Human Resilience: Standing Tall in the Face of Potentially Traumatic Events
Although most people consider themselves to be relatively safe from traumatic events, on average, every person is confronted with at least one experience that fits the criteria for a traumatic event (Ozer, Best, Lipsey, & Weiss, 2003). The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revised, defines a traumatic stressor as experiencing, either directly or indirectly, the death, serious injury, or the threat of either to oneself or another individual (4th ed., DSM–IV–TR; American Psychiatric Association, 2000). When the trauma involves the death of a loved one, a period of intense and potentially pathological grieving may ensue. This occurrence, known as bereavement, is relatively common and may be experienced by an individual multiple times over the course of his/her life (Bonanno, Westphal & Mancini, 2010).
Not all individuals react the same when faced with loss or trauma. Whereas some function normally and show no signs of distress, others experience varying levels of impairment manifested as posttraumatic stress disorder (PTSD) or anxiety (Bonanno, 2004). Due to the fact that not all individuals who go through such events experience signs of trauma, it seems sensible to rebrand this category of events as “potentially traumatic events” or PTE’s (Bonanno et al., 2010). Over the years, the concept of resilience was born from individuals who showed no decrease in functioning in the face of PTE’s.
Although a substantial amount of research has investigated the concept of resilience, different studies have operationalized resilience in diverse ways. There remains no universally agreed-upon definition of resilience (Luthar, Cicchetti, & Becker, 2000). Some researchers define it from a developmental point of view. They see resilience as the ability to continue normal development under circumstances of unusual hardship (Friborg, Hjemdal, Rosenvinge, & Martinussen, 2003). Other researchers see resilience as possessing the needed strength and assets to survive adversity (Connor & Davidson, 2003). Still others take a more philosophical approach and define resilience as a worldview that sees all life events as being both explainable and manageable (Almedom, Tesfamichael, Mohammad, Mascie-Taylor, & Alemu, 2007). In 2010, the UK Cross-Council program for Life Long Health and Wellbeing tasked the Resilience and Healthy Ageing Network with reviewing the literature, as well as contributing a unified definition of resilience (Luthar et al., 2000). After synthesizing over 270 articles, a definition was proposed that included all the key elements of resilience:
Resilience is the process of effectively negotiating, adapting to, or managing significant sources of stress or trauma. Assets and resources within the individual, their life and environment facilitate this capacity for adaptation and ‘bouncing back’ in the face of adversity. Across the life course, the experience of resilience will vary. (Windle, 2010, p.163)
After the concept of resilience was first described, researchers tried to identify factors that promote resilience (protective factors) and factors that place an individual at an increased risk for developing PTSD (risk factors). This line of research became an integral part of the investigation of resilience and remains prominent even in today’s research (e.g. Adams & Boscarino, 2005; Bonanno & Galea, 2007; Tugade & Fredrickson, 2007). A major change that has recently occurred in the field of resilience research is the shift from a PTSD/resilience dichotomy to a view that encompasses several distinct prototypical trajectories. The original dichotomy was based on the assumption that the possible variability in the outcomes of adults exposed to PTE’s is limited (Bonanno, Westphal, & Mancini, 2010).
In this paper, we will discuss the emerging body of research that supports the conceptualization of outcomes as trajectories with an emphasis on the resilience trajectory. We will also briefly discuss some of the existing research regarding potential protective and risk factors in relation to resilience.
Traditional Approaches to Studying Resilience
The vast majority of research into the outcomes of individuals after a potentially traumatic experience has used one of two traditional approaches: the psychopathology approach and the event (or averages) approach. Although each of these approaches have their own merit, they also possess inherent limitations and are therefore restricted in their explanatory power. Until recently, they remained the prominent paradigms in the field of resilience studies. As such, older studies must be interpreted cautiously with the knowledge that newer and more accurate models now exist.
