To strengthen the reliability of the model, the analytic sample was further restricted to 650 adolescent survivors with valid data for at least two time-points for the three primary variables. Attrition analyses showed that there were no significant differences on main study variables between the final sample of 650 participants and 138 participants who were excluded in the final analyses.

Measures

Posttraumatic stress disorder

PTSD symptoms were assessed with the Chinese version (Zang, 2010; Zhang, 2009) of the CPSS (Foe et al., 2001). The 17-item self-report measure was designed to assess the severity of DSM-IV-defined PTSD symptoms in relation to the most distressing event. In the current study, participants were asked how much they were distressed or bothered by the earthquake-related experiences from 0 (‘not at all / only at one time’) to 3 (‘many times a week or almost always’). Total possible CPSS scores ranged from 0–51, with higher scores indicating greater severity of PTSD symptoms. The original CPSS has demonstrated good psychometric properties (Foe et al., 2001). The Chinese version of the CPSS was first translated and used by Zang, Zhang, & Wu (2009) in a study of children exposed to the Wenchuan earthquake. It has demonstrated acceptable validity and reliability (Zhang, 2009; Zang et al., 2009; Ying, Wu, & Lin, 2012). The Cronbach’s αs of the scale in the present study were 0.90 at wave 1, 0.89 at wave 2, and 0.89 at wave 3.

Posttraumatic growth

PTG was assessed with the modified version of the PTGI (Zang, 2010). The original PTGI was developed by Tedeschi and Calhoun (1996) and consisted of five subscales: Personal strength, new possibilities, relating to others, appreciation of life, and spiritual change. Participants rated the extent to which they experienced various changes as a result of the trauma, ranging from 0 (‘not at all’) to 5 (‘extremely’). The original PTGI had good reliability and validity (Tedeschi & Calhoun, 1996). Compared with the original scale, the Chinese PTGI has been modified in two ways (Ying et al., 2014). First, some items were reworded to enhance comprehension among adolescent survivors of the Wenchuan earthquake. Second, the subscale of spiritual change was omitted because of its limited relevance to today’s Chinese adolescents, most of whom are not religious. For example, in the current sample, only 215 (33.1%) of 650 participants reported holding religious beliefs. The modified scale has been found to have good reliability and construct validity in the sample of child survivors of the Wenchuan earthquakes (Zang, 2010). Cronbach αs in the current study were 0.93 at wave 1, 0.95 at wave 2, and 0.95 at wave 3.

Trait resilience

Trait resilience was assessed using the Chinese version (Yu & Zhang, 2007) of CD-RISC, a 25-item self-report instrument to measure the ability of coping with stress and adversity. Participants were asked to respond to the 25 items on a five-point scale ranging from 0 (not true at all) to 4 (true nearly all of the time). Higher total scores indicated higher levels of resilience. This scale has been found to show high reliability and convergent and discriminant validity in various samples (Ickovics et al., 2006; Ramsay et al., 2015; Scali et al., 2013). The Chinese version of the CD-RISC was first translated and used by Yu and Zhang (2007) in a study of Chinese adults. The Cronbach’s α of the scale in the present study was 0.94.

Data analysis

First, descriptive analyses were conducted to calculate the means and standard deviations for the measures of PTSD symptoms, resilience, and PTG. Second, we calculated Pearson correlations among three main studies variables cross-sectionally and longitudinally. Then, to examine the relationship between PTSD symptoms and PTG, we conducted a cross-lagged, latent variable SEM with the AMOS7.0 software using the Maximum Likelihood (ML) iteration procedure. The nested models were compared based on the Chi-square difference test. Finally, to further examine whether the magnitude of association between PTSD symptoms and PTG differed at three levels (i.e., higher, middle, or lower) of trait resilience, we examined group invariance in the measurement model and final path model. Specifically, an unconstrained model where path coefficients were allowed to vary across low (1 SD below the mean on trait resilience), middle (from −1 to +1 SD), and high (1 SD above) resilience groups was compared with a model where these path coefficients were constrained to be equal.

To handle missing values, we used full information maximum likelihood (FIML) estimates (Anderson, 1957) that are enabled by AMOS7.0. Degree of model fit was assessed using the following fit indices: the Chi-square, the normed-chi-square tests (Normed χ²; Jöreskog, 1969), the Tucker–Lewis Index (TLI; Tucker & Lewis, 1973), the Comparative Fit Index (CFI; Bentler, 1990), and the Root Mean Square Error of Approximation (RMSEA; Steiger, 1980). Models are said to fit data well when the Normed χ² is < 2 (Carmines & McIver, 1981), TLI and CFI are > 0.95, and RMSEA is < 0.06 (Hu & Bentler, 1999).

