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Journal of Child & Adolescent Trauma logoLink to Journal of Child & Adolescent Trauma
. 2015 Oct 9;11(2):205–226. doi: 10.1007/s40653-015-0051-2

Understanding the Impact of Natural Disasters on Psychological Outcomes in Youth from Mainland China: a Meta-Analysis of Risk and Protective Factors for Post-Traumatic Stress Disorder Symptoms

Arlene T Gordon-Hollingsworth 1,2, Nisha Yao 2, Huijing Chen 2, Mingyi Qian 2,✉, Sen Chen 2
PMCID: PMC7163904  PMID: 32318151

Abstract

Post-traumatic Stress Disorder (PTSD) is a mental illness that causes significant distress and impairment. Studies generally indicate lower rates of PTSD post-disaster in Chinese child populations. Irrespective of population examined, findings suggest that trauma alone cannot account for the development of PTSD (Ma et al. 2011). It is important to understand what other variables may contribute to the onset of PTSD. This was the first meta-analysis conducted to investigate risk and protective factors for PTSD (as well as mediating/moderating variables) in children directly impacted by natural disasters in China. Understanding these factors can help guide disaster readiness efforts, as well as post-disaster interventions (Yule et al. 2000). Also, this study is extremely relevant given recent earthquakes in China that have devastated many.

Keywords: Adolescent, Children, Cultural issues, Mental health, Natural disasters

Introduction

Acute Stress Disorder and Post-traumatic Stress Disorder (PTSD) are mental illnesses that develop in reaction to a traumatic event and commonly co-occur with other psychological disorders. Research suggests that associated symptoms cause significant distress and impairment in social, academic, occupational, and cognitive functioning (Danckwerts & Leathem 2003). Although studies indicate that individuals who show significant stress reactions within 30 days following a trauma may not develop PTSD, a sizable number goes on to meet full diagnostic criteria for PTSD (Scheeringa et al. 2011).

Natural disasters are defined as major adverse events resulting from natural processes of the earth (Cutter et al. 2006). They have the capacity to negatively impact large groups of individuals at once, often causing destruction and injuries, as well as mortality (Neria et al. 2008; Norris et al. 2002). A subgroup of trauma investigators has focused on understanding this occurrence of PTSD relative to natural disasters. The most common natural disasters in China are earthquakes and floods (Liu et al. 2006). Studies conducted in Mainland China show that a notable percent of child natural disaster victims meet criteria for PTSD post-trauma (though lower compared to purported Western rates; approximately 11–13 %; Fan et al. 2011a, b; Liu et al. 2011).

Collectively, these studies indicate that trauma alone cannot account for the development of PTSD, as most children do not go on to develop severe and impairing symptoms. Thus, it is important to understand what other variables may contribute to the onset of atypical stress reactions. Past studies identified potential risk and protective factors including demographic variables (e.g., gender, socioeconomic status), pre-trauma variables (e.g., previous trauma, parent psychopathology), objective and subjective trauma characteristics (e.g., disaster exposure, fear/threat), and post-trauma variables (e.g., displacement, social support) in children exposed to natural disasters (Ma et al. 2011; Ying et al. 2013).

Demographic Variables

Age and grade are examined variables in many studies investigating correlates and/or predictors of PTSD. Overall, results from studies exploring the role of age and grade on PTSD status post-natural disaster are inconclusive, with some finding age and grade to significantly predict PTSD and others not (Fan et al. 2011a, b; Green et al. 1991; Piyasil et al. 2007; Wang et al. 2012). One explanation for the inconsistencies in the literature regarding the influence of age and grade on the development of PTSD post-natural disaster is the idea that they may interact with other variables such as degree of natural disaster exposure and indirectly influence PTSD symptomatology (Groome and Soureti 2004).

In regards to gender, studies conducted in China mirror those of the vast array of studies conducted in Western countries examining psychological outcomes in children exposed to natural disasters—female child participants, generally, reported a significantly greater number of PTSD symptoms than their male counterparts (Bokszczanin 2007; Fan et al. 2011a, b; Ma et al. 2011). In regards to understanding factors related to stress response in children post-trauma, a variable that differentiates studies conducted in China from those of other countries is the reported number of children in a family. For many years, China has enforced a one child per couple policy for families living within the country; although the majority of Chinese families only consist of one child, a small number of families defy this expectation (namely families residing in distal rural communities; Hesketh et al. 2005). Studies conducted in China which observed the influence of sibling presence on child psychological adjustment following natural disasters suggest that an only child tends to fair better psychologically and emotionally than children with siblings; however, these studies noted major limitations, including failure to directly assess and statistically control for variables such as socioeconomic status and income, which differ substantially between one child and multiple child families and, thus, may confound findings (Fan et al. 2011a, b; Zhang et al. 2012).

Overall, studies examining higher parent level of educational attainment as a potential protective factor for development of PTSD post-natural disaster have not found significant results (Nugent et al. 2007). The exception is Zhang et al. (2012) who found that maternal education level was inversely associated with child PTSD symptoms. Further research is needed to explain, clarify, and understand this discrepancy.

Until recently, another major difference between China and most other countries was that the total population in rural areas exceeded that of urban locales (National Bureau of Statistics, 2013). Despite comparable population estimates, distinct differences are noted when observing urban versus rural areas; for instance, rural areas tend to be less dense, lack technology, have less access to public resources due to the “hukou” system, and consist of lower socioeconomic status families than urban areas (e.g., tall buildings; Fang 1993; Su and Heshmati 2013). Even with these differences, most studies conducted examining Chinese child participants have failed to identify urban or rural residence as a factor significantly impacting the experience and recovery related to natural disasters (Kun et al. 2009; Liu et al. 2010a, b, c). Fan et al. (2011a, b), however, found that residence interacted with family composition (i.e., only or multiple child) to significantly predict PTSD; namely, only children from urban areas had lower PTSD prevalence rates relative to other observed groups (Fan et al. 2011a, b).

Pre-Disaster Variables

Several pre-disaster variables are linked to the development of PTSD following exposure to a natural disaster; these include but are not limited to the experience of prior trauma and negative life events. Research suggests that children who have been exposed to past-trauma are more likely to meet criteria for PTSD than children encountering their first traumatic event; additionally, studies show a positive relationship between number of experienced traumas and/or negative life events and child reported PTSD symptoms (Mullet-Hume et al. 2008; Wu et al. 2011).

Objective and Subjective Trauma Variables

As natural disasters often result in infrastructural damage (e.g., collapsing of buildings and other industrial structures), as well as the destruction of geographical formations (e.g., uprooting of trees), it is not surprising that individuals exposed to natural disasters may experience related inopportune occurrences, including bereavement, personal injury, witnessing another’s injury or death, becoming trapped or buried, being separated from family, and the loss or damage of property (Hsu et al. 2002). Although these events are not necessarily considered equal in impact (Ni et al. 2013), overall, studies have found positive associations between experiencing these events and PTSD symptomatology post-natural disaster; thus, they are each considered potential risk factors (Kun et al. 2009).

Subjective trauma variables that are explored in this paper include level of disaster exposure and perceived threat and/or fear. Research has generally shown a positive relationship between level of disaster exposure and PTSD symptom level (Lonigan et al. 1991; Neria et al. 2008). However, contrasting results were obtained in Wang et al. (2000); lower levels of disaster exposure were associated with higher frequency of PTSD. According to the authors, variables such as differential access to resources may indirectly account for this conflicting finding (Wang et al. 2000). The current study will attempt to clarify what impact disaster exposure level has on PTSD symptom level in Chinese populations.

The experience of extreme fear, many times accompanied by a feeling of helplessness, in relation to a traumatic event is a required criterion for diagnosis of PTSD (Brewin et al. 2000); however, the degree of perceived fear or threat is subjective, as all individuals will not experience the same situation in the same manner. Studies have attempted to quantify level of perceived fear/threat; these findings suggest a positive significant relationship between perceived fear/threat and PTSD symptomatology in children post-disaster (Wang et al. 2012; Ying et al. 2013).

