Background
The death of a loved one is among the most common and impactful traumatic events reported globally [
1,
2]. In line with extensive literature documenting the widespread impacts of adverse childhood experiences [
3,
4], bereavement among children and adolescents associates with adverse psychosocial outcomes across the life course, including disruptions to social and familial support structures [
5‐
7] and increased risk of substance use [
8], depressive symptoms and behaviors [
9‐
12], and sleep and school problems [
12]. Bereavement during childhood is also associated with adverse physical health outcomes, including cardiometabolic concerns [
13] and cortisol abnormalities [
14]. The high risks for these negative outcomes are not constrained to the loss of a parent or primary caregiver but extend to the loss of first- and second-degree relatives and close friends as well [
8,
9]. Despite the potential risks following bereavement, not all youth who face the loss of a loved one experience these adverse effects. Evidence suggests that most individuals who experience bereavement integrate grief without lasting adverse health outcomes [
15,
16]. Resilience, or the ability to adapt or maintain healthy levels of functioning in the face of trauma exposure [
16‐
18], is especially salient in the context of bereavement because of the high prevalence of this exposure and the multi-dimensional adverse impacts associated. Understanding resilience and risk is critical to better informing prevention and intervention efforts among bereaved youth.
A significant barrier to progress is that approaches to identifying and quantifying resilience proliferate with little scientific consensus on the relative advantages and disadvantages of each, especially among bereaved individuals [
19‐
21]. Furthermore, understanding resilience in the context of bereavement presents a unique set of considerations that do not necessarily intersect with other traumatic exposures. First, the loss of a loved one can have direct impacts on structural factors (e.g., loss of familial income, changes in education setting induced by relocation) and the social ecosystem on which children depend (e.g., reduced social network). Second, post-bereavement pathogenesis may be distinguishable from other post-trauma conditions as evidenced by extant literature demonstrating unique syndromic profiles associated with grief symptoms specifically [
22,
23]. Given the evidence that bereavement during childhood is likely to affect multiple health pathways, including biological regulatory systems, multidimensional evaluations of the impact of this common exposure are critical [
24]. Finally, resilience is often defined by the absence of psychopathology, assuming homogeneity in adjustment to trauma and overlooking a more comprehensive state of well-being that includes both positive psychosocial functioning and physical health [
25,
26]. Approaches commonly used to address these limitations employ methods such as latent growth mixture models (LGMMs), which suggest relative consistency in psychological outcome trajectories, with most individuals sustaining low symptoms over time following a common stressor [
16,
19,
27]. Other approaches assume that resilience is continuously distributed and model resilience in terms of deviation from what is expected relative to trauma exposure status [
28,
29]. However, congruence across approaches is not commonly investigated, resulting in limited comparability across studies and settings [
21,
30,
31]. Additionally, given the narrow focus on psychological functioning and internalizing disorders in the extant literature, individuals who may be asymptomatic in some domains of well-being, but struggling to adjust to loss in other unmeasured domains, are not typically identified [
32,
33].
In response, the present analysis develops and compares three resilience constructs on the same data to determine who is resilient under multiple definitions vs. one, with each construct informed by the strengths and limitations of existing approaches. We opt to compare different constructs given the lack of research about resilience among bereaved youth and the need for additional evaluation of different resilience constructs and related issues of misclassification. To address this, we vary (1) the domains of functioning or well-being through which we quantify resilience, (2) the timing of our outcome assessments, and (3) the assumptions underlying the distribution of resilience. Specifically, we construct trajectory-based psychological resilience, relative psychological resilience, and relative cross-domain resilience. The trajectory-based approach uses LGMMs to identify classes of bereaved youth with distinct longitudinal psychological symptom profiles. Relative psychological resilience draws on standardized residuals from a linear model regressing psychological symptoms on bereavement to determine who is doing better than expected given their bereavement status; relative cross-domain resilience is based on a sum score of the residuals approach applied to eight unique domains of health. We examine concordance and correlations between constructs as well as the predictive validity of each one. The aims of these analyses are to evaluate the performance of different resilience constructs using the same data among a bereaved youth sample, and to characterize how multiple domains of functioning and different assumed distributions of resilience result in potential misclassification of post-bereavement well-being.
Discussion
To our knowledge, this is the first study to compare different measures of resilience—trajectory-based psychological resilience, relative psychological resilience, and a relative cross-domain resilience score—among bereaved youth in the same longitudinal dataset. Growth models identified three bereavement response trajectories capturing low/stable (84%), worsening (8%), and elevated (8%) psychological symptom profiles. We found at most moderate correlation (r < = 0.32) between eight individual resilience domains, low correlation (r = 0.14) between relative psychological resilience and relative cross-domain resilience related to physical and social health (but excluding psychological health), relatively strong concordance between relative psychological resilience and corresponding trajectory classification, and relatively poor concordance between relative cross-domain resilience and trajectory classification. Each resilience measure displayed significant predictive validity with depressive symptoms at age 17.5, though the performance of the relative resilience constructs must be interpreted with caution given the high correlation between residuals and observed outcomes.