Results

Descriptive statistics

Table 1 presents the means and standard deviations of the three main study measures and the concurrent and longitudinal intercorrelations among them. PTSD symptoms at all three waves had significant and positive correlations with PTG at wave 1, but only PTSD symptoms at wave 2 had a significant correlation with PTG at wave 2. Trait resilience at wave 1 was significantly and negatively correlated with PTSD symptoms at waves 1 to 3 but positively with PTG for all three waves.
Table 1.
Descriptive statistics and intercorrelations among the three measures of PTSD symptoms, PTG, and trait resilience.

Variables N Mean SD 1 2 3 4 5 6 7

1. PTSD T1 650 0.92 0.50 –

2. PTSD T2 566 0.88 0.48 0.70 –

3. PTSD T3 329 0.90 0.47 0.68 0.71** –

4. PTG T1 650 2.88 0.99 0.11* 0.09* 0.12** –

5. PTG T2 566 2.64 1.08 0.06 0.08* 0.01 0.49 –

6. PTG T3 329 2.91 1.01 0.03 0.07 0.06 0.38 0.43** –

7. Trait resilience T1 650 2.20 0.90 −0.10* −0.09* −0.13* 0.54 0.35 0.31** –

Note. T1 = the first assessment at 12 months after the Wenchuan earthquake; T2 = the second assessment at 18 months after the Wenchuan earthquake; T3 = the third assessment at 24 months after the Wenchuan earthquake.

*
p < 0.05; **p < 0.01.

Cross-lagged associations between PTSD symptoms and PTG

Measurement models

We established two measurement models including six latent variable constructs: PTSD symptoms and PTG at wave 1, wave 2, and wave 3. At each wave, the latent construct of PTG was indicated by the means of the four subscales (i.e., personal strength, new possibilities, appreciation of life, and relating to others), whereas the latent variable of PTSD symptoms was indicated by the three CPSS-subscales (i.e., intrusion, avoidance, and hyper-arousal).

In the first measurement model (model 1), we estimated freely the factor loadings of the manifest indicators on their respective latent variables. All latent constructs were correlated with each other, and the error terms of individual indicators were permitted to correlate over time (Cole, Ciesla, & Steiger, 2007). For example, the error term of the avoidance manifest variable at wave 1 was correlated with the same error terms at wave 2, and wave 3, and the error terms of avoidance at wave 2 and wave 3 were also correlated with each other. The model fit the data well (χ²(153) = 274.33, p < 0.001, χ²/df = 1.793, CFI = 0.986, IFI = 0.987, TLI = 0.979, RMSEA = 0.035). The second measurement model (model 2) was identical to the first model except that we constrained the factor loadings of analogous manifest indicators to be equal across time (Hoyle & Smith, 1994). This measurement model still fit the data well (χ² (163) = 292.68, p < 0.001, χ²/df = 1.796, CFI = 0.985, IFI = 0.986, TLI = 0.979, RMSEA = 0.035). The test of chi-square difference indicated that the difference in fit between model 1 and model 2 was marginally significant (Δχ² (10) = 18.35, p = 0.05). Thus we still favored the more parsimonious model 2 and retained the longitudinal constraints on factor loading in subsequent analyses.

Structural models

We tested cross-lagged models, using the measurement model specified above. The cross-time covariance was converted to regression estimation; for example, a latent variable at wave 2 was predicted by the same variable at wave 1 (the autoregressor) and the other latent variable at wave 1. The cross-lagged paths indicated the influence of one variable on the other, after controlling for the stability of the variable over time (Finkel, 1995).

In the first cross-lagged model (model 3), all structural coefficients were freely estimated. Model fit was good (χ² (167) = 333.38, p < 0.001, χ²/df = 1.996, CFI = 0.981, IFI = 0.981, TLI = 0.973, RMSEA = 0.039). In the second cross-lagged model (model 4), we constrained the structural parameters to be equal across all three time intervals. model 4 still fit the data well (χ² (171) = 336.58, p < 0.001, χ²/df = 1.968, CFI = 0.981, IFI = 0.981, TLI = 0.974, RMSEA = 0.039). The test of Chi-square difference indicated that the difference in fit between models 3 and 4 was not significant(Δχ² (4) = 3.20, p > 0.05). Thus we favored the more parsimonious model 4 and retained the longitudinal constraints on structural coefficients in subsequent analyses. As shown in model 4, the cross-lagged paths from PTSD symptoms to PTG at two time intervals were not significant. Moreover, the cross-lagged paths from PTG to PTSD symptoms at two time intervals were also not significant.

