Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2025 Dec 12.
Published in final edited form as: Transl Issues Psychol Sci. 2024 Dec 12;11(2):195–205. doi: 10.1037/tps0000435

Flourishing as resilience: Flourishing among Hispanic/Latino adolescents during the COVID-19 pandemic

Kate Ryan Kuhlman 1,2, Neda Semsar 1, Elizabeth Antici 1, Nazly Restrepo 3
PMCID: PMC12453147  NIHMSID: NIHMS2061241  PMID: 40988930

Abstract

The COVID-19 pandemic disturbed the lives of adolescents during a well-established, sensitive period of development, and further disadvantaged communities already burdened with limited resources. Although there has consistently been discourse on human suffering during and since the COVID-19 pandemic, very little attention has been given to flourishing during this time of extraordinary adversity. Flourishing is a construct that describes a group of individuals who are concurrently reporting high or frequent hedonic (positive emotions) and eudaimonic (purpose, fulfilment) experiences. In the present study we modeled resilience as indexed by the association between early life adversity (ELA) and flourishing, as well as the mediating role of two indices of psychosocial resources (cumulative and compensatory) as a function of individual differences in the impact of COVID-19 in their lives. To do so, we used data collected from 223 predominantly Hispanic/Latino youth (age 11–18) assessed between April 2021 and April 2022 as part of a community-engaged partnership. Based on adolescent self-report on the Mental Health Continuum (MHC-SF), 36.3% of the sample met criteria for flourishing. Parallel moderated mediation showed that having more exposure to ELA was associated with a lower likelihood of flourishing (p < .001), and that this association was differentially explained by compensatory psychosocial resources depending on COVID-19 impact. Specifically, among adolescents experiencing high COVID-19 impact, ELA was associated with a lower likelihood of flourishing via lower compensatory psychosocial resources, indirect effect at high COVID-19 impact b = −0.01 (SE = 0.007), 95%CI[−0.03, −0.002]. These results underscore the importance of considering ELA and recent stress in conceptualizations of adolescent flourishing and demonstrate the potential advantages of identifying interventions that increase compensatory psychosocial resources among ELA-exposed youth.

Keywords: well-being, flourishing, languishing, adolescents, Hispanic, COVID-19

Introduction

Flourishing is not only the absence of psychopathology, but also the presence of positive emotions, pursuit or actualization of potential, and self-fulfillment. Flourishing has been linked concurrently with higher academic achievement during adolescence (Datu, 2018) and longitudinally with transitions to adulthood that include higher educational attainment, more civic engagement, and perceived competence (O’Connor et al., 2017). What is known about flourishing in adolescence has been summarized in two systematic reviews (Waigel & Lemos, 2023; Witten et al., 2019). Notably, the current literature remains largely unbound by a dominant theoretical framework; of the 11 studies in the literature to date, only three shared a common theoretical framework (Witten et al., 2019). Flourishing may be better understood as a form of resilience, particularly within the context of existing theory and empirical knowledge around resilience in development (Masten et al., 2021). Within this framework, it is necessary to measure a well-defined positive outcome, in this case flourishing, in the context of a risk factor such as early life adversity (ELA) which is widely known to be associated with risk for psychopathology (McLaughlin et al., 2010, 2012).

Yet, predictors of flourishing during adolescence remain largely limited to studies of individuals living in middle and high income communities (Witten et al., 2019), and only three studies to date have characterized adolescent flourishing in the context of ELA (Bethell et al., 2019; Kwong & Hayes, 2017; Rey et al., 2019; See Waigel & Lemos, 2023 for review). These studies have observed that ELA is associated with lower prevalence of flourishing (Kwong & Hayes, 2017), indicators of family resilience and connection increase the prevalence of flourishing independent of ELA (Bethell et al., 2019), and flourishing may be a mechanism through which risk for suicide is mitigated among adversity-exposed youth (Rey et al., 2019). The paucity of studies looking at flourishing in the context of past and current adversity is a critical barrier to advancing our understanding of flourishing as a form of resilience. However, doing advances the translation of empirical evidence linking risk for poor psychological well-being (i.e., not flourishing) to developmental and clinical science by moving the field from describing flourishing as a trait to understanding flourishing as a dynamic process.

Further, one of several recently identified barriers to translating causal research on early life stress to clinical studies in humans is the consideration of the role of recent stress (Kuhlman, 2024). Indeed, it appears to be the case that the associations between ELA and later functioning are more, if not exclusively, observable in the acute aftermath of stress. The COVID-19 pandemic exerted an outsized impact on the lives of adolescents including changes to opportunities for interaction with peers, cancelation of cultural traditions and celebrations of milestones, illness and death of family members, and financial instability, among many others. Of course, the impact of the COVID-19 pandemic was not evenly distributed across the population. Thus, adolescents whose lives were more affected by the pandemic may have needed more psychosocial resources to flourish, making their role in explaining links between ELA and flourishing more apparent among them.