The first approach, known as the psychopathology approach, emphasizes unhealthy psychological reactions such as PTSD or major depressive disorder (Bonanno et al., 2010). Historically, there has been a controversial debate over what responses should be considered psychopathological. Until the late 1900’s, the concept of psychological trauma was viewed with considerable caution, due to fears of malingering and potential secondary gain (Lamprecht & Sack, 2002). However, when PTSD was officially added to the third edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-III) in 1980, a new wave of research focusing on trauma began (Bonanno & Mancini, 2012).
The ability of this new diagnostic label to provoke and guide a surge of research came at a cost. Firstly, the diagnostic categories are conceptual rather than empirical entities, implying that there are no objective criteria against which they can be evaluated, reviewed, and updated (Bonanno et al., 2010). Since its addition to the DSM-III, the criteria for PTSD have expanded which in turn decreased the threshold for PTSD (Bonanno & Mancini, 2012). The validity of the diagnosis may suffer as a result of this relaxation of standards (Bonanno et al., 2010). Secondly, most evidence points to the idea that PTSD is a dimensional and non-categorical variable. As such, any cutoff point used to make a diagnosis will be arbitrary (Bonanno & Mancini, 2012). Lastly, the focus on PTSD has led to an oversimplified dichotomous view that makes distinctions based solely on the presence or absence of psychopathology. This view provides very little insight into normal reactions to stress and restricts the type of data collected and used for such studies (Bonanno & Mancini, 2012).
The second approach is referred to as the event approach. It focuses on differences between the averages of an exposed group and an unexposed group on continuous variables related to trauma adjustment (Bonanno et al., 2010). One strength of using averaged scores is that it allows the convenient estimation of the duration of posttraumatic responses and the detection of changes in the levels of PTSD in a sample over time (Bonanno & Mancini, 2012). Another strength is that it allows us to compare averages that vary across several within-group variables. This type of analyses proves very informative when studying the efficacy of various treatments (Brady et al., 2000) or when investigating potential risk or protective factors (Wagner, Heinrichs, & Ehlert, 1998).
However, this approach is not without its own flaws. Similar to the psychopathology approach, the event approach tells us very little about the nature of resilient responses to trauma (Bonanno et al., 2010). Also, since this approach focuses on averaged means for any given group, it does not provide any useful information about the distribution and frequency of various responses. The average is assumed to reflect the modal response but, when analyzed over time, the average does not display the typical response patterns that are seen after a PTE (Bonanno & Mancini, 2012).
A New Approach to Studying Resilience: Trajectories
Both of the traditional approaches to studying resilience succumb to the same limitation: an inability to describe and account for the full extent of variability in responses after a PTE due to an inherently binary model. This weakness is due to a faulty assumption that underlies both approaches. This is the assumption that hostile life events produce a uniform distribution of change over time (Muthen, 2004). However, recent advances in both theory and statistical analysis have shown that this assumption is unwarranted and that previous research has consistently underestimated the heterogeneity of reactions to stress (Curran & Hussong, 2003; Mancini & Bonanno, 2006).
The shift from homogenous variation to heterogeneous variation has occurred quite recently. One of the first studies that attempted to understand this heterogeneous variance was conducted less than two decades ago. Baseline levels of depression were collected from elderly couples. Following the death of a spouse, widows were assessed at a 6-month and 18-month follow up. Instead of assessing the averages at each point in time, the authors constructed a trajectory for each individual and categorized the resulting patterns. The results showed that the majority of the analyzed participants (90.2%) fit into one of five distinct trajectories. They found that the most frequent outcome (45.9%) was “resilience”, characterized by a low-low-low trajectory with only minor levels of depression at all three data points. The second most common response (15.6%) was dubbed “chronic grief” and exhibited a low-high-high trajectory. The next most common outcomes were “common grief” (10.7%) and “depressed-improved” (10.2%) which followed low-high-low and high-low-low trajectories respectively. The last and least common reaction to the loss of a spouse was “chronic depression” (7.8%) which displayed a continuous high-high-high trajectory (Bonanno et al., 2002).
