Abstract
There is scant research on how Asian American adolescents’ resiliency relates to mental well-being in adulthood. The objective of this study was to determine the prospective associations between resiliency factors (individual, family, and school community) in adolescence and mental health outcomes in adulthood, among a national sample of Asian Americans. We analyzed data from 1020 Asian American adolescents who were followed for 14 years in the National Longitudinal Study of Adolescent to Adult Health. Of the resiliency factors, individual self-esteem (Adjusted Odds Ratio [AOR] 0.54, 95% Confidence Interval [CI] 0.37–0.79) and family connectedness (AOR 0.78, 95% CI 0.65–0.93) in adolescence were found to be protective against adult mental health outcomes in logistic regression models adjusting for sociodemographic factors and baseline mental health. Our study identified individual and family resiliency factors which can be leveraged to help Asian American adolescents and families in cultivating better mental health.
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Introduction
Background
The Asian American community is currently one of the fastest growing populations in the nation [1]. They constitute a diverse population with multifaceted cultural, social, linguistic, familial, and religious values which span generations of acculturation [2]. Given this, many Asian American youth identify as third-culture children—straddling their American identity and that of their parents’ home country [3].
This unique positionality has both positive and negative implications for mental health. Overall, Asian Americans report lower rates of psychiatric disorders as compared to their white peers; however, the persistence of these conditions throughout one’s lifetime is similar between these two groups [4]. Serious mental illness, which is defined by the Substance Abuse and Mental Health Services Administration as a mental, emotional, or behavioral condition that significantly limits one’s functional ability and impedes one’s daily life, increased by almost two-fold among Asian American young adults (ages 18–25) between 2008 and 2018 [5]. Moreover, suicide was the most common cause of death among 15–24 year-old Asian American youth in 2019 [6]. In a study looking at the prevalence of psychiatric disorders among Asian American adults, 10.2% had a lifetime diagnosis of an anxiety or panic disorder, 9.5% had a lifetime diagnosis of a mood disorder, and 18.1% had a lifetime diagnosis of any mental health disorder [7].
Research on the disparities in Asian American mental health focuses on risk factors such as exposure to discrimination [8, 9], mental health stigma [10, 11], and poor rates of formal service utilization [12,13,14]. For Asian American youth, generational differences, language proficiency, ethnic marginalization, and family conflict have all been associated with increased depression [15, 16]. Meanwhile bicultural identity, personal spirituality, ethnic belonging, and enculturation have been shown to be protective against depression [16]. Furthermore, research has shown that peer relationships and ethnic identity may be protective against future depression and suicidal ideation among Filipino and Korean Americans [15]. Yet, there is little research that captures the richness of the Asian American community’s resiliency as a whole and how that might be elevated as a protective measure.
Theoretical Framework
Resiliency is the ability to adapt in the face of adverse experiences [17]. Resiliency can be built through protective factors that promote internal strength and connectedness [18]. A resiliency, rather than risk, framework centers the strengths and resources individuals, families, or communities employ to adapt to change and adversity [19, 20]. A socioecological framework provides a holistic and robust approach to exploring how to best support Asian Americans’ mental health throughout development (see Fig. 1) [21]. In a socioecological framework, protective factors can manifest on an individual (e.g., self-esteem, wellness), family (e.g., cohesion), and/or community (e.g., school inclusion) level in order to reduce behaviors that are harmful to the health and well-being of young people [17, 18, 17,22,18].
Previous literature has described resiliency as being fostered through protective factors that preserve one’s well-being through positive and productive engagement, connectedness with others, and optimized stress coping mechanisms [14].
While it has been repeatedly shown in the literature that Asian Americans underutilize mental health services and are at higher risk for adverse mental health symptomatology, there is limited research that provides insight on how to leverage this community’s assets in order to cultivate Asian American adolescents’ resiliency for future mental well-being in adulthood [24,25,26]. Furthermore, many existing studies on Asian American mental health utilize cross-sectional data and are not national, thus limiting the ability to understand associations between exposures and outcomes over time. Given these gaps in the literature, our study aims to determine the prospective associations between resiliency factors during adolescence within the context of the socioecological framework (individual, family, and community) and mental health outcomes, including depression, anxiety, and suicidality, in adulthood among a national sample of Asian Americans.