There are many psychosocial resources that could explain which adversity-exposed youth flourish. Identifying these psychosocial resources may then be leveraged in ways that promote more flourishing among adversity-exposed youth. Resilience is known to result from the combined benefits of multiple psychosocial resources (Masten, 2004; Schetter & Dolbier, 2011; Taylor & Stanton, 2007), and there are many psychosocial resources that have been identified as either protective or promotive of psychological well-being among adolescents or individuals exposed to ELA. These include receiving social support (Cosco et al., 2019; Masten et al., 2021; Schotanus-Dijkstra et al., 2016), sleep (Kuhlman et al., 2020), effective uses of humor (Kuhlman et al., 2021), and emotion regulation skills (Kuhlman et al., 2021, 2023; Masten et al., 2021). It is plausible that ELA leads youth to have a smaller repertoire of psychosocial resources to draw from, leading them to flourish less frequently. This possibility remains largely unknown as psychosocial resources that may explain links between ELA and resilience outcomes are typically examined in isolation (Schetter & Dolbier, 2011). Exploring the protective or promotive effects of singular psychosocial resources leaves unknown whether psychosocial resources confer resilience in a cumulative or compensatory manner. Cumulative indices of psychosocial resources test whether individuals demonstrate more resilience with increasing numbers of different psychosocial resources in which they are high or have mastery. By contrast, a compensatory index of psychosocial resources tests whether the presence of resources in which a person is high can make up for resources in which a person is low. These distinctions have direct implications for the development of targeted interventions among adversity-exposed youth.

Based on these gaps in the current literature, the present study sought to advance the empirical understanding of flourishing among adolescents by considering the role of ELA and psychosocial resources in the context of the COVID-19 pandemic. To do so, the moderated mediation shown in Figure 1 was tested to determine whether the association between ELA and flourishing was explained in part by psychosocial resources, and whether the role of those resources varied depending on the impact of COVID-19 in the participant’s life. Importantly, several psychosocial resources that are linked to resilience among youth have also been identified as either protective or promotive among adolescents in the context of the COVID-19 pandemic (See Doom et al., 2023 for review). Thus, the present study evaluated the indirect effect of both a cumulative and compensatory index of psychosocial factors (social support, cognitive reappraisal skills, expressive suppression, affiliative humor, self-enhancing humor, and sleep quality) on flourishing in this sample, and whether these indirect effects vary by COVID-19 impact. The present study was uniquely situated to do so with data collected as a part of a community-engaged research partnership between academic psychologists and a local non-profit organization that provides diversion programs to predominantly Hispanic/Latino and low-income youth and their families. Consistent with the broader under-representation of minoritized populations in biomedical research (Kuhlman et al., 2019), there is a genuine paucity of research on adolescent flourishing within both Spanish-speaking populations (Waigel & Lemos, 2023) and the impact of COVID-19 on under-represented minority youth (Doom et al., 2023). Again, this underscores the potential contribution of results from this sample to understanding flourishing during adolescence.

Figure 1.

Figure 1.

Open in a new tab

Conceptual model of parallel moderated mediation of adolescent flourishing during the COVID-19 pandemic.

Method

Participants were 223 youth aged 11–18 (47.5% female, 3.1% non-binary; 93.7% Hispanic and/or Latino). Participants were recruited in partnership with Project Youth OC (Project Youth OC » Empowering Youth Together, 2022), a nonprofit organization in Santa Ana, CA which provides comprehensive resources and services for youth at risk for adverse outcomes such as substance abuse, juvenile justice system involvement, and school truancy. Youth received referrals to Project Youth OC via the probation department, law enforcement, local schools, and the local school district’s Student Attendance Review Board (SARB). 403 youth were invited to participate, 317 (79%) consented to the survey, and 223 (55.3%) had complete data for the present analyses.

Procedures

The Institutional Review Board at the University of California Irvine approved all procedures used in this study. Procedures were developed following guidelines for conducting biobehavioral research with community partners in diverse settings (Kuhlman et al., 2019). To recruit participants, Project Youth staff called parents to inform them of the study or let them know about the study during their in-person visits to Project Youth. Interested parents were given a consent form and a parent survey. Staff offered parents a choice between Spanish or English recruitment materials and consent documents according to their preference; 58.2% of the parents who completed the consent form and parent survey completed them in Spanish. Parents who consented and filled out the parent survey were asked to provide their child’s name and contact information. Youth were then emailed or texted a link to the assent form (or an adult consent form for youth over 18) and the survey. Families with difficulties accessing technology with which to complete the survey were offered the opportunity to complete the survey at several in-person data collection events at the Project Youth facility. All data were collected via Qualtrics between April 2021 and April 2022. The vast majority of youth (83.1%) completed the survey within two hours, although participants were given the option to complete the survey across multiple sittings. Participants were given a $30 Target gift card as compensation.