These results have been replicated by various researchers in the past few years and hold true for a wide variety of PTE’s, such as the loss of a spouse or child (Bonanno, Moskowitz, Papa, & Folkman, 2005), terrorist attacks (Bonanno, Renicke, & Dekel, 2005), and radiation-based treatments for cancer (Deshields, Tibbs, Fan, & Taylor, 2006). Most of the recent research conducted in this field indicates that the majority of this heterogeneity can be explained by a model containing a small number of archetypal outcome trajectories (Bonanno, 2004). The most common trajectories are resilience, recovery, chronic distress, and delayed distress but two other trajectories (continuous distress, and distress-improvement) are sometimes observed. (Bonanno et al., 2010)
Due to the fact that most studies were carried out on samples that had either experienced significant psychological distress or pursued treatment, early theorists believed resilience to be a rare occurrence that was indicative of either an underlying pathology or extraordinary mental health (Bonanno, 2004). However, this view is quickly becoming obsolete as new research provides evidence that resilience is much more common than previously expected. Most people can endure a PTE with little or no impairment (Bryant, Harvey, Guthrie, & Moulds, 2000; Galea et al., 2002). Although this conceptualization of resilience as the “norm” has only recently gained traction, it has been around for almost 30 years. Wortman and Silver (1989) argued that there was no empirical evidence supporting the claim that a lack of impairment during bereavement is a sign of psychopathology (a prominent view at the time). However, their paper did not have a strong impact on the field of psychology at the time due to the dearth of proper studies needed to assess their claim (Bonanno, 2004). Today, there are a multitude of studies that have supported Wortman and Silver’s (1989) assertion. In a study examining depression in widows over the course of two years after the death of a spouse, almost half of the 328 participants showed no depression at all (Zisook, Paulus, Shuchter, & Judd, 1997). These results were replicated in many other studies that showed resilience to be the most frequently observed outcome (Bonanno et al., 2002; Hanson, Kilpatrick, Freedy, & Saunders, 1995; Tucker et al., 2002; Sutker, Davis, Uddo, & Ditta, 1995). Taken together, these findings suggest that resilience is in fact the most common trajectory after exposure to a PTE (Bonanno, 2004).
Most studies have found the rates of resilience to range between 40%-60% (Zisook et al., 1997). However, it is not uncommon to find rates of resilience as low as 25% (Jaffee et al., 2007) or as high as 92% (White, Moffitt, & Silva, 1989). This wide range is a testament to the importance of protective factors and risk factors. For example, a study that found resilient outcomes in 92% of the participants had chosen a sample of individuals with numerous potential protective factors such as higher socioeconomic status and higher levels of education (White et al., 1989). Several different factors that promote resilience have been identified, leading some researchers to adopt the view that there are multiple pathways to resilience (Bonanno, 2004). The effects of such factors will be more thoroughly discussed later in this paper.
Although the endpoint for the recovery outcome is the same as that of resilience, recovery is described by a very different trajectory (Bonanno et al., 2010). Many studies have shown that they and statistically resolvable, regardless of the nature of the PTE (deRoon-Cassini, Mancini, Rusch, & Bonanno, 2010; Lam et al., 2010; Mancini, Bonanno, & Clark, 2010). Recovery is characterized by the temporary disruption of normal functioning which, over time, resolves and returns to normal levels (Bonanno & Mancini, 2012). Although recovery seems to be a key mechanism in the field of trauma, there has been very little research investigating it. Most studies that have endeavored to explain recovery do not look into individual trajectories but rather a decline in the average prevalence of PTSD with time (Breslau, 2001; Rothbaum et al., 1992) or a decrease in average levels of symptoms (Port, Engdahl, & Frazier, 2001).
It has been shown that compared to the resilience and recovery trajectories, the number of individuals who develop sustained psychopathology is relatively small. PTSD is usually developed in only 5%-10% of individuals who are exposed to a PTE (Bonanno et al., 2010). As the PTE increases in severity or the exposure increases in duration, the rates of PTSD increase proportionally but only rarely surpass 30% of any given sample (Bonanno, 2005; Bonanno, Brewin, Kaniasty, & LaGreca, 2010). For example, in an analysis of the prevalence of PTSD in a representative sample of war veterans from Vietnam, only 9% of the sample was diagnosed with PTSD. However, when the sample was split into different groups based on levels of combat exposure, the rate of PTSD was found to be highest (28%) in the group of veterans that has experienced most combat (Dohrenwend et al., 2006). Similarly, following the death of a loved one, only 10%-15% of people show pathological symptoms of grief (Bonanno & Kaltman, 2001). However, when the death involved violence, the rates of pathological bereavement increase substantially (Kaltman & Bonanno, 2003).