Post-Disaster Individual and Environmental Variables

Several post-disaster individual variables have been examined in relation to PTSD status following a natural disaster, including coping style, PTSD at multiple time points, and other psychological symptoms (e.g., anxiety, depression). Coping style has been thoroughly examined in the disaster literature; research indicates that negative coping styles such as passive or avoidant coping are associated with higher levels of PTSD symptoms; whereas, positive coping styles such as active or ameliorative coping is associated with more favorable outcomes, including fewer PTSD symptoms (Norris et al. 2002).

Research has demonstrated a positive correlation between PTSD status at one time point and a subsequent time point; such findings support the notion that individuals who meet criteria for PTSD following a trauma are also likely to meet criteria for PTSD when assessed again at a later time point (Ying et al. 2012).

Although most trauma studies focus on measurement of post-trauma psychological symptoms, often due to problems related to retrospective recall, studies have shown that individuals who report significant symptoms of anxiety and/or depression prior to a trauma are more likely to develop clinically elevated symptoms of PTSD following a natural disaster (Ying et al. 2012). Coinciding with these findings, studies that have only collected prospective data show that both anxiety and depression have strong and positive relationships with PTSD symptomatology (Wang et al. 2012). The influence of this and the other aforementioned predictors will be further examined in the current study.

Research indicates that several post-disaster environmental factors may predict psychological adjustment following trauma exposure (Trickey et al. 2012); variables that were observed in this study include living arrangements following trauma, utilization of mental health services, social support, and familial atmosphere, specifically, family violence. For many families affected by natural disasters, the lingering damage and loss is so extensive they are displaced and forced to live in shelters or temporary housing (Kun et al. 2009). Research indicates that displacement is predictive of PTSD status in children who have experienced natural disasters (Asarnow et al. 1999). Findings appear to, however, be moderated by level of damage (Kun et al. 2009); thus, both displacement and housing damage will be examined in this study.

Few studies have examined post-disaster utilization of mental health services. Research suggest use of mental health services directly following trauma can be beneficial to families and even predicts more positive outcomes in children (McMillen et al. 1997). Unfortunately, the availability of mental health services directly following a trauma is generally limited due to a multitude of factors (e.g., widespread disruption, perceived barriers, and shortage of mental health professionals; Rodriguez and Kohn 2008). This is an important variable to observe, as it has the potential to impact future disaster preparedness planning (Jacob et al. 2007; Shen et al. 2006).

Social support literature provides sound evidence that in times of distress, social support promotes and protects psychological wellbeing, leading to better overall adjustment (López and Salas 2006). Also, social support is believed to act as a buffer that heightens the tolerance of inopportune life events; numerous studies support this premise (Cryder et al. 2006; Vigil and Geary 2008).

Research on natural disasters have found that associated trauma exposure has the potential to negatively impact and disrupt the family environment; parental stress and probable parent psychopathology following natural disasters tends to influence parent–child interactions post-trauma (Costa et al. 2009; Norris et al. 2002). For example, studies investigating predictors of PTSD in children and their families exposed to natural disasters have found family violence, specifically corporal punishment, to be positively associated with PTSD (Kelley et al. 2010; Lau et al. 2010; Yu et al. 2010).

Collectively, several limitations exist in the discussed studies; first, these studies were not all conducted with Chinese samples. Although research suggests that, despite cultural differences between Western and non-Western societies (e.g., collectivism versus individualism), there are more similarities than differences in stress reactions across varying populations; examining the Chinese child population in isolation will allow researchers to speculate with a higher degree of certainty what distinctions may exist, if any. Second, past research pinpointing risk and protective factors for children experiencing natural disasters in China have been limited in success due to mixed findings across studies; these discrepancies may be due to varying study procedures, sample sizes, and apparatus.

Meta-analysis is an analytical technique designed to summarize the results of multiple studies; such an approach may prove beneficial in clarifying and gaining new knowledge, as it, by combining studies, increases the sample size and thus the power to explore effects of interest (Borenstein et al. 2011). In addition, meta-analysis allows comparison of estimated effect sizes achieved through use of varying measurement techniques or instruments and allows researchers to assign weights to studies whose results may be weighted lower due to methodological differences when compared to other studies (Borenstein et al. 2011).

The current study was the first meta-analysis to investigate risk and protective factors for PTSD, as well as factors that may indirectly impact the relationship between these risk and protective factors and PTSD (i.e., mediating and moderating variables) in children directly impacted by natural disasters in China. This study thoroughly examined and consolidated all existing research of sufficient quality investigating risk and protective factors of PTSD in children impacted by natural disasters of various types in the People’s Republic of China using random-effects meta-analytic techniques. This work is vital, as it aims to not only clarify past findings but also distinguish any cultural differences that may exist by comparing findings to like studies conducted utilizing western samples (e.g., Cox et al. 2008; Trickey et al. 2012). In regards to hypotheses, this paper was exploratory in nature and thus, did not postulate specific outcomes a priori.

Method

Sample

Selection of Studies for the Meta-analysis

Literature search for relevant articles involved search engines geared toward finding both English, as well as Mandarin language articles within the last decade and a half (2000 onward). A variety of psychological and medical literature databases were searched (e.g., PSYCinfo, medline). Emphasis was placed on locating articles published in peer-reviewed journals and open access sites with an acceptable standard of scrutiny (e.g., blind peer review, review by at least two reviewers). To ensure a thorough search, secondary sources such as review articles and book chapters, as well as the reference sections of selected articles were examined as a means to locate other potential studies for inclusion. Search terms for the literature databases included the word China and combinations of the following: PTSD, post-traumatic/posttraumatic stress disorder, child, children, adolescent, youth, risk, protective, predictor, and/or prediction. A predictor or risk or protective factor was operationally defined as any variable explored as a potential contributor to variability in PTSD symptomatology or diagnostic status. This initial literature search yielded a preliminary database of over 200 published articles. In addition, to proactively guard against publication biases, researchers known for conducting research investigating mental health outcomes in Chinese samples affected by natural disasters, based on names and universities that commonly appeared during the literature search, as well as through systematic internet searches, were contacted regarding the current study and asked to contribute relevant unpublished papers (e.g., manuscripts, theses, dissertations). As a result, three unpublished manuscripts or papers were provided. These, as well as the published articles were reviewed for inclusion in the meta-analysis using predetermined inclusion and exclusion criteria.

Inclusion and Exclusion Criteria

To be included in the analysis, studies had to have 1) assessed acute stress or PTSD utilizing measures developed for use in child or adolescent populations (ages 6–18 years) that considered all three symptom clusters (intrusion, avoidance, and hyperarousal) and demonstrated adequate reliability and validity as shown by publication of their psychometric properties or by having good reliability and validity generalizability given data (e.g., reliability estimates, criterion validity estimates) provided by its use in a number of other studies and 2) examined children who had recently experienced a natural, not man-made, disaster in mainland China.

Articles were excluded based on the following grounds: 1) The study employed a categorical measure of acute stress or PTSD that failed to take into account the three symptom clusters; 2) the study sample lacked variability (e.g., consisted entirely of individuals who met full diagnostic criteria for PTSD) and thus, were not suitable for ascertaining the frequencies of PTSD symptomatology; 3) the study sample was selected on the basis that participants were experiencing a comorbid psychiatric disorder other than acute stress or PTSD (e.g., depression, anxiety), which would limit generalizability; 4) the article or paper did not provide sufficient data to calculate univariate effect sizes; 5) the article or paper was a review that did not present new data or only presented qualitative findings; 6) the article or paper presented a single case study; and 7) the article or paper examined a risk or protective factor that was not also examined by at least one other included study.

All eligible studies were carefully reviewed by at least two authors utilizing the aforementioned criteria to ensure decision-making consistency, with 100 % agreement. A total of 59 studies with a total sample size of 88,045 participants yielded 302 effect sizes that were included in the meta-analysis. Three of the studies assessed acute stress disorder due to employed measures or evaluation time-point; these studies were included, given the considerable overlap with assessed PTSD related symptoms and in addition, investigators felt they had the potential to remarkably contribute to the study. Table 1 provides a full list of the data extracted from each study for each risk or protective factor and Table 2 provides a detailed list of characteristics of the studies used in the meta-analysis.