Our investigation of trajectory-based psychological resilience in a bereaved youth cohort yielded two key insights that align with extant literature on bereavement and psychopathology. First, trajectory-based results in the present study were consistent with prior work using similar methods among other bereaved adult samples [
55‐
57]. Most bereaved youth in our sample maintained low and stable psychological symptom profiles over time, aligning with prior evidence demonstrating that a significant proportion of bereaved individuals will sustain low symptom trajectories over time [
20]. In addition, we note that psychiatric symptoms prior to bereavement–not just at the last assessment point–differentiated psychological functioning trajectories among bereaved individuals rather significantly. This finding is supported by prior studies linking pre-trauma psychopathology to worse post-trauma sequalae and underscores the value of incorporating pre-bereavement risk into assessments of resilience following bereavement [
58]. The application of the growth model approach to other domains of health and functioning (e.g., academic performance) may similarly facilitate identification of individuals at-risk for adverse outcomes after bereavement, even before the stressor occurs.
Next, the application of the residual-based approach to defining both psychological and cross-domain resilience highlighted two important limitations of existing approaches to defining resilience after trauma. First, we identify limited use of the residual-based approach to defining resilience in studies where the relationship between exposure and outcome is not meaningfully correlated. In this sample, bereavement was associated with minimal psychological risk, explaining little variance in observed psychological symptoms at age 16 and producing residuals that were nearly perfectly correlated with observed SDQ outcome values. Consequently, relative psychological resilience was just a proxy for the observed SDQ score, and interpretations of concordance and predictive validity shifted away from our resilience target and towards the SDQ scale itself. The low magnitude of association observed between bereavement and psychological symptoms may be explained by our broad definition of bereavement, which included the death of any family member; this limitation is explained in further detail below. Building on prior work that applied this residual-based method, we recommend consistent reporting of the amount of variance explained by the stressor to aid interpretability of findings [
21,
29]. We further caution against future application of this resilience construct for a binary trauma exposure that exerts a small effect, as the assumption of linearity between exposure and outcome will likely not be satisfied.
Second, the low correlation observed between relative psychological resilience and the relative cross-domain resilience score illustrates that health in any one resilience domain does not reliably associate with health in a different resilience domain. It is evident that integration of psychological, physical, and social domains of functioning in future studies of resilience is critical to better capturing heterogeneity in post-bereavement well-being. We discourage classification of individuals as resilient based on psychological functioning alone because post-bereavement decrements in health may manifest across social and/or physical domains [
33]. To date, recommendations for a more comprehensive assessment of resilience, including examination of a critical set of outcomes or of composite scores, remain empirically understudied [
18,
33,
59]. This may be explained, in part, by the methodological complexities of modeling longitudinal, multi-level outcomes [
17]. In our analysis, we weighted each resilience domain equally and assumed that domains contributed additively and independently towards the overall cross-domain resilience score. However, a burgeoning literature suggests that adolescents who face adversity yet demonstrate positive psychological adjustment are more likely to exhibit higher physiological stress over time [
60,
61]. Accordingly, the influence of these domains may ultimately be modeled differently, with observed correlations and interactions, timing of outcomes assessment, and prior evidence of relative impact all taken into account. From a clinical perspective, this cross-domain heterogeneity suggests that bereaved children may benefit from assessment of social and physical health outcomes even in the absence of mental health symptom endorsement. Youth who appear resilient from a mental health perspective may require services or interventions specific to other key domains of health and functioning.
Numerous study limitations should be considered. First, we were not able to determine the relationship of the study child to the deceased family member, and we expect this relationship to considerably shape subsequent risk of adverse outcomes. For example, we expect the loss of a parent to be more impactful to a child than the loss of a distant relative–and the variance explained in psychiatric symptoms to be larger, as a result. In addition, we could not disentangle time-varying estimates of acute post-bereavement symptoms vs. longer term effects without a more unified timing for our exposure or more outcome measurements. The latter two limitations likely help to explain the modest statistical association observed between bereavement and psychiatric symptoms. Third, the residual approach required outcomes to exhibit positive versus negative functioning valence along just one axis or direction. We selected low (vs. high) BMI and long (vs. short) sleep duration to represent the “healthy” valence or direction. In reality, of course, very low BMI values or very long sleep duration are not necessarily representative of positive functioning. Fourth, prior to our imputation, SDQ scores were prorated, whereas MFQ scores were not. However, given the high internal consistency for both SDQ and MFQ, coupled with our use of imputation for missing values, we do not suspect this to be an important limitation. Finally, we imputed outcomes and covariates using a robust set of auxiliary variables but required bereavement status to be ascertained for analytic sample inclusion, without the use of inverse probability weighting. We cannot rule out selection bias, especially as it relates to bereavement status ascertainment.
In conclusion, we compared three resilience constructs on the same longitudinal data to better understand the distribution of resilience among bereaved youth. Using LGMMs, we found evidence that psychological symptom trajectories among bereaved youth are similar to those identified among bereaved adults and that these trajectories are predictive of depressive symptoms in late adolescence. The residual-based approach, on the other hand, exhibited limited utility and interpretability in the context of bereavement. Despite this limitation, we showed that individual-level resilience varied greatly across domains of health. Our explorations of cross-domain resilience call for better address of the interplay across the psychosocial and physical health domains that shape resilience after trauma. Overall, this study contributes to the growing literature documenting important heterogeneity in the impact of and response to bereavement among youth.
Acknowledgements
We are extremely grateful to all the families who took part in this study, the midwives for their help in recruiting them, and the whole ALSPAC team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, and nurses.
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