This raises a very important question: when can a grief/trauma response be classified as chronically elevated or pathological? One attempt to answer this question relies on the diagnostic criteria of the DSM. However, this approach is subject to the same limitations as the psychopathological approach discussed earlier. The constraints of diagnostic labelling make this an inferior approach (Bonanno & Mancini, 2012). Another approach is to estimate dysfunctional trajectories based on the normal distribution of scores on a continuous variable representing pathological symptoms (Bonanno, 2004). Many scales already exist to this effect (e.g. PTSD Symptom Scale, Self-Report; Foa, Riggs, Dancu, & Rothbaum, 1993). Although continuous scales such as these require cutoff points, these cutoff points are not arbitrary. They are chosen based on statistical analysis instead of theoretical deduction (Bonanno & Mancini, 2012).
This is by far the most elusive of all trajectories. It is characterized by the development of pathological symptoms, such as PTSD, but not immediately after the PTE. For example, soldiers who are exposed to combat do not show signs of pathology until they have returned home. In this particular case, the lag is assumed to be due to the obvious maladaptive effects that psychopathology would have on a soldier in combat (Andreasen, 2004). Traditionally, delayed responses to environmental stressors were assumed be the result of denial (Bonanno & Mancini, 2012). Therefore, it was believed that any individual who did not show pathology in the immediate aftermath of a PTE would eventually develop symptoms that would manifest as a delayed distress response (Bowlby, 1980; Osterweis, Solomon, & Green, 1984; Sanders, 1993).
The existence of this outcome pattern is not unanimously agreed upon as not all studies have been able to detect it (Bryant & Harvey, 2002). For example, a study examining the outcome patterns of bereaved spouses, parents, and children found no evidence for a delayed grief response, despite the authors’ conviction that such a category would be identified (Middleton, Moylan, Raphael, & Martinek, 1996). Similarly, a recent study following bereaved individuals over a five-year span also found no evidence supporting the delayed distress trajectory (Bonanno & Field, 2001). In addition, unlike rates of resilience which typically cluster around 50%, prevalence estimates for delayed onset PTSD vary greatly (Bonanno et al., 2010). They have been reported to range from 0% to 60% (Andrews, Brewin, Philpott, & Stewart, 2007).
However, a substantial amount of research has indeed detected a distinct delayed distress trajectory (Bremner, Southwick, Darnell, & Charney, 1996; Mayou, Tyndel, & Bryant, 1997). In a 20-year longitudinal study that followed a sample of 83 war veterans, 63% of the developed cases of PTSD had delayed onset (Solomon & Mikulincer, 2006). As of now, the evidence that there is a trajectory characterized by a delayed elevation of psychopathological symptoms is too substantial to be ignored. Further research focusing on the in depth examination of this outcome pattern has suggested that the increase is most likely due to a worsening of subthreshold symptoms and not an abrupt onset of entirely novel symptoms (Bonanno et al., 2005; Buckley, Blanchard, & Hickling, 1996; deRoon-Cassini et al., 2010). These results have been combined in a recent literature review which concluded that delayed onset PTSD is best explained by the aggravation of pre-existing symptoms (Andrews et al., 2007).
Unlike the previous trajectories, the pattern of continuous distress is based on high levels of pathological baseline symptoms. It is characterized by distress and impairment before the onset of the PTE that carries over into the post-event phase (Bonanno et al., 2010). This trajectory is distinct from chronic distress as they vary in levels of pre-event symptomology. A five-year longitudinal study that followed a sample of bereaved gay men who had been caring for an HIV-positive partner found that 25% of the sample exhibited the continuous symptoms of depression characteristic of the continuous distress trajectory (Bonanno et al., 2005). This outcome pattern has been replicated and observed for varying types of PTE’s such as loss of a loved one (Bonanno et al., 2002), losing a job (Galatzer-Levy, Bonanno, & Mancini, 2010), and terrorism (Bonanno et al., 2005).