Measures

Risk factors

Early life adversity (ELA).

ELA was measured via the Center for Youth Wellness Adverse Childhood Experiences Questionnaire (Purewal et al., 2016). This is an adapted version of the adverse childhood experiences assessment that has been used widely for the past three decades to demonstrate links between ELA and poor health (Felitti et al., 1998), and has been linked to psychiatric symptoms in other pediatric samples (Hall et al., 2023; Thomas et al., 2024; Zhen-Duan et al., 2023). Consistent with current clinical practice guidelines (Kameg & Fradkin, 2021; Purewal et al., 2016), item-level data was not collected from participants in order to promote participant privacy and confidentiality. Adolescents were shown the list of potential adversities, then asked to self-report the number of adverse childhood events they experienced from nineteen potential events. Possible types of adversity included household dysfunction (e.g., you lived with a household member who served time in jail or prison), abuse (e.g., someone pushed, grabbed, slapped, or threw something at you), and neglect (e.g., more than once, you went without food, clothing, a place to live, or had no one to protect you). Possible scores ranged from 0–19.

COVID-19 impact.

COVID-19 impact was assessed with the COVID-19 Adolescent Symptom and Psychological Experience questionnaire (CASPE) (Ladouceur, 2020). COVID-19 impact was assessed using two approaches: COVID-19 events and COVID-19 concerns. To measure COVID-19 events, participants were given a list of 13 possible events and asked to indicate which ones had happened in their household. Example items included: you or anyone you know got sick with COVID-19, job loss by one or both of your parents/guardians, difficulty paying bills or buying necessities, and parent/guardian filed for unemployment. The number of affirmative responses was then summed. COVID-19 concern was assessed via 18 items on a six-point Likert scale, with options ranging from one (not at all) to six (significantly). Example items included, “How concerned are you about the impact of the COVID-19 outbreak on the following,” with example items including “Conflict between parents,” “Friends might get sick,” and “Not having enough money.” The COVID-19 concern subscale exhibited excellent reliability in this sample, α = .92. Finally, to create an overall measure of objective and subjective COVID-19 impact on youth, raw scores on the COVID-19 events and COVID-19 concerns subscales were converted to z-scores and averaged (Kuhlman et al., 2021). High scores on the COVID-19 impact index represented high numbers of COVID-19-related events and concerns.

Psychosocial Resources

The psychosocial resources assessed in this study included social support, sleep quality, emotion regulation skills in cognitive reappraisal and expressive suppression, and use of humor to promote self-esteem and affiliation with others which have each been identified as aspects of resilience in the context of coping with chronic stress (Schetter & Dolbier, 2011). All psychosocial resources were measured using adolescent self-report on four questionnaires: the receiving subscale of the 2-way Social Support Scale (Shakespeare-Finch & Obst, 2011), Emotion Regulation Questionnaire (Gross & John, 2003), the Pittsburgh Sleep Quality Index (Buysse et al., 1989), and the Humor Styles Questionnaire (Martin et al., 2003). All of these instruments demonstrated acceptable to excellent internal consistency within this sample, α > .69. Additional details on these measures and their psychometric performance in this sample can be found in (Kuhlman et al., 2023). Scales were reverse-coded as needed such that high values across the array of measures were indicative of “better” functioning in that domain (e.g., sleep disturbance was recoded into sleep quality). Cumulative psychosocial resources were computed by adding the number of psychosocial resource measures in which each participant was in the top 25th percentile relative to the rest of the sample. Compensatory psychosocial resources were computed by averaging the z-score standardized scores for each subscale. Distinguishing psychosocial resources in this way has been shown to elucidate resilience processes in the context of cancer survivorship (Manigault et al., 2022). Supplemental table 1 provides descriptive statistics and bivariate correlations between individual psychosocial resources and the cumulative and compensatory psychosocial resource indices.