Trait resilience moderated the longitudinal relationship between PTSD symptoms and PTG

To further examine whether trait resilience moderated the longitudinal relationship between PTSD symptoms and PTG, we first examined the measurement invariance of model 2 across the resilience levels. The unconstrained model whose factor loadings were allowed to vary across low (1 SD below the mean on trait resilience), middle (from −1 to+1 SD), and high (1 SD above) levels was compared to a model whose factor loadings were constrained to be equal. The test of Chi-square difference showed that the constrained model showed significantly poorer model fit relative to the unconstrained model (Δχ² (12) = 26.42, p < 0.001). Thus, the factor loadings were allowed to be freely estimated in the subsequent analyses. Next, the cross-lagged paths in the final structural model (model 4) were compared in three groups of trait resilience by means of a multigroup comparison. Results showed that the constrained model showed significantly poorer model fit relative to the unconstrained model (Δχ² (20) = 37.52, p < 0.05). As shown in Figures 1 and 2, in the unconstrained model, after controlling PTG at wave 1, PTSD symptoms at wave 1 predicted significantly PTG from at wave 2 for the low-resilience group (β = 0.22, p < 0.01), but was nonsignificant for the middle- and high-resilience groups. Additionally, after controlling PTSD symptoms at wave 1, PTG at wave 1 predicted significantly to PTSD symptoms at wave 2 for the middle-resilience group (β = 0.12, p < 0.05), but was nonsignificant for the low- and high-resilience groups.
Figure 1.
Structural model of the cross-lagged relationship between PTSD symptoms and PTG in individuals with a low level of trait resilience.

Figure 2.
Structural model of the cross-lagged relationship between PTSD symptoms and PTG in individuals with a middle level of trait resilience.

Discussion

In the current study of adolescent survivors of the Wenchuan earthquake, we used cross-lagged SEM with latent variables to examine the longitudinal relationship between PTSD symptoms and PTG as well as the potential moderating role of trait resilience in that relationship. Several key findings emerged. First, consistent with previous studies (Alisic et al., 2008; Hafstad et al., 2011; Kilmer & Gil-Rivas, 2010; Saccinto, Prati, Pietrantoni, & Perez-Testor, 2013), the current study found that the cross-sectional correlations between PTSD symptoms and PTG were significant at 12 and 18 months but not at 24 months post-earthquake. One possible explanation for the significant relationships was that both PTSD and PTG were outcomes of a highly stressful life experience and might have similar initial pathways such as the experience of a trauma leading to challenges to core beliefs (Janoff-Bulman, 2010). For example, previous studies showed that rumination, a powerful predictor of persistent PTSD (Murray, Ehlers, & Mayou, 2002), might be an important cognitive process in facilitating individual PTG (Taku, Cann, Tedeschi, & Calhoun, 2009). However, the finding of the nonsignificant relationship between PTSD symptoms and PTG at 24 months post-earthquake suggested that the common predictive factors shared by the two constructs may become weaker or disappear altogether overtime (Triplett, Tedeschi, Cann, Calhoun, & Reeve, 2012).

Additionally, the present study showed that after controlling for PTSD symptoms at wave 1, PTG at wave 1 predicted positively and significantly PTSD symptoms at wave 2 only in adolescents with a middle level of trait resilience. Although PTG can be considered as a coping strategy, Maercker and Zoellner (2004) contend that PTG has a realistic constructive and self-deceptive side. On the constructive side, PTG reflects functional adjustment or cognitive restructuring, and as such, it can relieve distress after trauma. The current study did not find evidence for the constructive side of PTG. Instead our results suggest that the personal growth perceived by the traumatized adolescents might actually be an illusory (perhaps self-protective or self-enhancing) process that signaled a derogation of one’s past self rather than an actual improvement from the past to the present (McFarland & Alvaro, 2000). In the long run, the illusory self-enhancement strategies may even deteriorate PTSD symptoms in these traumatized adolescents with a middle level of trait resilience. Therefore, the positive changes individuals experienced following the trauma did not necessarily undo the ongoing distress from the trauma.