Table 1.

Final list of risk and protective factors from included studies with descriptive statistics of the overall effect sizes from each study

Risk/protective factor Article name Assessment of risk factor k SD Min. Max. Mean r
Age 21 0.316 −0.161 0.308
Fan et al. (2011a, b) Demographic information 0.308
Fan et al. (2010) Demographic information 0.158
Fu and Y.-H (2011) Demographic information 0.000
Jia et al. (2010) Demographic information 0.107
Jing et al. (2012) Demographic information 0.074
Li et al. (2009) Demographic information 0.024
Liu et al. (2010a, b, c) Demographic information 0.139
Liu et al. (2003) Demographic information 0.080
Liu et al. (2010b) Demographic information 0.163
Liu et al. (2011) Demographic information 0.076
Peng et al. (2011) Demographic information 0.071
Zhang et al. (2012) Demographic information 0.050
Scott, Chen, Zhang, Liu, Liu, & Dyregrov (2012) Demographic information 0.240
Wang et al. (2012) Demographic information 0.037
Xin et al. (2010) Demographic information 0.043
Ying et al. (2013) Demographic information 0.200
Zheng (2011) Demographic information 0.100
Zheng et al. (2012) Demographic information −0.161
Zhou et al. (2014) Demographic information 0.077
Zhu et al. (2011) Demographic information 0.327

Grade

Gender

 11 0.192 −0.188 0.840
Fu and Y.-H (2011) Demographic information 0.017
Liao et al. (2008) Demographic information 0.157
Liu et al. (2011) Demographic information 0.353
Xia and Ding (2011) Demographic information −0.000
Xiang et al. (2010) Demographic information 0.045
Yu et al. (2010) Demographic information −0.188
Zang et al. (2009) Demographic information −0.185
Zhang et al. (2011a, b) Demographic information 0.073
Zhao and Zhao (2009) Demographic information 0.840
Zheng (2011) Demographic information 0.093
Zhu et al. (2013) Demographic information 0.150
39 0.354 0.005 0.918
An et al. (2013) Demographic information 1.68
Du et al. (2012b) Demographic information 0.018
Du et al. (2012b) Demographic information 0.088
Fan et al. (2011a, b) Demographic information 0.173
Fan et al. (2010) Demographic information 0.243
Fu and Y.-H (2011) Demographic information 0.005
Jia et al. (2010) Demographic information 0.167
Jing et al. (2009) Demographic information 0.207
Jing et al. (2012) Demographic information 0.158
Li et al. (2009) Demographic information 0.252
Li et al. (2011) Demographic information 0.003
Liao et al. (2008) Demographic information 0.030
Liu et al. (2003) Demographic information 0.010
Liu, Fan et al. (2010) Demographic information 0.119
Liu et al. (2011) Demographic information 0.016
Liu et al. (2010a, b, c) Demographic information 0.139
Ma et al. (2011) Demographic information 0.164
Peng et al. (2011) Demographic information −0.005
Scott et al. (2012) Demographic information 0.018
Sun et al. (2012) Demographic information 0.103
Wang et al. (2010) Demographic information 0.061
Wang et al. (2012) Demographic information 0.109
Xia and Ding (2011) Demographic information 0.033
Xiang et al. (2010) Demographic information 0.082
Xin et al. (2010) Demographic information 0.144
Ye et al. (2011) Demographic information 0.104
Ying et al. (2013) Demographic information 0.120
Zang et al. (2009) Demographic information 0.196
Zhang et al. (2012) Demographic information 0.270
Zhang et al. (2011a, b) Demographic information 0.061
Zhang et al. (2013) Demographic information 0.038
Zhao and Zhao (2009) Demographic information 0.918
Zhao et al. (2008) Demographic information 0.493
Zheng (2011) Demographic information 0.120
Zheng et al. (2012) Demographic information 0.070
Zhou et al. (2014) Demographic information 0.100
Zhu et al. (2011) Demographic information 0.208
Zhu et al. (2013) Demographic information 0.081
Only child 5 0.105 −0.103 0.0605
Fan et al. (2011a, b) Demographic information 0.021
Fan et al. (2010) Demographic information −0.103
Liu, Fan et al. (2010) Demographic information 0.065
Zhang et al. (2012) Demographic information −0.050
Zheng (2011) Demographic information 0.030
Father education 5 0.089 −0.173 0.021
Fan et al. (2011a, b) Demographic information 0.021
Fan et al. (2010) Demographic information −0.173
Zhang et al. (2012) Demographic information −0.021
Zhang et al. (2013) Demographic information −0.060
Zheng (2011) Demographic information −0.050
Mother education 5 0.095 −0.169 0.068
Fan et al. (2011a, b) Demographic information 0.068
Fan et al. (2010) Demographic information −0.169
Zhang et al. (2012) Demographic information −0.023
Zhang et al. (2013) Demographic information −0.073
Zheng (2011) Demographic information −0.040
Urban vs. rural 7 0.095 0.050 0.172
Liu et al. (2010b) Demographic information 0.114
Fan et al. (2011a, b) Demographic information 0.172
Fan et al. (2010) Demographic information 0.169
Xiang et al. (2010) Demographic information 0.054
Ye et al. (2011) Demographic information 0.070
Zheng (2011) Demographic information 0.050
Zheng et al. (2012) Demographic information 0.050
Physical health 3 0.055 0.207 0.340
Peng et al. (2011) The Rutter Parent Scale Chinese Version (Parents report, Rutter, 1967; Wong, 1988) −207
Zhao et al. (2008) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.260
Zheng et al. (2012) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.340
Negative life events 5 0.077 0.151 0.490
Fan et al. (2011a) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.490
Li et al. (2011) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.151
Liu et al. (2010b) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.388
Zheng (2011) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.480
Zheng et al. (2012) Adolescent Self-Rating Life Events Checklist (ASLEC; Liu et al., 1997) 0.480
Prior trauma 3 0.055 0.052 0.170
Ying et al. (2013) Study Questionnaire 0.170
Zhang et al. (2012) Study Questionnaire 0.052
Yu et al. (2010) Study Questionnaire 0.128

Bereavement (Family Member)