Methods
Participants
Our study utilized data from the National Longitudinal Study of Adolescent to Adult Health (Add Health) [27]. Add Health is a national, prospective cohort study that followed a U.S. population of adolescents into adulthood over five waves from 1994 to 2018. Data for the current study were from Wave I (1994–1995, adolescents aged 11–18 years) and Wave IV (2008–2009, adults aged 24–32 years).
The baseline (Wave I) Add Health study included 20,475 participants from 132 schools, recruiting from sites across the country. Among these participants, 1584 identified as Asian or Pacific Islander (Chinese, Korean, Filipino, Vietnamese, Indian, Japanese, & Other Asian) [28] and 1020 were followed through Wave IV. These 1020 participants who had data available for both Wave I and Wave IV comprised our final Asian American analytic sample.
The University of North Carolina School of Public Health Institutional Review Board (IRB) oversees the Add Health study. All participants provided informed consent in writing following IRB guidelines and the Code of Federal Regulations on the Protection of Human Subjects.
Data Collection
As part of the Wave I data collection, students were asked to fill out an hour-long questionnaire within their classroom settings. This survey captured student responses about themselves, their family, and their community. Wave IV data was completed in 2008–2009 through in-home interviews with 15,701 study participants, aged 24–32. 92.5% of Wave IV participants were identified and located, of whom 80.3% were successfully interviewed. Higher rates of response were noted for US-born, white, and female participants. Add Health study investigators studied the difference between those who completed the interview and those who did not, and found that after study estimates were adjusted for final sampling weights, all study measures showed little relative and total bias for respondents vs. nonrespondents. The only area that showed significant differences was noted in those nonrespondents with low verbal capabilities, though this may be due to low total population in the Add Health sample. Add Health study investigators note that Wave IV sample bias is minimal, and that the population surveyed is comparable to that interviewed in Wave I [29]. These interviews included questions about mental health outcomes including depression, suicidality, and anxiety.
Measures
Sociodemographic Covariates
We considered sex, country of birth, age, household income, household size, sexual identity, and baseline depression/suicidality as co-variates. A detailed description of independent, dependent, measures and covariates can be found in the below, Table 1.
Primary Exposure Variable: Resiliency
Our study’s primary independent variable was based on the socioecological model of resiliency–the ability to positively adapt even through the experience of hardship [17]. Building upon previous literature, the protective factors chosen were mapped to the validated questionnaire and responses from the Add Health codebook [23, 34,35,36]. Using prior research looking at Add Health data and adolescent resiliency as a guide, protective factors were grouped into individual, family, and school-community level measures [37]. The measures comprising our primary predictor variable of resiliency factors include the school connectedness scale [38], family connectedness scale [39, 40], parental presence scale [34], family activities scale [34], self-esteem scale [36, 41, 42], emotional well-being scale [34], and coping skills scale [35], all of which have been previously described in the literature.
Primary Outcome Variable: Mental Health Outcomes
Our study’s primary outcome variable of adult mental health outcomes comes from self-reported at-home interviews conducted during Wave IV with participants aged 24–32 in 2008–2009. The “mental health outcomes” variable includes any of the following: self-reported lifetime diagnosis of depression, lifetime diagnosis of anxiety or panic disorder, suicidality, and/or having a positive Center for Epidemiologic Studies Depression scale (CES-D-10) for current depressive symptoms [23, 43].
Statistical Analysis
Descriptive statistics were performed to characterize the sample. Unadjusted associations between each resiliency factor (Wave I), as the independent variable, and mental health outcomes (Wave IV), as the dependent variable, were determined using multiple logistic regression analyses. Resiliency factors associated with mental health outcomes at Wave IV were examined in adjusted logistic regression analyses. Adjusted analyses controlled for sociodemographic variables that were associated with mental health outcomes (Wave IV) in univariate analyses, including sexual minority status and baseline depression or suicidality (participants were not asked at baseline about anxiety or depressive symptoms). When checking for statistical assumptions, we were not able to include emotional well-being, self-esteem, and family connectedness in the same model because they were highly multicollinear (variance inflation factors > 50); thus, separate models were run for these predictors. Two-sided alpha was set at 0.05. All analyses utilized nationally representative sample weighting and were conducted using Stata 15.1.
