In light of the National Institutes of Health–initiated paradigm shift toward dimensional approaches to measuring mental health outcomes, as defined in the Research Domain Criteria (RDoC; see Cuthbert Reference Cuthbert2014a; Insel et al. Reference Insel, Cuthbert, Garvey, Heinssen, Pine, Quinn, Sanislow and Wang2010), the current review offers a new framework nicely aligned with this approach. Kalisch et al. provide not only a dimensional perspective but a quantifiable one. The review focuses on resilience rather than illness and suggests that resilience should be transdiagnostic, another tenet of the RDoC initiative. Of course, true resilience would necessarily be transdiagnostic – patients who compensate for deficits in one domain by showing impairments in another would not be considered resilient (e.g., post-traumatic stress disorder patients who successfully reduce hyperarousal symptoms by abusing substances; Bremner et al. Reference Bremner, Southwick, Darnell and Charney1996).
Quantifying resilience allows for several testable hypotheses, such as that resilience is equal to the number of mental health problems given a known quantity of stressor load. Although cataloguing stressor load may seem problematic, most studies assess stressors along a continuum – for example, post-traumatic stress disorder researchers quantify trauma load with questionnaires that assess degree of trauma exposure (Elhai et al. Reference Elhai, Gray, Kashdan and Franklin2005). A comprehensive measure of total stress exposure (both major and minor, as the authors suggest) may not always be possible, however; if the outcome of interest is resilience in the face of trauma, for example, a measure of trauma load may suffice.
The proposed model lends itself well to prospective studies with data collection at two time points (i.e., pre- and post-adversity); however, not all studies have the luxury of prestressor assessments. In such cases, the authors argue that the cumulative mental health problems post-stressor represent the individual's response, which assumes that there were no problems prior to the stressor. Although this ignores a host of predisposing risk factors, it may still provide a heuristic model to study – that is, the inverse ratio of problems to stressor load.
Kalisch et al. also suggest focusing on resilience mechanisms, rather than factors – an important distinction inasmuch as a number of factors could operate through the same mechanism, thereby reducing the number of analysis units. In fact, risk/resilience factors are many, including but not limited to genetic (Binder et al. Reference Binder, Bradley, Liu, Epstein, Deveau, Mercer, Tang, Gillespie, Heim, Nemeroff, Schwartz, Cubells and Ressler2008), epigenetic (Norrholm et al. Reference Norrholm, Jovanovic, Smith, Binder, Klengel, Conneely, Mercer, Davis, Kerley, Winkler, Gillespie, Bradley and Ressler2013), endocrine (Glover et al. Reference Glover, Jovanovic, Mercer, Kerley, Bradley, Ressler and Norrholm2012; Morgan et al. Reference Morgan, Wang, Southwick, Rasmusson, Hazlett, Hauger and Charney2000), neuroanatomical (Admon et al. Reference Admon, Milad and Hendler2013; Etkin & Wager Reference Etkin and Wager2007), and social (Feder et al. Reference Feder, Ahmad, Lee, Morgan, Singh, Smith, Southwick and Charney2013). Yet they may converge on a limited number of mechanisms. Further, the authors argue for a single global resilience mechanism, that is, positive appraisal, as an explanatory model for resilient outcomes. This is an attractive notion, but it may be overly simplistic and yet at the same time involve complex cognitive demands. In most cases, positive appraisal may be difficult to observe directly and is unlikely to model well in animal research, thereby decreasing its translational applications. Other alternate resilience mechanisms, however, such as less-sensitive amygdala reactivity to threat (Rauch et al. Reference Rauch, Whalen, Shin, McInerney, Macklin, Lasko, Orr and Pitman2000), better emotion regulation (Etkin et al. Reference Etkin, Egner, Peraza, Kandel and Hirsch2006), or prefrontal inhibition of fear memories (Milad et al. Reference Milad, Pitman, Ellis, Gold, Shin, Lasko, Zeidan, Handwerger, Orr and Rauch2009), can be applied to the same quantifiable framework without invoking higher cognitive function.