This trajectory is similar to the continuous distress pattern in that they both have elevated symptoms before the occurrence of the PTE. However, distress-improvement is characterized by a marked drop in symptoms after the event (Bonanno et al., 2010). This pattern is likely to occur under circumstances in which the aftermath of the PTE is somehow less stressful than the conditions preceding it. For example, the death of a terminally ill spouse may result in an overall decrease in stress, as caring for a sick loved one is a high stress endeavor. This would result in a reduction of stress symptoms after the PTE, which is exactly what Bonanno et al. (2002) found in 10.2% of their sample.
It is important to note that both the continuous stress and the distress-improvement trajectories are the least studied of all trajectories. This is due to the fact that there is often no pre-PTE data available for the measures being used (Bonanno et al., 2010). However, when such data is available, it is not uncommon to detect both of these trajectories.
Limitations of the Trajectory Approach
Although the trajectory approach has been very informative and has received substantial empirical support, the statistical analyses involved (hierarchical linear modeling, HLM) has three major limitations (Bonanno et al., 2010). Firstly, it bases its derivation of the trajectories based on a single mean and standard deviation (Bonanno et al., 2002). This single mean cannot capture the varying amounts of variance in each pathway and therefore the trajectory cannot be influenced by this variability (Bonanno et al., 2010). The second limitation is that past research relies on arbitrary cutoff points to delineate these trajectories. This method forces the trajectories onto the data instead of extracting the trajectories from the data. As a result, there is always doubt as to whether or not the defined trajectories actually exist naturally (Bonanno, Westphal, & Mancini, 2010). The third and final limitation is that the individual trajectories were defined based on nothing more than theoretical assumptions about the possible outcome patterns.
These theoretical limitations were addressed with the advent of latent growth mixture modeling (LGMM), a statistical analysis that is based on structural equation modeling (Muthen, 2004). This method of analysis is not subject to the shortcoming of HLM, as it is not restricted to the use of only one mean response. It therefore does not inherently posit the homogeneity of response distribution (Bonanno et al., 2010). One of the major strengths of the LGMM is the ability to distinguish the various trajectories and determine their relative frequencies. It does this in a way that is scientifically grounded and nonrandom (Bonanno et al., 2010). For a more thorough discussion of LGMM techniques, refer to Muthen (2004).
Factors that Predict an Individual’s Trajectory
Ever since it became clear that resilient outcomes were possible, research has tried to distinguish the factors that promote resilience (protective factors) from those that promote pathological outcomes (risk factors). This is no simple task. Since resilience is in fact quite common, it follows that we should expect significant heterogeneity among individuals displaying resilient outcomes (Bonannoet al., 2010). However, research has still managed to pinpoint several factors that seem to influence individuals’ outcomes after experiencing a PTE.
Multiple meta-analyses have shown that absence of social support, a history of psychopathology, and low levels of education are strong predictors of PTSD responses (Brewin, Andrews, & Valentine, 2000; Ozer et al., 2003). These two studies illustrate an important point about this line of research. The vast majority of investigation into predictive factors focuses on predictors of PTSD and not resilience (Bonanno, 2004). However, more recently, a shift is occurring from a focus on predictors of PTSD to predictors of resilience. This body of empirical knowledge is increasing steadily.
Research has shown that age, male gender, and high education levels are all predictive of resilient outcomes (Bonanno et al., 2007). Identifying with an ethnic majority is also associated with better outcomes (Adams & Boscarino, 2005). However, belonging to an ethnic minority is often linked to lower socioeconomic status which may act as a confounding variable as it has repeatedly been shown to predict worse outcomes after PTEs (Brewin et al., 2000). When socioeconomic status is controlled for, the relationship between ethnicity/race and resilience is usually no longer significant (Bonanno et al., 2007).