Results
Of the 1020 study participants with Wave I and Wave IV data who self-identified as Asian American or Pacific Islander, 20.4% identified as Chinese, 38.7% Filipino, 9.4% Japanese, 4.2% Asian Indian, 8.9% Korean, 6.9% Vietnamese, and 25.5% other Asian. The mean age ± standard error of participants at baseline was 15.6 ± 0.25 years. Just over half the participants were male (52%) and about 11% identified as sexual minorities in adulthood. Mean household size was 5.0 ± 0.26 people and average household income was 49.7 ± 2.39 thousands of dollars at baseline. Almost 60% of participants were born in the United States. The mean score of resiliency factor scales at baseline (Wave I) are grouped using the socioecological framework: individual (emotional wellbeing = 0.77 ± 0.02, coping skills = 3.20 ± 0.03, self-esteem = 4.78 ± 0.04), family (family connectedness = 8.44 ± 0.06, parental presence = 2.26 ± 0.05, family activities = 1.62 ± 0.07), and school community (school connectedness = 3.75 ± 0.04) levels. At Wave I, almost half of the participants reported depression or suicidality as opposed to Wave IV where about one-third of the respondents experienced mental health outcomes (Table 2).
In logistic regression analyses (Table 3), higher self-esteem in adolescence was associated with more than two-fold lower odds of poorer mental health outcomes in adulthood amongst study participants in both unadjusted and adjusted models (odds ratio [OR] 0.44, 95% confidence interval [CI] = 0.31–0.61; adjusted odds ratio [AOR] 0.54, 95% CI = 0.37–0.79). Similarly, greater levels of family connectedness during adolescence were associated with reduced odds of poor mental health outcomes in adulthood in both adjusted and unadjusted models (OR 0.69, 95% CI = 0.59–0.81; AOR 0.78, 95% CI = 0.65–0.93). Higher levels of adolescent emotional well-being were also associated with 60% lower odds of poorer adult mental health outcomes; however, this association was diminished and no longer significant after adjusting for potential confounders (OR 0.42, 95% CI = 0.26–0.69; AOR 0.66, 95% CI = 0.36–1.19). Significant associations were not found between coping skills, parental activities, school connectedness, or parent presence in adolescence and adult mental health outcomes.
Discussion
Our study shows that several individual and family adolescent resiliency factors present during adolescence are strong predictors of better mental health outcomes in early adulthood amongst the Asian American community. Particularly, self-esteem (individual) and family connectedness (family) were protective against mental health outcomes independent of other demographic and clinical factors. Among Asian American adolescents, self-esteem was associated with a roughly 50% lower odds of mental health outcomes in early adulthood. Similarly, family connectedness in adolescence was linked to four-fold lower odds of mental health outcomes.
Despite the known mental health burden among the Asian American population, many Asian Americans with mental health needs continue to have the lowest rates of formal treatment [13, 44], with evidence suggesting that Asian American immigrants are more likely to rely on informal supports or services [8]. Since mental health services have been chronically underutilized by the Asian American community [19, 20], protective resiliency factors like family connectedness and self-esteem should be cultivated among Asian American adolescents to promote positive psychological adaptation.
These findings are complemented by prior research and theory showing the importance of individual, family, and community level resiliency factors in preventing poor mental health outcomes within a socioecological model. Our results are consistent with established literature demonstrating that higher self-esteem, an individual level resiliency factor, is associated with better mental health [45,46,47]. It is important to note that prior literature has indicated that despite reporting the highest levels of personal and parental education, Asian American adolescents commonly report the lowest self-esteem scores compared to all other racial/ethnic subgroups [48]. Moreover, it has been previously demonstrated that self-esteem mediates the relationship between discrimination and depression, specifically in Asian American second generation immigrants [46]. One study looking at Chinese-American young adults shows that strong cultural identity, through multilingualism and pride in heritage, is positively associated with higher self-esteem [49]. With the context of these prior findings, our results indicated that improving mental health among the Asian American community requires dismantling the myth of the “Model Minority” and developing positive adolescent self-esteem through culturally relevant means in a way that strengthens resiliency at an individual level [50].