The innovative contribution of the positive appraisal style theory of resilience (PASTOR) may be less in the specific mechanism proposed than in the mathematical formulation of the resilience phenomenology. Although still largely theoretical in nature, the formula offers a guiding framework in which to organize the variables used in the study of resilience.
As stressors may vary and include physical threat or injury, pain, diseases, and challenges to immune system, to name a few, they impose various types of psychological and physical overload in an acute or chronic way – hence, various mechanisms may underlie coping responses. The idea of a global resilience mechanism can help put in perspective interpretations of studies of the anatomic, cellular, and molecular pathways underlying an improvement in survival and fitness. This can be instructive, as the molecular and cellular mechanisms are divided into those that are common versus those that are specific across different cell types, brain regions, and behaviors.
The idea of being resilient to many and not to just a few stressors can be used to calculate an overall resilience index to be compared with an index representing an animal's general behavioral flexibility. It has been argued that improving overall memory strength may improve the capability of coping with various mental disorders. Some of the biological mechanisms underlying general resilience may involve better control of the environment or be induced by exposure to an enriched environment.
Interpretations of the animal behavioral responses to stress as maladaptive can change as we learn more about their biological significance. For example, when the forced swim test is used repeatedly, an increase in the extent of the immobility during the re-test is often interpreted as despair or learned helplessness. Animals may show enhanced behavioral immobility in the re-test as an adaptive response, however: They display more immobility in the warmer water, but swim more in the colder water to combat the body temperature loss (Reul et al. Reference Reul2014).
Another caveat is that an organism may be resilient to certain adversities, but vulnerable to others. For example, an individual can be resilient to food deprivation or physical pain but sensitive to losing a mate. Would this suggest that there is vulnerability in the specific pathway related to empathy and reproductive function, or resilience to hunger and pain?
In conclusion, individual differences in coping with stress may allow “testing” different coping strategies both at the individual and species levels. Some maladaptations for an individual can be viewed as helpful and protective for species survival. For example, for an alpha male in some species, losing competitiveness because of inability to cope with stress or threat from other males can lead to a downgrade of the position in the hierarchy that is helpful for the survival of the population, even though it can be viewed as a loss for the individual.
In light of the National Institutes of Health–initiated paradigm shift toward dimensional approaches to measuring mental health outcomes, as defined in the Research Domain Criteria (RDoC; see Cuthbert Reference Cuthbert2014a; Insel et al. Reference Insel, Cuthbert, Garvey, Heinssen, Pine, Quinn, Sanislow and Wang2010), the current review offers a new framework nicely aligned with this approach. Kalisch et al. provide not only a dimensional perspective but a quantifiable one. The review focuses on resilience rather than illness and suggests that resilience should be transdiagnostic, another tenet of the RDoC initiative. Of course, true resilience would necessarily be transdiagnostic – patients who compensate for deficits in one domain by showing impairments in another would not be considered resilient (e.g., post-traumatic stress disorder patients who successfully reduce hyperarousal symptoms by abusing substances; Bremner et al. Reference Bremner, Southwick, Darnell and Charney1996).
Quantifying resilience allows for several testable hypotheses, such as that resilience is equal to the number of mental health problems given a known quantity of stressor load. Although cataloguing stressor load may seem problematic, most studies assess stressors along a continuum – for example, post-traumatic stress disorder researchers quantify trauma load with questionnaires that assess degree of trauma exposure (Elhai et al. Reference Elhai, Gray, Kashdan and Franklin2005). A comprehensive measure of total stress exposure (both major and minor, as the authors suggest) may not always be possible, however; if the outcome of interest is resilience in the face of trauma, for example, a measure of trauma load may suffice.
The proposed model lends itself well to prospective studies with data collection at two time points (i.e., pre- and post-adversity); however, not all studies have the luxury of prestressor assessments. In such cases, the authors argue that the cumulative mental health problems post-stressor represent the individual's response, which assumes that there were no problems prior to the stressor. Although this ignores a host of predisposing risk factors, it may still provide a heuristic model to study – that is, the inverse ratio of problems to stressor load.