Outcome: Flourishing

Flourishing was assessed using the Mental Health Continuum Short-Form (Keyes, 2002), which asked youth to self-report how often they experienced or felt 14 items over the past month on a 6-point Likert scale, with one being “never” and six being “every day.” These items queried both hedonic (positive emotions) and eudaimonic (purpose, fulfillment) experiences. Example items included “happy,” “satisfied with life,” “that you liked most parts of your personality,” and “that your life has a sense of direction or meaning to it.” Responses to these fourteen items were used to categorize respondents as Flourishing if they responded with a 5 or 6 on items 1–3, then a 5 or 6 on at least six additional items from questions 4–14. Consistent with the broader definition of flourishing, individuals categorized as flourishing had higher average scores across each of the MHC-SF subscales than the rest of the sample, hedonic well-being F(1, 221) = 135.60 p < .001, eudaimonic psychological well-being F(1, 221) = 244.47 p < .001, and eudaimonic social well-being F(1, 221) = 288.15 p < .001.

Data analysis

All data analysis was conducted using SPSS version 29 and the Process MACRO version 4.3.1. The associations between sex, ELA, and flourishing were conducted using unadjusted Χ2 distribution comparisons. The fit of the data to the conceptual model was tested using Model 14 within the Process MACRO which simultaneously computes a direct effect of the independent variable (x) on the dependent variable (y) while controlling for the mediator (m), and an indirect effect of x on y as represented by the cross-product of the association between x and m and the association between m and y (Hayes, 2013). Reliability of the direct, indirect, and total effects was determined using 95% confidence intervals which were derived using 5,000 bootstrap resamples for each effect. This model (shown in Figure 1) predicted the likelihood of flourishing as a function of the direct effect of ELA, and the indirect effect of ELA through cumulative and compensatory indices of psychosocial resources. Mediations were tested simultaneously at high, average, and low COVID-19 impact. This moderated mediation model covaried for the effects of participant age (in years) and sex. Sex was included as a covariate because flourishing was not equally distributed across genders. Specifically, male participants were more likely to be categorized as flourishing than other participants, Χ2 = 12.63, d = −0.17, p = .01. Supplemental figure 1 shows the proportion of adolescents categorized as flourishing by gender.

Results

Early life adversity was prevalent in this sample, such that adolescents reported exposure to between 0 and 14 adversities, with the average participant reporting exposure to 3.16 adversities (SD = 3.51) and 34.5% (n = 77) reporting exposure to four or more. Despite the high adversity exposure, flourishing was common in this sample; 36.3% (n=81) self-reported scores consistent with flourishing. Higher reported ELA was robustly associated with a lower likelihood of flourishing, Χ2 = 49.61, d = −0.34, p < .001. Figure 2 shows the proportion of adolescents categorized as flourishing by the number of self-reported early life adversities.

Figure 2.

Figure 2.

Open in a new tab

Flourishing by early life adversity

Table 1 summarizes the descriptive statistics for all continuous variables included in analyses, as well as the unadjusted bivariate correlations between them. We then tested a parallel, moderated mediation model evaluating whether the association between ELA and flourishing occurred through cumulative or compensatory psychosocial resources, and simultaneously whether the association between psychosocial resources and flourishing was moderated by the impact of COVID-19 on the participants. Figure 3 summarizes the results of the moderated mediation. This model accounted for 21.4% of variance in whether participants were categorized as flourishing or not, R2 = 0.21, p < .0001. There continued to be a significant direct effect of ELA on flourishing, such that higher ELA was associated with a lower likelihood of flourishing, b = −0.05 (SE = 0.01), p = .0004, 95%CI[−0.07, −0.02]. Higher ELA was associated with lower compensatory psychosocial resources, b = −0.03 (SE = 0.01), p = .003, 95%CI[−0.05, −0.01], but was not associated with cumulative psychosocial resources, b = −0.03 (SE = 0.03), p = .30, 95%CI[−0.07, 0.02]. When predicting flourishing, there was a significant interaction between the total cumulative psychosocial resources and COVID-19 impact, b = −0.19 (SE = 0.07), p = .01, 95%CI[−0.33, −0.05], such that having a more diverse repertoire of psychosocial resources was associated with a higher likelihood of flourishing among participants reporting very low impact of COVID-19 on their lives, b = 0.13 (SE = 0.06), p = .03, 95%CI[0.01, 0.26], but not among participants reporting moderate, b = 0.01 (SE = 0.05), p = .66, 95%CI[−0.07, 0.11], or high COVID-19 impact, b = −0.10 (SE = 0.07), p = .14, 95%CI[−0.23, 0.03]. By comparison, compensatory psychosocial resources was associated with a higher likelihood of flourishing among participants reporting high, b = 0.40 (SE = 0.14), p = .006, 95%CI[0.12, 0.69], and moderate COVID-19 impact in their lives, b = 0.24 (SE = 0.11), p = .02, 95%CI[0.03, 0.46], but not among participants reporting low impact, b = 0.09 (SE = 0.13), p = .52, 95%CI[−0.17, 0.34]. Overall, there was a significant indirect effect of ELA on flourishing through compensatory psychosocial resources for those participants who experienced high COVID-19 impact in their lives, b = −0.01 (SE = 0.01), 95%CI[−0.03, −0.002].