Research has suggested that strong family relationships have been protective against suicide attempts by Asian American adolescents, depending on the level of acculturation [51]. However, in a study addressing the unmet mental health needs of urban Asian American adolescents, family support was identified by service providers as the most prevalent need [52]. Our results amplify this identified gap in holistic care, suggesting that providing scaffolding to bolster family connectedness can be suppressive of future mental health disease.
This research has several strengths including its large and diverse participant sample, use of validated measures, asset-based approach, and longitudinal design. However, several limitations should be addressed. Since this was prospective cohort study, the associations between resiliency factors and mental health outcomes in the Asian American community may be affected by confounding variables, and causality cannot be established. Additionally, while we controlled for baseline depression/suicidality, we could not factor in lifetime diagnosis of depression or anxiety as we did in our primary outcome variable due to the fact these components were not collected in Wave I. However, we controlled for several potential sociodemographic confounders in the regression models. Given the vast diversity of the Asian American population, another limitation of our study is that our results are not disaggregated by any of the over 20 origin groups that constitute this community [2] due to the small sample sizes and insufficient power in each of the possible subgroups. The breakdown of Asian subgroups in our data does not fully capture the demographics of this population in the United States [2]; however, survey weighting was implemented as a means by which to mitigate the lack of representative data. Additionally, the socioecological model of resiliency may include additional individual, family, and community factors that might also be important in predicting adult mental health outcomes, which were not collected in Add Health [26].
New Contributions to the Literature
By utilizing a large, nationally representative study population and a 14-year, longitudinal, prospective analysis, this study provides insight on how to best identify Asian American adolescents’ strengths in order to support their adult mental health outcomes. Our results provide new insight on the importance of adolescent self-esteem, an individual level resiliency factor, and family connectedness, a family level resiliency factor, in protecting against adverse mental health outcomes in the Asian American population. Applying the socioecological model of resilience with Asian Americans is a novel approach to framing the factors that clinicians, educators, and caregivers should consider when addressing behavioral, emotional, or psychological issues within this population.
The Asian American community has been historically underrepresented and understudied in scientific research [53, 54]. Given the growing reports of discrimination against Asian Americans and hate crimes directed towards this population during the current COVID-19 pandemic [55,56,57], identifying ways to foster this community’s resilience and mental health is crucial. Our results may have important implications for clinical practice and mental health policy. Culturally relevant ways by which trusted adults can help foster self-esteem among Asian American youth and by which anchor institutions can provide guidance for primary caretakers in building family connection, should be considered as possible interventions. Leveraging the socioecological model of resilience with Asian American adolescents may be a way to prevent negative mental health outcomes in adulthood. Helping develop skills for both caretakers and their youth can promote resilience on a family and individual level. That being said, further research is still needed to explore the relationship between resiliency factors in Asian American youth stratifying by subgroup to study the impact of these communities’ unique cultural, linguistic, and social identities on adult mental health outcomes.
Data Availability
This study analyses restricted-use data from Add Health. Persons interested in obtaining Data Files from Add Health should contact Add Health, The University of North Carolina at Chapel Hill, Carolina Population Center, 206 W. Franklin Street, Chapel Hill, NC 27,516 − 2524 (addhealth_contracts@unc.edu). Further information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). The authors did not receive special access privileges to the data that others would not have.
References
Asian Americans | Pew Research Center [Internet]. [cited 2021 Feb 7]. Available from: https://www.pewsocialtrends.org/rise-of-asian-americans-2012-analysis/overview/.
Budiman A, Ruiz NG. Key facts about Asian Americans | Pew Research Center [Internet]. 2021 [cited 2021 Feb 7]. Available from: https://www.pewresearch.org/fact-tank/2017/09/08/key-facts-about-asian-americans/.