Family Member Injured

 12 0.009 .0.559
Du et al. (2012a, b) Study Questionnaire 0.036
Fan et al. (2011a, b) Study Questionnaire 0.232
Fan et al. (2010) Study Questionnaire 0.432
Jia et al. (2010) Earthquake exposure scale (Roussos et al. 2005) 0.462
Li et al. (2010d) Study Questionnaire 0.313
Liu, Fan et al. (2010) Study Questionnaire 0.189
Liu et al. (2011) Study Questionnaire 0.559
Xin et al. (2010) Study Questionnaire 0.038
Zhang et al. (2011b) Study Questionnaire 0.041
Zhao et al. (2001) Study Questionnaire 0.009
Zheng (2011) Study Questionnaire 0.170
Zheng et al. (2012) Adolescent Self-rating Life Events Checklist (ASLEC; Liu, et al., 1997) 0.150
8 0.221 0.027 0.234
Du et al. (2012a) Study Questionnaire 0.036
Fan et al. (2011b) Study Questionnaire 0.234
Jia et al. (2010) Earthquake exposure scale (Roussos et al. 2005) 0.123
Jing et al. (2012) Study Questionnaire 0.027
Li et al. (2010d) Study Questionnaire 0.111
Sun et al. (2012) Study Questionnaire 0.097
Zhang et al. (2012) Study Questionnaire 0.034
Zhao et al. (2001) Study Questionnaire 0.104
Other injured/killed 7 0.190 0.072 0.339
Jia et al. (2010) Study Questionnaire 0.339
Jing et al. (2009) Study Questionnaire 0.159
Li et al. (2009) Study Questionnaire 0.075
Li et al. (2010d) Study Questionnaire 0.128
Ma et al. (2011) Study Questionnaire 0.072
Zhang et al. (2011b) Study Questionnaire 0.078
Zhu et al. (2011) Study Questionnaire 0.226
Witnessed other injury/death 13 0.219 0.014 0.557
Jia et al. (2010) Earthquake exposure scale (Roussos et al. 2005) 0.342
Jing et al. (2012) Study Questionnaire 0.073
Li et al. (2010d) Study Questionnaire 0.557
Liu, Fan et al. (2010) Study Questionnaire 0.141
Liu et al. (2011) Study Questionnaire 0.280
Ma et al. (2011) Study Questionnaire 0.138
Peng et al. (2011) Study Interview 0.018
Wang et al. (2012) Study Questionnaire 0.087
Xin et al. (2010) Study Questionnaire 0.014
Ying et al. (2013) Study Questionnaire 0.220
Zhang et al. (2011b) Study Questionnaire 0.051
Zhu et al. (2011) Study Questionnaire 0.197
Zhu et al. (2013) Study Questionnaire 0.127
Separated from family 2 0.009 0.072
Li et al. (2010d) Study Questionnaire 0.072
Peng et al. (2011) Study Interview 0.009
Personal injury 14 0.277 0.004 0.370
Jia et al. (2010) Earthquake exposure scale (Roussos et al. 2005) 0.351
Jing et al. (2009) Study Questionnaire 0.056
Jing et al. (2012) Study Questionnaire 0.187
Li et al. (2009) Study Questionnaire 0.050
Li et al. (2010d) Study Questionnaire 0.160
Liu et al. (2011) Study Questionnaire 0.155
Ma et al. (2011) Study Questionnaire 0.370
Xiang et al. (2010) Study Questionnaire 0.039
Xin et al. (2010) Study Questionnaire 0.017
Ye et al. (2011) Study Questionnaire 0.241
Zhang et al. (2012) Study Questionnaire 0.004
Zhang et al. (2011b) Study Questionnaire 0.045
Zhao et al. (2001) Study Questionnaire 0.187
Zhu et al. (2011) Study Questionnaire 0.184
Hospitalization/surgery/amputation 4 0.037 0.441
Jing et al. (2012) Study Questionnaire −0.052
Li et al. (2009) Study Questionnaire 0.037
Liu et al. (2010a) Study Questionnaire 0.441
Zhu et al. (2011) Study Questionnaire −0.144
Trapped/buried 7 0.241 0.052 0.567
Jing et al. (2012) Study Questionnaire 0.052
Li et al. (2009) Study Questionnaire 0.567
Li et al. (2010d) Study Interview 0.111
Liu et al. (2011) Study Interview 0.070
Liu et al. (2010a) Study Questionnaire 0.501
Zhu et al. (2011) Study Questionnaire 0.180
Zhu et al. (2013) Study Questionnaire 0.307
House damage 14 0.195 0.010 0.235
Fan et al. (2011b) Study Questionnaire 0.052
Fan et al. (2011a) Study Questionnaire 0.090
Fan et al. (2010) Study Questionnaire 0.213
Jia et al. (2010) Earthquake exposure scale (Roussos et al. 2005) 0.157
Liu, Fan et al. (2010) Study Questionnaire 0.027
Ma et al. (2011) Study Questionnaire 0.182
Sun et al. (2012) Study Questionnaire 0.080
Wang et al. (2012) Study Questionnaire 0.235
Ye et al. (2011) Study Questionnaire 0.140
Ying et al. (2013) Study Questionnaire 0.180
Zhang et al. (2012) Study Questionnaire 0.020
Zhao et al. (2001) Study Questionnaire 0.058
Zheng (2011) Dissertation Study Questionnaire 0.100
Zheng et al. (2012) Study Questionnaire 0.010
Loss of property 9 0.110 0.028 0.250
Fan et al. (2011b) Study Questionnaire 0.074
Liu, Fan et al. (2010) Study Questionnaire 0.060
Sun et al. (2012) Study Questionnaire 0.073
Xiang et al. (2010) Study Questionnaire 0.028
Zhang et al. (2011b)) Study Questionnaire 0.130
Zhao et al. (2001) Study Questionnaire 0.068
Zhao et al. (2008) Study Questionnaire 0.250
Zheng (2011) Dissertation Study Questionnaire 0.120
Zheng et al. (2012) Study Questionnaire 0.050

Trauma severity

Perceived Threat/Fear

Positive Coping

 19 0.167 0.004 0.328
Du et al. (2012a) Study Questionnaire 0.004
Fan et al. (2011b) Study Questionnaire 0.189
Fan et al. (2011a) Study Questionnaire 0.190
Fan et al. (2010) Study Questionnaire 0.328
Fu and Y.-H (2011) Study Questionnaire 0.221
Li et al. (2010d) Area affected by flood 0.016
Li et al. (2011) Proximity to epicenter −0.205
Liu et al. (2003) Study Interview 0.307
Peng et al. (2011) Area affected by flood 0.137
Sun et al. (2012) Study Questionnaire 0.131
Wang et al. (2010) Study Questionnaire 0.101
Wang et al. (2012) Children’s Revised Impact of Event Scale (CRIES-13). 0.161
Zhang et al. (2010) Distance from epicenter, level of impact 0.215
Zhang et al. (2012) Study Questionnaire 0.075
Zhang et al. (2011b) Study Questionnaire 0.062
Zheng (2011) Study Questionnaire 0.180
Zheng et al. (2012) Study Questionnaire 0.120
Zhou et al. (under review) Study Questionnaire 0.080
Zhu et al. (2013) Study Questionnaire 0.182
6 0.214 0.129 0.371
Jia et al. (2010) Earthquake exposure scale (Roussos et al. 2005) 0.304
Jing et al. (2012) Study Questionnaire 0.128
Liu et al. (2011) Study Questionnaire 0.193
Wang et al. (2012) Study Questionnaire 0.328
Xin et al. (2010) Study Questionnaire 0.305
Zhao et al. (2001) Study Questionnaire 0.355
5 0.077 −0.114 −0.340
Jiang et al. (2013) Simplified Coping Style Questionnaire (Xie, 1999) −0.327
Liu et al. (2010b) Children Simple Coping Style Questionnaire (Xie, 1998) −0.187
Zhang et al. (2010) Coping Scale, CS (Xiao & Xu, 1996) −0.114
Zheng (2011) Simplified Coping Style Questionnaire (Xie, 1998) −0.140
Zheng et al. (2012) Simplified Coping Style Questionnaire (Xie, 1998) −0.140
Negative coping 5 0.071 0.224 0.548
Jiang et al. (2013) Simplified Coping Style Questionnaire (Xie, 1998) 0.499
Liu et al. (2010b) Children Simple Coping Style Questionnaire (Xie, 1998) 0.265
Zhang et al. (2010) Coping Scale, CS (Xiao & Xu, 1996) 0.316
Zheng (2011) Simplified Coping Style Questionnaire (Xie, 1998) 0.240
Zheng et al. (2012) Simplified Coping Style Questionnaire (Xie, 1998) 0.220
PTSD T1 7 0.100 −0.096 0.621
Du et al. (2012a) Children’s Revised Impact of Event Scale (Perrin, Meiser-Stedman, & Smith, 2005) −0.115
Fan et al. (2011a) PTSD Self-rating Scale (Liu, Ma, & Liu, 1998)
0.540
Liu et al. (2011) Trauma Symptom Checklist for Children-Alternate Version (Briere, 1996) −0.097
Ye et al. (2011) PTSD Checklist-Civilian Chinese Version (Wu et al. 2008) −0.109
Ying et al. (2012) Child PTSD Symptom Scale (Foa, Johnson, Feeny, & Treadwell, 2001) 0.621
Zhang et al. (2011a) Children’s Revised Impact of Event Scale (Perrin, Meiser-Stedman, & Smith, 2005) −0.096
Zheng (2011) PTSD Self-rating Scale (Liu, Ma, & Liu, 1998) −0.466
Anxiety 2 0.032 0.414 0.510
Fan et al. (2011b) The Screen for Child Anxiety Related Emotional Disorders (Birmaher, Khetarpal, & Brent, 1997) 0.470
Tao et al. (2009) The Screen for Child Anxiety Related Emotional Disorders (Birmaher, Khetarpal, & Brent, 1997) 0.392
Depression 7 0.122 0.247 0.780
Fan et al. (2011b) The Depression Self-rating Scale for Children (Birleson, 1981) 0.640
Jing et al. (2009) The Depression Self-rating Scale for Children (Birleson, 1981) 0.708
Li et al. (2011) Children’s Depression Inventory Chinese Version, CDI (Yu & Li 2000) 0.247
Tao et al. (2009) The Depression Self-rating Scale for Children (Birleson, 1981) 0.294
Ying et al. (2013) Center for Epidemiologic Studies Depression Scale for Children (Cheung & Bagley, 1998) 0.780
Ying et al. (2012) Center for Epidemiologic Studies Depression Scale for Children (Cheung & Bagley, 1998) 0.715
Zhang et al. (2012) Beck Depression Inventory Chinese Version, BDI (Shek, 1990) 0.499
Utilization of mental health services 2 0.204 0.49 0.358
Jia et al. (2010) Study Interview 0.358
Zhang et al. (2011b) Study Questionnaire 0.049
Displacement 2 0.000 0.046 0.070
Jing et al. (2012) Study Questionnaire 0.046
Ying et al. (2013)** Study Questionnaire 0.070
Social support 8 0.100 −0.224 −0.008
Fan et al. (2011a) Social Support Questionnaire (Wang, 1999) −0.150
Fan et al. (2010) Social Support Rating Scale for Children and Adolescent, SSRS-CA (Xiao, 1999) −0.053
Liu et al. (2009) Perceived Social Support Scale, PSSS (Jiang, 2001) −0.208
Ma et al. (2011) Social Support Rating Scale, SSRS (Xiao, 1999; Tan et al. 2011) −0.163
Ye et al. (2011) Perceived Social Support Scale, PSSS (Jiang, 2001) −0.008
Zang et al. (2009) Subjective Perception of Social Support Scale, SPSS (Furman & Buhrmester, 1985; Zhou et al. 2014) −0.224
Zheng (2011) Social Support Rating Scale, SSRS (Xiao, 1999) −0.140
Zheng et al. (2011) Social Support Rating Scale, SSRS (Xiao, 1999) −0.170
Family violence 2 0.045 0.022 0.528
Li et al. (2010d) Study Questionnaire 0.528
Lau et al. (2010) Study Questionnaire 0.022
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k = the number of effect sizes