Kalisch et al. also suggest focusing on resilience mechanisms, rather than factors – an important distinction inasmuch as a number of factors could operate through the same mechanism, thereby reducing the number of analysis units. In fact, risk/resilience factors are many, including but not limited to genetic (Binder et al. Reference Binder, Bradley, Liu, Epstein, Deveau, Mercer, Tang, Gillespie, Heim, Nemeroff, Schwartz, Cubells and Ressler2008), epigenetic (Norrholm et al. Reference Norrholm, Jovanovic, Smith, Binder, Klengel, Conneely, Mercer, Davis, Kerley, Winkler, Gillespie, Bradley and Ressler2013), endocrine (Glover et al. Reference Glover, Jovanovic, Mercer, Kerley, Bradley, Ressler and Norrholm2012; Morgan et al. Reference Morgan, Wang, Southwick, Rasmusson, Hazlett, Hauger and Charney2000), neuroanatomical (Admon et al. Reference Admon, Milad and Hendler2013; Etkin & Wager Reference Etkin and Wager2007), and social (Feder et al. Reference Feder, Ahmad, Lee, Morgan, Singh, Smith, Southwick and Charney2013). Yet they may converge on a limited number of mechanisms. Further, the authors argue for a single global resilience mechanism, that is, positive appraisal, as an explanatory model for resilient outcomes. This is an attractive notion, but it may be overly simplistic and yet at the same time involve complex cognitive demands. In most cases, positive appraisal may be difficult to observe directly and is unlikely to model well in animal research, thereby decreasing its translational applications. Other alternate resilience mechanisms, however, such as less-sensitive amygdala reactivity to threat (Rauch et al. Reference Rauch, Whalen, Shin, McInerney, Macklin, Lasko, Orr and Pitman2000), better emotion regulation (Etkin et al. Reference Etkin, Egner, Peraza, Kandel and Hirsch2006), or prefrontal inhibition of fear memories (Milad et al. Reference Milad, Pitman, Ellis, Gold, Shin, Lasko, Zeidan, Handwerger, Orr and Rauch2009), can be applied to the same quantifiable framework without invoking higher cognitive function.
The innovative contribution of the positive appraisal style theory of resilience (PASTOR) may be less in the specific mechanism proposed than in the mathematical formulation of the resilience phenomenology. Although still largely theoretical in nature, the formula offers a guiding framework in which to organize the variables used in the study of resilience.
As stressors may vary and include physical threat or injury, pain, diseases, and challenges to immune system, to name a few, they impose various types of psychological and physical overload in an acute or chronic way – hence, various mechanisms may underlie coping responses. The idea of a global resilience mechanism can help put in perspective interpretations of studies of the anatomic, cellular, and molecular pathways underlying an improvement in survival and fitness. This can be instructive, as the molecular and cellular mechanisms are divided into those that are common versus those that are specific across different cell types, brain regions, and behaviors.
The idea of being resilient to many and not to just a few stressors can be used to calculate an overall resilience index to be compared with an index representing an animal's general behavioral flexibility. It has been argued that improving overall memory strength may improve the capability of coping with various mental disorders. Some of the biological mechanisms underlying general resilience may involve better control of the environment or be induced by exposure to an enriched environment.
Interpretations of the animal behavioral responses to stress as maladaptive can change as we learn more about their biological significance. For example, when the forced swim test is used repeatedly, an increase in the extent of the immobility during the re-test is often interpreted as despair or learned helplessness. Animals may show enhanced behavioral immobility in the re-test as an adaptive response, however: They display more immobility in the warmer water, but swim more in the colder water to combat the body temperature loss (Reul et al. Reference Reul2014).
Another caveat is that an organism may be resilient to certain adversities, but vulnerable to others. For example, an individual can be resilient to food deprivation or physical pain but sensitive to losing a mate. Would this suggest that there is vulnerability in the specific pathway related to empathy and reproductive function, or resilience to hunger and pain?
In conclusion, individual differences in coping with stress may allow “testing” different coping strategies both at the individual and species levels. Some maladaptations for an individual can be viewed as helpful and protective for species survival. For example, for an alpha male in some species, losing competitiveness because of inability to cope with stress or threat from other males can lead to a downgrade of the position in the hierarchy that is helpful for the survival of the population, even though it can be viewed as a loss for the individual.