Tanu D. Toward an interdisciplinary analysis of the diversity of “Third Culture Kids.” In: Benjamin S, Dervin F, editors. Migration, diversity, and education. London: Palgrave Macmillan; 2015.
Xu Y, Okuda M, Hser Y-I, Hasin D, Liu S-M, Grant BF, et al. Twelve-month prevalence of psychiatric disorders and treatment-seeking among Asian Americans/Pacific Islanders in the United States: Results from the National Epidemiological Survey on Alcohol and Related Conditions. J Psychiatr Res. 2011;45:910.
Department of Health and Human Services. Substance Abuse and Mental Health Services Administration. 2018 National Survey on Drug Use and Health: Asians/Native Hawaiians and Other Pacific Islanders (NHOPI) [Internet]. 2018. Available from: https://www.samhsa.gov/data/sites/default/files/reports/rpt23248/3_Asian_NHOPI_2020_01_14_508.pdf.
The Office of Minority Health. Mental and Behavioral Health - Asian Americans - The Office of Minority Health [Internet]. 2021 [cited 2021 Jul 8]. Available from: https://minorityhealth.hhs.gov/omh/browse.aspx?lvl=4&lvlid=54.
Hong S, Walton E, Tamaki E, Sabin JA. Lifetime prevalence of mental disorders among Asian Americans: Nativity, gender, and sociodemographic correlates. Asian Am J Psychol. 2014;5:353.
Spencer MS, Chen J, Gee GC, Fabian CG, Takeuchi DT. Discrimination and mental health-related service use in a national study of Asian Americans. Am J Public Health. 2010;100:2410.
Spencer MS, Chen J. Effect of discrimination on mental health service utilization among Chinese Americans. Am J Public Health. 2004;94:809.
Augsberger A, Yeung A, Dougher M, Hahm HC. Factors influencing the underutilization of mental health services among Asian American women with a history of depression and suicide. BMC Health Serv Res [Internet]. BioMed Central Ltd.; 2015 [cited 2021 Jan 21];15
Kwok J. Factors that influence the diagnoses of Asian Americans in mental health: an exploration. Perspect Psychiatr Care. 2013;49:288–92.
Le Meyer O, Zane N, Cho Y, Il, Takeuchi DT. Use of Specialty Mental Health Services by Asian Americans With Psychiatric Disorders. J Consult Clin Psychol 2009 77:1000–5.
Yang KG, Rodgers CRR, Lee E, Cook BL. Disparities in mental health care utilization and perceived need among Asian Americans: 2012–2016. Psychiatr Serv. 2020;71:21–7.
Brice C, Masia Warner C, Okazaki S, Ma PWW, Sanchez A, Esseling P, et al. Social anxiety and mental health service use among Asian American high school students. Child Psychiatry Hum Dev. 2015;46:693–701.
Choi Y, Park M, Noh S, Lee JP, Takeuchi D. Asian American mental health: longitudinal trend and explanatory factors among young Filipino- and Korean Americans. SSM - Popul Health. 2020;10:100542.
Wyatt LC, Ung T, Park R, Kwon SC, Trinh-Shevrin C. Risk factors of suicide and depression among asian American, native Hawaiian, and Pacific Islander youth: a systematic literature review. J Health Care Poor Underserved. 2015;26(2 Suppl):191–237.
Luthar SS, Cicchetti D, Becker B. The construct of resilience: a critical evaluation and guidelines for future work. Child Dev. 2000;71(3):543–62.
Prince-Embury S, Saklofske DH, Nordstokke DW. The resiliency scale for young adults. J Psychoeduc Assess. 2017;35:276–90.
Ungar M. The social ecology of resilience: A handbook of theory and practice. Soc. Ecol. Resil. A Handb. Theory Pract. Springer New York; 2012.
Walsh F. Facilitating family resilience: Relational resources for positive youth development in conditions of adversity. Soc Ecol Resil A Handb Theory Pract [Internet]. Springer New York; 2012 [cited 2021 Feb 24]. pp. 173–85. Available from: /record/2011-30122-015.