Table 2.

Characteristics of included studies

Article Disaster type Sample size Acute stress/PTSD measure Age range Mean age %Male
An et al. 2013, Mud-rock flow 554 PCL-C 8–18 N/A 47.1 %
Chen et al. 2012a, b Earthquake 268 PCL-C 8–18 12.58 (2.19) 45.9 %
Du et al. 2012a Earthquake 522 CRIES 8–12 11.6 47.5 %
Du et al. 2012b Earthquake 553 CRIES-13 10–16 11.61 (1.48) 48.1 %
Fan et al. 2010 Earthquake 1925 PTSD-SS 11–18 14.6 (1.3) 86 %
Fan et al. 2011a Earthquake 1074 PTSD-SS 11–17 N/A 42.4 %
Fan et al. 2011b Earthquake 2081 PTSD-SS 14–17 14.6 (1.3, male) 14.5(1.3, female) 45.9 %
Fu 2011 Earthquake 2132(Control) 1988(intervention) UCLA-PTSD Index for DSM-IV 6–16 11.7 (2.18) 11.1(1.89) 50 % 48 %
Han et al. 2012 Earthquake 188 MHS (modified version) 11–15 13.76 (0.8) 45.2 %
Hu and Zhao 2010 Earthquake 456 SCL-90 14–18 16.98 (4.67) 42.1 %
Jia et al. 2010 Earthquake 596 UCLA PTSD Reaction Index 8–16 11.4 (2.2) 49.8 %
Jiang et al. 2013 Mud-rock flow 592 PCL-C 8–18 13.1 47.5 %
Jing et al. 2009 Earthquake 278 UCLA PTSD Index for DSM-IV 14–16 15.6 49.6 %
Jing et al. 2012 Earthquake 1498 CRIES-13 11–16 13.66 (2.83) 51.8 %
Lau et al. 2010 Earthquake 3324 CRIES N/A N/A 54.3 %
Li et al. 2009 Earthquake 99 CPSS 8–18 12.56 (3.26) 42.4 %
Li et al. 2011 Earthquake 341 CRIES 12–16 13.40 (0.77) 44.58 %
Li et al. 2010d Flood 4327 DSM-IV diagnostic interview 7–15 N/A 52.3 %
Li et al. 2010a Earthquake 962 The screen for child anxiety related emotional disorders 6–16 11.7 N/A
Li et al. 2010b Earthquake 370 MHS 11–17 N/A 51.6 %
Li et al. 2010c Earthquake 370 MHS 8–18 13.8 51.6 %
Liao et al. 2008 Earthquake 3239 CRIES-13 10–19 14.5 54.2 %
Liu et al. 2003 Flood 6555 Research interview based on DSM-IV Criteria for PTSD 7–15 N/A N/A
Liu et al. 2009 Earthquake 1958 PCL-C N/A N/A 47.2 %
Liu et al. 2011 Earthquake 330 TSCC-A 8–11 10.36 (0.98) N/A
Liu, Fan et al. 2010 Earthquake 2004 PTSD-SS 11–17 14.6 45.9 %
Liu et al. 2010a Earthquake 105 ASDS 5–18 11.77 (3.79) 47.6 %
Ma et al. 2011 Earthquake 3208 CRIES, K-SADS-PL 12–18 13.8 (1.1) 47.9 %
Peng et al. 2011 Flood 7038 DSM-IV diagnostic interview 7–15 N/A 53 %
Situ et al. 2009 Earthquake 1268 SDQ (Self-reported version) 11–17 14.2 (1.02) 49.5 %
Sun et al. 2012 Earthquake 984 PTSD-SS 16–18 16.5 43.0 %
Tan et al. 2011 Earthquake 147 Study Questionnaire 7–10 N/A 54.4 %
Tao et al. 2009 Earthquake 1925 PTSD-SS 11–18 14.6 46.0 %
Wang 2010 Earthquake 761 Study Questionnaire 1–3 N/A 52.7 %
Wang et al. 2010 Earthquake 1472 IES-R N/A 15.7 46.6 %
Wang et al. 2012 Earthquake 1841 CRIES-13 11–20 14.2 (1.2) 48.7 %
Xiang et al. 2010 Earthquake 1960 PCL-C 11–18 N/A 47 %
Xia and Ding 2011 Earthquake 617 IES-R N/A N/A 46.68 %
Xin et al. 2010 Earthquake 587 LASC 15–20 17.28 (0.79) 48 %
Yang et al. 2010 Earthquake 252 PTGI 10–17 13.98 (1.13) 52.78 %
Ye et al. 2011 Earthquake 1958 PCL-C N/A N/A 47.2 %
Ying et al. 2012 Earthquake 200 CPSS 13.6–16.4 N/A 38 %
Ying et al. 2013 Earthquake 3052 CPSS 8–19 13.31 (2.27) 46.5 %
Yu et al. 2010 Earthquake 3324 CRIES N/A N/A 54.3 %
Zang et al. 2009 Earthquake 338 CPSS N/A 15.6 (1.76) 41.4 %
Zhang et al. 2011b Earthquake 1976 PCL-C 12–20 15.34 (1.4) 45.7 %
Zhang et al. 2012 Earthquake 737 PCL-C 15–18 16.86 (0.58) 43.2 %
Zhang et al. 2010 Earthquake 188 (HEA) 235 (LEA) MHS 11–15 (HEA) 12–16 (LEA) 13.21 (0.62, HEA) 13.11 (0.60, LEA) 45.2 % (HEA) 43.8 % (LEA)
Zhang et al. 2011a Earthquake 585 CRIES 10–17 14.0 49.6 %
Zhang et al. 2013 Earthquake 1123 The UCLA PTSD Reaction Index for DSM-IV, Revision 1 11–17 14.0 48.1 %
Zhao et al. 2001 Earthquake 2001 Study Questionnaire 14–18 15.9 55.7 %
Zhao and Zhao 2009 Earthquake 413 DSM-IV diagnostic self-rating scale N/A 15.7 42.13 %
Zheng (2011) Earthquake 1573 PTSD-SS N/A 14.91 (1.32) 45.8 %
Zheng et al. 2011 Earthquake 1439 PTSD-SS N/A 15.96 (1.35, male), 15.93 (1.29, female) 45.2 %
Zheng et al. 2012 Earthquake 2250 PTSD-SS 12–15 14.5 (1.33) 45.9 %
Zhu et al. 2011 Earthquake 7341 CRIES 8–16 12 (1.8) 50.3 %
Zhou et al. (2014) Earthquake 304 UCLA PTSD Index, ASDS 9–17 12.06 (2.45) 44.4 %
Zhao et al. 2008 Earthquake 394 PTSD-SS 13–18 15.7 41.9 %
Zhu et al. 2013 Mud-rock flow 592 PCL-C 8–18 13.1 47.5 %
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1 ASDS Acute Stress Disorder Scale, CPSS Child PTSD Symptom Scale, CRIES Children’s Revised Impact of Event Scale, IES-R Impact of Event Scale-Revised, K-SADS-PL Schedule for Affective Disorders and Schizophrenia for School-Age Children (Kiddie-SADS-Present and Lifetime Version), LASC Los Angeles Symptom Checklist (King LA,1995), MHS Mental Health Scale (Psychology Association of China, 2000), PCL-C PTSD Checklist-Civilian Chinese Version, PTGI Posttraumatic Growth Inventory, PTSD-SS Post-traumatic stress disorder self-rating scale, SDQ Strengths and Difficulties Questionnaire (Goodman,2001), TSCC-A Trauma Symptom Checklist for Children-Alternate Version. 2 HEA high exposure area, LEA low exposure area