Finally, the results of the current study showed that after adjusting PTG at a prior wave, PTSD symptoms did not significantly predict subsequent PTG. This finding suggested that although there was the concurrent relationship between PTSD symptoms and PTG, PTSD symptoms were not necessarily indicative of the development or absence of psychological growth. We further found that trait resilience moderated the relationship between PTSD symptoms and change in PTG. That is, compared to high-resilience adolescents, low-resilience adolescents showed a stronger association between PTSD symptoms and change in PTG. This finding supported the theory of PTG, which proposed that experiencing growth is only possible if trauma has been upsetting enough to drive the survivor to engage in meaning-making behavior. Accordingly, individuals with low resilience were at a greater risk of developing PTSD, which in turn resulted in a greater need or opportunity for posttraumatic growth (Westphal & Bonanno, 2007). Additionally, if PTG corresponds to unrealistic optimism to manage encountered adversity, low-resilience adolescents may experience such illusions (Johnson et al., 2007). On the contrary, adolescent survivors with a high level of resilience could retain their equilibrium by virtue of changing flexibly their affective and physiological responses to adapt successfully to the frequently changing environmental circumstances (Waugh, Thompson, & Gotlib, 2011). In this case, the individuals might experience less growth as they did not perceive traumatic stressful experiences at a precipitous level necessitating recovery (Schuettler & Boals, 2011).

Several limitations of the present study should be mentioned. First, we collected all data one year following the traumatic event, without earlier data (e.g., the experiences of stress and growth between the event and the first assessment Meyerson, Grant, Carter, & Kilmer, 2011). Second, the pertinent variables (i.e., PTSD symptoms, PTG, and resilience) were measured with self-report questionnaires, so the shared method variance might have inflated the relations among the three constructs (Podsakoff, Mackenzie, Lee, & Podsakoff, 2003). Finally, participants in the current study consisted of adolescent survivors of the extremely serious earthquake. Thus, it is unclear whether our findings can be generalized to individuals who experience other types of traumatic events (e.g., serious motor-vehicle accidents, sexual abuse).

Conclusions and Implications

Despite these limitations, the findings of the current study can provide valuable information for psychological service providers working with adolescents who have experienced traumas, perhaps guiding aspects of their assessment and interventions. Specifically, our research found positive relationships between PTSD symptoms and change in PTG, suggesting that psychological distress is necessary for low-resilience adolescents to experience the growth following a disaster. They can use PTG as an alternative coping approach to obtain a reconfiguration of their goals, beliefs, and worldviews. Thus, schools are the locales preeminently situated to provide interventions following disasters (Heath & Cole, 2011). School psychologists should be aware of the possibility of growth among traumatized adolescents. For example, school psychologists should recognize adolescents’ struggle to understand the impact of the earthquake not only as a posttraumatic response but also as a potential precursor to growth. However, the current study showed that the positive relationship between PTG and change in PTSD symptoms only existed in adolescents with a middle level of trait resilience, which suggests that PTG may be not a useful target for psychological service providers/school psychologists who focus on adolescents’ long-term emotional adjustments (Sawyer, Ayers, & Field, 2010). Care should also be taken to avoid imposing an expectation of PTG in the face of traumatic events. As mentioned in previous studies (Calhoun & Tedeschi, 2006; Joseph, 2004), growth must proceed at the pace of the client and should be identified, but not forced, by the psychological service provider.

Variables	N	Mean	SD	1	2	3	4	5	6	7
1. PTSD T1	650	0.92	0.50	–
2. PTSD T2	566	0.88	0.48	0.70**	–
3. PTSD T3	329	0.90	0.47	0.68**	0.71**	–
4. PTG T1	650	2.88	0.99	0.11*	0.09*	0.12**	–
5. PTG T2	566	2.64	1.08	0.06	0.08*	0.01	0.49**	–
6. PTG T3	329	2.91	1.01	0.03	0.07	0.06	0.38**	0.43**	–
7. Trait resilience T1	650	2.20	0.90	−0.10*	−0.09*	−0.13*	0.54**	0.35**	0.31**	–

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by grants from the Key Projects of Philosophy and Social Sciences Research, Ministry of Education, China (Grant number: 08JZD0026), the National Foundation of Natural Science (Grant number: 31400889), and 521 training programme foundation for the talents and the Science Foundation of Zhejiang Sci-Tech University (Grant number: 13062175-Y).

Author biographies

Liuhua Ying, PhD, is a Lecturer in the Department of Psychology, Zhejiang Sci-Tech University, China. He received his PhD from Beijing Normal University in China. His research and scholarly interests focus on those questions of how children and adolescents cope with stress, trauma, and other forms of adversity.

Yanli Wang, is a Master candidate at the Department of Psychology, Zhejiang Sci-Tech University, China. Her main research interest is those emotion-related factors in predicting adjustment to trauma and loss.

Chongde Lin, PhD, is a Professor at the Institute of Developmental Psychology at Beijing Normal University. His main research interests include theories of intelligence and development, education and development, and mental health education.

Chuansheng Chen, PhD, is a Professor of Psychology and Social Behavior and Education Culture at the University of California, Irvine. His main research interests include cross-cultural psychology, adolescent development, cognitive neuroscience, genes and behavior.

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