Yoshikawa H, Mistry R, Wang Y. Advancing methods in research on Asian American children and youth. Child Dev. 2016;87:1033–50.
Croll J, Neumark-Sztainer D, Story M, Ireland M. Prevalence and risk and protective factors related to disordered eating behaviors among adolescents: relationship to gender and ethnicity. J Adolesc Health. 2002;31:166–75.
Easterlin MC, Chung PJ, Leng M, Dudovitz R. Association of team sports participation with long-term mental health outcomes among individuals exposed to adverse childhood experiences. JAMA Pediatr. 2019;173:681–8.
Chen P, Hussey JM, Monbureau TO. Depression and Antidepressant Use Among Asian and Hispanic Adults: Association with Immigrant Generation and Language Use. J Immigr Minor Health. 2018;20:619–31.
Erausquin JT, McCoy TP, Bartlett R, Park E. Trajectories of suicide ideation and attempts from early adolescence to mid-adulthood: associations with race/ethnicity. J Youth Adolesc. 2019;48:1796–805.
Balis T, Postolache TT. Ethnic Differences in Adolescent Suicide in the United States. 2008.
Harris KM. The Add Health Study: Design and Accomplishments. [cited 2021 Jul 15]; Available from: https://doi.org/10.17615/C6TW87.
Codebook Explorer. – Add Health [Internet]. [cited 2021 Jun 16]. Available from: https://addhealth.cpc.unc.edu/documentation/codebook-explorer/#/display_variable/341.
Harris KM. The Add Health Study: Design and Accomplishments University of North Carolina at Chapel Hill. 2013 [cited 2022 Apr 1];1–22. Available from: https://doi.org/10.17615/C6TW87.
Fish JN, Russell ST. Have mischievous responders misidentified sexual minority youth disparities in the National Longitudinal Study of Adolescent to Adult Health? Arch Sex Behav. 2018;47:1053–67.
Tabler J, Geist C, Schmitz RM, Nagata JM. Does it get better? Change in depressive symptoms from late-adolescence to early-adulthood, disordered eating behaviors, and sexual identity. J Gay Lesbian Ment Health. 2019;23:221–43.
Radloff LS. The CES-D Scale: a Self-report Depression Scale for research in the general population. Appl Psychol Meas. 1977;1:385–401.
Radloff LS. The use of the Center for Epidemiologic Studies Depression Scale in adolescents and young adults. J Youth Adolesc. 1991;20:149–66.
Borowsky IW, Ireland M, Resnick MD. Adolescent suicide attempts: risks and protectors. Pediatrics. 2001;107:485–93.
Kort-Butler LA. Coping styles and sex differences in depressive symptoms and delinquent behavior. J Youth Adolesc. 2009;38:122–36.
Swallen KC, Reither EN, Haas SA, Meier AM. Overweight, obesity, and health-related quality of life among adolescents: the National Longitudinal Study of Adolescent Health. Pediatrics. 2005;115:340–7.
Parmar DD, Tabler J, Okumura MJ, Nagata JM. Investigating protective factors associated with mental health outcomes in sexual minority youth. J Adolesc Health. 2022;70:470–7.
Furlong MJ, O’Brennan LM, You S. Psychometric properties of the add Health School Connectedness Scale for 18 sociocultural groups. Psychol Sch. 2011;48:986–97.
Steiner RJ, Sheremenko G, Lesesne C, Dittus PJ, Sieving RE, Ethier KA. Adolescent connectedness and adult health outcomes. Pediatrics. 2019;144:e20183766.
Resnick MD, Bearman PS, Blum RW, Bauman KE, Harris KM, Jones J, et al. Protecting adolescent’s from harm: findings from the National Longitudinal Study on Adolescent Health. J Am Med Assoc. 1997;278:823–32.
Rosenberg M. Society and the Adolescent Self-Image. Princeton University Press; 1965.
Morrison LF, Sieving RE, Pettingell SL, Hellerstedt WL, McMorris BJ, Bearinger LH. Protective factors, risk indicators, and contraceptive consistency among college women. J Obstet Gynecol Neonatal Nurs. 2016;45:155–65.