Procedure

Coding of Included Studies

Eligible studies were coded utilizing a detailed coding scheme. Effect-sizes for repeated measures of PTSD symptoms, both current and past, as well as longitudinal studies that presented multiple assessment time-points, were included. Simple mean was computed for studies contributing more than one effect-size for the same factor.

Meta-analysis was not carried out on any risk or protective factor in which only a single effect size was reported. Continuous measures were utilized over categorical measures, when both presented in a study due to the statistical advantages of continuous measures in correlational research.

Calculating of Effect Sizes

Pearson’s correlation coefficient, r, was chosen as the effect size for this study, as r is a common metric utilized in many studies, is easily interpreted, and can be easily computed from other provide indices of effect size (e.g., odds ratio, chi-square; Field 2001). Comprehensive Meta-analysis (CMA; Borenstein et al. 2000), a statistical software program designed specifically to carry out meta-analyses, was used to compute effect-sizes and covert effect-sizes not reported as r.

For categorical data, correlation coefficients were computed such that a positive correlation coefficient reflected a higher mean in the high PTSD symptom level group than the comparison group, and a negative correlation coefficient represented a lower mean in the high PTSD symptom level group than the comparison group. For continuous data, correlation coefficients were computed such that a positive correlation coefficient reflected more severe PTSD symptoms, and a negative correlation coefficient reflected less severe PTSD symptoms. Higher values of r indicate a stronger positive association with PTSD symptom level. Table 1 provides the effect sizes included in the meta-analysis for each risk or protective factor.

Statistical Approach

Meta-analyses were conducted using CMA. A separate meta-analysis was conducted for each risk or protective factor. Random-effect meta-analysis was performed for each predictor variable. This method was selected over the fixed-effect model based on findings from a study conducted by Field (2003), which demonstrated that fixed-effects model of meta-analysis may yield unreliable results (i.e., inflated estimates of population effect-sizes), specifically when examined effect sizes violate homogeneity rules, and result in increased Type I error probability. The Hedges’ method was applied using Fisher-transformed correlation coefficients with results reported upon transformation back to the Pearson product–moment correlation coefficient (Field 2001). Utilization of this method allowed each effect size to be weighted by a value reflecting both the within and between study variance (Cooper, Hedges, & Valentine, 2009).

In addition, moderator analyses were conducted in CMA to assess potential indirect effects of study related factors; examined variables were selected based on review of the literature, as well as construct level analysis (Wong et al. 2008) and included: Type of disaster, first evaluative time-point, and disaster severity as assessed by proximity to most severely impacted areas (e.g., epicenter). Potential continuous moderators were analyzed using unstandardized regression slopes via a meta-analytic analogue of regression, while categorical moderators were analyzed by between-group heterogeneity statistics using a meta-analytic analogue of ANOVA. In accordance with recommendations made by Borenstein et al. (2011) and Chen et al. (2012a, b), only significant risk and protective factors with at least eight effect sizes were included in the moderation analyses. Examined predictors were: Age, gender, bereavement, family member injured, witnessed other’s injury or death, personal injury, house damage, loss of property, subjective trauma severity (within study) and social support.

Results

Examination of Risk and Protective Factors

Seventy of the examined predictors yielded significant small to medium effect sizes, with Pearson’s correlation coefficients less than 0.3; these included: Age (older more vulnerable), gender (females more vulnerable), father level of education (higher education of paternal figure less vulnerable), urban versus rural residence prior to trauma exposure (rural residents more vulnerable), experience of prior trauma, bereavement, having a family member that was injured, knowing someone other than a family member (e.g., friend, classmate) who was injured or killed, witnessing someone get injured or killed, suffering personal injury during the trauma, becoming trapped or buried, house damage, loss of property, trauma severity (those with a higher or more severe degree of exposure more vulnerable), perceived threat or fear during the natural disaster (those who experienced a higher degree of fear or threat experienced more PTSD symptoms), positive coping (less use of positive coping related to increased PTSD symptomatology), displacement (those displaced as a result of the disaster more vulnerable), and social support (perception of inadequate social support associated with more PTSD symptoms).

Five of the examined predictors yielded medium to large effect sizes, with Pearson’s correlation coefficients greater than or equal to 0.3; these included: Negative life events, negative coping, the presence of anxiety post-trauma, the presence of depression post-trauma, and the presence of PTSD at a previous time point post-trauma. Those with high levels of anxiety and/or depression were also likely to have high levels of PTSD symptomatology.

As expected, given results from previous studies (Brewin et al. 2000; Cox et al. 2008) that utilized meta-analyses on this topic, although, not with Chinese participants, significant heterogeneity was observed amongst the majority of examined effect-sizes (based on the test of homogeneity for each explored risk or protective factor), indicating that the majority of the effect sizes were not uniform and varied significantly across studies. This variability may be random or systematic in nature, but, overall, suggest that risk and protective factors vary in the degree to which they predict; this should be kept in mind when interpreting results. The only significant predictors to exhibit relatively homogeneous effect-sizes were father education, urban versus rural residence, separation from family, trapped or buried, and displacement. Moderation analyses were conducted to, in part, explore whether sample or study characteristics accounted for the variable effect sizes (see below). Results of the Meta-analyses for individual risk and protective factors are presented in Table 3.

Table 3.