Table 1.

Participant characteristics and bivariate correlations between psychosocial factors and flourishing.

M (SD) Correlations
1. 2. 3. 4. 5. 6. 7. 8.
1. Age (years) 15.04 (2.22) 1.0
2. Early life adversity 3.16 (3.51) .13+ 1.0
3. COVID-19 Impact (z-score) 0.18 (0.62) .28*** .31*** 1.0
4. Cumulative psychosocial resources 1.60 (1.31) −.02 −.08 −.06 1.0
5. Compensatory psychosocial resources (z-score) 0.00 (0.57) .02 −.20** −.07 .71*** 1.0
6. Eudaimonic social well-being 12.50 (6.66) −.02 −.41*** −.17 .27*** .33*** 1.0
7. Eudaimonic psychological well-being 17.73 (8.61) .03 −.34*** −.14* .29*** .37*** .78*** 1.0
8. Hedonic well-being 10.14 (4.18) −.04 −.38*** −.25 .27*** .38*** .75*** .75*** 1.0
Open in a new tab
***

p<.001,

**

p<.01,

*

p<.05,

+

p<.10

Figure 3.

Figure 3.

Open in a new tab

ELA and flourishing among adolescents as a function of psychosocial resources during the COVID-19 pandemic

Discussion

In this predominantly Hispanic/Latino sample of adolescents, higher ELA was robustly associated with a lower likelihood of flourishing. This was partly explained by compensatory, but not cumulative, psychosocial resources. Specifically, among the adolescents in the sample with the highest COVID-19 impact, higher ELA was associated with having lower compensatory psychosocial resources which explained the lower likelihood of flourishing. The present results highlight the complexity of resilience in development as indexed by flourishing, the value of leveraging existing theoretical frameworks on resilience that consider flourishing in the context of adversity, and the clinical utility of identifying interventions that increase compensatory psychosocial resources among adversity-exposed youth.

The prevalence of flourishing in the present sample was similar to estimates of flourishing more broadly among adolescents in the U.S.; 36% in the present sample and 40% nationally (Bethell et al., 2019). Consistent with the limited existing literature (Kwong & Hayes, 2017; van Schalkwyk & Wissing, 2010), higher ELA was robustly associated with lower likelihood of flourishing. Specifically, more than 60% of youth with no ELA were categorized as flourishing whereas fewer than 20% of youth with four or more ELA were categorized as flourishing. That so few studies have looked at flourishing in the context of adversity or even within low-income populations is striking. This begs the question: what can be known about flourishing in the absence of psychosocial contexts that are known to be so closely tied to mental health? The present study attempted to demonstrate the utility of using theoretical models developed within developmental psychopathology to better understand flourishing as a measure of resilience. Using this theoretically-driven approach, we showed that while ELA was closely and negatively linked to flourishing independent of psychosocial resources and the impact of COVID-19, an indirect pathway emerged among youth reporting high COVID-19 impact through lower compensatory psychosocial resources.

Psychosocial resources were indexed in two separate ways in this data: cumulative and compensatory. Compensatory psychosocial resources reflected an individual’s tendency to be high or low relative to the sample across the array of resources measured. However, a person could be somewhat moderate across the board and have the same score as another person who had relative strengths in a few areas and relative weaknesses in others. By comparison, cumulative psychosocial resources reflect the number of measured resources in which the participant was relatively high (>75th percentile). In the former, relative strengths can compensate for relative weaknesses; in the latter, they cannot. In this sample, higher ELA was associated with lower compensatory psychosocial resources, but ELA was not associated with cumulative psychosocial resources. Further, for youth reporting high COVID-19 impact, compensatory psychosocial resources explained the association between high ELA and lower flourishing. While the implications of this data remain theoretical, this observation suggests that clinical interventions that help youth gain a relative strength or even mastery in even one psychosocial resource domain may confer more potential for resilience in high-risk populations who are experiencing high contextual stress. This is largely consistent with the growing empirical literature on resilience in development (Masten, 2001; Masten et al., 2021) as well as converging evidence on youth resilience in the context of the COVID-19 pandemic (Doom et al., 2023). In the present sample, higher scores on compensatory psychosocial resources were most closely associated with higher social support, more frequent use of self-enhancing humor, and cognitive reappraisal (See supplemental table 1), all of which may be promising targets to explore. Considering psychosocial resource repertoires in this way may help to clarify why ELA is a robust predictor of group-level, but not individual-level, health outcomes (Baldwin et al., 2021), as well as guide identification of resilience-promoting interventions for this population.