Nagata JM, Garber AK, Tabler JL, Murray SB, Bibbins-Domingo K. Differential risk factors for unhealthy weight control behaviors by sex and weight status among U.S. adolescents. J Adolesc Health. 2018;63:335–41.
Lipson SK, Kern A, Eisenberg D, Breland-Noble AM. Mental health disparities among college students of color. J Adolesc Health. 2018;63:348–56.
Sowislo JF, Orth U. Does low self-esteem predict depression and anxiety? a meta-analysis of longitudinal studies. Psychol Bull. 2013;139:213–40.
Espinosa A, Discrimination. Self-Esteem, and Mental Health Across Ethnic Groups of Second-Generation Immigrant Adolescents. Available from: https://doi.org/10.1007/s40615-020-00917-1.
Masselink M, Van Roekel E, Oldehinkel AJ. Self-esteem in early adolescence as predictor of depressive symptoms in late adolescence and early adulthood: The mediating role of motivational and social factors. J Youth Adolesc. 2018;47:932–46.
Bachman JG, O’Malley PM, Freedman-Doan P, Trzesniewski KH, Donnellan MB. Adolescent Self-esteem: Differences by Race/Ethnicity, Gender, and Age. Self Identity. 2011;10:445–73.
Tsai JL, Ying YW, Lee PA. Cultural predictors of self-esteem: A study of Chinese American female and male young adults. Cult Divers Ethn Minor Psychol. 2001;7:284–97.
Lee S, Juon HS, Martinez G, Hsu CE, Robinson ES, Bawa J, et al. Model minority at risk: Expressed needs of mental health by Asian American young adults. J Community Health [Internet] NIH Public Access. 2009;34:144–52.
Wong YJ, Maffini CS. Predictors of Asian American Adolescents’ Suicide Attempts: A Latent Class Regression Analysis. J Youth Adolesc. 2011.
Ling A, Okazaki S, Tu MC, Kim JJ. Challenges in meeting the mental health needs of urban asian american adolescents: service providers’ perspectives. Race Soc Probl. 2014;6:25–37.
Shah NS, Kandula NR. Addressing Asian American misrepresentation and underrepresentation in research. Ethn Dis. 2020;30:513.
Nguyen HAT, Zheng A, Gugel A, Kistin CJ. Asians and Asian subgroups are underrepresented in medical research studies published in high-impact generalist journals. J Immigr Minor Health. 2021;23:646–9.
Wu C, Qian Y, Wilkes R. Anti-Asian discrimination and the Asian-white mental health gap during COVID-19. Ethn Racial Stud. 2020;44:819–35.
Tessler H, Choi M, Kao G. The anxiety of being Asian American: hate crimes and negative biases during the COVID-19 pandemic. Am J Crim Justice. 2021;45:636–46.
Lee S, Waters SF. Asians and Asian Americans’ experiences of racial discrimination during the COVID-19 pandemic: Impacts on health outcomes and the buffering role of social support. Stigma Health. 2021;6:70–8.
Funding
Dr. Nagata is supported by the American Heart Association (CDA34760281) and the National Institutes of Health (K08HL159350). This research uses data from Add Health, a program project directed by Kathleen Mullan Harris and designed by J. Richard Udry, Peter S. Bearman, and Kathleen Mullan Harris at the University of North Carolina at Chapel Hill, and funded by grant P01-HD31921 from the Eunice Kennedy Shriver National Institute of Child Health and Human Development, with cooperative funding from 23 other federal agencies and foundations. Information on how to obtain the Add Health data files is available on the Add Health website (http://www.cpc.unc.edu/addhealth). No direct support was received from grant P01-HD31921 for this analysis. The funders had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and the decision to submit the manuscript for publication.
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Iyer, P., Parmar, D., Ganson, K.T. et al. Investigating Asian American Adolescents’ Resiliency Factors and Young Adult Mental Health Outcomes at 14-year Follow-up: A Nationally Representative Prospective Cohort Study. J Immigrant Minority Health 25, 75–85 (2023). https://doi.org/10.1007/s10903-022-01373-1
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DOI: https://doi.org/10.1007/s10903-022-01373-1