Individual meta-analysis of individual risk and protective factors

Risk/protective factor k γ2 Q Pest 95 confidence interval of Pest Z P
Lower Upper
Demographic variables
 Age 21 0.008 498.110*** 0.104 0.061 0.146 4.778 0.000***
 Grade 11 0.073 731.400*** 0.101 −0.061 0.259 1.221 0.222
 Gender 38 0.027 2199.839*** 0.141 0.088 0.194 5.159 0.000***
 Only child 5 0.002 11.312* 0.005 −0.051 0.060 0.164 0.869
 Father education 5 0.001 8.019 −0.049 −0.095 −0.003 −2.084 0.037*
 Mother education 5 0.003 12.995* −0.043 −0.101 0.016 −1.428 0.153
 Urban vs. rural 7 0.001 12.290 0.079 0.051 0.108 5.456 0.000***
Pre-trauma factors
 Physical health 3 0.145 569.11*** 0.135 −0.289 0.514 0.615 0.539
 Negative life events 5 0.010 56.100*** 0.413 0.335 0.485 9.452 0.000***
 Prior trauma 3 0.002 7.186* 0.127 0.067 0.186 4.141 0.000***
Objective trauma characteristics
 Bereavement (Family Member) 12 0.010 126.221*** 0.181 0.116 0.245 5.400 0.000***
 Family member injured 8 0.002 27.854*** 0.076 0.034 0.118 3.545 0.000***
 Other injured/killed (e.g., friend) 7 0.008 37.766*** 0.155 0.074 0.235 3.722 0.000***
 Witnessed other injury/death 13 0.009 169.740*** 0.146 0.089 0.203 4.943 0.000***
 Separated from family 2 0.001 1.504 0.022 −0.028 0.072 0.859 0.391
 Personal injury 14 0.007 96.342*** 0.134 0.080 0.187 4.843 0.000***
 Hospitalization/surgery/amputation 4 0.057 27.530*** 0.085 −0.169 0.328 0.652 0.514
 Trapped/buried 7 0.045 81.592 0.266 0.101 0.416 3.128 0.002**
 House damage 14 0.006 99.837*** 0.105 0.061 0.149 4.645 0.000***
 Loss of property (excluding home) 9 0.002 27.856** 0.088 0.055 0.121 5.191 0.000***
Subjective trauma characteristics
 Trauma severity 19 0.019 1106.753*** 0.135 0.072 0.198 4.155 0.000***
 Perceived threat/fear 6 0.016 38.509*** 0.263 0.149 0.371 4.418 0.000***
 Post-trauma individual factors
 Positive coping 5 0.004 23.047*** −0.181 −0.239 −0.121 −5.885 0.000***
 Negative coping 5 0.011 58.136*** 0.309 0.221 0.392 6.579 0.000***
 PTSD (Time 1) 7 0.051 406.690*** 0.307 0.147 0.451 3.674 0.000***
 Anxiety 2 0.004 9.298*** 0.432 0.353 0.505 9.576 0.000***
 Depression 7 0.120 762.596*** 0.584 0.388 0.730 5.057 0.000***
Post-trauma environmental factors
 Displacement 2 0.000 1.170 0.055 0.032 0.077 4.744 0.000***
 Utilization of mental health services 2 0.046 7.684** 0.190 −0.124 0.469 1.190 0.234
 Social support 9 0.010 218.045*** −0.137 −0.207 −0.065 −3.696 0.000***
 Family violence (e.g., corporal punishment) 2 0.159 165.042*** 0.294 −0.246 0.695 1.072 0.284
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*** = p < .001, ** p < .01, * p < .05, k number of studies, γ 2 tau square, Q test of heterogeneity, P est point of estimate, p p-value

Moderation Analyses

Moderation analyses of the categorical study related variables revealed a significant moderation effect of type of disaster (i.e., earthquake, flood, other) on gender and PTSD. In addition, a significant moderation effect was found for age range (i.e., younger/<12, older/<12 years, both) with regard to PTSD and gender, bereavement, witnessed other’s injury or death, subjective trauma severity, and social support. Analysis of the continuous variables indicated that first evaluative time point (i.e., within 1 month, <6 months, within 6–12 months, within 12–18 months, and >18 months) appeared to moderate the relationship between PTSD and age, gender, bereavement, witnessed other’s injury or death, house damage, subjective trauma severity, and social support. Finally, disaster severity, as assessed by the distance to the most severely impacted areas (e.g., epicenter; i.e., most severe, severe, moderate, mild) exhibited a moderation effect between PTSD and gender, house damage, and subjective trauma severity. See Table 4.

Table 4.

Moderation analyses of individual risk and protective factors

Risk/protective factor Moderator k Pest/b 95 confidence interval of Pest/b Q/Z p
Lower Upper
Age Disaster Type 21 1.055 0.304
Earthquake 0.106 0.050 0.161
Flood 0.075 0.059 0.092
Other – – –
Age Range 21 2.858 0.239
Younger 0.076 −0.118 0.265
Older 0.053 −0.009 0.115
Both 0.132 0.065 0.199
First Evaluative Time Point 21 0.00658 0.00079 0.01237 2.227 0.026*
Disaster Severity 21 −0.00965 −0.02893 0.00962 −0.981 0.326
Gender Disaster Type 39 25.651 0.000***
Earthquake 0.170 0.110 0.229
Flood 0.007 −0.019 0.033
Other 0.092 0.019 0.165
Age Range 39
Younger 0.040 −0.023 0.103 7.222 0.027*
Older 0.192 0.100 0.280
Both 0.101 0.048 0.153
First Evaluative Time Point 39 −0.04821 −0.05295 −0.04346 −19.907 0.000***
Disaster Severity 39 −0.02034 −0.03839 −0.00229 −2.209 0.027*
Bereavement Disaster Type 12 2.514 0.113
Earthquake 0.171 0.105 0.237
Flood 0.313 0.150 0.459
Other – – –
Age Range 39 6.904 0.032*
Younger 0.280 −0.280 0.698
Older 0.112 0.049 0.175
Both 0.343 0.181 0.487
First Evaluative Time Point 39 −0.01921 −0.03105 −0.00737 −0.3.179 0.001**
Disaster Severity – – – – – –
Family member injured Disaster Type 8 0.049 0.824
Earthquake 0.076 0.033 0.119
Flood 0.111 −0.195 0.397
Other – – –
Age Range 8 2.647 0.266
Younger 0.036 0.005 0.067
Older 0.094 0.021 0.166
Both 0.119 −0.063 0.294
First Evaluative Time Point 8 0.00883 −0.00131 0.01898 1.707 0.088
Disaster Severity – – – – – –
Witnessed other injury/death Disaster Type 13 0.413 0.814
Earthquake 0.141 0.087 0.195
Flood 0.300 −0.281 0.719
Other 0.127 0.057 0.196
Age Range 13 13.282 0.001**
Younger 0.280 0.098 0.444
Older 0.060 0.031 0.089
Both 0.196 0.109 0.279
First Evaluative Time Point 13 −0.02588 −0.03643 −0.01533 −0.4806 0.000***
Disaster Severity 13 −0.02276 −0.14629 0.10077 −0.361 0.718
Personal injury Disaster Type 14 0.033 0.857
Earthquake 0.133 0.078 0.187
Flood 0.160 −0.131 0.426
Other – – –
Age Range 14 1.378 0.502
Younger 0.155 −0.030 0.331
Older 0.118 0.050 0.185
Both 0.186 0.094 0.275
First Evaluative Time Point 14 0.02087 −0.01865 0.06039 1.035 0.301
Disaster Severity – – – – – –
House damage Disaster Type 14 – –
Earthquake 0.105 0.061 0.149
Flood – – –
Other – – –
Age Range 14 0.513 0.474
Younger – – –
Older 0.095 0.044 0.145
Both 0.139 0.029 0.244
First Evaluative Time Point 14 0.03827 0.02176 0.05478 4.543 0.000***
Disaster Severity 14 0.14823 0.09991 0.19655 6.01292 0.000***
Loss of property Disaster Type 9 – –
Earthquake 0.088 0.055 0.121
Flood – – –
Other – – –
Age Range 9 1.225 0.268
Younger – – –
Older 0.093 0.055 0.131
Both 0.060 0.016 0.104
First Evaluative Time Point 9 0.00521 −0.01008 0.02496 0.517 0.605
Disaster Severity – – – – – –
Trauma severity Disaster Type 19 1.101 0.577
Earthquake 0.129 0.069 0.189
Flood 0.148 0.019 0.273
Other 0.182 0.103 0.259
Age Range 19 48.669 0.000***
Younger 0.004 0.000 0.007
Older 0.114 0.070 0.157
Both 0.193 0.119 0.265
First Evaluative Time Point 19 −0.06988 −0.07566 −0.06410 −23.682 0.000***
Disaster Severity 19 0.15627 0.11514 0.19740 7.446 0.000***
Social support Disaster Type 9 – –
Earthquake −0.145 −0.214 −0.076
Flood – – –
Other – – –
Age Range 9 4.993 0.025*
Younger – – –
Older −0.158 −0.236 −0.077
Both −0.053 −0.097 −0.008
First Evaluative Time Point 9 −0.10518 −0.12072 −0.08963 −13.261 0.000***
Disaster Severity – – – – – –
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*** = p < .001, ** p < .01, * p < .05, k number of studies, P est point of estimate, b moderator estimate (slope), Q test of heterogeneity, Z z value, p p-value, (–) indicates that values could not me computed because of lack of observation or variability