The results of this study must be considered in the context of the study’s limitations. First, the present study was conducted with data from a relatively small community sample. One notable strength of the adolescent flourishing literature has been the use of datasets with thousands of participants (Waigel & Lemos, 2023). The present findings extend this knowledge to a smaller but high-risk and under-served population of Hispanic/Latino youth, and highlight the need for more and larger studies in similar populations in the context of the adversities they face. While adolescent membership in adversity-related risk groups does not differ based on parent and self-reported exposure (e.g., Kuhlman et al., 2022), adversity in this study was indexed by adolescent self-report which may have under-represented exposure that occurred in infancy or early childhood. Further, the aim of this study was to model resilience as indexed by flourishing within the theoretical framework proposed for studies of resilience to psychopathology during development (Masten et al., 2021), however this theoretical framework clearly calls for consideration of the role of family, school, and community in the lives of children. The present data only assessed individual psychological resources, therefore the role of additional systems in this model remains unknown. From the present data, we can conclude that flourishing decreases with increasing exposure to ELA, that this association is more evident in the context of a chronic stressor such as the COVID-19 pandemic, and that compensatory psychosocial resources may be a modifiable target through which this risk pathway may be mitigated.

Supplementary Material

supplemental material

Public Significance Statement:

This study advances the understanding of flourishing by placing it within the context of resilience in development and highlighting how adolescents exposed to early life adversity benefit from compensatory psychosocial resources when facing a chronic ongoing stressor. Further, the present study aims to shift the narrative within research on adversity-exposed youth from focusing on risk and psychopathology to recognizing pathways to resilience.

Acknowledgements

Funding for this project was provided by the National Center for Research Resources and the National Center for Advancing Translational Sciences, National Institutes of Health (UL1 TR001414) through a UCI Campus-Community Research Incubator grant awarded to Kate Kuhlman and Project Youth OC. The data for this project was collected by the team at the UCI Teen Resilience Lab (teenresilience.org).

Footnotes

The authors have no known conflicts of interest to disclose.

