Background: Up to half of Western children and adolescents experience at least one type of childhood adversity. Individuals with a history of childhood adversity have an increased risk of psychopathology. Resilience enhancing factors reduce the risk of psychopathology following childhood adversity. A comprehensive overview of empirically supported resilience factors is critically important for interventions aimed to increase resilience in young people. Moreover, such an overview may aid the development of novel resilience theories. Therefore, we conducted the first systematic review of social, emotional, cognitive and/or behavioral resilience factors after childhood adversity.Methods: We systematically searched Web of Science, PsycINFO, and Scopus (e.g., including MEDLINE) for English, Dutch, and German literature. We included cohort studies that examined whether a resilience factor was a moderator and/or a mediator for the relationship between childhood adversity and psychopathology in young people (mean age 13–24). Therefore, studies were included if the resilience factor was assessed prior to psychopathology, and childhood adversity was assessed no later than the resilience factor. Study data extraction was based on the STROBE report and study quality was assessed with an adapted version of Downs and Black's scale. The preregistered protocol can be found at: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016051978.Results: The search identified 1969 studies, of which 22 were included (eight nationalities, study sample n range: 59–6780). We found empirical support for 13 of 25 individual-level (e.g., high self-esteem, low rumination), six of 12 family-level (e.g., high family cohesion, high parental involvement), and one of five community-level resilience factors (i.e., high social support), to benefit mental health in young people exposed to childhood adversity. Single vs. multiple resilience factor models supported the notion that resilience factors should not be studied in isolation, and that interrelations between resilience factors should be taken into account when predicting psychopathology after childhood adversity.Conclusions: Interventions that improve individual, family, and/or social support resilience factors may reduce the risk of psychopathology following childhood adversity. Future research should scrutinize whether resilience factors function as a complex interrelated system that benefits mental health resilience after childhood adversity.

Resilience is still often viewed as a unitary personality construct that, as a kind of antinosological entity, protects individuals against stress-related mental problems. However, increasing evidence indicates that maintaining mental health in the face of adversity results from complex and dynamic processes of adaptation to stressors that involve the activation of several separable protective factors. Such resilience factors can reside at biological, psychological, and social levels and may include stable predispositions (such as genotype or personality traits) and malleable properties, skills, capacities, or external circumstances (such as gene-expression patterns, emotion-regulation abilities, appraisal styles, or social support). We abandon the notion of resilience as an entity here. Starting from a conceptualization of psychiatric disorders as dynamic networks of interacting symptoms that may be driven by stressors into stable maladaptive states of disease, we deconstruct the maintenance of mental health during stressor exposure into time-variant dampening influences of resilience factors onto these symptom networks. Resilience factors are separate additional network nodes that weaken symptom–symptom interconnections or symptom autoconnections, thereby preventing maladaptive system transitions. We argue that these hybrid symptom-and-resilience-factor networks provide a promising new way of unraveling the complex dynamics of mental health.

Resilience factors (RFs) help prevent mental health problems after childhood adversity (CA). RFs are known to be related, but it is currently unknown how their interrelations facilitate mental health. Here, we used network analysis to examine the interrelations between ten RFs in 14-year-old adolescents exposed (‘CA’; n = 638) and not exposed to CA (‘no-CA’; n = 501). We found that the degree to which RFs are assumed to enhance each other is higher in the no-CA compared to the CA group. Upon correction for general distress levels, the global RF connectivity also differed between the two groups. More specifically, in the no-CA network almost all RFs were positively interrelated and thus may enhance each other, whereas in the CA network some RFs were negatively interrelated and thus may hamper each other. Moreover, the CA group showed more direct connections between the RFs and current distress. Therefore, CA seems to influence how RFs relate to each other and to current distress, potentially leading to a dysfunctional RF system. Translational research could explore whether intervening on negative RF interrelations so that they turn positive and RFs can enhance each other, may alter ‘RF-mental distress’ relations, resulting in a lower risk for subsequent mental health problems.

MEDLINE) for English, Dutch and German literature. We included cohort studies that examined 36 whether a resilience factor was a moderator and/ or a mediator for the relationship between childhood 37 adversity and psychopathology in young people (mean age 13-24). Therefore, studies were included if 38 the resilience factor was assessed prior to psychopathology, and childhood adversity was assessed no 39 later than the resilience factor. Study data extraction was based on the STROBE report and study 40 quality was assessed with an adapted version of Downs and Black's scale. The preregistered protocol 41 can be found at: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016051978. 43Results: The search identified 1969 studies, of which 22 were included (eight nationalities, study 44 sample n range: 59-6780). We found empirical support for 13 of 25 individual-level (e.g. high self-45 esteem, low rumination), six of 12 family-level (e.g. high family cohesion, high parental involvement), 46 and one of five community-level resilience factors (i.e. high social support), to benefit mental health in 47 young people exposed to childhood adversity. Single versus multiple resilience factor models 48 supported the notion that resilience factors should not be studied in isolation, and that interrelations 49 between resilience factors should be taken into account when predicting psychopathology after 50 childhood adversity. 51 52 Conclusions:Interventions that improve individual, family, and/ or social support resilience factors 53 may reduce the risk of psychopathology following childhood adversity. Future research should 54 scrutinize whether resilience factors function as a complex interrelated system that benefits mental 55 health resilience after childhood adversity. 56 57

In psychiatry, severity of mental health conditions and their change over time are usually measured via sum scores of items on psychometric scales. However, inferences from such scores can be biased if psychometric properties such as unidimensionality and temporal measurement invariance for instruments are not met. Here, we aimed to evaluate these properties for common measures of depression (Patient Health Questionnaire–9) and anxiety (Generalized Anxiety Disorder Assessment–7) in a large clinical sample ( N = 22,362) undergoing psychotherapy. In addition, we tested consistency in dimensionality results across different methods (parallel analysis, factor analysis, explained common variance, the partial credit model, and the Mokken model). Results showed that while both Patient Health Questionnaire–9 and Generalized Anxiety Disorder Assessment–7 are multidimensional instruments with highly correlated factors, there is justification for sum scores as measures of severity. Temporal measurement invariance across 10 therapy sessions was evaluated. Strict temporal measurement invariance was established in both scales, allowing researchers to compare sum scores as severity measures across time.