Discussion

The current study examined multiple potential risk and protective factors of PTSD in youth exposed to natural disasters in Mainland China via meta-analysis of 59 studies, with a combined total of 88,045 participants and 302 effect sizes. Separate meta-analyses of individual predictors revealed small to medium effect sizes for the following risk factors: older age, female gender, rural locale, previous trauma, having a family member or knowing someone other than a family member who was injured or killed during the natural disaster, witnessing another’s death or injury, sustaining a personal injury oneself, becoming trapped or buried in disaster related debris, house damage, loss of personal property, high subjective trauma severity, greater perceived fear/threat related to the trauma, and displacement. In regards to protective factors, small to medium effect sizes were found for father higher level of education, greater use of positive coping, and higher levels of perceived social support. Additionally, the following risk factors demonstrated medium to large effect sizes: Endorsement of negative life events, greater use of negative coping, the presence of anxiety post-trauma, the presence of depression post-trauma, and PTSD at a prior evaluative time point following the natural disaster.

Due to high levels of heterogeneity across effect sizes, as well as theoretical and construct level reasoning, moderation analyses were conducted examining the potential indirect effects of study related characteristics, including disaster type, age range, first evaluative time point, and across study disaster severity (based on proximity to most severely affected regions) on the relationship between PTSD and significant risk and protective factors. Results suggest that the relationship between older age and PTSD incidence post-disaster appeared to be moderated by study determined evaluative time point, with more differences being seen across age level the further out the first evaluation time point was from the experienced disaster (e.g., 12 months versus 3 months post-disaster). Although females experienced a higher degree of PTSD symptoms than males, moderation analyses indicated that multiple variables perhaps influenced the magnitude of this relationship; specifically, effect size differences among females and males were most notable when the experienced disaster was an earthquake, when studies utilized an older age range of participants, when the first evaluative time point was earlier versus later, and in studies that included participants from the most ravaged, devastated areas. Both bereavement and the witnessing of another’s injury or death were significant risk factors for PTSD; effect sizes were, however, larger in studies that included a wider age range of participants and conducted first evaluations of PTSD symptomatology or incidence earlier. Additionally, meta-analysis findings provided evidence that house damage resulting from a natural disaster is predictive of PTSD, though this relationship appears to be influenced by first evaluative time point and disaster severity, as greater effect sizes were reported in studies that began assessment at a later time point and observed participants from less severely impacted areas (i.e., severe or moderate versus most severe). The current study found that high trauma severity level was a risk factor for PTSD; this relationship was, however shown to be moderated by first evaluative time point and disaster severity via proximity to worse impacted areas (study characteristic), as reported effect sizes were larger for studies in which initial assessment was closer to the actual date of the natural disaster and in studies that examined child participants with severe or moderate levels of disaster severity exposure versus most severe levels. Finally, analyses revealed that the relationship between social support and PTSD was moderated by study age range and first evaluative time point; larger effect sizes were reported for studies with a wider age range of child participants and that first examined PTSD symptoms on dates closer to the experienced trauma.

As expected, more similarities than differences were found when comparing the results of the current study to other meta-analyses conducted utilizing Western, instead of solely Chinese samples. In alignment with findings from Cox et al. (2008) and Trickey et al. (2012), significant effect sizes were found for gender, negative life events or exposure to prior trauma, other psychological problems (e.g., anxiety, depression), bereavement, personal injury, perceived fear/threat, social support, and poor family functioning. However, contrary to these previous meta-analyses (Trickey et al. found age was not a significant risk factor; Cox, et al. found that younger age was a significant risk factor), but corresponding with many of the studies conducted using Chinese samples (Fan et al. 2011a, b; Liu et al. 2010a, b, c; Peng et al. 2011), older age was a significant risk factor for PTSD. This finding may be partially accounted for by the primary use of older participants in the current study, whereas, the referenced meta-analyses had a greater range of ages across studies, or may perhaps reflect cultural differences in indirect variables beyond the scope of this study. With respect to potential cultural variations that may explain this discrepancy, Dong et al. (1994) found that older Chinese children endorsed a more heightened level of fear than younger children (this trend was not seen in the Western sample explored) and cited developmental differences as a probable explanation for this finding; specifically, older Chinese children may have more perceived pressures in their environment due to societal expectations and demands, which makes them more prone to emotional stress. Also, research carried out by Wang and Leichtman (2000) revealed that Chinese children, when compared to American children exhibited greater orientation toward emotional expression and situational details in their verbal narratives; age appeared to mediate these variables. Finally, when investigating trauma severity level as a potential risk factor, as expected, results of the current study suggest that higher or more severe levels of trauma exposure are predictive of PTSD status following a natural disaster. However, when observing the highly related study characteristic of disaster severity, which was measured based on locale of participants in relation to disaster and not primarily questionnaires assessing events that occurred during the disaster, findings indicate that participants deemed to be from severely and moderately exposed areas were more likely to develop heightened levels of PTSD symptomatology after experiencing disaster caused house damage and high levels of trauma severity than those individuals deemed to be from very severely exposed areas; this finding is in alignment with Wang et al. (2000) who postulated that unequal distribution of government provided resources during recovery efforts may account for these phenomenon, but contradicts the results of Lonigan et al. (1991) and Vogel and Vernberg (1993), who found a linear, positive relationship between disaster exposure and PTSD. These studies examined all Western samples, which may be the distinguishing factor.

There are multiple limitations of the current study; first, the studies included in this meta-analysis were highly heterogeneous due to varying sampling and study procedures, the wide array of measurement instruments employed, and the differing construct conceptualizations. Second, interpretation of results may be limited for several variables explored due to the low number of yielded studies that observed these variables; this reflects the relative novelty of this area of research in China, as well as the absence of an uniformed approach to investigating risk and protective factors of PTSD in child populations following a natural disaster. Along the same lines, this study failed to assess many of the protective factors shown to promote resiliency in Western youth (e.g., self esteem, social competence, problem solving; Bernard 1991), due to the scarcity of works that observed these variables in Chinese populations. Future research should incorporate study of these variables into their design †o assess whether these factors act in the same protective manner. Third, majority of the variables explored in this paper were assessed via questionnaires, versus performance or behavioral measures, and were also limited by informant. Although questionnaires can yield valuable information in scientific research, they are limited to the content included and thus, may be insufficient to measure targeted constructs; additionally, questionnaires may be prone to certain response biases or within subject variables that pose threat to internal validity (Podsakoff et al. 2003). Future meta-analyses should look to include studies not limited to questionnaires or surveys. Finally, this study focused exclusively on PTSD as the dependent variable; inclusion of other outcome variables may augment or enhance the understanding of natural disasters and their impact on children in China and should be strongly considered in subsequent work.

Despite the aforementioned shortcomings, the current study has several implications for the theoretical understanding of post-disaster psychological recovery and resilience. First, by combining and analyzing the studies collectively, this study was able to detect which risk and protective factors appeared the strongest predictors of PTSD in youth according to effect sizes across studies. This is valuable information, as it can aid mental health professionals in identifying children and adolescence more vulnerable to PTSD following a natural disaster and has the potential to impact recovery efforts at the organizational or even national level. Second, this study reiterates how similar the experience of natural disasters may be across geographical regions, as results from this study exhibited more similarities than differences when compared to like studies conducted with Western samples. It also highlights the minute differences such as PTSD related to age and disaster severity, which may or may not be due to cultural differences, that should be explored more thoroughly in future projects. Although a plethora of research has investigated and identified values and attitudes that are salient for specific cultures (Wang and Leichtman 2000), little work has been conducted to understand how they may impact one’s reactions to inopportune events. This is undeniably an important area to explore in the future.

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