References

  1. Baldwin JR, Caspi A, Meehan AJ, Ambler A, Arseneault L, Fisher HL, Harrington H, Matthews T, Odgers CL, Poulton R, Ramrakha S, Moffitt TE, & Danese A (2021). Population vs individual prediction of poor health from results of adverse childhood experiences screening. JAMA Pediatrics, 175(4), 1–9. 10.1001/jamapediatrics.2020.5602 [DOI] [Google Scholar]
  2. Bethell CD, Gombojav N, & Whitaker RC (2019). Family resilience and connection promote flourishing among US children, even amid adversity. Health Affairs (Project Hope), 38(5), 729–737. 10.1377/hlthaff.2018.05425 [DOI] [PubMed] [Google Scholar]
  3. Buysse DJ, Reynolds CF III, Monk TH, Berman SR, & Kupfer DJ (1989). The Pittsburgh sleep quality index: A new instrument for psychiatric practice and research. Psychiatry Research, 28(2), 193–213. 10.1016/0165-1781(89)90047-4 [DOI] [PubMed] [Google Scholar]
  4. Cosco TD, Hardy R, Howe LD, & Richards M (2019). Early-life adversity, later-life mental health, and resilience resources: A longitudinal population-based birth cohort analysis. International Psychogeriatrics, 31(9), 1249–1258. 10.1017/S1041610218001795 [DOI] [PubMed] [Google Scholar]
  5. Datu JAD (2018). Flourishing is associated with higher academic achievement and engagement in Filipino undergraduate and high school students. Journal of Happiness Studies, 19(1), 27–39. 10.1007/s10902-016-9805-2 [DOI] [Google Scholar]
  6. Doom JR, Deer LK, Dieujuste N, Han D, Rivera KM, & Scott SR (2023). Youth psychosocial resilience during the COVID-19 pandemic. Current Opinion in Psychology, 53, 101656. 10.1016/j.copsyc.2023.101656 [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Felitti VJ, Anda RF, Nordenberg D, Williamson DF, Spitz AM, Edwards V, Koss MP, & Marks JS (1998). Relationship of childhood abuse and household dysfunction to many of the leading causes of death in adults: The Adverse Childhood Experiences (ACE) Study. American Journal of Preventive Medicine, 14(4), 245–258. 10.1016/S0749-3797(98)00017-8 [DOI] [PubMed] [Google Scholar]
  8. Gross JJ, & John OP (2003). Individual differences in two emotion regulation processes: Implications for affect, relationships, and well-being. Journal of Personality and Social Psychology, 85(2), 348–362. 10.1037/0022-3514.85.2.348 [DOI] [PubMed] [Google Scholar]
  9. Hall A, West X, Brown M, Hall E, Kim E, Leib A, Mergaman P, Salih Z, & Aronoff S (2023). Association of adverse childhood experiences and resilience with obesity, high blood pressure, and parental report of behavioral health symptoms in children: A cross sectional study. Global Pediatric Health, 10, 2333794X231159518. 10.1177/2333794X231159518 [DOI] [Google Scholar]
  10. Hayes AF (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach. Guilford Press. [Google Scholar]
  11. Kameg BN, & Fradkin D (2021). Adverse Childhood Experiences in Youth: Trauma-Informed Assessment, Diagnosis, and Management. The Journal for Nurse Practitioners, 17(1), 87–92. 10.1016/j.nurpra.2020.04.026 [DOI] [Google Scholar]
  12. Keyes CL (2002). The Mental Health Continuum: From languishing to flourishing in life. Journal of Health and Social Behavior, 43(2), 207–222. [PubMed] [Google Scholar]
  13. Kuhlman KR (2024). Pitfalls and potential: Translating the two-hit model of early life stress from pre-clinical non-human experiments to human samples. Brain, Behavior, & Immunity - Health, 35, 100711. 10.1016/j.bbih.2023.100711 [DOI] [Google Scholar]
  14. Kuhlman KR, Antici E, Tan E, Tran M-L, Rodgers-Romero EL, & Restrepo N (2023). Predictors of adolescent resilience during the COVID-19 pandemic in a community sample of Hispanic and Latinx youth: Expressive suppression and social support. Research on Child and Adolescent Psychopathology, 51(5), 639–651. 10.1007/s10802-022-01019-8 [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Kuhlman KR, Chiang JJ, Bower JE, Irwin MR, Cole SW, Dahl RE, Almeida DM, & Fuligni AJ (2020). Persistent low positive affect and sleep disturbance across adolescence moderate link between stress and depressive symptoms in early adulthood. Journal of Abnormal Child Psychology, 48(1), 109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Kuhlman KR, Cole SW, Craske MG, Fuligni AJ, Irwin MR, & Bower JE (2022). Enhanced immune activation following acute social stress among adolescents with early life adversity. Biological Psychiatry: Global Open Science. 10.1016/j.bpsgos.2022.03.001 [DOI] [Google Scholar]
  17. Kuhlman KR, Straka K, Mousavi Z, Tran M-L, & Rodgers E (2021). Predictors of adolescent resilience during the COVID-19 pandemic: Cognitive reappraisal and humor. The Journal of Adolescent Health, 69(5), 729–736. 10.1016/j.jadohealth.2021.07.006 [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kuhlman KR, Urizar GG, Robles TF, Yim IS, & Dunkel Schetter C (2019). Testing plausible biopsychosocial models in diverse community samples: Common pitfalls and strategies. Psychoneuroendocrinology, 107, 191–200. 10.1016/j.psyneuen.2019.05.017 [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Kwong TY, & Hayes DK (2017). Adverse family experiences and flourishing amongst children ages 6–17 years: 2011/12 National Survey of Children’s Health. Child Abuse & Neglect, 70, 240–246. 10.1016/j.chiabu.2017.06.016 [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Ladouceur CD (2020). COVID-19 Adolescent Symptom and Psychological Experience Questionnaire (CASPE). NIH Public Health Emergency and Disaster Research Response (D2). https://www.nlm.nih.gov/dr2/CASPE_AdolSelfReport_Qualtrics.pdf