An other surprising predictor of resilience has been identified. Individuals who use repressive coping mechanisms displayed more reilient outcomes on average than other individuals (Weinberger, Schwartz, & Davidson, 1979). Further research indicates that this connection is due to the fact that repressive copers are better able to dispel disturbing memories and emotions (Weinberger, 1990). Repressive coping seems to function at the level of emotions. As such, although repressive copers report only minimal levels of emotional distress when put in a stressful situation, they still score high on physiological arousal, an indirect measure of distress (Weinberger et al., 1979).
Personality traits have also long been thought to play a crucial role in fostering resilience. Several personality traits that are linked to resilience have been identified. The relationship between personality and resilience is discussed further in detail below.
Although much research has investigated the link between resilience and personality, Bonanno, Westphal and Macini (2010) point out two major limitations inherent to all of these studies. The first limitation, which was initially pointed out by Mischel (1969), is that personality traits can only explain 10% of the variance in human behavior. The second limitation points out that, although personality is relatively stable, we can never be completely confident that experiencing the PTE did not alter the individual’s personality. Since measures of personality are usually administered after the occurrence of the PTE, this uncertainty calls into question the validity of any results.
That being said, many strong studies have found a link between resilience and certain personality traits. For example, Weems et al. (2010) studied a sample of 191 school children in the wake of Hurricane Katrina. They found that resilience was linked to lower levels of negative affect. A 1997 study by Bonnano and Keltner, provides another piece of evidence that lends support to the previous study. They found that facial expressions of positive affect (e.g. smiling, laughing) when talking about a recently deceased spouse predicted better outcomes for recently widowed individuals. Taken together, these two studies provide evidence that positive affect is a protective factor whereas negative affect is a risk factor.
Kobsa, Maddi, and Kahn (1982) identified another personality trait that acts as a protective factor. They found that individuals who scored high on measures of hardiness coped better than their low-hardiness counterparts. People possessing the trait of hardiness believe that there is a meaning and purpose in life and that they can influence their surroundings. They also believe that they can learn something from all of their life experiences both positive and negative (Bonanno, 2005). Interestingly, other studies have shown that attempting to make negative life experiences meaningful may not be healthy and can even result in poorer outcomes (Bonanno et al., 2005; Park, 2010). Further research is needed to clarify whether meaning-making is a protective factor or a risk factor.
A final personality factor that influences resilience is self-enhancement: an exaggerated positive view of oneself. Two separate studies by Bonanno, Field, Kovacevic, and Kaltman (2002) showed that individuals who displayed self-enhancing tendencies also showed better adjustment in the wake of traumatic events. These studies were carried out on different populations (Bosnian citizens vs. citizens of the United States of America) and for two different PTEs (civil war and spousal bereavement respectively). Researchers first proposed this link between overly positive self-bias and adjustment over thirty years ago (Greenwald, 1980). Since then, the empirical support has only increased (Bonanno et al., 2005; Taylor & Brown, 1988).
Although it is almost inevitable that everyone will face at least one potentially traumatic event over the course of his/her life, that does not mean that all will develop adverse reactions to these stressful situations. A review of the literature shows that there are distinct trajectories that are followed after a traumatic event. Of all the potential outcome patterns, resilience is by far the most common. Another common outcome is recovery characterized by elevated symptoms that then subside with time. Taken together, this means that most individuals, when faced with a potentially traumatic event, will be able to cope and adjust without any long term distress. A substantial body of research investigating the predictors of various outcomes is readily available. In this review, a few major personality traits were discussed in relation to resilience. The literature shows that self-enhancement biases, positive affect, and high levels of trait hardiness are all predictive of resilience and positive outcome after a stressful event.
There is still much that is unknown about human resilience in the face of traumatic events. As research fills these gaps, we will be able to better understand the nature of our stress reactions and better inform our therapies and treatments of PTSD. Although we cannot eradicate or totally prevent the occurrence of traumatic events, with the knowledge acquired through research, we will be able to provide better care and protection for those who are in need of it.
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