  21. Manigault AW, Kuhlman KR, Irwin MR, Cole SW, Ganz PA, Crespi CM, & Bower JE (2022). Psychosocial resilience to inflammation-associated depression: A prospective study of breast-cancer survivors. Psychological Science, 33(8), 1328–1339. 10.1177/09567976221079633 [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Martin RA, Puhlik-Doris P, Larsen G, Gray J, & Weir K (2003). Individual differences in uses of humor and their relation to psychological well-being: Development of the Humor Styles Questionnaire. Journal of Research in Personality, 37(1), 48–75. 10.1016/S0092-6566(02)00534-2 [DOI] [Google Scholar]
  23. Masten AS (2001). Ordinary magic: Resilience processes in development. The American Psychologist, 56(3), 227–238. 10.1037//0003-066x.56.3.227 [DOI] [PubMed] [Google Scholar]
  24. Masten AS (2004). Regulatory processes, risk, and resilience in adolescent development. Annals of the New York Academy of Sciences 2004, 310–319. [Google Scholar]
  25. Masten AS, Lucke CM, Nelson KM, & Stallworthy I (2021). Resilience in development and psychopathology: Multisystem perspectives. Annual Review of Clinical Psychology, 17, 521–549. 10.1146/annurev-clinpsy-081219-120307 [DOI] [Google Scholar]
  26. McLaughlin KA, Green JG, Gruber MJ, Sampson NA, Zaslavsky AM, & Kessler RC (2010). Childhood adversities and adult psychiatric disorders in the National Comorbidity Survey Replication II: Associations with persistence of DSM-IV disorders. Arch Gen Psychiatry, 67(2), 124–132. 10.1001/archgenpsychiatry.2009.187 [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. McLaughlin KA, Green JG, Gruber MJ, Sampson NA, Zaslavsky AM, & Kessler RC (2012). Childhood adversities and first onset of psychiatric disorders in a national sample of US adolescents. Archives of General Psychiatry, 69(11), 1151–1160. 10.1001/archgenpsychiatry.2011.2277 [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. O’Connor M, Sanson AV, Toumbourou JW, Norrish J, & Olsson CA (2017). Does positive mental health in adolescence longitudinally predict healthy transitions in young adulthood? Journal of Happiness Studies, 18(1), 177–198. 10.1007/s10902-016-9723-3 [DOI] [Google Scholar]
  29. Project Youth OC » Empowering Youth Together. (2022). https://projectyouthocbf.org/
  30. Purewal SK, Bucci M, Wang LG, Koita K, Marques SS, Oh D, & Harris NB (2016). Screening for adverse childhood experiences (ACEs) in an integrated pediatric care model. Zero to Three, 37(1), 10–17. [Google Scholar]
  31. Rey L, Mérida-López S, Sánchez-Álvarez N, & Extremera N (2019). When and how do emotional intelligence and flourishing protect against suicide risk in adolescent bullying victims? International Journal of Environmental Research and Public Health, 16(12), 2114. 10.3390/ijerph16122114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  32. Schetter CD, & Dolbier C (2011). Resilience in the context of chronic stress and health in adults. Social and Personality Psychology Compass, 5(9), 634. 10.1111/j.1751-9004.2011.00379.x [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Schotanus-Dijkstra M, Pieterse ME, Drossaert CHC, Westerhof GJ, de Graaf R, ten Have M, Walburg JA, & Bohlmeijer ET (2016). What factors are associated with flourishing? Results from a large representative national sample. Journal of Happiness Studies, 17(4), 1351–1370. 10.1007/s10902-015-9647-3 [DOI] [Google Scholar]
  34. Shakespeare-Finch J, & Obst PL (2011). The development of the 2-Way Social Support Scale: A measure of giving and receiving emotional and instrumental support. Journal of Personality Assessment, 93(5), 483–490. 10.1080/00223891.2011.594124 [DOI] [PubMed] [Google Scholar]
  35. Taylor SE, & Stanton AL (2007). Coping resources, coping processes, and mental health. Annual Review of Clinical Psychology, 3, 377–401. 10.1146/annurev.clinpsy.3.022806.091520 [DOI] [Google Scholar]
  36. Thomas SA, Thompson EC, Peters JR, Micalizzi L, Meisel SN, Maron M, Ryan SK, & Wolff JC (2024). Investigating substance use as a coping strategy among adolescent psychiatric inpatients: A comparative analysis before and during the COVID-19 pandemic. Child Psychiatry & Human Development. 10.1007/s10578-024-01731-0 [DOI] [Google Scholar]
  37. van Schalkwyk I, & Wissing MP (2010). Psychosocial well-being in a group of South African adolescents. Journal of Psychology in Africa, 20(1), 53–60. 10.1080/14330237.2010.10820342 [DOI] [Google Scholar]
  38. Waigel NC, & Lemos VN (2023). A systematic review of adolescent flourishing. Europe’s Journal of Psychology, 19(1), 79–99. 10.5964/ejop.6831 [DOI] [Google Scholar]
  39. Witten H, Savahl S, & Adams S (2019). Adolescent flourishing: A systematic review. Cogent Psychology, 6(1), 1640341. 10.1080/23311908.2019.1640341 [DOI] [Google Scholar]
  40. Zhen-Duan J, Nuñez M, Solomon MB, Geracioti T, & Jacquez F (2023). Adverse childhood experiences and alcohol use among U.S.-born and immigrant Latinx youth: The roles of social support and stress hormones. Journal of Child and Family Studies, 32(11), 3568–3580. 10.1007/s10826-023-02550-y [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

supplemental material
NIHMS2061241-supplement-supplemental_material.docx (33KB, docx)

RESOURCES